Publications

2017
Chantal MW Tax, Carl-Fredrik Westin, Tom Dela Haije, Andrea Fuster, Max A Viergever, Evan Calabrese, Luc Florack, and Alexander Leemans. 2017. “Quantifying the Brain's Sheet Structure with Normalized Convolution.” Med Image Anal, 39, Pp. 162-77.Abstract
The hypothesis that brain pathways form 2D sheet-like structures layered in 3D as "pages of a book" has been a topic of debate in the recent literature. This hypothesis was mainly supported by a qualitative evaluation of "path neighborhoods" reconstructed with diffusion MRI (dMRI) tractography. Notwithstanding the potentially important implications of the sheet structure hypothesis for our understanding of brain structure and development, it is still considered controversial by many for lack of quantitative analysis. A means to quantify sheet structure is therefore necessary to reliably investigate its occurrence in the brain. Previous work has proposed the Lie bracket as a quantitative indicator of sheet structure, which could be computed by reconstructing path neighborhoods from the peak orientations of dMRI orientation density functions. Robust estimation of the Lie bracket, however, is challenging due to high noise levels and missing peak orientations. We propose a novel method to estimate the Lie bracket that does not involve the reconstruction of path neighborhoods with tractography. This method requires the computation of derivatives of the fiber peak orientations, for which we adopt an approach called normalized convolution. With simulations and experimental data we show that the new approach is more robust with respect to missing peaks and noise. We also demonstrate that the method is able to quantify to what extent sheet structure is supported for dMRI data of different species, acquired with different scanners, diffusion weightings, dMRI sampling schemes, and spatial resolutions. The proposed method can also be used with directional data derived from other techniques than dMRI, which will facilitate further validation of the existence of sheet structure.
KT Huang, S Ludy, D Calligaris, IF Dunn, E Laws, S Santagata, and NYR Agar. 2017. “Rapid Mass Spectrometry Imaging to Assess the Biochemical Profile of Pituitary Tissue for Potential Intraoperative Usage.” Adv Cancer Res, 134, Pp. 257-82.Abstract

Pituitary adenomas are relatively common intracranial neoplasms that are frequently treated with surgical resection. Rapid visualization of pituitary tissue remains a challenge as current techniques either produce little to no information on hormone-secreting function or are too slow to practically aid in intraoperative or even perioperative decision-making. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) represents a powerful method by which molecular maps of tissue samples can be created, yielding a two-dimensional representation of the expression patterns of small molecules and proteins from biologic samples. In this chapter, we review the use of MALDI MSI, its application to the characterization of the pituitary gland, and its potential applications for guiding the management of pituitary adenomas.

Mukund Balasubramanian, William M Wells, John R Ives, Patrick Britz, Robert V Mulkern, and Darren B Orbach. 2017. “RF Heating of Gold Cup and Conductive Plastic Electrodes during Simultaneous EEG and MRI.” Neurodiagn J, 57, 1, Pp. 69-83.Abstract
PURPOSE: To investigate the heating of EEG electrodes during magnetic resonance imaging (MRI) scans and to better understand the underlying physical mechanisms with a focus on the antenna effect. MATERIALS AND METHODS: Gold cup and conductive plastic electrodes were placed on small watermelons with fiberoptic probes used to measure electrode temperature changes during a variety of 1.5T and 3T MRI scans. A subset of these experiments was repeated on a healthy human volunteer. RESULTS: The differences between gold and plastic electrodes did not appear to be practically significant. For both electrode types, we observed heating below 4°C for straight wires whose lengths were multiples of ½ the radiofrequency (RF) wavelength and stronger heating (over 15°C) for wire lengths that were odd multiples of ¼ RF wavelength, consistent with the antenna effect. CONCLUSIONS: The antenna effect, which has received little attention so far in the context of EEG-MRI safety, can play as significant a role as the loop effect (from electromagnetic induction) in the heating of EEG electrodes, and therefore wire lengths that are odd multiples of ¼ RF wavelength should be avoided. These results have important implications for the design of EEG electrodes and MRI studies as they help to minimize the risk to patients undergoing MRI with EEG electrodes in place.
