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The unfortunate ending of the Tower of Babel construction project and its effect on modern imaging-based cancer patients’ management
Curator: Dror Nir, PhD
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…:-)
Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?
Author: Dror Nir, PhD
Article 9.6.Knowing the tumor’s size and location, could we target treatment to THE ROI by applying imaging-guided intervention?
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.”
References
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
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.
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.
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
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).
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
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
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
Introducing smart-imaging into radiologists’ daily practice.
Author and Curator: Dror Nir, PhD
Article 11.3.1 Introducing smart imaging into radiologists daily practice
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:
A. The link between image reconstruction and image analysis.
B. Semantic web technologies for sharing and reusing imaging-related information
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): http://www.hamam-project.org
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): http://www.hamam-project.org
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).
Anyone who follows healthcare news, as I do , cannot help being impressed with the number of scientific and non-scientific items that mention the applicability of Magnetic Resonance Imaging (‘MRI’) to medical procedures.
A very important aspect that is worthwhile noting is that the promise MRI bears to improve patients’ screening – pre-clinical diagnosis, better treatment choice, treatment guidance and outcome follow-up – is based on new techniques that enables MRI-based tissue characterisation.
Magnetic resonance imaging (MRI) is an imaging device that relies on the well-known physical phenomena named “Nuclear Magnetic Resonance”. It so happens that, due to its short relaxation time, the 1H isotope (spin ½ nucleus) has a very distinctive response to changes in the surrounding magnetic field. This serves MRI imaging of the human body well as, basically, we are 90% water. The MRI device makes use of strong magnetic fields changing at radio frequency to produce cross-sectional images of organs and internal structures in the body. Because the signal detected by an MRI machine varies depending on the water content and local magnetic properties of a particular area of the body, different tissues or substances can be distinguished from one another in the scan’s resulting image.
MRI scan of a breast lesion (Source Radiology.com)
The main advantages of MRI in comparison to X-ray-based devices such as CT scanners and mammography systems are that the energy it uses is non-ionizing and it can differentiate soft tissues very well based on differences in their water content.
In the last decade, the basic imaging capabilities of MRI have been augmented for the purpose of cancer patient management, by using magnetically active materials (called contrast agents) and adding functional measurements such as tissue temperature to show internal structures or abnormalities more clearly.
In order to increase the specificity and sensitivity of MRI imaging in cancer detection, various imaging strategies have been developed. The most discussed in MRI related literature are:
T2 weighted imaging: The measured response of the 1H isotope in a resolution cell of a T2-weighted image is related to the extent of random tumbling and the rotational motion of the water molecules within that resolution cell. The faster the rotation of the water molecule, the higher the measured value of the T2 weighted response in that resolution cell. For example, prostate cancer is characterized by a low T2 response relative to the values typical to normal prostatic tissue [5].
T2 MRI pelvis with Endo Rectal Coil ( DATA of Dr. Lance Mynders, MAYO Clinic)
Dynamic Contrast Enhanced (DCE) MRI involves a series of rapid MRI scans in the presence of a contrast agent. In the case of scanning the prostate, the most commonly used material is gadolinium [4].
Axial MRI Lava DCE with Endo Rectal ( DATA of Dr. Lance Mynders, MAYO Clinic)
Diffusion weighted (DW) imaging: Provides an image intensity that is related to the microscopic motion of water molecules [5].
DW image of the left parietal glioblastoma multiforme (WHO grade IV) in a 59-year-old woman, Al-Okaili R N et al. Radiographics 2006;26:S173-S189
Multifunctional MRI: MRI image overlaid with combined information from T2-weighted scans, dynamic contrast-enhancement (DCE), and diffusion weighting (DW) [5].
Blood oxygen level-dependent (BOLD) MRI: Assessing tissue oxygenation. Tumors are characterized by a higher density of micro blood vessels. The images that are acquired follow changes in the concentration of paramagnetic deoxyhaemoglobin [5].
