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MRI-guided focused ultrasound (MRgFUS) surgery is a noninvasive thermal ablation method that uses magnetic resonance imaging (MRI) for target definition, treatment planning, and closed-loop control of energy deposition. Ultrasound is a form of energy that can pass through skin, muscle, fat and other soft tissue so no incisions or inserted probes are needed. High intensity focused ultrasound (HIFU) pinpoints a small target and provides a therapeutic effect by raising the temperature high enough to destroy the target with no damage to surrounding tissue. Integrating FUS and MRI as a therapy delivery system allows physicians to localize, target, and monitor in real time, and thus to ablate targeted tissue without damaging normal structures. This precision makes MRgFUS an attractive alternative to surgical resection or radiation therapy of benign and malignant tumors.
Hypothalamic hamartoma is a rare, benign (non-cancerous) brain tumor that can cause different types of seizures, cognitive problems or other symptoms. While the exact number of people with hypothalamic hamartomas is not known, it is estimated to occur in 1 out of 200,000 children and teenagers worldwide. In one such case at Nicklaus Children’s Brain Institute, USA the patient was able to return home the following day after FUS, resume normal regular activities and remained seizure free. Patients undergoing standard brain surgery to remove similar tumors are typically hospitalized for several days, require sutures, and are at risk of bleeding and infections.
MRgFUS is already approved for the treatment of uterine fibroids. It is in ongoing clinical trials for the treatment of breast, liver, prostate, and brain cancer and for the palliation of pain in bone metastasis. In addition to thermal ablation, FUS, with or without the use of microbubbles, can temporarily change vascular or cell membrane permeability and release or activate various compounds for targeted drug delivery or gene therapy. A disruptive technology, MRgFUS provides new therapeutic approaches and may cause major changes in patient management and several medical disciplines.
Imaging living cells is for a good number of years a hot place in Biology, Physics, Chemistry as well as Engineering and Technology for producing specific devices to visualize living cells. In this presentation is shown my opinion on this topic regarding actual status of applied technology for visualizing living cells as well as small small areas of interest.
Slide #1
Slide #2
As an overview, slide #2 describes: higher resolution imaging of living cells based on advanced CT and MicroCT scanners, and their actual technological trend, advanced optical microscopy, optical magnetic imaging of living cells, and conclusion.
Slide #3
Slide #3 describes a schematic of a computing tomography applied to a single cell, see the inside URL address. The work is in progress as a SBIR application of a group of researchers from Arizona State.The partial section of the cell is supposed to reveal the contents of the cell, which is very important in Biology and Medicine.
Slide #4
Slide #4 describes the principle of computed tomography for relative small objects that are expose by a soft x-ray source on the left, an x-ray detector screen that takes the x-ray projection radiography for the sample on the right. The sample is rotated discretely a small number of degrees and pictures recorded. Depending on the absorption of the sample, the reconstructed 3D object is possible. The resolution of the reconstructed object is a function of the number of pixels as well as the pitch distance d (in the slide 0.127 microns). Because the sample is rotated, the precision of the axis of rotation is very important and becomes a challenging task for small objects.
Slide #5
Slide #5 shows a sample taken from the URL address given below the picture. It represents an insect and the future CT development is expected to produce similar images for mono living cells.
Slide #6
For many Bio-labs the reverse optical microscope is the working horse. The slide above shows a such microscope with a culture cell inside a transparent box. The picture can be found at the address shown inside the slide.
Slide #7
Slide #7 describes an innovative digital microscope from Keyence in which we can observe any object entirely in focus, a 20x greater depth-of-field than an optical microscope, we can view objects from any angle, and measure lengths directly on screen.
Slide #8
Slide #8 shows an actual innovative digital microscope from Keyence, see the website address at the bottom of the slide.
Slide #9
As we know, the samples visualized by a common optical microscope have to be flat on the surface to be visualized because there is no clear image above and below the focal plane, which is the surface of the sample. For a con-focal microscope the situation is changed. Objects can be visualized at different depths and image files recorded can reconstruct as 3D image object.
Slide #10
Slide #10 describes the principle of a con-focal microscope, in which a green laser on left side excites molecules of the specimen at a given depth of focusing, the molecules emit on red light (less energetic than green light) that go all way to the photo-multiplier, which has a small pinhole aperture in front of it that limits the entrance of red rays (parasitic light) from out of range area. More details can be found at the URL address given at the bottom of the slide.
Slide #11
Slide #11 shows a sample of a living specimen taken with a Leica micro-system, see the website address inside the slide.
Slide #12
Slide #12 shows the principle of fluorescent microscope and how it works. A light source is filtered to allow blue light (energetic photons for excitation of the molecules of the specimen), the green light emitted is going through objective and ocular lenses and further to the photo-multiplier or digital camera.
Slide #13
For their discovery of fluorescent microscopy, Eric Betzig, William Moerner and Stefan Hell won the Nobel Prize in Chemistry on 2014, for “the development of super-resolved fluorescence microscopy,” which brings optical microscopy into the nano-dimension.
Slide #14
Slide #14 introduces the improvement on micro CT scanners for imaging living cells which now is on R & D under heavy development. The goal is to visualize the interior of living cells. Challenging tasks are: miniaturization, respond to customer needs, low cost, and versatility.
Slide #15
Slide #15 shows the schematic for an optical magnetic imaging microscope for visualizing living cells with one dimension less than 500 nm. The website address gven describes in details the working principle.
Slide #16
Slide #16 shows the picture of a hand held microscope that is useful on finding spot cancer in moments, ses the website.
Slide #17
Slide #17 shows a hand held MRI that connects to an iPhone. It is useful device for detecting cancer cells.
Slide #18
Slide #18 shows in comparison a portable NMR device, left side, and a Lab NMR instrument whose height is greater than 5 Ft. The spectrum in the left side is that of Toluene and a capillary sample holder is shown also next to the magnetic device.
Slide #19
Slide #19 shows that the hand held MRI can recognize complex molecules, can diagnose cancer faster, can be connected to a smartphone, and be accurate on precise measurements.
Slide #20
An optical dental camera is shown in slide #20. It is less then $100 and a USB cable can connect to a computer. It is very useful for every family in checking the status of the teeth and gums.
Slide #21
For detecting dental cavities the x-ray source packaged as a camera and the sensor that connects to a computer are very useful tools in a dental office.
Slide #22
Slide #22 shows the conclusions of the presentation, in which we summarize: the automated con-focal microscope partially satisfies the actual needs for imaging of living cells, the optical magnetic imaging microscope for living cells is a promising technique,
a higher resolution is needed on all actual microscopes, the advanced CT and Micro CT scanners provide a new avenue on the investigation of living cells, more research needed
on hand-held MRI, which is a new solution for complex molecules recognition including cancer
Nano magnetite refers to small crystals of Fe3O4 in nano-metric range that preserves some specific magnetic properties of the magnetite bulk crystal such as the magnetism at saturation, Curie temperature, coercive magnetic force, hysteresis loop, etc. A discussion of medical applications of nano-magnetic particles is shown in here.
Opportunities for magnetite nanoparticles to be effectively incorporated into environmental contaminant removal and cell separation ([1] Honda et al., 1998;[2] Ebner et al.,1999; [3] Rikers et al., 1998; [4] Navratil, 2003), magnetically guided-drug delivery (Roger et al., 1999), magnetocytolysis ([5] Roger et al., 1999), sealing agents (liquid O-rings) ([6] Enzel et al., 1999), dampening and cooling mechanisms in loudspeakers ([6] Enzel et al., 1999), and contrasting agents for magnetic resonance imaging (MRI) ([7] Schütt, 2004). Advancement of synthesis and stabilization procedures towards production of uniformly sized, dispersed (potentially embedded) magnetite nanoparticles has clearly inspired creative imagination and application in various fields. The following subsections address two topics, magnetic guided drug delivery and magnetic resonance tomography which helps us better understanding the capabilities offered by magnetite nanoparticles.
Magnetically Guided Drug Delivery
Ferrofluids containing encapsulated (with biologically compatible surface chemistries) magnetite nanoparticles, as described above, can be employed for drug delivery to specific locations. Exploitation of superparamagnetic magnetization of magnetite nanoparticles allows for “magnetic dragging” of internal (present in bloodstream or elsewhere) magnetite nanoparticles carrying DNA, enzymes, drugs to target-areas. Similarly, biological effectors, which are proteins (containing DNA specific to target cells) incorporated into encapsulated nanoparticle surface functionality, allow for target cell specificity. Once biological effector carrying magnetic nanoparticles bind to target-cells, the applied magnetic field is fluctuated (approximately 1 MHz) causing magnetocytolysis, or cell destruction, which eliminates target-cells. Similarly, after being dragged to target areas, magnetocytolysis of encapsulated nanoparticles can release drugs. Research towards these ends is currently being heavily investigated as potential for novel drug/cancer treatment abounds. ([5] Roger et al., 1999). Picture below shows schematically drug-loaded magnetic nanoparticles targeting for tumor therapy in which the magnetic nanoparticles are noninvasively moved toward the target.
Magnetic Resonance Tomography (MRT) permits noninvasive visualization of cross-sectional images of the human body, tissues, and organs ([7] Schütt, 2004). The MRT technique provides better tissue resolution than traditional radiation based technologies; with addition of contrasting agents, this resolution can be further enhanced ([8] Shao et al., 2005). Magnetite nanoparticles (in ferrofluid form) are powerful contrasting agents due to their paramagnetic magnetization. Ferrofluid physico-morphosis under magnetic field Blaney 65 Human bloodstreams readily reject the nanoparticle colloidal solution, which quickly passes into the liver ([8] Shao et al., 2005). Consequently, ferrofluids have thus far only been useful in distinguishing between healthy and malignant liver cells. This limitation can be overcome through functionalization of magnetite nanoparticles with various ligands that allows for organ-specific transport; therefore, MRT imaging of various bodily organs can be possible. Furthermore, polymeric (i.e., polyethylene oxide – PEO) coating of functionalized magnetite particles permits ferrofluids longer bloodstream retention. ([7] Schütt, 2004) PEO coatings are applied through magnetite interaction with copolymer PEO-polypeptide; polypeptides interact with the positively charged magnetite surface and provide nanoparticle masking to allow longer bloodstream residence. These coated magnetite nanoparticles could also be employed as extremely efficient capsules for drug delivery systems, which are discussed by ([7] Schütt, 2004).