Tobias Frank, Axel Krieger, Simon Leonard, Niravkumar A Patel, and Junichi Tokuda. 2017. “ROS-IGTL-Bridge: An Open Network Interface for Image-Guided Therapy using the ROS Environment.” Int J Comput Assist Radiol Surg, 12, 8, Pp. 1451-60.Abstract
PURPOSE: With the growing interest in advanced image-guidance for surgical robot systems, rapid integration and testing of robotic devices and medical image computing software are becoming essential in the research and development. Maximizing the use of existing engineering resources built on widely accepted platforms in different fields, such as robot operating system (ROS) in robotics and 3D Slicer in medical image computing could simplify these tasks. We propose a new open network bridge interface integrated in ROS to ensure seamless cross-platform data sharing. METHODS: A ROS node named ROS-IGTL-Bridge was implemented. It establishes a TCP/IP network connection between the ROS environment and external medical image computing software using the OpenIGTLink protocol. The node exports ROS messages to the external software over the network and vice versa simultaneously, allowing seamless and transparent data sharing between the ROS-based devices and the medical image computing platforms. RESULTS: Performance tests demonstrated that the bridge could stream transforms, strings, points, and images at 30 fps in both directions successfully. The data transfer latency was <1.2 ms for transforms, strings and points, and 25.2 ms for color VGA images. A separate test also demonstrated that the bridge could achieve 900 fps for transforms. Additionally, the bridge was demonstrated in two representative systems: a mock image-guided surgical robot setup consisting of 3D slicer, and Lego Mindstorms with ROS as a prototyping and educational platform for IGT research; and the smart tissue autonomous robot surgical setup with 3D Slicer. CONCLUSION: The study demonstrated that the bridge enabled cross-platform data sharing between ROS and medical image computing software. This will allow rapid and seamless integration of advanced image-based planning/navigation offered by the medical image computing software such as 3D Slicer into ROS-based surgical robot systems.
Isaiah Norton, Walid Ibn Essayed, Fan Zhang, Sonia Pujol, Alex Yarmarkovich, Alexandra J Golby, Gordon Kindlmann, Demian Wasserman, Raul San Jose Estepar, Yogesh Rathi, Steve Pieper, Ron Kikinis, Hans J Johnson, Carl-Fredrik Westin, and Lauren J O'Donnell. 2017. “SlicerDMRI: Open Source Diffusion MRI Software for Brain Cancer Research.” Cancer Res, 77, 21, Pp. e101-e103.Abstract
Diffusion MRI (dMRI) is the only noninvasive method for mapping white matter connections in the brain. We describe SlicerDMRI, a software suite that enables visualization and analysis of dMRI for neuroscientific studies and patient-specific anatomic assessment. SlicerDMRI has been successfully applied in multiple studies of the human brain in health and disease, and here, we especially focus on its cancer research applications. As an extension module of the 3D Slicer medical image computing platform, the SlicerDMRI suite enables dMRI analysis in a clinically relevant multimodal imaging workflow. Core SlicerDMRI functionality includes diffusion tensor estimation, white matter tractography with single and multi-fiber models, and dMRI quantification. SlicerDMRI supports clinical DICOM and research file formats, is open-source and cross-platform, and can be installed as an extension to 3D Slicer (www.slicer.org). More information, videos, tutorials, and sample data are available at dmri.slicer.org Cancer Res; 77(21); e101-3. ©2017 AACR.
K Fischer, S Ohori, FC Meral, M Uehara, S Giannini, T Ichimura, RN Smith, FA Jolesz, I Guleria, Y. Zhang, PJ White, NJ McDannold, K Hoffmeister, MM Givertz, and R Abdi. 2017. “Testing the Efficacy of Contrast-Enhanced Ultrasound in Detecting Transplant Rejection using a Murine Model of Heart Transplantation.” Am J Transplant, 17, 7, Pp. 1791-1801.Abstract
One of the key unmet needs to improve long-term outcomes of heart transplantation is to develop accurate, noninvasive, and practical diagnostic tools to detect transplant rejection. Early intragraft inflammation and endothelial cell injuries occur prior to advanced transplant rejection. We developed a novel diagnostic imaging platform to detect early declines in microvascular perfusion (MP) of cardiac transplants using contrast-enhanced ultrasonography (CEUS). The efficacy of CEUS in detecting transplant rejection was tested in a murine model of heart transplants, a standard preclinical model of solid organ transplant. As compared to the syngeneic groups, a progressive decline in MP was demonstrated in the allografts undergoing acute transplant rejection (40%, 64%, and 92% on days 4, 6, and 8 posttransplantation, respectively) and chronic rejection (33%, 33%, and 92% on days 5, 14, and 30 posttransplantation, respectively). Our perfusion studies showed restoration of MP following antirejection therapy, highlighting its potential to help monitor efficacy of antirejection therapy. Our data suggest that early endothelial cell injury and platelet aggregation contributed to the early MP decline observed in the allografts. High-resolution MP mapping may allow for noninvasive detection of heart transplant rejection. The data presented have the potential to help in the development of next-generation imaging approaches to diagnose transplant rejection.
