Posts Tagged ‘Magnetic resonance imaging’

New development in measuring mechanical properties of tissue

Author – Writer: Dror Nir, PhD

Measuring the effects induced onto imaging by the mechanical properties of tissue is a common approach to differentiate tissue abnormalities. In previous posts I discussed the applicability of imaging applications that visualize variations in tissue stiffness; e.g. ultrasound-elastography and MRI-elastography as aid in the diagnosis workflow of cancer. Today, I would like to report on a recent publication made in SPIE Newsroom describing an optical-imaging system to measure tissue stiffness at high resolution. I think that such emerging technologies should be followed up as they bear promise to bridge deficiencies of the traditional modalities currently in use.

Reporting on: Optical elastography probes mechanical properties of tissue at high resolution

By: David Sampson, Kelsey Kennedy, Robert McLaughlin and Brendan Kennedy

Information published at: SPIE Newsroom – Biomedical Optics & Medical Imaging

Probing the micro-mechanical properties of tissue using optical imaging might offer new surgical tools that enable improved differentiation of tissue pathologies, such as cancer or atherosclerosis.

11 January 2013, SPIE Newsroom. DOI: 10.1117/2.1201212.004605

Elastography is an emerging branch of medical imaging that uses mechanical contrast to better characterize tissue pathology than can be achieved with structural imaging alone. It achieves this by imaging a tissue’s response to mechanical loading. Although commercial products based on ultrasonography and magnetic resonance imaging (MRI) have been available for several years, these new modalities offer superior tissue differentiation deep in the human body. However, elastography is limited by its low resolution compared with the length scales relevant to many diseases. Increasing the resolution with optical techniques might offer new opportunities for elastography in medical imaging and surgical guidance.

An elastography system requires a means of loading the tissue to cause deformation and an imaging system with sufficient sensitivity and range to capture this deformation. Implicit in these requirements is access to the tissue of interest. Optical elastography has previously been largely based on schemes that suit small tissue samples rather than intact tissue in living humans. Additionally, such schemes have not had the sensitivity or range to produce high-fidelity images of mechanical properties. We have addressed both these issues in our recent work, developing the means to access tissues in vivo and improve the sensitivity and range of optical elastography using phase-sensitive optical coherence tomography as the underlying modality. The use of optical coherence tomography to perform elastography has come to be referred to as optical coherence elastography.1

To make optical coherence elastography on human subjects feasible, we designed an annular piezoelectric loading transducer (see Figure 1), through which we could simultaneously image, enabling the first in vivo dynamic optical coherence elastography on human subjects.2 We were subsequently able to extend this to three dimensions (see Figure 2), in collaboration with Stephen Boppart’s group at the University of Illinois at Urbana-Champaign.3 This extension took advantage of the high speed of spectral-domain optical coherence tomography, and the maturity of phase-sensitive detection techniques originally developed for Doppler flowmetry and microangiography.

Figure 1. Schematic (left) and photograph (right) of the annular load transducer and imaging optics for in vivo optical coherence elastography.


Figure 2. 2D images of in vivo human skin selected from 3D stacks. (a) Optical coherence tomography image and (b) the same image overlaid by the 2D dynamic elastogram recorded at 125Hz load frequency, highlighting the greater strain in the epidermis. Reprinted in modified form with permission.3

For general access to tissues in the body, optical coherence elastography faces two basic limitations. The free-space probe requires miniaturization for versatile access to tissue in confined or convoluted geometries. We addressed this in studies of the elastic properties of human airways using catheter-based anatomical optical coherence tomography.4


Figure 3. (a) Schematic diagram of needle optical coherence elastography. The phase difference Δφ=φ1– φ2 determines the displacement, d, when scaled by the wavelength, λ, and refractive index, n. (b) Needle and pig trachea. (c) Local displacement versus distance, with tissue boundaries indicated by red stars. (d) Representative histology. Reprinted in modified form with permission.6

More fundamentally, optical coherence tomography can only penetrate, at best, 1–2mm into most tissues, limiting it to superficial applications. To address this issue, we combined optical coherence elastography with needle probes, an active research area in our group (see Figure 3).5 We conveniently use the needle probe itself to deform the tissue during insertion.6 The deformation ahead of the needle tip depends on the mechanical properties of the tissue encountered, as well as on the nearby tissue environment, particularly on any interfaces ahead of it. We measure the local sub-micrometer displacement of the tissue between two positions of the moving needle probe. We plot this displacement versus distance ahead of the probe: see Figure 3(c). The slope of the displacement at location z is a measure of the local strain. A change in slope signifies a change in tissue stiffness; the steeper the slope, the softer the tissue (other things being equal). Figure 3 highlights this effect in a layered sample of pig trachea. The positions of the changes in slope correlate well with the tissue interfaces shown in the accompanying histology: see Figure 3(d).

The other key area of improvement we have focused on is lowering the optical coherence elastography noise floor by increasing the detection sensitivity, which is vital to make clinical imaging practical. We firstly showed that Gaussian-smoothed, weighted-least squares strain estimation improved the sensitivity of estimates by up to 12dB over conventional finite-difference methods.7 Next, we showed that performance could be further improved at low optical coherence tomo- graphy signal-to-noise ratios (and, therefore, at greater depths in tissue) by employing a 2D Fourier transform technique.8Combined with other system refinements, these improvements have enabled us to reach a displacement sensitivity of 300pm for typical optical coherence tomography signal-to-noise ratios in tissue, with room for improvement.

The Young’s modulus of soft tissue varies from kPa to tens of MPa, whereas the scattering coefficient of such tissues—which is largely responsible for determining the contrast of optical coherence tomography—is typically in the range 2–20mm−1. This apparent native advantage in mechanical over optical contrast (see the example in Figure 4), combined with the maturation of optical coherence elastography methods, bodes well for the future. In our group, we are pursuing tumor-margin identification using elastography; others have begun to consider corneal elastography,9, 10 and still others are examining shear wave schemes with the aim of probing Young’s modulus much deeper in tissues.11,12


Figure 4. Optical coherence tomography (a) and optical coherence elastography (b) images of the same phantom with two inclusions visible, showing enhanced mechanical over scattering contrast.