In the last couple of years, medical opinion leaders are offering to use MRI to solve almost every weakness of the cancer patients’ pathway. Such proposals are not always supported by any evidence of feasibility. For example, a couple of weeks ago, the British Medical Journal published a study [1] concluding that women carrying a mutation in the BRCA1 or BRCA2 genes who have undergone a mammogram or chest x-ray before the age of 30 are more likely to develop breast cancer than those who carry the gene mutation but who have not been exposed to mammography. What is published over the internet and media to patients and lay medical practitioners is: “The results of this study support the use of non-ionising radiation imaging techniques (such as magnetic resonance imaging) as the main tool for surveillance in young women with BRCA1/2 mutations.”.
Why is ultrasound not mentioned as a potential “non-ionising radiation imaging technique”?
Another illustration is the following advert:
Advert in favour of MRI termal imaging of breast
An MRI scan takes between 30 to 45 minutes to perform (not including the time of waiting for the interpretation by the radiologist). It requires the support of around 4 well-trained team members. It costs between $400 and $3500 (depending on the scan).
The important question, therefore, is: Are there, in the USA, enough MRI systems to meet the demand of 40 million scans a year addressing women with radiographically dense breasts? Toda there are approximately 10,000 MRI systems in the USA. Only a small percentage (~2%) of the examinations are related to breast cancer. A
A rough calculation reveals that around 10,000 additional MRI centers would need to be financed and operated to meet that demand alone.
References
Exposure to diagnostic radiation and risk of breast cancer among carriers of BRCA1/2 mutations: retrospective cohort study (GENE-RAD-RISK), BMJ 2012; 345 doi: 10.1136/bmj.e5660 (Published 6 September 2012), Cite this as: BMJ 2012;345:e5660 – http://www.bmj.com/content/345/bmj.e5660
Ahmed HU, Kirkham A, Arya M, Illing R, Freeman A, Allen C, Emberton M. Is it time to consider a role for MRI before prostate biopsy? Nat Rev Clin Oncol. 2009;6(4):197-206.
Puech P, Potiron E, Lemaitre L, Leroy X, Haber GP, Crouzet S, Kamoi K, Villers A. Dynamic contrast-enhanced-magnetic resonance imaging evaluation of intraprostatic prostate cancer: correlation with radical prostatectomy specimens. Urology. 2009;74(5):1094-9.
Advanced MR Imaging Techniques in the Diagnosis of Intraaxial Brain Tumors in Adults, Al-Okaili R N et al. Radiographics 2006;26:S173-S189 ,
We are all used to clichés such as “seeing is believing”, “seeing is knowing”, “don’t be blind” and so on. Out of our seven (natural and supernatural) senses we tend to use and trust our eyes the most. Especially, when it comes to learning, accumulation of experience and acceptance of information as correct. On the other hand, we are taught from childhood to be aware of illusions and not to judge according to looks but rather according to matter. The problem is, does one recognise the substance inside an image? To answer this, a wide-ranging discipline of image interpretation was developed alongside with imaging technology. In order not to fatigue the innocent reader, I’ll review the state of the art of imaging in medicine in subsequent posts, each dedicated to a specific modality. This post is dedicated to…
Current main trends in ultrasound imaging in cancer patients’ management;
The most used imaging modality in medicine is ultrasound. This is due to the fact that it is noninvasive, practically harmless, relatively inexpensive and fairly accessible; i.e. everyone can operate it, even a layman! No formal training or certification is required!
Interesting enough, ultrasound is labeled by the regulatory agencies, FDA and CE, as a diagnostic medical device! This is real demonstration of the aforementioned tendency to believe our eyes, even if these eyes do not see well or the brain behind them is lacking the experience required for ultrasound image interpretation.
Since “ultrasound imaging in medicine” is the subject of many text books and articles I found it appropriate, for the sake of this post, simply to refer the reader to Wikipedia’s page (http://en.wikipedia.org/wiki/Medical_ultrasonography) on ultrasound in medicine: “Diagnostic Sonography (ultrasonography) is an ultrasound-based diagnostic imaging technique used for visualizing subcutaneous body structures including tendons, muscles, joints, vessels and internal organs for possible pathology or lesions. Obstetric sonography is commonly used during pregnancy and is widely recognized by the public. In physics, the term “ultrasound” applies to all sound waves with a frequency above the audible range of normal human hearing, about 20 kHz. The frequencies used in diagnostic ultrasound are typically between 2 and 18 MHz.”