Dimitris Mitsouras, Thomas C Lee, Peter Liacouras, Ciprian N Ionita, Todd Pietilla, Stephan E. Maier, and Robert V. Mulkern. 2017. “Three-dimensional Printing of MRI-visible Phantoms and MR Image-guided Therapy Simulation.” Magn Reson Med, 77, 2, Pp. 613-22.Abstract

PURPOSE: To demonstrate the use of anatomic MRI-visible three-dimensional (3D)-printed phantoms and to assess process accuracy and material MR signal properties. METHODS: A cervical spine model was generated from computed tomography (CT) data and 3D-printed using an MR signal-generating material. Printed phantom accuracy and signal characteristics were assessed using 120 kVp CT and 3 Tesla (T) MR imaging. The MR relaxation rates and diffusion coefficient of the fabricated phantom were measured and (1) H spectra were acquired to provide insight into the nature of the proton signal. Finally, T2 -weighted imaging was performed during cryoablation of the model. RESULTS: The printed model produced a CT signal of 102 ± 8 Hounsfield unit, and an MR signal roughly 1/3(rd) that of saline in short echo time/short repetition time GRE MRI (456 ± 36 versus 1526 ± 121 arbitrary signal units). Compared with the model designed from the in vivo CT scan, the printed model differed by 0.13 ± 0.11 mm in CT, and 0.62 ± 0.28 mm in MR. The printed material had T2 ∼32 ms, T2*∼7 ms, T1 ∼193 ms, and a very small diffusion coefficient less than olive oil. MRI monitoring of the cryoablation demonstrated iceball formation similar to an in vivo procedure. CONCLUSION: Current 3D printing technology can be used to print anatomically accurate phantoms that can be imaged by both CT and MRI. Such models can be used to simulate MRI-guided interventions such as cryosurgeries. Future development of the proposed technique can potentially lead to printed models that depict different tissues and anatomical structures with different MR signal characteristics. 

Mohsen Ghafoorian, Alireza Mehrtash, Tina Kapur, Nico Karssemeijer, Elena Marchiori, Mehran Pesteie, Charles RG Guttmann, Frank-Erik de Leeuw, Clare MC Tempany, Bram van Ginneken, Andriy Fedorov, Purang Abolmaesumi, Bram Plate, and William M Wells. 2017. “Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation.” Int Conf Med Image Comput Comput Assist Interv 20 (Pt3), Pp. 516-24.Abstract
Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of normal and diseased tissue in the images. Convolutional neural networks (CNNs), which have shown to be successful in many medical image analysis tasks, are typically sensitive to the variations in imaging protocols. Therefore, in many cases, networks trained on data acquired with one MRI protocol, do not perform satisfactorily on data acquired with different protocols. This limits the use of models trained with large annotated legacy datasets on a new dataset with a different domain which is often a recurring situation in clinical settings. In this study, we aim to answer the following central questions regarding domain adaptation in medical image analysis: Given a fitted legacy model, (1) How much data from the new domain is required for a decent adaptation of the original network?; and, (2) What portion of the pre-trained model parameters should be retrained given a certain number of the new domain training samples? To address these questions, we conducted extensive experiments in white matter hyperintensity segmentation task. We trained a CNN on legacy MR images of brain and evaluated the performance of the domain-adapted network on the same task with images from a different domain. We then compared the performance of the model to the surrogate scenarios where either the same trained network is used or a new network is trained from scratch on the new dataset. The domain-adapted network tuned only by two training examples achieved a Dice score of 0.63 substantially outperforming a similar network trained on the same set of examples from scratch.