Optical elastography currently sits at a similar stage of development as ultrasound elastography did in 1999. Based on a similar trajectory, this field will rapidly expand over the next decade. Our recent results point to the first convincing applications of optical elastography being just around the corner.

We acknowledge funding for this work from Perpetual Trustees, the Raine Medical Research Foundation, the Cancer Council of Western Australia, the Australian Research Council, the National Health and Medical Research Council (Australia), and the National Breast Cancer Foundation (Australia).

David Sampson

Optical+Biomedical Engineering Laboratory
School of Electrical, Electronic and Computer Engineering

Centre for Microscopy, Characterisation and Analysis
The University of Western Australia

Perth, Australia
Kelsey Kennedy, Robert McLaughlin, Brendan Kennedy

Optical+Biomedical Engineering Laboratory
School of Electrical, Electronic and Computer Engineering
The University of Western Australia

Perth, Australia

1. J. Schmitt, OCT elastography: imaging microscopic deformation and strain of tissue, Opt. Express 3(6), p. 199-211, 1998.doi:10.1364/OE.3.000199
2. B. F. Kennedy, T. R. Hillman, R. A. McLaughlin, B. C. Quirk, D. D. Sampson, In vivo dynamic optical coherence elastography using a ring actuator, Opt. Express 17(24), p. 21762-21772, 2009.doi:10.1364/OE.17.021762
3. B. F. Kennedy, X. Liang, S. G. Adie, D. K. Gerstmann, B. C. Quirk, S. A. Boppart, D. D. Sampson, In vivo three-dimensional optical coherence elastography, Opt. Express 19(7), p. 6623-6634, 2011.doi:10.1364/OE.19.006623
4. J. P. Williamson, R. A. McLaughlin, W. J. Noffsingerl, A. L. James, V. A. Baker, A. Curatolo, J. J. Armstrong, Elastic properties of the central airways in obstructive lung diseases measured using anatomical optical coherence tomography, Am. J. Resp. Crit. Care 183(5), p. 612-619, 2011.doi:10.1164/rccm.201002-0178OC
5. R. A. McLaughlin, B. C. Quirk, A. Curatolo, R. W. Kirk, L. Scolaro, D. Lorenser, P. D. Robbins, B. A. Wood, C. M. Saunders, D. D. Sampson, Imaging of breast cancer with optical coherence tomography needle probes: Feasibility and initial results, IEEE J. Sel. Topics Quantum Electron. 18(3), p. 1184-1191, 2012. doi:10.1109/JSTQE.2011.2166757
6. K. M. Kennedy, B. F. Kennedy, R. A. McLaughlin, D. D. Sampson, Needle optical coherence elastography for tissue boundary detection, Opt. Lett. 37(12), p. 2310-2312, 2012. doi:10.1364/OL.37.002310
7. B. F. Kennedy, S. H. Koh, R. A. McLaughlin, K. M. Kennedy, P. R. T. Munro, D. D. Sampson, Strain estimation in phase-sensitive optical coherence elastography, Biomed. Opt. Express 3(8), p. 1865-1879, 2012.doi:10.1364/BOE.3.001865
8. B. F. Kennedy, M. Wojtkowski, M. Szkulmowski, K. M. Kennedy, K. Karnowski, D. D. Sampson, Improved measurement of vibration amplitude in dynamic optical coherence elastography, Biomed. Opt. Express 3(12), p. 3138-3152, 2012. doi:10.1364/BOE.3.003138
9. R. K. Manapuram, S. R. Aglyamov, F. M. Monediado, M. Mashiatulla, J. Li, S. Y. Emelianov, K. V. Larin, In vivo estimation of elastic wave parameters using phase-stabilized swept source optical coherence elastography, J. Biomed. Opt. 17(10), p. 100501, 2012.doi:10.1117/1.JBO.17.10.100501
10. W. Qi, R. Chen, L. Chou, G. Liu, J. Zhang, Q. Zhou, Z. Chen, Phase-resolved acoustic radiation force optical coherence elastography, J. Biomed. Opt. 17(11), p. 110505, 2012. doi:10.1117/1.JBO.17.11.110505
11. C. Li, G. Guan, S. Li, Z. Huang, R. K. Wang, Evaluating elastic properties of heterogeneous soft tissue by surface acoustic waves detected by phase-sensitive optical coherence tomography, J. Biomed. Opt. 17(5), p. 057002, 2012. doi:10.1117/1.JBO.17.5.057002
12. M. Razani, A. Mariampillai, C. Sun, T. W. H. Luk, V. X. D. Yang, M. C. Kolios, Feasibility of optical coherence elastography measurements of shear wave propagation in homogeneous tissue equivalent phantoms,Biomed. Opt. Express 3(5), p. 972-980, 2012. doi:10.1364/BOE.3.00097

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Author and curator: Ritu Saxena, Ph.D.

This post attempts to integrate three posts and to embed all comments made to all three papers, allowing the reader a critically thought compilation of evidence-based medicine and scientific discourse.

Dr. Dror Nir authored a post on October 16th titled “Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?” The article attracted over 20 comments from readers including researchers and oncologists debating the following issues:

  • imaging technologies in cancer
  • tumor size, and
  • tumor response to treatment.

The debate lead to several new posts authored by:

This post is a compilation of the views of authors representing different specialties including research and medicine. In medicine: Pathology, Oncology Surgery and Medical Imaging, are represented.

Dr. Nir’s post talked about an advanced technique developed by the researchers at Sunnybrook Health Sciences Centre, University of Toronto, Canada for cancer lesions’ detection and image-guided cancer treatment in the specific Region of Interest (ROI). The group was successfully able to show the feasibility and safety of magnetic resonance imaging (MRI) – controlled transurethral ultrasound therapy for prostate cancer in eight patients.