References
[1] Honda H, Kawabe A, Shinkai M, and Kobayashi T (1998). Development of chitosan-conjugated magnetite for magnetic cell separation. Journal of Fermentation and Bioengineering 86, 191-196
[2] Ebner AD, Ritter JA, Ploehn HJ, Kochen RL, and Navratil JD (1999). New magnetic field-enhanced process for the treatment of aqueous wastes. Separation Science and Technology 34, 1277-1300
[3] Rikers RA, Voncken JHL, and Dalmijn WL (1998). Cr-polluted soil studied by high gradient magnetic separation and electron probe. Journal of Environmental Engineering 124, 1159-1164
[4] Navratil JD (2003). Adsorption and nanoscale magnetic separation of heavy metals from water. U.S. EPA workshop on managing arsenic risks to the environment: characterization of waste, chemistry, and treatment and disposal. Denver, CO
[5] Roger J, Pons JN, Massart R, Halbreich A, and Bacri JC (1999). Some biomedical applications of ferro fluids. Eur. Phys. J. AP 5, 321-325
[6] Enzel P, Adelman N, Beckman KJ, Campbell DJ, Ellis AB, Lisensky GC (1999). Preparation of an aqueous-based ferrofluid. J. Chem. Educ. 76, 943-948
[7] Schütt D (2004). Magnetite colloids for drug delivery and magnetic resonance imaging. Institute Angewandte Polymerforschung: thesis Selim MS, Cunningham LP, Srivastava R, Olson JM (1997). Preparation of nano-size magnetic gamma ferric oxide (γ-Fe2O3) and magnetite (Fe3O4) particles for toner and color imaging applications. Recent Progress in Toner Technologies, 108- 111
[8] Shao H, Lee H, Huang Y, Kwak BK, and Kim CO (2005). Synthesis of nano-size magnetite coated with chitosan for MRI contrast agent by sonochemistry. Magnetics Conference, 2005. INTERMAG Asia 2005. Digests of the IEEE International, 461-462
3-D Images of representative biological cells taken with the HT-1
Researchers have developed a powerful method for 3D imaging of live cells without staining.
Professor YongKeun Park of the Physics Department at the Korea Advanced Institute of Science and Technology (KAIST) is a leading researcher in the field of biophotonics and has dedicated much of his research career to working on digital holographic microscopy technology. Park and his research team collaborated with the R&D team of a start-up that Park co-founded to develop a state-of-the-art, 2D/3D/4D holographic microscope that would allow a real-time label-free visualization of biological cells and tissues.
The HT is an optical analogy of X-ray computed tomography (CT). Both X-ray CT and HT share the same physical principle—the inverse of wave scattering. The difference is that HT uses laser illumination, whereas X-ray CT uses X-ray beams. From the measurement of multiple 2D holograms of a cell, coupled with various angles of laser illuminations, the 3-D refractive index (RI) distribution of the cell can be reconstructed. The reconstructed 3D RI map provides structural and chemical information of the cell including mass, morphology, protein concentration and dynamics of the cellular membrane.
The HT enables users to quantitatively and non-invasively investigate the intrinsic properties of biological cells, for example, dry mass and protein concentration. Some of the research team’s breakthroughs that have leveraged HT’s unique and special capabilities can be found in several recent publications, including a lead article on the simultaneous 3-D visualization and position tracking of optically trapped particles which was published in Optica on April 20, 2015.
Current fluorescence confocal microscopy techniques require the use of exogenous labeling agents to render high-contrast molecular information. Therefore, drawbacks include possible
photo-bleaching
photo-toxicity
interference with normal molecular activities
Immune or stem cells that need to be reinjected into the body are considered particularly difficult to employ with fluorescence microscopy.
“As one of the two currently available, high-resolution tomographic microscopes in the world, I believe that the HT-1 is the best-in-class regarding specifications and functionality. Users can see 3D/4D live images of cells, without fixing, coating or staining cells. Sample preparation times are reduced from a few days or hours to just a few minutes,” said Park.
“Our technology has set a new paradigm for cell observation under a microscope. I expect that this tomographic microscopy will be more widely used in future in various areas of pharmaceuticals, neuroscience, immunology, hematology and cell biology,” Park added.
The researchers announced the launch of their new microscopic tool, the holotomography (HT)-1, to the global marketplace through the Korean start-up TomoCube. Two Korean hospitals, Seoul National University Hospital in Bundang and Boramae Hospital in Seoul, are currently using this microscope. The research team has also introduced the HT-1 at the Photonics West Exhibition 2016 that took place on February 16-18, 2016, in San Francisco, CA.
Chip-Based Atomic Physics Makes Second Quantum Revolution a Reality
A quartz surface above the electrodes used to trap atoms. The color map on the surface shows the electric field amplitude.
A University of Oklahoma-led team of physicists believes chip-based atomic physics holds promise to make the second quantum revolution—the engineering of quantum matter with arbitrary precision—a reality. With recent technological advances in fabrication and trapping, hybrid quantum systems are emerging as ideal platforms for a diverse range of studies in quantum control, quantum simulation and computing.
James P. Shaffer, professor in the Homer L. Dodge Department of Physics and Astronomy, OU College of Arts and Sciences; Jon Sedlacek, OU graduate student; and a team from the University of Nevada, Western Washington University, The United States Naval Academy, Sandia National Laboratories and Harvard-Smithsonian Center for Astrophysics, have published research important for integrating Rydberg atoms into hybrid quantum systems and the fundamental study of atom-surface interactions, as well as applications for electrons bound to a 2-D surface.
“A convenient surface for application in hybrid quantum systems is quartz because of its extensive use in the semiconductor and optics industries,” Sedlacek said. “The surface has been the subject of recent interest as a result of it stability and low surface energy. Mitigating electric fields near ‘trapping’ surfaces is the holy grail for realizing hybrid quantum systems,” added Hossein Sadeghpour, director of the Institute for Theoretical Atomic Molecular and Optical Physics, Harvard-Smithsonian Center for Astrophysics.
In this work, Shaffer finds ionized electrons from Rydberg atoms excited near the quartz surface form a 2-D layer of electrons above the surface, canceling the electric field produced by rubidium surface adsorbates. The system is similar to electron trapping in a 2-D gas on superfluid liquid helium. The binding of electrons to the surface substantially reduces the electric field above the surface.
“Our results show that binding is due to the image potential of the electron inside the quartz,” said Shaffer. “The electron can’t diffuse into the quartz because the rubidium adsorbates make the surface have a negative electron affinity. The approach is a promising pathway for coupling Rydberg atoms to surfaces, as well as for using surfaces close to atomic and ionic samples.”
A paper on this research was published in the American Physics Society’s Physical Review Letters. The OU part of this work was supported by the Defense Advanced Research Projects Agency Quasar program by a grant through the Army Research Office, the Air Force Office of Scientific Research and the National Science Foundation.
New Spin on Biomolecular Tags Lets MRI Catch Metabolic Wobbles
Duke scientists have discovered a new class of inexpensive and long-lived molecular tags that enhance MRI signals by 10,000-fold. To activate the tags, the researchers mix them with a newly developed catalyst (center) and a special form of hydrogen (gray), converting them into long-lived magnetic resonance “lightbulbs” that might be used to track disease metabolism in real time. [Thomas Theis, Duke University]
In principle, magnetic resonance imaging (MRI) could be used to track disease-related biomolecular processes. In practice, magnetic resonance signals die out too quickly. Also, these signals are detectable only with incredibly expensive equipment. The necessary devices, called hyperpolarizers, are commercially available, but they cost as much as $3 million each.
Yet magnetic resonance can be more practical, report scientists from Duke University. These scientists say that they have discovered a new class of molecular tags that enhance magnetic resonance signals by 10,000-fold and generate detectable signals that last over an hour, and not just a few seconds, as is the case with currently available tags. Moreover, the tags are biocompatible and inexpensive to produce, paving the way for widespread use of MRI to monitor metabolic process of conditions such as cancer and heart disease in real time.
According to the Duke team, which was led by physicist Warren S. Warren, Ph.D., and chemist Thomas Theis, Ph.D., the hyperpolarization window to in vitro and in vivo biochemistry can be opened by combining two advances: (1) the use of 15N2-diazirines as storage vessels for hyperpolarization, and (2) a relatively simple and inexpensive approach to hyperpolarization called SABRE-SHEATH.
The details appeared March 25 in the journal Science Advances, in an article entitled, “Direct and Cost-Efficient Hyperpolarization of Long-Lived Nuclear Spin States on Universal 15N2-Diazirine Molecular Tags.” The article explains that the promise of magnetic resonance in tracking chemical transformations has not been realized because of the limitations of existing techniques, such as dissolution dynamic nuclear polarization (d-DNP). Such techniques have lacked adequate sensitivity and are unable to detect small number of molecules without using unattainably massive magnetic fields.
MRI takes advantage of a property called spin, which makes the nuclei in hydrogen atoms act like tiny magnets. Applying a strong magnetic field, followed by a series of radio waves, induces these hydrogen magnets to broadcast their locations. Most of the hydrogen atoms in the body are bound up in water; therefore, the technique is used in clinical settings to create detailed images of soft tissues like organs, blood vessels, and tumors inside the body.
With greater sensitivity, however, magnetic resonance techniques could be used to track chemical transformations in real time. This degree of sensitivity, say the Duke scientists, could be within reach.
“We use a recently developed method, SABRE-SHEATH, to directly hyperpolarize 15N2 magnetization and long-lived 15N2 singlet spin order, with signal decay time constants of 5.8 and 23 minutes, respectively,” wrote the authors of the Science Advances article. “We find >10,000-fold enhancements generating detectable nuclear MR signals that last for over an hour.” The authors added that 15N2-diazirines represent a class of particularly promising and versatile molecular tags and can be incorporated into a wide range of biomolecules without significantly altering molecular function.
“This represents a completely new class of molecules that doesn’t look anything at all like what people thought could be made into MRI tags,” said Dr. Warren “We envision it could provide a whole new way to use MRI to learn about the biochemistry of disease.”
Qiu Wang, Ph.D., an assistant professor of chemistry at Duke and co-author on the paper, said the structure of 15N2-diazirine is a particularly exciting target for hyperpolarization because it has already been demonstrated as a tag for other types of biomedical imaging.
“It can be tagged on small molecules, macromolecules, amino acids, without changing the intrinsic properties of the original compound,” said Dr. Wang. “We are really interested to see if it would be possible to use it as a general imaging tag.” Magnetic resonance, added Dr. Theis, is uniquely sensitive to chemical transformations: “With magnetic resonance, you can see and track chemical transformations in real time.”
The scientists believe their SABRE-SHEATH catalyst could be used to hyperpolarize a wide variety of chemical structures at a fraction of the cost of other methods. “You could envision, in five or ten years, you’ve got the container with the catalyst, you’ve got the bulb with the hydrogen gas,” explained Dr. Warren. “In a minute, you’ve made the hyperpolarized agent, and on the fly you could actually take an image. That is something that is simply inconceivable by any other method.”
Direct and cost-efficient hyperpolarization of long-lived nuclear spin states on universal 15N2-diazirine molecular tags
Thomas Theis1,*,†, Gerardo X. Ortiz Jr.1,†, Angus W. J. Logan1, Kevin E. Claytor2, Yesu Feng, et al.
Conventional magnetic resonance (MR) faces serious sensitivity limitations which can be overcome by hyperpolarization methods, but the most common method (dynamic nuclear polarization) is complex and expensive, and applications are limited by short spin lifetimes (typically seconds) of biologically relevant molecules. We use a recently developed method, SABRE-SHEATH, to directly hyperpolarize 15N2 magnetization and long-lived 15N2 singlet spin order, with signal decay time constants of 5.8 and 23 minutes, respectively. We find >10,000-fold enhancements generating detectable nuclear MR signals that last for over an hour. 15N2-diazirines represent a class of particularly promising and versatile molecular tags, and can be incorporated into a wide range of biomolecules without significantly altering molecular function.
Hyperpolarization enables real-time monitoring of in vitro and in vivo biochemistry
Conventional magnetic resonance (MR) is an unmatched tool for determining molecular structures and monitoring structural transformations. However, even very large magnetic fields only slightly magnetize samples at room temperature and sensitivity remains a fundamental challenge; for example, virtually all MR images are of water because it is the molecule at the highest concentration in vivo. Nuclear spin hyperpolarization significantly alters this perspective by boosting nuclear MR (NMR) sensitivity by four to nine orders of magnitude (1–3), giving access to detailed chemical information at low concentrations. These advances are beginning to transform biomedical in vivo applications (4–9) and structural in vitro studies (10–16).