Ghafoorian MICCAI 2017
Walid I Essayed, Fan Zhang, Prashin Unadkat, Rees G Cosgrove, Alexandra J Golby, and Lauren J O'Donnell. 2017. “White Matter Tractography for Neurosurgical Planning: A Topography-based Review of the Current State of the Art.” Neuroimage Clin, 15, Pp. 659-72.Abstract
We perform a review of the literature in the field of white matter tractography for neurosurgical planning, focusing on those works where tractography was correlated with clinical information such as patient outcome, clinical functional testing, or electro-cortical stimulation. We organize the review by anatomical location in the brain and by surgical procedure, including both supratentorial and infratentorial pathologies, and excluding spinal cord applications. Where possible, we discuss implications of tractography for clinical care, as well as clinically relevant technical considerations regarding the tractography methods. We find that tractography is a valuable tool in variable situations in modern neurosurgery. Our survey of recent reports demonstrates multiple potentially successful applications of white matter tractography in neurosurgery, with progress towards overcoming clinical challenges of standardization and interpretation.
Andre Mastmeyer, Guillaume Pernelle, Ruibin Ma, Lauren Barber, and Tina Kapur. 2017. “Accurate Model-based Segmentation of Gynecologic Brachytherapy Catheter Collections in MRI-images.” Med Image Anal, 42, Pp. 173-88.Abstract
The gynecological cancer mortality rate, including cervical, ovarian, vaginal and vulvar cancers, is more than 20,000 annually in the US alone. In many countries, including the US, external-beam radiotherapy followed by high dose rate brachytherapy is the standard-of-care. The superior ability of MR to visualize soft tissue has led to an increase in its usage in planning and delivering brachytherapy treatment. A technical challenge associated with the use of MRI imaging for brachytherapy, in contrast to that of CT imaging, is the visualization of catheters that are used to place radiation sources into cancerous tissue. We describe here a precise, accurate method for achieving catheter segmentation and visualization. The algorithm, with the assistance of manually provided tip locations, performs segmentation using image-features, and is guided by a catheter-specific, estimated mechanical model. A final quality control step removes outliers or conflicting catheter trajectories. The mean Hausdorff error on a 54 patient, 760 catheter reference database was 1.49  mm; 51 of the outliers deviated more than two catheter widths (3.4  mm) from the gold standard, corresponding to catheter identification accuracy of 93% in a Syed-Neblett template. In a multi-user simulation experiment for evaluating RMS precision by simulating varying manually-provided superior tip positions, 3σ maximum errors were 2.44  mm. The average segmentation time for a single catheter was 3 s on a standard PC. The segmentation time, accuracy and precision, are promising indicators of the value of this method for clinical translation of MR-guidance in gynecologic brachytherapy and other catheter-based interventional procedures.
Shinn-Huey S Chou, Eva C Gombos, Sona A Chikarmane, Catherine S Giess, and Jagadeesan Jayender. 2017. “Computer-Aided Heterogeneity Analysis in Breast MR Imaging Assessment of Ductal Carcinoma In Situ: Correlating Histologic Grade and Receptor Status.” J Magn Reson Imaging, 46, 6, Pp. 1748-59.Abstract

PURPOSE: To identify breast MR imaging biomarkers to predict histologic grade and receptor status of ductal carcinoma in situ (DCIS). MATERIALS AND METHODS: Informed consent was waived in this Health Insurance Portability and Accountability Act-compliant Institutional Review Board-approved study. Case inclusion was conducted from 7332 consecutive breast MR studies from January 1, 2009, to December 31, 2012. Excluding studies with benign diagnoses, studies without visible abnormal enhancement, and pathology containing invasive disease yielded 55 MR-imaged pathology-proven DCIS seen on 54 studies. Twenty-eight studies (52%) were performed at 1.5 Tesla (T); 26 (48%) at 3T. Regions-of-interest representing DCIS were segmented for precontrast, first and fourth postcontrast, and subtracted first and fourth postcontrast images on the open-source three-dimensional (3D) Slicer software. Fifty-seven metrics of each DCIS were obtained, including distribution statistics, shape, morphology, Renyi dimensions, geometrical measure, and texture, using the 3D Slicer HeterogeneityCAD module. Statistical correlation of heterogeneity metrics with DCIS grade and receptor status was performed using univariate Mann-Whitney test. RESULTS: Twenty-four of the 55 DCIS (44%) were high nuclear grade (HNG); 44 (80%) were estrogen receptor (ER) positive. Human epidermal growth factor receptor-2 (HER2) was amplified in 10/55 (18%), nonamplified in 34/55 (62%), unknown/equivocal in 8/55 (15%). Surface area-to-volume ratio showed significant difference (P < 0.05) between HNG and non-HNG DCIS. No metric differentiated ER status (0.113 < p ≤ 1.000). Seventeen metrics showed significant differences between HER2-positive and HER2-negative DCIS (0.016 < P < 0.050). CONCLUSION: Quantitative heterogeneity analysis of DCIS suggests the presence of MR imaging biomarkers in classifying DCIS grade and HER2 status. Validation with larger samples and prospective studies is needed to translate these results into clinical applications. LEVEL OF EVIDENCE: 3 J. Magn. Reson. Imaging 2017.