The dilemma of defining the Region of Interest for imaging-based therapy

Dr. Bernstein, one of the authors at, a Fellow of the American College of Pathology, reiterated the objective of the study stating that “Their study’s objective was to prove that using real-time MRI guidance of HIFU treatment is possible and it guarantees that the location of ablated tissue indeed corresponds to the locations planned for treatment.” He expressed his opinion about the study by bringing into focus a very important issue i.e., given the fact that the part surrounding the cancer tissue is in the transition state, challenge in defining a ROI that could be approached by imaging-based therapy. Regarding the study discussed, he states – “This is a method demonstration, but not a proof of concept by any means.  It adds to the cacophany of approaches, and in a much larger study would prove to be beneficial in treatment, but not a cure for serious prostate cancer because it is unlikely that it can get beyond the margin, and also because there is overtreatment at the cutoff of PSA at 4.0. I think that the pathologist has to see the tissue, and the standard in pathology now is for any result that is cancer, two pathologists or a group sitting together should see it. It’s not an easy diagnosis.”

“The crux of the matter in terms of capability is that the cancer tissue, adjacent tissue, and the fibrous matrix are all in transition to the cancerous state. It is taught to resect leaving “free margin”, which is better aesthetically, and has had success in breast surgery. The dilemma is that the patient may return, but how soon?” concludes Dr. Larry.

Dr. Nir responded, “The philosophy behind lumpectomy is preserving quality of life. It was Prof. Veronesi (IEO) who introduced this method 30 years ago noticing that in the majority of cases; the patient will die from something else before presenting recurrence of breast cancer. It is well established that when the resection margins are declared by a pathologist (as good as he/she could be) as “free of cancer”, the probability of recurrence is much lower than otherwise. He explains further, “The worst enemy of finding solutions is doing nothing while using the excuse of looking for the “ultimate solution.” Personally, I believe in combining methods and improving clinical assessment based on information fusion. Being able to predict, and then timely track the response to treatment is a major issue that affects survival and costs!

In this discussion my view is expressed, below.

  • The paper that discusses imaging technique had the objective of finding out whether real-time MRI guidance of treatment was even possible and if yes, whether the treatment could be performed in accurate location of the ROI? The data reveals they were pretty successful in accomplishing their objective and of course that gives hope to the imaging-based targeted therapies.
  • Whether the ROI is defined properly and if it accounts for the real tumor cure, is a different question. Role of pathologists and the histological analysis and what they bring to the table cannot be ruled out, and the absence of a defined line between the tumor and the stromal region in the vicinity is well documented. However, that cannot rule out the value and scope of imaging-based detection and targeted therapy. After all, it is seminal in guiding minimally invasive surgery.
  • As another arm of personalized medicine-based cure for cancer, molecular biologists at MD Anderson have suggested molecular and genetic profiling of the tumor to determine genetic aberrations on the basis of which matched-therapy could be recommended to patients.
  • When phase I trial was conducted, the results were encouraging and the survival rate was better in matched-therapy patients compared to unmatched patients. Therefore, every time there is more to consider when treating a cancer patient and who knows a combination of views of oncologists, pathologists, molecular biologists, geneticists, surgeons would device improvised protocols for diagnosis and treatment. It is always going to be complicated and generalizations would never give an answer. Smart interpretations of therapies – imaging-based or others would always be required!

To read additional comments, including those from Dr. Williams, Dr. Lev-Ari, refers to:

Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention? Author and Reporter: Dror Nir, Ph.D.

Dr. Lev-Ari in her paper linked three fields that bear weight in the determination of Tumor Response to Therapy:

  • Personalized Medicine
  • Cancer Cell Biology, and
  • Minimally Invasive Surgery (MIS)

Her objectives were to address research methodology, the heterogeneity innate to Cancer Cell Biology and Treatment choice in the Operating Room — all are related to the topic at hand: How to deliver optimal care with least invasive intervention course.

Any attempt aimed at approaching this desirable result, called Personalized Medicine,  involves engagement in three strategies:

  • prediction of Patient’s reaction to Drug induction
  • design of Clinical Trials to validate drug efficacy on small subset of patients predicted to react favorable to drug regimen, increasing validity and reliability
  • Genetical identification of patients at no need to have a drug administered if non sensitivity to the drug has been predicted

These method are to be applied to a list of 56 leading Cancer types.

While the executive task of the clinician remains to assess the differentiation in Tumor Response to Treatment, pursuit of  individualized histopathology, as well as tumor molecular, genetic and functional characteristics has to take into consideration the “total” individual patients’ characteristics: age, co-morbidities, secondary risks and allergies to drugs.

In Dr. Lev-Ari’s paper Minimally Invasive Treatment (MIT) is compared with Minimally Invasive Surgery (MIS) applied for tumor resection.  In many cases MIS is not the right surgical decision, yet, it is applied for a corollary of patient-centered care considerations. At present, facing the unknown of the future behavior of the tumor as its response to therapeutics bearing uncertainty related to therapy outcomes.

Forget me not – says the ‘Stroma’

Dr. Brücher, the author of review on tumor response criteria, expressed his views on the topic. He remembers that 10 years ago, every cancer researcher stated – “look at the tumor cells only – forget the stroma”. However, the times have changed, “now, everyone knows that it is a system we are looking at, and viewing and analyzing only tumor cells is really not enough.”

He went on to state “if we would be honest, we would have to declare that all data, which had been produced 8-13 years ago, dealing with laser capture microdissection, would need a rescrutinization, because the influence of the stroma was ‘forgotten’.”

He added, “the surgeon looks at the ‘free margin’ in a kind of reductionable model, the pathologist is more the control instance. I personally see the pathologist as ‘the control instance’ of surgical quality. Therefore, not the wish of the surgeon is important, the objective way of looking into problems or challenges. Can a pathologist always state if a R0-resection had been performed?”

What is the real RO-resection?

There have been many surrogate marker analysis, says Dr. Brücher, and that a substantially well thought through structured analysis has never been done: mm by mm and afterwards analyzing that by a ROC analysis. For information on genetic markers on cancer, refer to the following post by Dr. Lev-Ari’s: Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

He also stated that there is no gold standard to compare the statistical ROC analysis to. Often it is just declared and stated but it is still not clear what the real RO-resection is?

He added, “in some organs it is very difficult and we all (surgeons, pathologists, clinicians) that we always get to the limit, if we try interpreting the R-classification within the 3rd dimension.”

Dr. Brücher explains regarding resectability classification, “If lymph nodes are negative it does not mean, lymph nodes are really negative. For example, up to 38% upper GI cancers have histological negative lymph nodes, but immunohistochemical positive lymph nodes. And, Stojadinovic et al have also shown similar observations at el in colorectal cancer. So the 4th dimension of cancer – the lymph nodes / the lymphatic vessel invasion are much more important than just a TNM classification, which unfortunately does often not reflect real tumor biology.”