When it comes to cancer patients’ management, ultrasound provides real-time imaging of body organs at a relatively cost effective workflow. However, it suffers from lack of sensitivity and specificity, especially if the investigator is still fairly inexperienced. Therefore, no diagnosis is confirmed without biopsy of the suspected lesion discovered during the ultrasound scan. As mentioned in my previous post; identification of suspicious lesions in the prostate during TRUS is so inconclusive that in order to reach diagnosis biopsies are taken randomly.
Did we hit the target?
To improve prostate cancer detection, various biopsy strategies to increase the diagnostic yield of prostate biopsy have been devised: sampling of visually abnormal areas; more lateral placement of biopsies; anterior biopsies; and obtaining an increased number of cores, with up to 45 biopsy cores [1-5].
In recent years, new features such as 3D and contrast-enhanced sonography, elastography and HistoScanning were added to the basic video image in order to improve the quality of ultrasound based investigation of cancer patients.
3-D Sonography.
3-D ultrasound allows simultaneous biplanar imaging of the organ with computer reconstructions providing a coronal plane as well as a rendered 3-D image. This promises to improve the detection and pre-clinical grading of cancer lesions. Still, the interpretation is very much “image quality” and “user experience” dependent.
3D imaging of breast using ABUS by Siemens; using the coronal view to better investigate a lesion.
3D imaging of breast using Voluson 730 by GE; three planes are presented for review by the radiologist.
Using intravenous micro-bubble agents in combination with color and power Doppler imaging contributes to increase in the signal obtained in areas of increased vascularity. The underlying assumption is that vascularization in the tumor’s area will be more pronounced than in normal tissue. Hot off the press: The UK National Institute for Health and Clinical Excellence (NICE) has published guidance that supports the use of contrast-enhanced ultrasound with Bracco’s SonoVue ultrasound contrast agent for the diagnosis of liver cancer [6]. The main use of contrast-enhanced ultrasound is directing biopsies to the “most suspicious” areas; i.e. those who presents higher vascularity. Nevertheless, in reported clinical studies [7] targeted biopsies’ sensitivity on contrast-enhanced ultrasound was only 68%.
Elastography.
Elastography is an imaging technique that evaluates the elasticity of the tissue. The underlying assumption is that tumors present greater stiffness than normal tissue and therefore will be characterized by limited compressibility. The first person to introduce this concept was Professor Jonathan Ophir, University of Huston, Texas [http://www.uth.tmc.edu/schools/med/rad/elasto/]: Estimation of differences in lesions’ stiffness relies on computing the level of correlation between consecutive imaging frames while the tissue that is being imaged is subjected to changing compression, usually applied by the sonographer who manipulates the ultrasound probe. Since malignant and benign lesions exhibit similar elasticity, elastography is not suitable for lesion characterisation. Therefore, as in the previous example, elastography’s main use is identifying suspicious areas in which to take biopsies [8, 9]. Furthermore, users’ experiences related to elastography reveal a lot of controversy. For example, according to Prof. Bruno Fornage of MD. Anderson [http://www.auntminnie.com/index.aspx?sec=sup&sub=wom&pag=dis&ItemID=99028]; “current commercially available scanners are confounded by a lack of intraobserver reliability, so that it’s not unusual to produce an opposite result on repeat testing a few seconds later”. “There are very few evidence-based non-industry sponsored studies reporting substantial superiority [of elastography] over standard grayscale ultrasound,” he said. “In fact, a sensitivity of 82% in the diagnosis of breast cancer has been reported for elastography, versus 94% for conventional grayscale ultrasound. More disturbing is that even if the technology of elastography worked flawlessly, the huge overlap in breast pathology between very firm solid benign lesions and less firm malignancies gives this technology no practical place in the differential diagnosis of solid breast masses.”