Pelin Aksit Ciris, Cheng-Chieh Cheng, Chang-Sheng Mei, Lawrence P. Panych, and Bruno Madore. 2017. “Dual-Pathway Sequences for MR Thermometry: When and Where to use Them.” Magn Reson Med, 77, 3, Pp. 1193-200.Abstract

PURPOSE: Dual-pathway sequences have been proposed to help improve the temperature-to-noise ratio (TNR) in MR thermometry. The present work establishes how much of an improvement these so-called "PSIF-FISP" sequences may bring in various organs and tissues. METHODS: Simulations and TNR calculations were validated against analytical equations, phantom, abdomen, and brain scans. Relative TNRs for PSIF-FISP, as compared to a dual-FISP reference standard, were calculated for flip angle (FA) = 1 to 85 º and repetition time (TR) = 6 to 60 ms, for gray matter, white matter, cervix, endometrium, myometrium, prostate, kidney medulla and cortex, bone marrow, pancreas, spleen, muscle, and liver tissues. RESULTS: PSIF-FISP was TNR superior in the kidney, pelvis, spleen, or gray matter at most tested TR and FA settings, and benefits increased at shorter TRs. PSIF-FISP was TNR superior in other tissues, e.g., liver, muscle, pancreas, for only short TR settings (20 ms or less). The TNR benefits of PSIF-FISP increased slightly with FA, and strongly with decreasing TR. Up to two- to three-fold reductions in TR with 20% TNR gains were achievable. In any given tissue, TNR performance is expected to further improve with heating, due to changes in relaxation rates. CONCLUSION: Dual-pathway PSIF-FISP can improve TNR and acquisition speed over standard gradient-recalled echo sequences, but optimal acquisition parameters are tissue dependent. Magn Reson Med 77:1193-1200, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Tzu-Cheng Chao, Jr-yuan George Chiou, Stephan E. Maier, and Bruno Madore. 2017. “Fast Diffusion Imaging with High Angular Resolution.” Magn Reson Med, 77, 2, Pp. 696-706.Abstract

PURPOSE: High angular resolution diffusion imaging (HARDI) is a well-established method to help reveal the architecture of nerve bundles, but long scan times and geometric distortions inherent to echo planar imaging (EPI) have limited its integration into clinical protocols. METHODS: A fast imaging method is proposed here that combines accelerated multishot diffusion imaging (AMDI), multiplexed sensitivity encoding (MUSE), and crossing fiber angular resolution of intravoxel structure (CFARI) to reduce spatial distortions and reduce total scan time. A multishot EPI sequence was used to improve geometrical fidelity as compared to a single-shot EPI acquisition, and acceleration in both k-space and diffusion sampling enabled reductions in scan time. The method is regularized and self-navigated for motion correction. Seven volunteers were scanned in this study, including four with volumetric whole brain acquisitions. RESULTS: The average similarity of microstructural orientations between undersampled datasets and their fully sampled counterparts was above 85%, with scan times below 5 min for whole-brain acquisitions. Up to 2.7-fold scan time acceleration along with four-fold distortion reduction was achieved. CONCLUSION: The proposed imaging strategy can generate HARDI results with relatively good geometrical fidelity and low scan duration, which may help facilitate the transition of HARDI from a successful research tool to a practical clinical one. Magn Reson Med, 2016. © 2016 Wiley Periodicals, Inc.