Current hyperpolarization technology is expensive and associated with short signal lifetimes
Still, two important challenges remain. First, hyperpolarized MR is associated with high cost for the most widespread hyperpolarization technology [dissolution dynamic nuclear polarization (d-DNP), $2 million to $3 million for commercial hyperpolarizers]. Second, hyperpolarized markers typically have short signal lifetimes: typically, hyperpolarized signals may only be tracked for 1 to 2 min in the most favorable cases (6), greatly limiting this method as a probe for slower biological processes.
The presented approach is inexpensive and produces long-lived signals
Here, we demonstrate that both of these challenges can be overcome simultaneously, setting the stage for hour-long tracking of molecular markers with inexpensive equipment. Specifically, we illustrate the potential of 15N2-diazirines as uniquely powerful storage vessels for hyperpolarization. We show that diazirine can be hyperpolarized efficiently and rapidly (literally orders of magnitude cheaper and quicker than d-DNP), and that this hyperpolarization can be induced in states that maintain hyperpolarization for more than an hour.
Our approach uses parahydrogen (p-H2) to directly polarize long-lived nuclear spin states. The first demonstration of parahydrogen-induced polarization (PHIP) was performed in the late 1980s (17–19). Then, PHIP was used to rely on the addition of p-H2 to a carbon double or triple bond, incorporating highly polarized hydrogen atoms into molecules. This approach generally requires specific catalyst-substrate pairs; in addition, hydrogen atoms usually have short relaxation times (T1) that cause signal decay within a few seconds. A more recent variant, SABRE (signal amplification by reversible exchange) (20, 21), uses p-H2 to polarize 1H atoms on a substrate without hydrogenation. In SABRE, both p-H2 and substrate reversibly bind to an iridium catalyst and the hyperpolarization is transferred from p-H2 to the substrate through J-couplings established on the catalytic intermediate. Recently, we extended this method to SABRE-SHEATH (SABRE in SHield Enables Alignment Transfer to Heteronuclei) for direct hyperpolarization of 15N molecular sites (22–24). This method has several notable features. Low-γ nuclei (13C, 15N) tend to have long relaxation times, particularly if a proton is not attached. In addition, conventional SABRE relies on small differences between four-bond proton-proton J-couplings (detailed in the Supplementary Materials), whereas SABRE-SHEATH uses larger two-bond heteronuclear J-couplings. It is extremely simple: SABRE-SHEATH requires nothing but p-H2, the catalyst, and a shield to reduce Earth’s field by about 99%. After 1 to 5 min of bubbling p-H2into the sample in the shield, we commonly achieve 10% nitrogen polarization, many thousands of times stronger than thermal signals (22). In contrast, d-DNP typically produces such polarization levels in an hour, at much higher cost.
Diazirines are small and versatile molecular tags
A general strategy for many types of molecular imaging is the creation of molecular tags, which ideally do not alter biochemical pathways but provide background-free signatures for localization. This strategy has not been very successful in MR because of sensitivity issues. Here, we demonstrate that SABRE-SHEATH enables a MR molecular beacon strategy using diazirines (three-membered rings containing a nitrogen-nitrogen double bond). They are highly attractive as molecular tags, primarily because of their small size. Diazirines have already been established as biocompatible molecular tags for photoaffinity labeling (25). They can be incorporated into many small molecules, metabolites, and biomolecules without drastically altering biological function. Diazirines share similarities with methylene (CH2) groups in terms of electronic and steric properties such that they can replace methylene groups without drastically distorting biochemical behavior. Furthermore, diazirines are stable at room temperature, are resistant to nucleophiles, and do not degrade under either acidic or alkaline conditions (25). With these attractive properties, diazirines have been used for the study of many signaling pathways. For example, they have been incorporated into hormones (26), epileptic drugs (27), antibiotics (28), hyperthermic drugs (29), anticancer agents (30), anesthetics (31), nucleic acids (32), amino acids (33), and lipids (34). They also have been introduced into specific molecular reporters to probe enzyme function and their binding sites such as in kinases (35), aspartic proteases (36), or metalloproteinases (37), to name a few. The nitrogen-nitrogen moiety is also intrinsically interesting, because the two atoms are usually very close in chemical shift and strongly coupled, thus suited to support a long-lived singlet state as described below.
Fig. 1The hyperpolarization mechanism.
(A) The precatalyst, 15N2-diazirine substrate, and p-H2 are mixed, resulting in the activated species depicted in (B). (B) Both p-H2 and the free 15N2-diazirine [2-cyano-3-(D3 methyl-15N2-diazirine)-propanoic acid] are in reversible exchange with the catalytically active iridium complex. The catalyst axial position is occupied by IMes [1,3-bis(2,4,6-trimethylphenyl)-imidazolium] and Py (pyridine) as nonexchanging ligands. The structure shown is a local energy minimum of the potential energy surface based on all-electron DFT calculations and the dispersion-corrected PBE density functional. In the complex, hyperpolarization is transferred from the parahydrogen (p-H2)–derived hydrides to the 15N nuclei (white, hydrogen; gray, carbon; blue, nitrogen; red, oxygen).
Density functional theory calculations shed light on polarization transfer catalyst
The Ir complex conformation shown in Fig. 1B was determined by all-electron density functional theory (DFT) calculations [semilocal Perdew-Burke-Ernzerhof (PBE) functional (38), corrected for long-range many-body dispersion interactions (39), in the FHI-aims software package (40, 41); see the Supplementary Materials for details]. The calculations indicate a η1 single-sided N attachment rather than η2-N=N attachment of the diazirines. In the Ir complex, hyperpolarization is transferred from p-H2 gas (~92% para-state, 7.5 atm) to the 15N2-diazirine. Both p-H2 and substrate are in reversible exchange with the central complex, which results in continuous pumping of hyperpolarization: p-H2 is continually refreshed and hyperpolarization accumulated on the diazirine substrate.
An alternate polarization transfer catalyst is introduced
As opposed to the traditional [Ir(COD)(IMes)(Cl)] catalyst (18), the synthesized [Ir(COD)(IMes)(Py)][PF6] results in a pyridine ligand trans to IMes, improving our hyperpolarization levels by a factor of ~3 (see the Supplementary Materials). We have found that this new approach, which avoids competition from added pyridine, makes it possible to directly hyperpolarize a wide variety of different types of15N-containing molecules (and even 13C). However, diazirines represent a particularly general and interesting class of ligands for molecular tags and are the focus here.
As depicted in Fig. 2A, the hyperpolarization proceeds outside the high-field NMR magnet at low magnetic fields, enabling SABRE-SHEATH directly targeting 15N nuclei (22). To establish the hyperpolarization, we bubble p-H2 for ~5 min at the adequate field. Then, the sample is transferred into the NMR magnet within ~10 s, and 15N2 signal detection is performed with a simple 90° pulse followed by data acquisition.
Fig. 2Experimental and spectral distinction between magnetization and singlet spin order.
(A) Experimental procedure. The sample is hyperpolarized by bubbling parahydrogen (p-H2) through the solution in the NMR tube for 5 min and subsequently transferred into the high-field magnet for detection. If the hyperpolarization/bubbling is performed in a magnetic shield at ~6 mG, z-magnetization is created (black). If the hyperpolarization/bubbling is performed in the laboratory field anywhere between ~0.1 and ~1 kG, singlet order is created (blue). (B) Z-magnetization and singlet spin order can easily be distinguished based on their spectral appearance. a.u., arbitrary units. Z-magnetization produces an in-phase quartet (black). Singlet order gives an anti-phase quartet (blue). The spin system parameters for the 15N2 two-spin system are JNN = 17.3 Hz and Δδ = 0.58 parts per million.
Two types of hyperpolarized states can be created: Magnetization and singlet order
We create two different types of hyperpolarization on the 15N2-diazirine. We can hyperpolarize traditional z-magnetization, which corresponds to nuclear spins aligned with the applied magnetic field and is associated with pure in-phase signal as illustrated with the black trace in Fig. 2B. Alternatively, we can hyperpolarize singlet order on the 15N2-diazirine, which corresponds to an anti-aligned spin state, with both spins pointing in opposite directions, entangled in a quantum mechanically “hidden” state. This hidden singlet order is converted into a detectable state when transferred to a high magnetic field and associated with the anti-phase signal illustrated by the blue trace in Fig. 2B (see the Supplementary Materials for details). The difference in symmetry of z-magnetization and singlet order leads to differences in signal decay rates; z-magnetization is directly exposed to all NMR relaxation mechanisms and is often associated with shorter signal lifetimes, which may impede molecular tracking on biologically relevant time scales. Singlet order, on the other hand, is protected from many relaxation mechanisms because it has no angular momentum (42–52) and can therefore exhibit much longer lifetimes, enabling hour-long molecular tracking.
The type of hyperpolarized state is selected by the magnetic field
We can control which type of hyperpolarization we create by choosing the appropriate magnetic fields for the bubbling process. Z-magnetization is created in the SABRE-SHEATH mode at low magnetic fields inside a magnetic shield (22–24, 53, 54). This behavior is explained by resonance conditions for hyperpolarizing magnetization versus singlet order that we derive in the Supplementary Materials. The condition for creating magnetization, νH − νN = |JHH ± JNN|, is field-dependent in the NMR frequencies, νH and νN, and field-independent in the J-couplings. Accordingly, hyperpolarized magnetization is created at a magnetic field where the frequency difference matches the J-couplings. This magnetic field is ~6 mG, which is obtained by using JHH = −10 Hz, JNN = −17.3 Hz, γ1H = 4.2576 kHz/G, and γ15N = −0.4316 kHz/G (see the Supplementary Materials). The theoretical prediction of 6 mG matches the experimental maximum for hyperpolarized z-magnetization illustrated by the blue data in Fig. 3A.
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The demonstrated hyperpolarization lifetimes, combined with the ease of hyperpolarization in these broadly applicable biomolecular tags, may establish a paradigm shift for biomolecular sensing and reporting in optically opaque tissue. The demonstrated lifetimes even exceed lifetimes of some common radioactive tracers used in positron emission tomography (PET) (for example, 11C, 20.3 min). However, unlike PET, MR is exquisitely sensitive to chemical transformations and does not use ionizing radiation (such that, for example, daily progression monitoring of disease is easily possible). The presented work may allow direct access to biochemical mechanisms and kinetics in optically opaque media. We therefore envision tracking subtle biochemical processes in vitro with unprecedented NMR sensitivities as well as real-time in vivo biomolecular imaging with hyperpolarized diazirines.
The atoms in the new structure are arranged in a hexagonal pattern as in graphene, but that is where the similarity ends. The three elements forming the new material all have different sizes; the bonds connecting the atoms are also different. As a result, the sides of the hexagons formed by these atoms are unequal, unlike in graphene. (credit: Madhu Menon)
A new one-atom-thick flat material made up of silicon, boron, and nitrogen can function as a conductor or semiconductor (unlike graphene) and could upstage graphene and advance digital technology, say scientists at the University of Kentucky, Daimler in Germany, and the Institute for Electronic Structure and Laser (IESL) in Greece.