HistoScanning.
HistoScanning™ is a novel ultrasound-based software technology that utilizes advanced tissue characterization algorithms to address the clinical requirements for tissue characterization. It visualizes the position and extent of tissue suspected of being malignant in the target organ. In this respect its design is unique and superior to other ultrasound based-technologies [10, 11]. HistoScanning’s first clinically available application (since 2009) is in the management of prostate cancer patients.
HistoScanning indicating suspicious lesions superimposed on 3-D ultrasound of the prostate. The three imaging plans and 3D reconstruction of the segmented prostate are presented.
To conclude; if we are looking to improve the current state of the art in ultrasound-based cancer patients’ management we should strive to introduce systems which will enable the medical practitioners to rule in or rule out suspicious lesions at imaging before they biopsy them. Using ultrasound just as a tool for directing biopsies as done today is not enough. Indeed, this requires capability of ultrasound-based tissue characterisation in addition to detection of ultrasound-based abnormality (i.e. circumstantial evidence for cancer). To-date, the only available system that bears the promise to provide such improvement is HistoScanning. Obviously, the level of confidence in the Negative Predictive Value of HistoScanning and future systems alike must be built to become high enough to provide the medical practitioner the reassurance and comfort that he is not missing any significant cancer by not taking a biopsy. Such confidence can only be built by subjecting these systems (i.e. HistoScanning and alike) to properly designed clinical studies and, not less important, by reporting the experience of early adopters who will test them in a controlled routine use.
References
Flanigan RC, Catalona WJ, Richie JP, Ah-mann FR, Hudson MA, Scardino PT, de-Kernion JB, Ratliff TL, Kavoussi LR, Dalkin BL: Accuracy of digital rectal examination and transrectal ultrasonography in localizing prostate cancer: results of a multicenter clinical trial of 6,630 men. J Urol 1994; 152: 1506–1509.
Eichler K, Hempel S, Wilby J, Myers L, Bachmann LM, Kleijnen J: Diagnostic value of systematic biopsy methods in the investigation of prostate cancer: a systematic review. J Urol 2006; 175: 1605–1612.
Delongchamps NB, de la Roza G, Jones R, Jumbelic M, Haas GP: Saturation biopsies on autopsied prostates for detecting and characterizing prostate cancer. BJU Int 2009; 10: 49–54.
Yi A, Kim JK, Park SH, Kim KW, Kim HS, Kim JH, Eun HW, Cho KS: Contrast-enhanced sonography for prostate cancer detection in patients with indeterminate clinical findings. Am J Roentgenol 2006; 186: 1431–1435.
König K, Scheipers U, Pesavento A, Lorenz A, Ermert H, Senge T: Initial experiences with real-time elastography guided biopsies of the prostate. J Urol 2005; 174: 115–117.
32 Pallwein L, Mitterberger M, Struve P, Hor-ninger W, Aigner F, Bartsch G, Gradl J, Schurich M, Pedross F, Frauscher F: Comparison of sonoelastography guided biopsy with systematic biopsy: impact on prostate cancer detection. Eur Radiol 2007; 17: 2278– 2285.
SALOMON (G.), SPETHMANN (J.), BECKMANN (A.), AUTIER (P.), MOORE (C.), DURNER (L.), SANDMANN (M.), HASE (A.), SCHLOMM (T.), MICHL (U.), HEINZER (H.), GRAFEN (M.), STEUBER (T.).Accuracy of HistoScanning for the prediction of a negative surgical margin in patients undergoing radical prostatectomy. Published online in British Journal of Urology International (BJUI). 09/08/2012.
SIMMONS (L.A.M.), AUTIER (P.), ZATURA (F.), BRAECKMAN (J.G.), PELTIER (A.), ROMICS (I.), STENZL (A.), TREURNICHT (K.), WALKER (T.), NM (D.), MOORE (C.M.), EMBERTON (M.). Detection, localisation and characterisation of prostate cancer by Prostate Hist°Scanning; Published in British Journal of Urology International (BJUI). Issue 1 (July). Vol 110, P 28-35.
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