The discussion regarding the transition state of the tumor surrounding tissue and the ‘free margin’ led to a bigger issue, the heterogeneity of tumors.

Dr. Bernstein quoted a few lines from the review article titled “Tumor response criteria: are they appropriate?, authored by Dr Björn LDM Brücher et al published in Future Oncology in 2012.

  • Tumor heterogeneity is a ubiquitous phemomenon. In particular, there are important differences among the various types of gastrointestinal (GI) cancers in terms of tumor biology, treatment response and prognosis.
  • This forms the principal basis for targeted therapy directed by tumor-specific testing at either the gene or protein level. Despite rapid advances in our understanding of targeted therapy for GI cancers, the impact on cancer survival has been marginal.
  • Can tumor response to therapy be predicted, thereby improving the selection of patients for cancer treatment?
  • In 2000, the NCI with the European Association for Research and Treatment of Cancer, proposed a replacement of 2D measurement with a decrease in the largest tumor diameter by 30% in one dimension. Tumor response as defined would translate into a 50% decrease for a spherical lesion
  • We must rethink how we may better determine treatment response in a reliable, reproducible way that is aimed at individualizing the therapy of cancer patients.
  • We must change the tools we use to assess tumor response. The new modality should be based on empirical evidence that translates into relevant and meaningful clinical outcome data.
  • This becomes a conundrum of sorts in an era of ‘minimally invasive treatment’.
  • Integrated multidisciplinary panel of international experts – not sure that that will do it.

Dr. Bernstein followed up by authoring a separate post on tumor response. His views on tumor response criteria have been quoted in the following paragraphs:

Can tumor response to therapy be predicted?

The goal is not just complete response. Histopathological response seems to be related post-treatment histopathological assessment but it is not free from the challenge of accurately determining treatment response, as this method cannot delineate whether or not there are residual cancer cells. Functional imaging to assess metabolic response by 18-fluorodeoxyglucose PET also has its limits, as the results are impacted significantly by several variables:

• tumor type
• sizing
• doubling time
• anaplasia?
• extent of tumor necrosis
• type of antitumor therapy and the time when response was determined.

The new modality should be based on individualized histopathology as well as tumor molecular, genetic and functional characteristics, and individual patients’ characteristics, a greater challenge in an era of ‘minimally invasive treatment’.

This listing suggests that for every cancer the following data has to be collected (except doubling time). If there were five variables, the classification based on these alone would calculate to be very sizable based on Eugene Rypka’s feature extraction and classification.

But looking forward, time to remission and disease free survival are additionally important. Treatment for cure is not the endpoint, but the best that can be done is to extend the time of survival to a realistic long term goal and retain a quality of life.

For detailed discussion on the topic of tumor response and comments refer to the following posts:

What can we expect of tumor therapeutic response?

Author: Larry H. Bernstein, MD, FCAP

Judging ‘Tumor response’-there is more food for thought

Reporter: Ritu Saxena, Ph.D.

Additional Sources:

Research articles:

Brücher BLDM  et al. Tumor response criteria: are they appropriate? Future Oncol. August Vol. 8, No. 8, Pages 903-906 (2012).

Brücher BLDM, Piso P, Verwaal V et al. Peritoneal carcinomatosis: overview and basics. Cancer Invest.30(3),209–224 (2012).

Brücher BLDM, Swisher S, Königsrainer A et al. Response to preoperative therapy in upper gastrointestinal cancers. Ann. Surg. Oncol.16(4),878–886 (2009).

Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer47(1),207–214 (1981).

Therasse P, Arbuck SG, Eisenhauer EA et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J. Natl Cancer Inst.92(3),205–216 (2000).

Brücher BLDM, Becker K, Lordick F et al. The clinical impact of histopathological response assessment by residual tumor cell quantification in esophageal squamous cell carcinomas. Cancer106(10),2119–2127 (2006).

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The unfortunate ending of the Tower of Babel construction project and its effect on modern imaging-based cancer patients’ management

The story of the city of Babel is recorded in the book of Genesis 11 1-9. At that time, everyone on earth spoke the same language.

Picture: Pieter Bruegel the Elder: The Tower of Babel_(Vienna)

It is probably safe to assume that medical practitioners at that time were reporting the status of their patients in a standard manner. Although not mentioned, one might imagine that, at that time, ultrasound or MRI scans were also reported in a standard and transferrable manner. The people of Babel noticed the potential in uniform communication and tried to build a tower so high that it would  reach the gods. Unfortunately, God did not like that, so he went down (in person) and confounded people’s speech, so that they could not understand each another. Genesis 11:7–8.

This must be the explanation for our inability to come to a consensus on reporting of patients’ imaging-outcome. Progress in development of efficient imaging protocols and in clinical management of patients is withheld due to high variability and subjectivity of clinicians’ approach to this issue.

Clearly, a justification could be found for not reaching a consensus on imaging protocols: since the way imaging is performed affects the outcome, (i.e. the image and its interpretation) it takes a long process of trial-and-error to come up with the best protocol.  But, one might wonder, wouldn’t the search for the ultimate protocol converge faster if all practitioners around the world, who are conducting hundreds of clinical studies related to imaging-based management of cancer patients, report their results in a standardized and comparable manner?

Is there a reason for not reaching a consensus on imaging reporting? And I’m not referring only to intra-modality consensus, e.g. standardizing all MRI reports. I’m referring also to inter-modality consensus to enable comparison and matching of reports generated from scans of the same organ by different modalities, e.g. MRI, CT and ultrasound.

As developer of new imaging-based technologies, my personal contribution to promoting standardized and objective reporting was the implementation of preset reporting as part of the prostate-HistoScanning product design. For use-cases, as demonstrated below, in which prostate cancer patients were also scanned by MRI a dedicated reporting scheme enabled matching of the HistoScanning scan results with the prostate’s MRI results.