Reported in Physical Review B, Rapid Communications, the new Si2BN material was discovered in theory (not yet made in the lab). It uses light, inexpensive earth-abundant elements and is extremely stable, a property many other graphene alternatives lack, says University of Kentucky Center for Computational Sciences physicist Madhu Menon, PhD.
Limitations of other 2D semiconducting materials
A search for new 2D semiconducting materials has led researchers to a new class of three-layer materials called transition-metal dichalcogenides (TMDCs). TMDCs are mostly semiconductors and can be made into digital processors with greater efficiency than anything possible with silicon. However, these are much bulkier than graphene and made of materials that are not necessarily earth-abundant and inexpensive.
Other graphene-like materials have been proposed but lack the strengths of the new material. Silicene, for example, does not have a flat surface and eventually forms a 3D surface. Other materials are highly unstable, some only for a few hours at most.
The new Si2BN material is metallic, but by attaching other elements on top of the silicon atoms, its band gap can be changed (from conductor to semiconductor, for example) — a key advantage over graphene for electronics applications and solar-energy conversion.
The presence of silicon also suggests possible seamless integration with current silicon-based technology, allowing the industry to slowly move away from silicon, rather than precipitously, notes Menon.
Abstract of Prediction of a new graphenelike Si2BN solid
While the possibility to create a single-atom-thick two-dimensional layer from any material remains, only a few such structures have been obtained other than graphene and a monolayer of boron nitride. Here, based upon ab initiotheoretical simulations, we propose a new stable graphenelike single-atomic-layer Si2BN structure that has all of its atoms with sp2 bonding with no out-of-plane buckling. The structure is found to be metallic with a finite density of states at the Fermi level. This structure can be rolled into nanotubes in a manner similar to graphene. Combining first- and second-row elements in the Periodic Table to form a one-atom-thick material that is also flat opens up the possibility for studying new physics beyond graphene. The presence of Si will make the surface more reactive and therefore a promising candidate for hydrogen storage.
Close-up of nanostructures grown on cotton textiles. Image magnified 150,000 times. (credit: RMIT University)
Researchers at at RMIT University in Australia have developed a cheap, efficient way to grow special copper- and silver-based nanostructures on textiles that can degrade organic matter when exposed to light.
Don’t throw out your washing machine yet, but the work paves the way toward nano-enhanced textiles that can spontaneously clean themselves of stains and grime simply by being put under a light or worn out in the sun.
The nanostructures absorb visible light (via localized surface plasmon resonance — collective electron-charge oscillations in metallic nanoparticles that are excited by light), generating high-energy (“hot”) electrons that cause the nanostructures to act as catalysts for chemical reactions that degrade organic matter.
Steps involved in fabricating copper- and silver-based cotton fabrics: 1. Sensitize the fabric with tin. 2. Form palladium seeds that act as nucleation (clustering) sites. 3. Grow metallic copper and silver nanoparticles on the surface of the cotton fabric. (credit: Samuel R. Anderson et al./Advanced Materials Interfaces)
The challenge for researchers has been to bring the concept out of the lab by working out how to build these nanostructures on an industrial scale and permanently attach them to textiles. The RMIT team’s novel approach was to grow the nanostructures directly onto the textiles by dipping them into specific solutions, resulting in development of stable nanostructures within 30 minutes.
When exposed to light, it took less than six minutes for some of the nano-enhanced textiles to spontaneously clean themselves.
The research was described in the journal Advanced Materials Interfaces.
Scaling up to industrial levels
Rajesh Ramanathan, a RMIT postdoctoral fellow and co-senior author, said the process also had a variety of applications for catalysis-based industries such as agrochemicals, pharmaceuticals, and natural products, and could be easily scaled up to industrial levels. “The advantage of textiles is they already have a 3D structure, so they are great at absorbing light, which in turn speeds up the process of degrading organic matter,” he said.
Cotton textile fabric with copper-based nanostructures. The image is magnified 200 times. (credit: RMIT University)
“Our next step will be to test our nano-enhanced textiles with organic compounds that could be more relevant to consumers, to see how quickly they can handle common stains like tomato sauce or wine,” Ramanathan said.
“There’s more work to do to before we can start throwing out our washing machines, but this advance lays a strong foundation for the future development of fully self-cleaning textiles.”
Abstract of Robust Nanostructured Silver and Copper Fabrics with Localized Surface Plasmon Resonance Property for Effective Visible Light Induced Reductive Catalysis
Inspired by high porosity, absorbency, wettability, and hierarchical ordering on the micrometer and nanometer scale of cotton fabrics, a facile strategy is developed to coat visible light active metal nanostructures of copper and silver on cotton fabric substrates. The fabrication of nanostructured Ag and Cu onto interwoven threads of a cotton fabric by electroless deposition creates metal nanostructures that show a localized surface plasmon resonance (LSPR) effect. The micro/nanoscale hierarchical ordering of the cotton fabrics allows access to catalytically active sites to participate in heterogeneous catalysis with high efficiency. The ability of metals to absorb visible light through LSPR further enhances the catalytic reaction rates under photoexcitation conditions. Understanding the modes of electron transfer during visible light illumination in Ag@Cotton and Cu@Cotton through electrochemical measurements provides mechanistic evidence on the influence of light in promoting electron transfer during heterogeneous catalysis for the first time. The outcomes presented in this work will be helpful in designing new multifunctional fabrics with the ability to absorb visible light and thereby enhance light-activated catalytic processes.
Duke scientists have discovered a new class of inexpensive, long-lived molecular tags that enhance MRI signals by 10,000 times. To activate the tags, the researchers mix them with a newly developed catalyst (center) and a special form of hydrogen (gray), converting them into long-lived magnetic resonance “lightbulbs” that might be used to track disease metabolism in real time. (credit: Thomas Theis, Duke University)
Duke University researchers have discovered a new form of MRI that’s 10,000 times more sensitive and could record actual biochemical reactions, such as those involved in cancer and heart disease, and in real time.
Let’s review how MRI (magnetic resonance imaging) works: MRI takes advantage of a property called spin, which makes the nuclei in hydrogen atoms act like tiny magnets. By generating a strong magnetic field (such as 3 Tesla) and a series of radio-frequency waves, MRI induces these hydrogen magnets in atoms to broadcast their locations. Since most of the hydrogen atoms in the body are bound up in water, the technique is used in clinical settings to create detailed images of soft tissues like organs (such as the brain), blood vessels, and tumors inside the body.
MRI’s ability to track chemical transformations in the body has been limited by the low sensitivity of the technique. That makes it impossible to detect small numbers of molecules (without using unattainably more massive magnetic fields).
So to take MRI a giant step further in sensitivity, the Duke researchers created a new class of molecular “tags” that can track disease metabolism in real time, and can last for more than an hour, using a technique called hyperpolarization.* These tags are biocompatible and inexpensive to produce, allowing for using existing MRI machines.
“This represents a completely new class of molecules that doesn’t look anything at all like what people thought could be made into MRI tags,” said Warren S. Warren, James B. Duke Professor and Chair of Physics at Duke, and senior author on the study. “We envision it could provide a whole new way to use MRI to learn about the biochemistry of disease.”
Sensitive tissue detection without radiation
The new molecular tags open up a new world for medicine and research by making it possible to detect what’s happening in optically opaque tissue instead of requiring expensive positron emission tomography (PET), which uses a radioactive tracer chemical to look at organs in the body and only works for (typically) about 20 minutes, or CT x-rays, according to the researchers.
This research was reported in the March 25 issue of Science Advances. It was supported by the National Science Foundation, the National Institutes of Health, the Department of Defense Congressionally Directed Medical Research Programs Breast Cancer grant, the Pratt School of Engineering Research Innovation Seed Fund, the Burroughs Wellcome Fellowship, and the Donors of the American Chemical Society Petroleum Research Fund.
* For the past decade, researchers have been developing methods to “hyperpolarize” biologically important molecules. “Hyperpolarization gives them 10,000 times more signal than they would normally have if they had just been magnetized in an ordinary magnetic field,” Warren said. But while promising, Warren says these hyperpolarization techniques face two fundamental problems: incredibly expensive equipment — around 3 million dollars for one machine — and most of these molecular “lightbulbs” burn out in a matter of seconds.
“It’s hard to take an image with an agent that is only visible for seconds, and there are a lot of biological processes you could never hope to see,” said Warren. “We wanted to try to figure out what molecules could give extremely long-lived signals so that you could look at slower processes.”
So the researchers synthesized a series of molecules containing diazarines — a chemical structure composed of two nitrogen atoms bound together in a ring. Diazirines were a promising target for screening because their geometry traps hyperpolarization in a “hidden state” where it cannot relax quickly. Using a simple and inexpensive approach to hyperpolarization called SABRE-SHEATH, in which the molecular tags are mixed with a spin-polarized form of hydrogen and a catalyst, the researchers were able to rapidly hyperpolarize one of the diazirine-containing molecules, greatly enhancing its magnetic resonance signals for over an hour.
The scientists believe their SABRE-SHEATH catalyst could be used to hyperpolarize a wide variety of chemical structures at a fraction of the cost of other methods.
Abstract of Direct and cost-efficient hyperpolarization of long-lived nuclear spin states on universal 15N2-diazirine molecular tags
Abstract of Direct and cost-efficient hyperpolarization of long-lived nuclear spin states on universal 15N2-diazirine molecular tags
Conventional magnetic resonance (MR) faces serious sensitivity limitations, which can be overcome by hyperpolarization methods, but the most common method (dynamic nuclear polarization) is complex and expensive, and applications are limited by short spin lifetimes (typically seconds) of biologically relevant molecules. We use a recently developed method, SABRE-SHEATH, to directly hyperpolarize 15N2 magnetization and long-lived 15N2singlet spin order, with signal decay time constants of 5.8 and 23 min, respectively. We find >10,000-fold enhancements generating detectable nuclear MR signals that last for more than an hour. 15N2-diazirines represent a class of particularly promising and versatile molecular tags, and can be incorporated into a wide range of biomolecules without significantly altering molecular function.
[Seems like they have a great idea, now all they need to do is confirm very specific uses or types of cancers/diseases or other processes they can track or target. Will be interesting to see if they can do more than just see things, maybe they can use this to target and destroy bad things in the body also. Keep up the good work….. this sounds like a game changer.]
Scientists time-reverse developed stem cells to make them ‘embryonic’ again
Researchers have reversed “primed” (developed) “epiblast” stem cells (top) from early mouse embryos using the drug MM-401, causing the treated cells (bottom) to revert to the original form of the stem cells. (credit: University of Michigan)
University of Michigan Medical School researchers have discovered a way to convert mouse stem cells (taken from an embryo) that have become “primed” (reached the stage where they can differentiate, or develop into every specialized cell in the body) to a “naïve” (unspecialized) state by simply adding a drug.
This breakthrough has the potential to one day allow researchers to avoid the ethically controversial use of human embryos left over from infertility treatments. To achieve this breakthrough, the researchers treated the primedembryonic stem cells (“EpiSC”) with a drug called MM-401* (a leukemia drug) for a short period of time.
Embryonic stem cells are able to develop into any type of cell, except those of the placenta (credit: Mike Jones/CC)
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* The drug, MM-401, specifically targets epigenetic chemical markers on histones, the protein “spools” that DNA coils around to create structures called chromatin. These epigenetic changes signal the cell’s DNA-reading machinery and tell it where to start uncoiling the chromatin in order to read it.
A gene called Mll1 is responsible for the addition of these epigenetic changes, which are like small chemical tags called methyl groups. Mll1 plays a key role in the uncontrolled explosion of white blood cells in leukemia, which is why researchers developed the drug MM-401 to interfere with this process. But Mll1 also plays a role in cell development and the formation of blood cells and other cells in later-stage embryos.
Stem cells do not turn on the Mll1 gene until they are more developed. The MM-401 drug blocks Mll1’s normal activity in developing cells so the epigenetic chemical markers are missing. These cells are then unable to continue to develop into different types of specialized cells but are still able to revert to healthy naive pluripotent stem cells.
Abstract of MLL1 Inhibition Reprograms Epiblast Stem Cells to Naive Pluripotency
The interconversion between naive and primed pluripotent states is accompanied by drastic epigenetic rearrangements. However, it is unclear whether intrinsic epigenetic events can drive reprogramming to naive pluripotency or if distinct chromatin states are instead simply a reflection of discrete pluripotent states. Here, we show that blocking histone H3K4 methyltransferase MLL1 activity with the small-molecule inhibitor MM-401 reprograms mouse epiblast stem cells (EpiSCs) to naive pluripotency. This reversion is highly efficient and synchronized, with more than 50% of treated EpiSCs exhibiting features of naive embryonic stem cells (ESCs) within 3 days. Reverted ESCs reactivate the silenced X chromosome and contribute to embryos following blastocyst injection, generating germline-competent chimeras. Importantly, blocking MLL1 leads to global redistribution of H3K4me1 at enhancers and represses lineage determinant factors and EpiSC markers, which indirectly regulate ESC transcription circuitry. These findings show that discrete perturbation of H3K4 methylation is sufficient to drive reprogramming to naive pluripotency.
Abstract of Naive Pluripotent Stem Cells Derived Directly from Isolated Cells of the Human Inner Cell Mass
Conventional generation of stem cells from human blastocysts produces a developmentally advanced, or primed, stage of pluripotency. In vitro resetting to a more naive phenotype has been reported. However, whether the reset culture conditions of selective kinase inhibition can enable capture of naive epiblast cells directly from the embryo has not been determined. Here, we show that in these specific conditions individual inner cell mass cells grow into colonies that may then be expanded over multiple passages while retaining a diploid karyotype and naive properties. The cells express hallmark naive pluripotency factors and additionally display features of mitochondrial respiration, global gene expression, and genome-wide hypomethylation distinct from primed cells. They transition through primed pluripotency into somatic lineage differentiation. Collectively these attributes suggest classification as human naive embryonic stem cells. Human counterparts of canonical mouse embryonic stem cells would argue for conservation in the phased progression of pluripotency in mammals.
Could treat bacterial infections without using antibiotics, which could help reduce the risk of spreading antibiotics resistance
Researchers at the University of Houston have developed a new technique for killing bacteria in 5 to 25 seconds using highly porous gold nanodisks and light, according to a study published today in Optical Materials Express. The method could one day help hospitals treat some common infections without using antibiotics
3D Printing Confirms Physical Model of Brain Folds
Reporter: Irina Robu, PhD
Highly folded brains are not present in most animals but only in some primates, dolphins, elephants and pigs. However, not a lot is understood of how the brain folds. Researchers at Harvard John A. Paulson School of Engineering and Applied Sciences collaborating with scientists in Finland and France have shown that while many molecular processes are important in determining cellular events,what ultimately causes the brain to fold in a simple mechanical instability associated with buckling. Understanding how the brain folds is important because it can unlock the inner workings of the brain and unravel brain-related disorders.
The number, size, shape and position of neuronal cells during brain growth all lead to the expansion of the gray matter,relative to the underlying white matter. This puts the cortex under compression, leading to a mechanical instability that causes it to crease locally. Growth differential between the brain’s outer cortex and the soft tissue underneath explains the variations in the folding patterns, the relative size of the brain, and the relative expansion of the cortex.
A gel model of a fetal brain after being immersed in liquid solvent. The resulting compression led to the formation of folds similar in size and shape to real brains. Credit: Mahadevan Lab/Harvard SEAS
Based on this, the team collaborated with neuroanatomists and radiologists in France and tested the theory using data from human fetuses. The team made a three-dimensional, gel model of a smooth fetal brain based on MRI images. The model’s surface was coated with a thin layer of elastomer gel, as an analog of the cortex. To mimic cortical expansion, the gel brain was immersed in a solvent that is absorbed by the outer layer causing it to swell relative to the deeper regions. Within minutes of being immersed in liquid solvent, the resulting compression led to the formation of folds similar in size and shape to real brains.
The research shows that if part of the brain does not grow properly or the geometry is disrupted, the major folds are not in the right place causing a dysfunction in the brain.
Tweets can give medical professionals a window into the minds of patients, according to a new study published in the Journal of Medical Imaging and Radiation Sciences
Philadelphia, PA, October 28, 2015 – Magnetic Resonance Imaging (MRI) can be a stressful experience for many people, but clinicians have few ways to track the thoughts and feelings of their patients regarding this procedure. While the social networking site Twitter is known for breaking news and celebrity tweets, it may also prove to be a valuable feedback tool for medical professionals looking to improve the patient experience, according to a new study published in the December issue of the Journal of Medical Imaging and Radiation Sciences.
Johnathan Hewis, MSc, PgCert (LTHE), PgCert (BE), BSc Hon, an investigator from Charles Sturt University in Australia, analyzed 464 tweets related to MRI over the course of one month and found that patients, their friends, and family members were sharing their thoughts and feelings about all aspects of the procedure through the microblogging site. Tweets were categorized into three themes: MRI appointment, scan experience, and diagnosis.
Twitter is a giant in the social media space. In 2014, 19% of the entire adult population of the U.S. used Twitter, with almost 90% of those individuals accessing the service from their mobile phones. Because it is so ubiquitous, Twitter can provide crucial new insights to which practitioners would otherwise not be privy. In the study, patients expressed anxiety about many aspects of the process, including a lot of stress over the possibility of bad news. “The findings of this study indicate that anticipatory anxiety can manifest over an extended time period and that the focus can shift and change along the MRI journey,” explained Hewis. “An appreciation of anxiety related to results is an important clinical consideration for MRI facilities and referrers.”
The study found that tweets encapsulated patient thoughts about many other parts of the procedure including the cost, the feelings of claustrophobia, having to keep still during the scan, and the sound the MRI machine makes. One particularly memorable tweet about the sound read, “Ugh, having an MRI is like being inside a pissed off fax machine!”
Not all the tweets were centered around stress. Many friends and family members expressed sentiments of support including prayers and offering messages of strength. Some patients used Twitter to praise their healthcare team or give thanks for good results. Others spoke about the fact they liked having an MRI because it gave them some time to themselves or offered them a chance to nap.
Twitter isn’t just words, it’s also a way to share pictures. “An unexpected discovery of the examination preparation process was the ‘MRI gown selfie,'” revealed Hewis. “Fifteen patients tweeted a self-portrait photograph taken inside the changing cubicle while posing in their MRI gown/scrubs. Anecdotally, the ‘MRI gown selfie’ seemed to transcend age.”
During the course of his analysis, Hewis discovered that many patients took issue with the fact that they were not allowed to select the music they listened to during the MRI. “Music choice,” said Hewis, “is a simple intervention that can provide familiarity within a ‘terrifying’ environment.’ The findings of this study reinforce the ‘good practice’ of enabling patients’ choice of music, which may alleviate procedural anxiety.”
With such a broad reach, social networks like Twitter offer medical practitioners the opportunity to access previously unavailable information from their patients, which can help them continuously improve the MRI experience. “MRI patients do tweet about their experiences and these correlate with published findings employing more traditional participant recruitment methods,” concluded Hewis. “This study demonstrates the potential use of Twitter as a viable platform to conduct research into the patient experience within the medical radiation sciences.”
It is estimated that the medical imaging market will exceed $30 billion in 2014 (FierceMedicalImaging). To put this amount in perspective; the global pharmaceutical market size for the same year is expected to be ~$1 trillion (IMS) while the global health care spending as a percentage of Gross Domestic Product (GDP) will average 10.5% globally in 2014 (Deloitte); it will reach ~$3 trillion in the USA.
Recent technology-advances, mainly miniaturization and improvement in electronic-processing components is driving increased introduction of innovative medical-imaging devices into critical nodes of major-diseases’ management pathways. Consequently, in contrast to it’s very small contribution to global health costs, medical imaging bears outstanding potential to reduce the future growth in spending on major segments in this market mainly: Drugs development and regulation (e.g. companion diagnostics and imaging surrogate markers); Disease management (e.g. non-invasive diagnosis, guided treatment and non-invasive follow-ups); and Monitoring aging-population (e.g. Imaging-based domestic sensors).
In; The Role of Medical Imaging in Personalized Medicine I discussed in length the role medical imaging assumes in drugs development. Integrating imaging into drug development processes, specifically at the early stages of drug discovery, as well as for monitoring drug delivery and the response of targeted processes to the therapy is a growing trend. A nice (and short) review highlighting the processes, opportunities, and challenges of medical imaging in new drug development is: Medical imaging in new drug clinical development.
The following is dedicated to the role of imaging in guiding treatment.
Precise treatment is a major pillar of modern medicine. An important aspect to enable accurate administration of treatment is complementing the accurate identification of the organ location that needs to be treated with a system and methods that ensure application of treatment only, or mainly to, that location. Imaging is off-course, a major component in such composite systems. Amongst the available solution, functional-imaging modalities are gaining traction. Specifically, molecular imaging (e.g. PET, MRS) allows the visual representation, characterization, and quantification of biological processes at the cellular and subcellular levels within intact living organisms. In oncology, it can be used to depict the abnormal molecules as well as the aberrant interactions of altered molecules on which cancers depend. Being able to detect such fundamental finger-prints of cancer is key to improved matching between drugs-based treatment and disease. Moreover, imaging-based quantified monitoring of changes in tumor metabolism and its microenvironment could provide real-time non-invasive tool to predict the evolution and progression of primary tumors, as well as the development of tumor metastases.
A recent review-paper: Image-guided interventional therapy for cancer with radiotherapeutic nanoparticles nicely illustrates the role of imaging in treatment guidance through a comprehensive discussion of; Image-guided radiotherapeutic using intravenous nanoparticles for the delivery of localized radiation to solid cancer tumors.
Abstract
One of the major limitations of current cancer therapy is the inability to deliver tumoricidal agents throughout the entire tumor mass using traditional intravenous administration. Nanoparticles carrying beta-emitting therapeutic radionuclides[DN: radioactive isotops that emits electrons as part of the decay process a list of β-emitting radionuclides used in radiotherapeutic nanoparticle preparation is given in table1 of this paper.) that are delivered using advanced image-guidance have significant potential to improve solid tumor therapy. The use of image-guidance in combination with nanoparticle carriers can improve the delivery of localized radiation to tumors. Nanoparticles labeled with certain beta-emitting radionuclides are intrinsically theranostic agents that can provide information regarding distribution and regional dosimetry within the tumor and the body. Image-guided thermal therapy results in increased uptake of intravenous nanoparticles within tumors, improving therapy. In addition, nanoparticles are ideal carriers for direct intratumoral infusion of beta-emitting radionuclides by convection enhanced delivery, permitting the delivery of localized therapeutic radiation without the requirement of the radionuclide exiting from the nanoparticle. With this approach, very high doses of radiation can bedelivered to solid tumors while sparing normal organs. Recent technological developments in image-guidance, convection enhanced delivery and newly developed nanoparticles carrying beta-emitting radionuclides will be reviewed. Examples will be shown describing how this new approach has promise for the treatment of brain, head and neck, and other types of solid tumors.