The MRI reporting scheme used as a reference is one of the schemes offered in a report by Miss Louise Dickinson on the following European consensus meeting : Magnetic Resonance Imaging for the Detection, Localisation, and Characterisation of Prostate Cancer: Recommendations from a European Consensus Meeting, Louise Dickinson a,b,c,*, Hashim U. Ahmed a,b, Clare Allen d, Jelle O. Barentsz e, Brendan Careyf, Jurgen J. Futterer e, Stijn W. Heijmink e, Peter J. Hoskin g, Alex Kirkham d, Anwar R. Padhani h, Raj Persad i, Philippe Puech j, Shonit Punwani d, Aslam S. Sohaib k, Bertrand Tomball,Arnauld Villers m, Jan van der Meulen c,n, Mark Emberton a,b,c,

Image of MRI reporting scheme taken from the report by Miss Louise Dickinson

The corresponding HistoScanning report is following the same prostate segmentation and the same analysis plans:

Preset reporting enabling matching of HistoScanning and MRI reporting of the same case.

It is my wish that already in the near-future, the main radiology societies (RSNA, ESR, etc..) will join together to build the clinical Imaging’s “Tower of Babel” to effectively address the issue of standardizing reporting of imaging procedures. This time it will not be destroyed…:-)

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Nanotechnology and MRI imaging

Author: Tilda Barliya PhD

The recent advances of “molecular and medical imaging” as an integrated discipline in academic medical centers has set the stage for an evolutionary leap in diagnostic imaging and therapy. Molecular imaging is not a substitute for the traditional process of image formation and interpretation, but is intended to improve diagnostic accuracy and sensitivity.

Medical imaging technologies allow for the rapid diagnosis and evaluation of a wide range of pathologies. In order to increase their sensitivity and utility, many imaging technologies such as CT and MRI rely on intravenously administered contrast agents. While the current generation of contrast agents has enabled rapid diagnosis, they still suffer from many undesirable drawbacks including a lack of tissue specificity and systemic toxicity issues. Through advances made in nanotechnology and materials science, researchers are now creating a new generation of contrast agents that overcome many of these challenges, and are capable of providing more sensitive and specific information (1)

Magnetic resonance imaging (MRI) contrast enhancement for molecular imaging takes advantage of superb and tunable magnetic properties of engineered magnetic nanoparticles, while a range of surface chemistry offered by nanoparticles provides multifunctional capabilities for image-directed drug delivery. In parallel with the fast growing research in nanotechnology and nanomedicine, the continuous advance of MRI technology and the rapid expansion of MRI applications in the clinical environment further promote the research in this area.

It is well known that magnetic nanoparticles, distributed in a magnetic field, create extremely large microscopic field gradients. These microscopic field gradients cause substantial diphase and shortening of longitudinal relaxation time (T1) and transverse relaxation time (T2 and T2*) of nearby nuclei, e.g., proton in the case of most MRI applications. The magnitudes of MRI contrast enhancement over clinically approved conventional gadolinium chelate contrast agents combined with functionalities of biomarker specific targeting enable the early detection of diseases at the molecular and cellular levels with engineered magnetic nanoparticles. While the effort in developing new engineered magnetic nanoparticles and constructs with new chemistry, synthesis, and functionalization approaches continues to grow, the importance of specific material designs and proper selection of imaging methods have been increasingly recognized (2)

Earlier investigations have shown that the MRI contrast enhancement by magnetic nanoparticles is highly related to their composition, size, surface properties, and the degree of aggregation in the biological environment.

Therefore, understanding the relationships between these intrinsic parameters and relaxivities of nuclei under influence of magnetic nanoparticles can provide critical information for predicting the properties of engineered magnetic nanoparticles and enhancing their performance in the MRI based theranostic applications. On the other hand, new contrast mechanisms and imaging strategies can be applied based on the novel properties of engineered magnetic nanoparticles. The most common MRI sequences, such as the spin echo (SE) or fast spin echo (FSE) imaging and gradient echo (GRE), have been widely used for imaging of magnetic nanoparticles due to their common availabilities on commercial MRI scanners. In order to minimize the artificial effect of contrast agents and provide a promising tool to quantify the amount of imaging probe and drug delivery vehicles in specific sites, some special MRI methods, such as  have been developed recently to take maximum advantage of engineered magnetic NPs

  • off-resonance saturation (ORS) imaging
  • ultrashort echo time (UTE) imaging

Because one of the major limitations of MRI is its relative low sensitivity, the strategies of combining MRI with other highly sensitive, but less anatomically informative imaging modalities such as positron emission tomography (PET) and NIRF imaging, are extensively investigated. The complementary strengths from different imaging methods can be realized by using engineered magnetic nanoparticles via surface modifications and functionalizations. In order to combine optical or nuclear with MR for multimodal imaging, optical dyes and radio-isotope labeled tracer molecules are conjugated onto the moiety of magnetic nanoparticles

Since most functionalities assembled by magnetic nanoparticles are accomplished by the surface modifications, the chemical and physical properties of nanoparticle surface as well as surface coating materials have considerable effects on the function and ability of MRI contrast enhancement of the nanoparticle core.

The longitudinal and transverse relaxivities, Ri (i=1, 2), defined as the relaxation rate per unit concentration (e.g., millimole per liter) of magnetic ions, reflects the efficiency of contrast enhancement by the magnetic nanoparticles as MRI contrast agents. In general, the relaxivities are determined, but not limited, by three key aspects of the magnetic nanoparticles:

  1. Chemical composition,
  2. Size of the particle or construct and the degree of their aggregation
  3. Surface properties that can be manipulated by the modification and functionalization.

(It is also recognized that the shape of the nanoparticles can affect the relaxivities and contrast enhancement. However these shaped particles typically have increased sizes, which may limit their in vivo applications. Nevertheless, these novel magnetic nanomaterials are increasingly attractive and currently under investigation for their applications in MRI and image-directed drug delivery).

Composition Effect: The composition of magnetic nanoparticles can significantly affect the contrast enhancing capability of nanoparticles because it dominates the magnetic moment at the atomic level. For instance, the magnetic moments of the iron oxide nanoparticles, mostly used nanoparticulate T2 weighted MRI contrast agents, can be changed by incorporating other metal ions into the iron oxide.  The composition of magnetic nanoparticles can significantly affect the contrast enhancing capability of nanoparticles because it dominates the magnetic moment at the atomic level. For instance, the magnetic moments of the iron oxide nanoparticles, mostly used nanoparticulate T2 weighted MRI contrast agents, can be changed by incorporating other metal ions into the iron oxide.

Size Effect: The dependence of relaxation rates on the particle size has been widely studied both theoretically and experimentally. Generally the accelerated diphase, often described by the R2* in magnetically inhomogeneous environment induced by magnetic nanoparticles, is predicted into two different regimes. For the relatively small nanoparticles, proton diffusion between particles is much faster than the resonance frequency shift. This resulted in the relative independence of T2 on echo time. The values for R2 and R2*are predicted to be identical. This process is called “motional averaging regime” (MAR). It has been well demonstrated that the saturation magnetization Ms increases with the particle size. A linear relationship is predicted between Ms1/3 and d-1. Therefore, the capability of MRI signal enhancement by nanoparticles correlates directly with the particle size. 

Surface Effect: MRI contrast comes from the signal difference between water molecules residing in different environments that are under the effect of magnetic nanoparticles. Because the interactions between water and the magnetic nanoparticles occur primarily on the surface of the nanoparticles, surface properties of magnetic nanoparticles play important roles in their magnetic properties and the efficiency of MRI contrast enhancement. As most biocompatible magnetic nanoparticles developed for in vivo applications need to be stabilized and functionalized with coating materials, the coating moieties can affect the relaxation of water molecules in various forms, such as diffusion, hydration and hydrogen binding.

The early investigation carried at by Duan et al suggested that hydrophilic surface coating contributes greatly to the resulted MRI contrast effect. Their study examined the proton relaxivities of iron oxide nanocrystals coated by copolymers with different levels of hydrophilicity including: poly(maleic acid) and octadecene (PMO), poly(ethylene glycol) grated polyethylenimine (PEG-g-PEI), and hyperbranched polyethylenimine (PEI). It was found that proton relaxivities of those IONPs depend on the surface hydrophilicity and coating thickness in addition to the coordination chemistry of inner capping ligands and the particle size.

The thickness of surface coating materials also contributed to the relaxivity and contrast effect of the magnetic nanoparticles. Generally, the measured T2 relaxation time increases as molecular weight of PEG increases.

In Summary

Much progress has taken place in the theranostic applications of engineered magnetic nanoparticles, especially in MR imaging technologies and nanomaterials development. As the feasibilities of magnetic nanoparticles for molecular imaging and drug delivery have been demonstrated by a great number of studies in the past decade, MRI guiding and monitoring techniques are desired to improve the disease specific diagnosis and efficacy of therapeutics. Continuous effort and development are expected to be focused on further improvement of the sensitivity and quantifications of magnetic nanoparticles in vivo for theranostics in future.

The new design and preparation of magnetic nanoparticles need to carefully consider the parameters determining the relaxivities of the nanoconstructs. Sensitive and reliable MRI methods have to be established for the quantitative detection of magnetic nanoparticles. The new generations of magnetic nanoparticles will be made not only based on the new chemistry and biological applications, but also with combined knowledge of contrast mechanisms and MRI technologies and capabilities. As new magnetic nanoparticles are available for theranostic applications, it is anticipated that new contrast mechanism and MR imaging strategies can be developed based on the novel properties of engineered magnetic nanoparticles.











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Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?

Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?

Author: Dror Nir, PhD


Advances in techniques for cancer lesions’ detection and localisation [1-6] opened the road to methods of localised (“focused”) cancer treatment [7-10].  An obvious challenge on the road is reassuring that the imaging-guided treatment device indeed treats the region of interest and preferably, only it.

A step in that direction was taken by a group of investigators from Sunnybrook Health Sciences Centre, University of Toronto, Ontario, Canada who evaluate the feasibility and safety of magnetic resonance (MR) imaging–controlled transurethral ultrasound therapy for prostate cancer in humans [7]. Their study’s objective was to prove that using real-time MRI guidance of HIFU treatment is possible and it guarantees that the location of ablated tissue indeed corresponds to the locations planned for treatment. Eight eligible patients were recruited.


The setup


Treatment protocol


The result


“There was excellent agreement between the zone targeted for treatment and the zone of thermal injury, with a targeting accuracy of ±2.6 mm. In addition, the temporal evolution of heating was very consistent across all patients, in part because of the ability of the system to adapt to changes in perfusion or absorption properties according to the temperature measurements along the target boundary.”


Technological problems to be resolved in the future:

“Future device designs could incorporate urinary drainage during the procedure, given the accumulation of urine in the bladder during treatment.”

“Sufficient temperature resolution could be achieved only by using 10-mm-thick sections. Our numeric studies suggest that 5-mm-thick sections are necessary for optimal three-dimensional conformal heating and are achievable by using endorectal imaging coils or by performing the treatment with a 3.0-T platform.”

Major limitation: “One of the limitations of the study was the inability to evaluate the efficacy of this treatment; however, because this represents, to our knowledge, the first use of this technology in human prostate, feasibility and safety were emphasized. In addition, the ability to target the entire prostate gland was not assessed, again for safety considerations. We have not attempted to evaluate the effectiveness of this treatment for eradicating cancer or achieving durable biochemical non-evidence of disease status.”