The challenges this review discusses
intravenously administered drugs are inhibited in their intratumoral penetration by high interstitial pressures which prevent diffusion of drugs from the blood circulation into the tumor tissue [1–5].
relatively rapid clearance of intravenously administered drugs from the blood circulation by kidneys and liver.
drugs that do reach the solid tumor by diffusion are inhomogeneously distributed at the micro-scale – This cannot be overcome by simply administering larger systemic doses as toxicity to normal organs is generally the dose limiting factor.
even nanoparticulate drugs have poor penetration from the vascular compartment into the tumor and the nanoparticles that do penetrate are most often heterogeneously distributed
How imaging could mitigate the above mentioned challenges
The inclusion of an imaging probe during drug development can aid in determining the clearance kinetics and tissue distribution of the drug non-invasively. Such probe can also be used to determine the likelihood of the drug reaching the tumor and to what extent.
Note:Drugs that have increased accumulation within the targeted site are likely to be more effective as compared with others. In that respect, Nanoparticle-based drugs have an additional advantage over free drugs with their potential to be multifunctional carriers capable of carrying both therapeutic and diagnostic imaging probes (theranostic) in the same nanocarrier. These multifunctional nanoparticles can serve as theranostic agents and facilitate personalized treatment planning.
Imaging can also be used for localization of the tumor to improve the placement of a catheter or external device within tumors to cause cell death through thermal ablation or oxidative stress secondary to reactive oxygen species.
Note: Image guided thermal ablation methods include radiofrequency (RF) ablation, microwave ablation or high intensity focused ultrasound (HIFU). Photodynamic therapy methods using external light devices to activate photosensitizing agents can also be used to treat superficial tumors or deeper tumors when used with endoscopic catheters.
Quality control during and post treatment
For example: The use of high intensity focused ultrasound (HIFU) combined with nanoparticle therapeutics: HIFU is applied to improve drug delivery and to trigger drug release from nanoparticles. Gas-bubbles are playing the role of the drug’s nano-carrier. These are used both to increase the drug transport into the cell and as ultrasound-imaging contrast material. The ultrasound is also used for processes of drug-release and ablation.
Additional example; Multifunctional nanoparticles for tracking CED (convection enhanced delivery) distribution within tumors: Nanoparticle that could serve as a carrier not only for the therapeutic radionuclides but simultaneously also for a therapeutic drug and 4 different types of imaging contrast agents including an MRI contrast agent, PET and SPECT nuclear diagnostic imaging agents and optical contrast agents as shown below. The ability to perform multiple types of imaging on the same nanoparticles will allow studies investigating the distribution and retention of nanoparticles initially in vivo using non-invasive imaging and later at the histological level using optical imaging.
Conclusions
Image-guided radiotherapeutic nanoparticles have significant potential for solid tumor cancer therapy. The current success of this therapy in animals is most likely due to the improved accumulation, retention and dispersion of nanoparticles within solid tumor following image-guided therapies as well as the micro-field of the β-particle which reduces the requirement of perfectly homogeneous tumor coverage. It is also possible that the intratumoral distribution of nanoparticles may benefit from their uptake by intratumoral macrophages although more research is required to determine the importance of this aspect of intratumoral radionuclide nanoparticle therapy. This new approach to cancer therapy is a fertile ground for many new technological developments as well as for new understandings in the basic biology of cancer therapy. The clinical success of this approach will depend on progress in many areas of interdisciplinary research including imaging technology, nanoparticle technology, computer and robot assisted image-guided application of therapies, radiation physics and oncology. Close collaboration of a wide variety of scientists and physicians including chemists, nanotechnologists, drug delivery experts, radiation physicists, robotics and software experts, toxicologists, surgeons, imaging physicians, and oncologists will best facilitate the implementation of this novel approach to the treatment of cancer in the clinical environment. Image-guided nanoparticle therapies including those with β-emission radionuclide nanoparticles have excellent promise to significantly impact clinical cancer therapy and advance the field of drug delivery.
Current Advanced Research Topics in MRI-based Management of Cancer Patients
Author: Dror Nir, PhD
Step forward towards quantitative and reproducible MRI of cancer patients is the combination of structure and morphology based imaging with expressions of typical bio-chemical processes using imaging contrast materials. The following list brings the latest publications on this subject in Radiology magazine.
Purpose: To evaluate the effects of breast compression on breast cancer masses, contrast material enhancement of glandular tissue, and quality of magnetic resonance (MR) images in the identification and characterization of breast lesions.
Materials and Methods: This was a HIPAA-compliant, institutional review board–approved retrospective study, with waiver of informed consent. Images from 300 MR imaging examinations in 149 women (mean age ± standard deviation, 51.5 years ± 10.9; age range, 22–76 years) were evaluated. The women underwent diagnostic MR imaging (no compression) and MR-guided biopsy (with compression) between June 2008 and February 2013. Breast compression was expressed as a percentage relative to the noncompressed breast. Percentage enhancement difference was calculated between noncompressed- and compressed-breast images obtained in early and delayed contrast-enhanced phases. Breast density, lesion type (mass vs non-masslike enhancement [NMLE]), lesion size, percentage compression, and kinetic curve type were evaluated. Linear regression, receiver operating characteristic (ROC) curve analysis, and κ test were performed.
Conclusion: Breast compression during biopsy affected breast lesion detection, lesion size, and dynamic contrast-enhanced MR imaging interpretation and performance. Limiting the application of breast compression is recommended, except when clinically necessary.
Purpose: To characterize uptake of 1-amino-3-fluorine 18-fluorocyclobutane-1-carboxylic acid (18F FACBC) in patients with localized prostate cancer, benign prostatic hyperplasia (BPH), and normal prostate tissue and to evaluate its potential utility in delineation of intraprostatic cancers in histopathologically confirmed localized prostate cancer in comparison with magnetic resonance (MR) imaging.
Materials and Methods: Institutional review board approval and written informed consent were obtained for this HIPAA-compliant prospective study. Twenty-one men underwent dynamic and static abdominopelvic 18F FACBC combined positron emission tomography (PET) and computed tomography (CT) and multiparametric (MP) 3-T endorectal MR imaging before robotic-assisted prostatectomy. PET/CT and MR images were coregistered by using pelvic bones as fiducial markers; this was followed by manual adjustments. Whole-mount histopathologic specimens were sliced with an MR-based patient-specific mold. 18F FACBC PET standardized uptake values (SUVs) were compared with those at MR imaging and histopathologic analysis for lesion- and sector-based (20 sectors per patient) analysis. Positive and negative predictive values for each modality were estimated by using generalized estimating equations with logit link function and working independence correlation structure.
Conclusion: 18F FACBC PET/CT shows higher uptake in intraprostatic tumor foci than in normal prostate tissue; however, 18F FACBC uptake in tumors is similar to that in BPH nodules. Thus, it is not specific for prostate cancer. Nevertheless, combined 18F FACBC PET/CT and T2-weighted MR imaging enable more accurate localization of prostate cancer lesions than either modality alone.
Purpose: To perform a multilevel radiogenomics study to elucidate the glioblastoma multiforme (GBM) magnetic resonance (MR) imaging radiogenomic signatures resulting from changes in messenger RNA (mRNA) expression and DNA copy number variation (CNV).
Materials and Methods: Radiogenomic analysis was performed at MR imaging in 23 patients with GBM in this retrospective institutional review board–approved HIPAA-compliant study. Six MR imaging features—contrast enhancement, necrosis, contrast-to-necrosis ratio, infiltrative versus edematous T2 abnormality, mass effect, and subventricular zone (SVZ) involvement—were independently evaluated and correlated with matched genomic profiles (global mRNA expression and DNA copy number profiles) in a significant manner that also accounted for multiple hypothesis testing by using gene set enrichment analysis (GSEA), resampling statistics, and analysis of variance to gain further insight into the radiogenomic signatures in patients with GBM
Conclusion: Construction of an MR imaging, mRNA, and CNV radiogenomic association map has led to identification of MR traits that are associated with some known high-grade glioma biomarkers and association with genomic biomarkers that have been identified for other malignancies but not GBM. Thus, the traits and genes identified on this map highlight new candidate radiogenomic biomarkers for further evaluation in future studies.
Instruments that combine positron emission tomography (PET) and magnetic resonance (MR) imaging have recently been assembled for use in humans, and may have diagnostic performance superior to that of PET/computed tomography (CT) for particular clinical and research applications. MR imaging has major strengths compared with CT, including superior soft-tissue contrast resolution, multiplanar image acquisition, and functional imaging capability through specialized techniques such as diffusion-tensor imaging, diffusion-weighted (DW) imaging, functional MR imaging, MR elastography, MR spectroscopy, perfusion-weighted imaging, MR imaging with very short echo times, and the availability of some targeted MR imaging contrast agents. Furthermore, the lack of ionizing radiation from MR imaging is highly appealing, particularly when pediatric, young adult, or pregnant patients are to be imaged, and the safety profile of MR imaging contrast agents compares very favorably with iodinated CT contrast agents. MR imaging also can be used to guide PET image reconstruction, partial volume correction, and motion compensation for more accurate disease quantification and can improve anatomic localization of sites of radiotracer uptake, improve diagnostic performance, and provide for comprehensive regional and global structural, functional, and molecular assessment of various clinical disorders. In this review, we discuss the historical development, software-based registration, instrumentation and design, quantification issues, potential clinical applications, potential clinical roles of image segmentation and global disease assessment, and challenges related to PET/MR imaging.
The importance of spatially-localized and quantified image interpretation in cancer management
Writer & reporter: Dror Nir, PhD
I became involved in the development of quantified imaging-based tissue characterization more than a decade ago. From the start, it was clear to me that what clinicians needs will not be answered by just identifying whether a certain organ harbors cancer. If imaging devices are to play a significant role in future medicine, as a complementary source of information to bio-markers and gene sequencing the minimum value expected of them is accurate directing of biopsy needles and treatment tools to the malignant locations in the organ. Therefore, the design goal of the first Prostate-HistoScanning (“PHS”) version I went into the trouble of characterizing localized volume of tissue at the level of approximately 0.1cc (1x1x1 mm). Thanks to that, the imaging-interpretation overlay of PHS localizes the suspicious lesions with accuracy of 5mm within the prostate gland; Detection, localisation and characterisation of prostate cancer by prostate HistoScanning(™).
I then started a more ambitious research aiming to explore the feasibility of identifying sub-structures within the cancer lesion itself. The preliminary results of this exploration were so promising that it surprised not only the clinicians I was working with but also myself. It seems, that using quality ultrasound, one can find Imaging-Biomarkers that allows differentiation of inside structures of a cancerous lesions. Unfortunately, for everyone involved in this work, including me, this scientific effort was interrupted by financial constrains before reaching maturity.
My short introduction was made to explain why I find the publication below important enough to post and bring to your attention.
From the Departments of Radiology and Cancer Imaging and Metabolism, Moffitt Cancer Center, 12902 Magnolia Dr, Tampa, FL 33612. Address correspondence toR.A.G. (e-mail: Robert.Gatenby@Moffitt.org).
Abstract
Cancer therapy, even when highly targeted, typically fails because of the remarkable capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are both a cause and a consequence of cancer system heterogeneity at many scales, ranging from genetic properties of individual cells to large-scale imaging features. Tumors of the same organ and cell type can have remarkably diverse appearances in different patients. Furthermore, even within a single tumor, marked variations in imaging features, such as necrosis or contrast enhancement, are common. Similar spatial variations recently have been reported in genetic profiles. Radiologic heterogeneity within tumors is usually governed by variations in blood flow, whereas genetic heterogeneity is typically ascribed to random mutations. However, evolution within tumors, as in all living systems, is subject to Darwinian principles; thus, it is governed by predictable and reproducible interactions between environmental selection forces and cell phenotype (not genotype). This link between regional variations in environmental properties and cellular adaptive strategies may permit clinical imaging to be used to assess and monitor intratumoral evolution in individual patients. This approach is enabled by new methods that extract, report, and analyze quantitative, reproducible, and mineable clinical imaging data. However, most current quantitative metrics lack spatialness, expressing quantitative radiologic features as a single value for a region of interest encompassing the whole tumor. In contrast, spatially explicit image analysis recognizes that tumors are heterogeneous but not well mixed and defines regionally distinct habitats, some of which appear to harbor tumor populations that are more aggressive and less treatable than others. By identifying regional variations in key environmental selection forces and evidence of cellular adaptation, clinical imaging can enable us to define intratumoral Darwinian dynamics before and during therapy. Advances in image analysis will place clinical imaging in an increasingly central role in the development of evolution-based patient-specific cancer therapy.
Cancers are heterogeneous across a wide range of temporal and spatial scales. Morphologic heterogeneity between and within cancers is readily apparent in clinical imaging, and subjective descriptors of these differences, such as necrotic, spiculated, and enhancing, are common in the radiology lexicon. In the past several years, radiology research has increasingly focused on quantifying these imaging variations in an effort to understand their clinical and biologic implications (1,2). In parallel, technical advances now permit extensive molecular characterization of tumor cells in individual patients. This has led to increasing emphasis on personalized cancer therapy, in which treatment is based on the presence of specific molecular targets (3). However, recent studies (4,5) have shown that multiple genetic subpopulations coexist within cancers, reflecting extensive intratumoral somatic evolution. This heterogeneity is a clear barrier to therapy based on molecular targets, since the identified targets do not always represent the entire population of tumor cells in a patient (6,7). It is ironic that cancer, a disease extensively and primarily analyzed genetically, is also the most genetically flexible of all diseases and, therefore, least amenable to such an approach.
Genetic variations in tumors are typically ascribed to a mutator phenotype that generates new clones, some of which expand into large populations (8). However, although identification of genotypes is of substantial interest, it is insufficient for complete characterization of tumor dynamics because evolution is governed by the interactions of environmental selection forces with the phenotypic, not genotypic, properties of populations as shown, for example, by evolutionary convergence to identical phenotypes among cave fish even when they are from different species (9–11). This connection between tissue selection forces and cellular properties has the potential to provide a strong bridge between medical imaging and the cellular and molecular properties of cancers.
We postulate that differences within tumors at different spatial scales (ie, at the radiologic, cellular, and molecular [genetic] levels) are related. Tumor characteristics observable at clinical imaging reflect molecular-, cellular-, and tissue-level dynamics; thus, they may be useful in understanding the underlying evolving biology in individual patients. A challenge is that such mapping across spatial and temporal scales requires not only objective reproducible metrics for imaging features but also a theoretical construct that bridges those scales (Fig 1).
Figure 1a: Computed tomographic (CT) scan of right upper lobe lung cancer in a 50-year-old woman.
Figure 1b: Isoattenuation map shows regional heterogeneity at the tissue scale (measured in centimeters).
Figure 1c & 1d: (c, d)Whole-slide digital images (original magnification, ×3) of a histologic slice of the same tumor at the mesoscopic scale (measured in millimeters) (c) coupled with a masked image of regional morphologic differences showing spatial heterogeneity (d).
Figure 1e:Subsegment of the whole slide image shows the microscopic scale (measured in micrometers) (original magnification, ×50).
Figure 1f: Pattern recognition masked image shows regional heterogeneity. In a, the CT image of non–small cell lung cancer can be analyzed to display gradients of attenuation, which reveals heterogeneous and spatially distinct environments (b). Histologic images in the same patient (c, e) reveal heterogeneities in tissue structure and density on the same scale as seen in the CT images. These images can be analyzed at much higher definition to identify differences in morphologies of individual cells (3), and these analyses reveal clusters of cells with similar morphologic features (d, f). An important goal of radiomics is to bridge radiologic data with cellular and molecular characteristics observed microscopically.
To promote the development and implementation of quantitative imaging methods, protocols, and software tools, the National Cancer Institute has established the Quantitative Imaging Network. One goal of this program is to identify reproducible quantifiable imaging features of tumors that will permit data mining and explicit examination of links between the imaging findings and the underlying molecular and cellular characteristics of the tumors. In the quest for more personalized cancer treatments, these quantitative radiologic features potentially represent nondestructive temporally and spatially variable predictive and prognostic biomarkers that readily can be obtained in each patient before, during, and after therapy.
Quantitative imaging requires computational technologies that can be used to reliably extract mineable data from radiographic images. This feature information can then be correlated with molecular and cellular properties by using bioinformatics methods. Most existing methods are agnostic and focus on statistical descriptions of existing data, without presupposing the existence of specific relationships. Although this is a valid approach, a more profound understanding of quantitative imaging information may be obtained with a theoretical hypothesis-driven framework. Such models use links between observable tumor characteristics and microenvironmental selection factors to make testable predictions about emergent phenotypes. One such theoretical framework is the developing paradigm of cancer as an ecologic and evolutionary process.
For decades, landscape ecologists have studied the effects of heterogeneity in physical features on interactions between populations of organisms and their environments, often by using observation and quantification of images at various scales (12–14). We propose that analytic models of this type can easily be applied to radiologic studies of cancer to uncover underlying molecular, cellular, and microenvironmental drivers of tumor behavior and specifically, tumor adaptations and responses to therapy (15).
In this article, we review recent developments in quantitative imaging metrics and discuss how they correlate with underlying genetic data and clinical outcomes. We then introduce the concept of using ecology and evolutionary models for spatially explicit image analysis as an exciting potential avenue of investigation.
Quantitative Imaging and Radiomics
In patients with cancer, quantitative measurements are commonly limited to measurement of tumor size with one-dimensional (Response Evaluation Criteria in Solid Tumors [or RECIST]) or two-dimensional (World Health Organization) long-axis measurements (16). These measures do not reflect the complexity of tumor morphology or behavior, and in many cases, changes in these measures are not predictive of therapeutic benefit (17). In contrast, radiomics (18) is a high-throughput process in which a large number of shape, edge, and texture imaging features are extracted, quantified, and stored in databases in an objective, reproducible, and mineable form (Figs 1, 2). Once transformed into a quantitative form, radiologic tumor properties can be linked to underlying genetic alterations (the field is called radiogenomics) (19–21) and to medical outcomes (22–27). Researchers are currently working to develop both a standardized lexicon to describe tumor features (28,29) and a standard method to convert these descriptors into quantitative mineable data (30,31) (Fig 3).
Figure 2: Contrast-enhanced CT scans show non–small cell lung cancer (left) and corresponding cluster map (right). Subregions within the tumor are identified by clustering pixels based on the attenuation of pixels and their cumulative standard deviation across the region. While the entire region of interest of the tumor, lacking the spatial information, yields a weighted mean attenuation of 859.5 HU with a large and skewed standard deviation of 243.64 HU, the identified subregions have vastly different statistics. Mean attenuation was 438.9 HU ± 45 in the blue subregion, 210.91 HU ± 79 in the yellow subregion, and 1077.6 HU ± 18 in the red subregion.
Figure 3: Chart shows the five processes in radiomics.
Several recent articles underscore the potential power of feature analysis. After manually extracting more than 100 CT image features, Segal and colleagues found that a subset of 14 features predicted 80% of the gene expression pattern in patients with hepatocellular carcinoma (21). A similar extraction of features from contrast agent–enhanced magnetic resonance (MR) images of glioblastoma was used to predict immunohistochemically identified protein expression patterns (22). Other radiomic features, such as texture, can be used to predict response to therapy in patients with renal cancer (32) and prognosis in those with metastatic colon cancer (33).
These pioneering studies were relatively small because the image analysis was performed manually, and the studies were consequently underpowered. Thus, recent work in radiomics has focused on technical developments that permit automated extraction of image features with the potential for high throughput. Such methods, which rely heavily on novel machine learning algorithms, can more completely cover the range of quantitative features that can describe tumor heterogeneity, such as texture, shape, or margin gradients or, importantly, different environments, or niches, within the tumors.
Generally speaking, texture in a biomedical image is quantified by identifying repeating patterns. Texture analyses fall into two broad categories based on the concepts of first- and second-order spatial statistics. First-order statistics are computed by using individual pixel values, and no relationships between neighboring pixels are assumed or evaluated. Texture analysis methods based on first-order statistics usually involve calculating cumulative statistics of pixel values and their histograms across the region of interest. Second-order statistics, on the other hand, are used to evaluate the likelihood of observing spatially correlated pixels (34). Hence, second-order texture analyses focus on the detection and quantification of nonrandom distributions of pixels throughout the region of interest.
The technical developments that permit second-order texture analysis in tumors by using regional enhancement patterns on dynamic contrast-enhanced MR images were reviewed recently (35). One such technique that is used to measure heterogeneity of contrast enhancement uses the Factor Analysis of Medical Image Sequences (or FAMIS) algorithm, which divides tumors into regions based on their patterns of enhancement (36). Factor Analysis of Medical Image Sequences–based analyses yielded better prognostic information when compared with region of interest–based methods in numerous cancer types (19–21,37–39), and they were a precursor to the Food and Drug Administration–approved three-time-point method (40). A number of additional promising methods have been developed. Rose and colleagues showed that a structured fractal-based approach to texture analysis improved differentiation between low- and high-grade brain cancers by orders of magnitude (41). Ahmed and colleagues used gray level co-occurrence matrix analyses of dynamic contrast-enhanced images to distinguish benign from malignant breast masses with high diagnostic accuracy (area under the receiver operating characteristic curve, 0.92) (26). Others have shown that Minkowski functional structured methods that convolve images with differently kernelled masks can be used to distinguish subtle differences in contrast enhancement patterns and can enable significant differentiation between treatment groups (42).
It is not surprising that analyses of heterogeneity in enhancement patterns can improve diagnosis and prognosis, as this heterogeneity is fundamentally based on perfusion deficits, which generate significant microenvironmental selection pressures. However, texture analysis is not limited to enhancement patterns. For example, measures of heterogeneity in diffusion-weighted MR images can reveal differences in cellular density in tumors, which can be matched to histologic findings (43). Measures of heterogeneity in T1- and T2-weighted images can be used to distinguish benign from malignant soft-tissue masses (23). CT-based texture features have been shown to be highly significant independent predictors of survival in patients with non–small cell lung cancer (24).