  1. SIMMONS (L.A.M.), AUTIER (P.), ZATURA (F.), BRAECKMAN (J.G.), PELTIER (A.), ROMICS (I.), STENZL (A.), TREURNICHT (K.), WALKER (T.), NIR (D.), MOORE (C.M.), EMBERTON (M.). Detection, localisation and characterisation of prostate cancer by Prostate HistoScanning.. British Journal of Urology International (BJUI). Issue 1 (July). Vol. 110, Page(s): 28-35
  2. WILKINSON (L.S.), COLEMAN (C.), SKIPPAGE (P.), GIVEN-WILSON (R.), THOMAS (V.). Breast HistoScanning: The development of a novel technique to improve tissue characterization during breast ultrasound. European Congress of Radiology (ECR), A.4030, C-0596, 03-07/03/2011.
  3. Hebert Alberto Vargas, MD, Tobias Franiel, MD,Yousef Mazaheri, PhD, Junting Zheng, MS, Chaya Moskowitz, PhD, Kazuma Udo, MD, James Eastham, MD and Hedvig Hricak, MD, PhD, Dr(hc) Diffusion-weighted Endorectal MR Imaging at 3 T for Prostate Cancer: Tumor Detection and Assessment of Aggressiveness. June 2011 Radiology, 259,775-784.
  4. Wendie A. Berg, Kathleen S. Madsen, Kathy Schilling, Marie Tartar, Etta D. Pisano, Linda Hovanessian Larsen, Deepa Narayanan, Al Ozonoff, Joel P. Miller, and Judith E. Kalinyak Breast Cancer: Comparative Effectiveness of Positron Emission Mammography and MR Imaging in Presurgical Planning for the Ipsilateral Breast Radiology January 2011 258:1 59-72.
  5. Anwar R. Padhani, Dow-Mu Koh, and David J. Collins Reviews and Commentary – State of the Art: Whole-Body Diffusion-weighted MR Imaging in Cancer: Current Status and Research Directions Radiology December 2011 261:3 700-718
  6. Eggener S, Salomon G, Scardino PT, De la Rosette J, Polascik TJ, Brewster S. Focal therapy for prostate cancer: possibilities and limitations. Eur Urol 2010;58(1):57–64).
  7. Rajiv Chopra, PhD, Alexandra Colquhoun, MD, Mathieu Burtnyk, PhD, William A. N’djin, PhD, Ilya Kobelevskiy, MSc, Aaron Boyes, BSc, Kashif Siddiqui, MD, Harry Foster, MD, Linda Sugar, MD, Masoom A. Haider, MD, Michael Bronskill, PhD and Laurence Klotz, MD. MR Imaging–controlled Transurethral Ultrasound Therapy for Conformal Treatment of Prostate Tissue: Initial Feasibility in Humans. October 2012 Radiology, 265,303-313.
  8. Black, Peter McL. M.D., Ph.D.; Alexander, Eben III M.D.; Martin, Claudia M.D.; Moriarty, Thomas M.D., Ph.D.; Nabavi, Arya M.D.; Wong, Terence Z. M.D., Ph.D.; Schwartz, Richard B. M.D., Ph.D.; Jolesz, Ferenc M.D.  Craniotomy for Tumor Treatment in an Intraoperative Magnetic Resonance Imaging Unit. Neurosurgery: September 1999 – Volume 45 – Issue 3 – p 423
  9. Medel, Ricky MD,  Monteith, Stephen J. MD, Elias, W. Jeffrey MD, Eames, Matthew PhD, Snell, John PhD, Sheehan, Jason P. MD, PhD, Wintermark, Max MD, MAS, Jolesz, Ferenc A. MD, Kassell, Neal F. MD. Neurosurgery: Magnetic Resonance–Guided Focused Ultrasound Surgery: Part 2: A Review of Current and Future Applications. October 2012 – Volume 71 – Issue 4 – p 755–763
  10. Bruno Quesson PhD, Jacco A. de Zwart PhD, Chrit T.W. Moonen PhD. Magnetic resonance temperature imaging for guidance of thermotherapy. Journal of Magnetic Resonance Imaging, Special Issue: Interventional MRI, Part 1, Volume 12, Issue 4, pages 525–533, October 2000

Writer: Dror Nir, PhD


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Author and Curator: Dror Nir, PhD

Radiology congresses are all about imaging in medicine. Interestingly, radiology originates from radiation. It was the discovery of X-ray radiation at the beginning of the 20th century that opened the road to “seeing” the inside of the human body without harming it (at that time that meant cutting into the body).

Radiology meetings are about sharing experience and knowhow on imaging-based management patients. The main topic is always image-interpretation: the bottom line of clinical radiology! This year’s European Congress of Radiology (ECR) dedicated few of its sessions to recent developments in image-interpretation tools. I chose to discuss the one that I consider contributing the most to the future of cancer patients’ management.

In the refresher course dedicated to computer application the discussion was aimed at understanding the question “How do image processing and CAD impact radiological daily practice?” Experts’ reviews gave the audience some background information on the following subjects:

  1. A.     The link between image reconstruction and image analysis.
  2. B.     Semantic web technologies for sharing and reusing imaging-related information
  3. C.     Image processing and CAD: workflow in clinical practice.

I find item A to be a fundamental education item. Not once did I hear a radiologist saying: “I know this is the lesion because it’s different on the image”.  Being aware of the computational concepts behind image rendering, even if it is at a very high level and lacking deep understanding of the computational processes,  will contribute to more balanced interpretations.

Item B is addressing the dream of investigators worldwide. Imagine that we could perform a web search and find educating, curated materials linking visuals and related clinical information, including standardized pathology reporting. We would only need to remember that search engines used certain search methods and agree, worldwide, on the method and language to be used when describing things. Having such tools is a pre-requisite to successful pharmaceutical and bio-tech development.

I find item C strongly linked to A, as all methods for better image interpretation must fit into a workflow. This is a design goal that is not trivial to achieve. To understand what I mean by that, try to think about how you could integrate the following examples in your daily workflow: i.e. what kind of expertise is needed for execution, how much time it will take, do you have the infrastructure?

In the rest of this post, I would like to highlight, through examples that were discussed during ECR 2012, the aspect of improving cancer patients’ clinical assessment by using information fusion to support better image interpretation.

  • Adding up quantitative information from MR spectroscopy (quantifies biochemical property of a target lesion) and Dynamic Contrast Enhanced MR imaging (highlights lesion vasculature).

Image provided by: Dr. Pascal Baltzer, director of mammography at the centre for radiology at Friedrich Schiller University in Jena, Germany

  • Registration of images generated by different imaging modalities (Multi-modal imaging registration).

The following examples: Fig 2 demonstrates registration of a mammography image of a breast lesion to an MRI image of this lesion. Fig3 demonstrates registration of an ultrasound image of a breast lesion scanned by an Automatic Breast Ultrasound (ABUS) system and an MRI image of the same lesion.

Images provided by members of the HAMAM project (an EU, FP7 funded research project: Highly Accurate Breast Cancer Diagnosis through Integration of Biological Knowledge, Novel Imaging Modalities, and Modelling):


 Multi-modality image registration is usually based on the alignment of image-features apparent in the scanned regions. For ABUS-MRI matching these were: the location of the nipple and the breast thickness; the posterior of the nipple in both modalities; the medial-lateral distance of the nipple to the breast edge on ultrasound; and an approximation of the rib­cage using a cylinder on the MRI. A mean accuracy of 14mm was achieved.

Also from the HAMAM project, registration of ABUS image to a mammography image:

registration of ABUS image to a mammography image, Image provided by members of the HAMAM project (an EU, FP7 funded research project: Highly Accurate Breast Cancer Diagnosis through Integration of Biological Knowledge, Novel Imaging Modalities, and Modelling):

  • Automatic segmentation of suspicious regions of interest seen in breast MRI images

Segmentation of suspicious the lesions on the image is the preliminary step in tumor evaluation; e.g. finding its size and location. Since lesions have different signal/image character­istics to the rest of the breast tissue, it gives hope for the development of computerized segmentation techniques. If successful, such techniques bear the promise of enhancing standardization in the reporting of lesions size and location: Very important information for the success of the treatment step.

Roberta Fusco of the National Cancer Institute of Naples Pascal Foundation, Naples/IT suggested the following automatic method for suspi­cious ROI selection within the breast using dynamic-derived information from DCE-MRI data.


Automatic segmentation of suspicious ROI in breast MRI images, image provided by Roberta Fusco of the National Cancer Institute of Naples Pascal Foundation, Naples/IT


 Her algorithm includes three steps (Figure 2): (i) breast mask extraction by means of automatic intensity threshold estimation (Otsu Thresh-holding) on the par­ametric map obtained through the sum of intensity differences (SOD) calculated pixel by pixel; (ii) hole-filling and leakage repair by means of morphological operators: closing is required to fill the holes on the boundaries of breast mask, filling is required to fill the holes within the breasts, erosion is required to reduce the dilation obtained by the closing operation; (iii) suspicious ROIs extraction: a pixel is assigned to a suspicious ROI if it satisfies two conditions: the maximum of its normalized time-intensity curve should be greater than 0.3 and the maximum signal intensity should be reached before the end of the scan time. The first condition assures that the pixels within the ROI have a significant contrast agent uptake (thus excluding type I and type II curves) and the second condition is required for the time-intensity pattern to be of type IV or V (thus excluding type III curves).

Written by: Dror Nir, PhD

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Author: Dror Nir, PhD


The most stressful period in a cancer patients’ pathway is from the moment they fail a screening test or present with suspicious symptoms to the moment they are diagnosed. Today’s medical guidelines require histopathology findings as the only acceptable proof: positive results  mean you are a cancer patient, negative results mean, well…maybe you are and maybe you are not. You now enter into what might be a very long period, sometime years, of uncertainty regarding your health and prospects. And why?

Because the substance for histopathology is acquired by biopsies, and biopsies are known to be inaccurate. For example, breast and prostate biopsies  fail to find 25% to 35% of the cancer lesions at the first biopsy session.

Therefore, it is not surprising that from the beginning of this procedure,  medical practitioners look for ways to incorporate imaging into the workflow. In the last decade, significant progress has been made in the introduction of imaging-guided biopsies. The most common modalities were ultrasound and CT/mammography. Recently, as the industry solved the issues of magnetic field compatibility for biopsy needles and the introduction of open MRI systems, MRI-guided biopsies were also made  possible.

Ultrasound-guided biopsies are  by far the most commonly used procedure. Why? Because they  can be often performed as an office-based procedure. Here are some interesting links to YouTube videos describing such procedures:

  • Prostate

Prostate Ultrasound and Prostate Biopsy by Dr. Neil Baum

Transrectal ultrasound (Trus) Biopsy of the prostate

  • Breast

Ultrasound-Guided Breast Biopsy

Breast Tissue Biopsy

The main advantages: they are easily accessible, low cost and quick. The disadvantages of these procedures are  that they are very much operator dependent, rather than standardized, and there are no quality assurance guidelines attached. Efforts to standardize ultrasound-based biopsies and increase their efficiency are evident by recent introductions of ultrasound systems into the market ,  which support real-time guided biopsies and ultrasound applications that perform real-time biopsy tracking. But these systems are still far from being widely available. I will touch on this issue in my upcoming posts as I am part of these efforts.

CT and Mammography guided biopsies require more sophisticated equipment and well-trained operators. As an example:

Breast Biopsy – What To Expect

The main advantage: if you return to the same operator, the process is likely to be reproducible. The disadvantages are identical to that of ultrasound-based biopsies. It is worthwhile to note that, recently, radiologists who perform biopsies are required to go through a certification process. Still, such certification demands vary between the various radiology societies.

MRI-guided biopsies are an even more sophisticate and complex procedure:

  • Prostate:

DynaTRIM Video

DynaTRIM Intervention

An interesting quote from Dr. Hashim U. Ahmed, M.D., MRCS, Division of Urology  Department of Surgery, University College of London ( “Advocating the widespread use of MRI before biopsy in a population of men with risk parameters for harboring prostate cancer has a number of advantages, which might ultimately benefit the care these men undergo. Increasing the detection of prostate cancer that requires treatment while avoiding biopsy – and hence unnecessary treatment – in those with insignificant or no cancer are compelling arguments for this approach.”

  • Breast

MRI Breast Biopsy – Diagnostic and Biopsy Services for Breast Evaluation

I recommend reading the following article regarding the use of Open MRI to guide freehand biopsies of breast lesions. Especially interesting is the discussion where the authors give a good description of the difficulties in breast biopsies they are trying to overcome in order to achieve good lesion sampling.

MR-guided Freehand Biopsy of Breast Lesions in a 1.0-T Open MR Imager with a Near-Real-time Interactive Platform: Preliminary Experience Frank Fischbach, MD, et. al

The question remains: which biopsy procedure is the best? And does this question have one coherent answer, i.e. one that will satisfy the patients, the doctors and the health-care insurers?  Will the answer to this question remain the subject of endless uncoordinated clinical studies?

If anyone who reads this post knows on methodological scientific or regulatory initiatives aimed at answering this question on a level of global guide lines  I would appreciate his comment.

Written by: Dror Nir, PhD.


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