Texture analyses can also be applied to positron emission tomographic (PET) data, where they can provide information about metabolic heterogeneity (25,26). In a recent study, Nair and colleagues identified 14 quantitative PET imaging features that correlated with gene expression (19). This led to an association of metagene clusters to imaging features and yielded prognostic models with hazard ratios near 6. In a study of esophageal cancer, in which 38 quantitative features describing fluorodeoxyglucose uptake were extracted, measures of metabolic heterogeneity at baseline enabled prediction of response with significantly higher sensitivity than any whole region of interest standardized uptake value measurement (22). It is also notable that these extensive texture-based features are generally more reproducible than simple measures of the standardized uptake value (27), which can be highly variable in a clinical setting (44).
Spatially Explicit Analysis of Tumor Heterogeneity
Although radiomic analyses have shown high prognostic power, they are not inherently spatially explicit. Quantitative border, shape, and texture features are typically generated over a region of interest that comprises the entire tumor (45). This approach implicitly assumes that tumors are heterogeneous but well mixed. However, spatially explicit subregions of cancers are readily apparent on contrast-enhanced MR or CT images, as perfusion can vary markedly within the tumor, even over short distances, with changes in tumor cell density and necrosis.
An example is shown in Figure 2, which shows a contrast-enhanced CT scan of non–small cell lung cancer. Note that there are many subregions within this tumor that can be identified with attenuation gradient (attenuation per centimeter) edge detection algorithms. Each subregion has a characteristic quantitative attenuation, with a narrow standard deviation, whereas the mean attenuation over the entire region of interest is a weighted average of the values across all subregions, with a correspondingly large and skewed distribution. We contend that these subregions represent distinct habitats within the tumor, each with a distinct set of environmental selection forces.
These observations, along with the recent identification of regional variations in the genetic properties of tumor cells, indicate the need to abandon the conceptual model of cancers as bounded organlike structures. Rather than a single self-organized system, cancers represent a patchwork of habitats, each with a unique set of environmental selection forces and cellular evolution strategies. For example, regions of the tumor that are poorly perfused can be populated by only those cells that are well adapted to low-oxygen, low-glucose, and high-acid environmental conditions. Such adaptive responses to regional heterogeneity result in microenvironmental selection and hence, emergence of genetic variations within tumors. The concept of adaptive response is an important departure from the traditional view that genetic heterogeneity is the product of increased random mutations, which implies that molecular heterogeneity is fundamentally unpredictable and, therefore, chaotic. The Darwinian model proposes that genetic heterogeneity is the result of a predictable and reproducible selection of successful adaptive strategies to local microenvironmental conditions.
Current cross-sectional imaging modalities can be used to identify regional variations in selection forces by using contrast-enhanced, cell density–based, or metabolic features. Clinical imaging can also be used to identify evidence of cellular adaptation. For example, if a region of low perfusion on a contrast-enhanced study is necrotic, then an adaptive population is absent or minimal. However, if the poorly perfused area is cellular, then there is presumptive evidence of an adapted proliferating population. While the specific genetic properties of this population cannot be determined, the phenotype of the adaptive strategy is predictable since the environmental conditions are more or less known. Thus, standard medical images can be used to infer specific emergent phenotypes and, with ongoing research, these phenotypes can be associated with underlying genetic changes.
This area of investigation will likely be challenging. As noted earlier, the most obvious spatially heterogeneous imaging feature in tumors is perfusion heterogeneity on contrast-enhanced CT or MR images. It generally has been assumed that the links between contrast enhancement, blood flow, perfusion, and tumor cell characteristics are straightforward. That is, tumor regions with decreased blood flow will exhibit low perfusion, low cell density, and high necrosis. In reality, however, the dynamics are actually much more complex. As shown in Figure 4, when using multiple superimposed sequences from MR imaging of malignant gliomas, regions of tumor that are poorly perfused on contrast-enhanced T1-weighted images may exhibit areas of low or high water content on T2-weighted images and low or high diffusion on diffusion-weighted images. Thus, high or low cell densities can coexist in poorly perfused volumes, creating perfusion-diffusion mismatches. Regions with poor perfusion with high cell density are of particular clinical interest because they represent a cell population that is apparently adapted to microenvironmental conditions associated with poor perfusion. The associated hypoxia, acidosis, and nutrient deprivation select for cells that are resistant to apoptosis and thus are likely to be resistant to therapy (46,47).
Figure 4: Left: Contrast-enhanced T1 image from subject TCGA-02-0034 in The Cancer Genome Atlas–Glioblastoma Multiforme repository of MR volumes of glioblastoma multiforme cases. Right: Spatial distribution of MR imaging–defined habitats within the tumor. The blue region (low T1 postgadolinium, low fluid-attenuated inversion recovery) is particularly notable because it presumably represents a habitat with low blood flow but high cell density, indicating a population presumably adapted to hypoxic acidic conditions.
Furthermore, other selection forces not related to perfusion are likely to be present within tumors. For example, evolutionary models suggest that cancer cells, even in stable microenvironments, tend to speciate into “engineers” that maximize tumor cell growth by promoting angiogenesis and “pioneers” that proliferate by invading normal issue and co-opting the blood supply. These invasive tumor phenotypes can exist only at the tumor edge, where movement into a normal tissue microenvironment can be rewarded by increased proliferation. This evolutionary dynamic may contribute to distinct differences between the tumor edges and the tumor cores, which frequently can be seen at analysis of cross-sectional images (Fig 5).
Figure 5a: CT images obtained with conventional entropy filtering in two patients with non–small cell lung cancer with no apparent textural differences show similar entropy values across all sections.
Figure 5b: Contour plots obtained after the CT scans were convolved with the entropy filter. Further subdividing each section in the tumor stack into tumor edge and core regions (dotted black contour) reveals varying textural behavior across sections. Two distinct patterns have emerged, and preliminary analysis shows that the change of mean entropy value between core and edge regions correlates negatively with survival.
Interpretation of the subsegmentation of tumors will require computational models to understand and predict the complex nonlinear dynamics that lead to heterogeneous combinations of radiographic features. We have exploited ecologic methods and models to investigate regional variations in cancer environmental and cellular properties that lead to specific imaging characteristics. Conceptually, this approach assumes that regional variations in tumors can be viewed as a coalition of distinct ecologic communities or habitats of cells in which the environment is governed, at least to first order, by variations in vascular density and blood flow. The environmental conditions that result from alterations in blood flow, such as hypoxia, acidosis, immune response, growth factors, and glucose, represent evolutionary selection forces that give rise to local-regional phenotypic adaptations. Phenotypic alterations can result from epigenetic, genetic, or chromosomal rearrangements, and these in turn will affect prognosis and response to therapy. Changes in habitats or the relative abundance of specific ecologic communities over time and in response to therapy may be a valuable metric with which to measure treatment efficacy and emergence of resistant populations.
Emerging Strategies for Tumor Habitat Characterization
A method for converting images to spatially explicit tumor habitats is shown in Figure 4. Here, three-dimensional MR imaging data sets from a glioblastoma are segmented. Each voxel in the tumor is defined by a scale that includes its image intensity in different sequences. In this case, the imaging sets are from (a) a contrast-enhanced T1 sequence, (b) a fast spin-echo T2 sequence, and (c) a fluid-attenuated inversion-recovery (or FLAIR) sequence. Voxels in each sequence can be defined as high or low based on their value compared with the mean signal value. By using just two sequences, a contrast-enhanced T1 sequence and a fluid-attenuated inversion-recovery sequence, we can define four habitats: high or low postgadolinium T1 divided into high or low fluid-attenuated inversion recovery. When these voxel habitats are projected into the tumor volume, we find they cluster into spatially distinct regions. These habitats can be evaluated both in terms of their relative contributions to the total tumor volume and in terms of their interactions with each other, based on the imaging characteristics at the interfaces between regions. Similar spatially explicit analysis can be performed with CT scans (Fig 5).
Analysis of spatial patterns in cross-sectional images will ultimately require methods that bridge spatial scales from microns to millimeters. One possible method is a general class of numeric tools that is already widely used in terrestrial and marine ecology research to link species occurrence or abundance with environmental parameters. Species distribution models (48–51) are used to gain ecologic and evolutionary insights and to predict distributions of species or morphs across landscapes, sometimes extrapolating in space and time. They can easily be used to link the environmental selection forces in MR imaging-defined habitats to the evolutionary dynamics of cancer cells.
Summary
Imaging can have an enormous role in the development and implementation of patient-specific therapies in cancer. The achievement of this goal will require new methods that expand and ultimately replace the current subjective qualitative assessments of tumor characteristics. The need for quantitative imaging has been clearly recognized by the National Cancer Institute and has resulted in formation of the Quantitative Imaging Network. A critical objective of this imaging consortium is to use objective, reproducible, and quantitative feature metrics extracted from clinical images to develop patient-specific imaging-based prognostic models and personalized cancer therapies.
It is increasingly clear that tumors are not homogeneous organlike systems. Rather, they contain regional coalitions of ecologic communities that consist of evolving cancer, stroma, and immune cell populations. The clinical consequence of such niche variations is that spatial and temporal variations of tumor phenotypes will inevitably evolve and present substantial challenges to targeted therapies. Hence, future research in cancer imaging will likely focus on spatially explicit analysis of tumor regions.
Clinical imaging can readily characterize regional variations in blood flow, cell density, and necrosis. When viewed in a Darwinian evolutionary context, these features reflect regional variations in environmental selection forces and can, at least in principle, be used to predict the likely adaptive strategies of the local cancer population. Hence, analyses of radiologic data can be used to inform evolutionary models and then can be mapped to regional population dynamics. Ecologic and evolutionary principles may provide a theoretical framework to link imaging to the cellular and molecular features of cancer cells and ultimately lead to a more comprehensive understanding of specific cancer biology in individual patients.
Essentials
• Marked heterogeneity in genetic properties of different cells in the same tumor is typical and reflects ongoing intratumoral evolution.
• Evolution within tumors is governed by Darwinian dynamics, with identifiable environmental selection forces that interact with phenotypic (not genotypic) properties of tumor cells in a predictable and reproducible manner; clinical imaging is uniquely suited to measure temporal and spatial heterogeneity within tumors that is both a cause and a consequence of this evolution.
• Subjective radiologic descriptors of cancers are inadequate to capture this heterogeneity and must be replaced by quantitative metrics that enable statistical comparisons between features describing intratumoral heterogeneity and clinical outcomes and molecular properties.
• Spatially explicit mapping of tumor regions, for example by superimposing multiple imaging sequences, may permit patient-specific characterization of intratumoral evolution and ecology, leading to patient- and tumor-specific therapies.
• We summarize current information on quantitative analysis of radiologic images and propose future quantitative imaging must become spatially explicit to identify intratumoral habitats before and during therapy.
Disclosures of Conflicts of Interest: R.A.G. No relevant conflicts of interest to disclose. O.G. No relevant conflicts of interest to disclose.R.J.G. No relevant conflicts of interest to disclose.
Acknowledgments
The authors thank Mark Lloyd, MS; Joel Brown, PhD; Dmitry Goldgoff, PhD; and Larry Hall, PhD, for their input to image analysis and for their lively and informative discussions.
Footnotes
Received December 18, 2012; revision requested February 5, 2013; revision received March 11; accepted April 9; final version accepted April 29.
Funding: This research was supported by the National Institutes of Health (grants U54CA143970-01, U01CA143062; R01CA077575, andR01CA170595).
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