Stephanie M Wong, Rachel A Freedman, Yasuaki Sagara, Fatih Aydogan, William T Barry, and Mehra Golshan. 2017. “Growing Use of Contralateral Prophylactic Mastectomy Despite no Improvement in Long-term Survival for Invasive Breast Cancer.” Ann Surg, 265, 3, Pp. 581-9.Abstract
OBJECTIVE: To update and examine national temporal trends in contralateral prophylactic mastectomy (CPM) and determine whether survival differed for invasive breast cancer patients based on hormone receptor (HR) status and age. METHODS: We identified women diagnosed with unilateral stage I to III breast cancer between 1998 and 2012 within the Surveillance, Epidemiology, and End Results registry. We compared characteristics and temporal trends between patients undergoing breast-conserving surgery, unilateral mastectomy, and CPM. We then performed Cox proportional-hazards regression to examine breast cancer-specific survival (BCSS) and overall survival (OS) in women diagnosed between 1998 and 2007, who underwent breast-conserving surgery with radiation (breast-conserving therapy), unilateral mastectomy, or CPM, with subsequent subgroup analysis stratifying by age and HR status. RESULTS: Of 496,488 women diagnosed with unilateral invasive breast cancer, 59.6% underwent breast-conserving surgery, 33.4% underwent unilateral mastectomy, and 7.0% underwent CPM. Overall, the proportion of women undergoing CPM increased from 3.9% in 2002 to 12.7% in 2012 (P < 0.001). Reconstructive surgery was performed in 48.3% of CPM patients compared with only 16.0% of unilateral mastectomy patients, with rates of reconstruction with CPM rising from 35.3% in 2002 to 55.4% in 2012 (P < 0.001). When compared with breast-conserving therapy, we found no significant improvement in BCSS or OS for women undergoing CPM (BCSS: HR 1.08, 95% confidence interval 1.01-1.16; OS: HR 1.08, 95% confidence interval 1.03-1.14), regardless of HR status or age. CONCLUSIONS: The use of CPM more than tripled during the study period despite evidence suggesting no survival benefit over breast conservation. Further examination on how to optimally counsel women about surgical options is warranted.
Daniel I Glazer, William W Mayo-Smith, Nisha I Sainani, Cheryl A Sadow, Mark G Vangel, Clare M Tempany, and Ruth M Dunne. 2017. “Interreader Agreement of Prostate Imaging Reporting and Data System Version 2 Using an In-Bore MRI-Guided Prostate Biopsy Cohort: A Single Institution's Initial Experience.” AJR Am J Roentgenol, 209, 3, Pp. W145-51.Abstract
OBJECTIVE: The purpose of this study is to determine the interobserver agreement of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for diagnosing prostate cancer using in-bore MRI-guided prostate biopsy as the reference standard. MATERIALS AND METHODS: Fifty-nine patients underwent in-bore MRI-guided prostate biopsy between January 21, 2010, and August 21, 2013, and underwent diagnostic multiparametric MRI 6 months or less before biopsy. A single index lesion per patient was selected after retrospective review of MR images. Three fellowship-trained abdominal radiologists (with 1-11 years' experience) blinded to clinical information interpreted all studies according to PI-RADSv2. Interobserver agreement was assessed using Cohen kappa statistics. RESULTS: Thirty-eight lesions were in the peripheral zone and 21 were in the transition zone. Cancer was diagnosed in 26 patients (44%). Overall PI-RADS scores were higher for all biopsy-positive lesions (mean ± SD, 3.9 ± 1.1) than for biopsy-negative lesions (3.1 ± 1.0; p < 0.0001) and for clinically significant lesions (4.2 ± 1.0) than for clinically insignificant lesions (3.1 ± 1.0; p < 0.0001). Overall suspicion score interobserver agreement was moderate (κ = 0.45). There was moderate interobserver agreement among overall PI-RADS scores in the peripheral zone (κ = 0.46) and fair agreement in the transition zone (κ = 0.36). CONCLUSION: PI-RADSv2 scores were higher in the biopsy-positive group. PI-RADSv2 showed moderate interobserver agreement among abdominal radiologists with no prior experience using the scoring system.
Erik Velez, Andriy Fedorov, Kemal Tuncali, Olutayo Olubiyi, Christopher B Allard, Adam S Kibel, and Clare M Tempany. 2017. “Pathologic Correlation of Transperineal In-Bore 3-Tesla Magnetic Resonance Imaging-Guided Prostate Biopsy Samples with Radical Prostatectomy Specimen.” Abdom Radiol (NY), 42, 8, Pp. 2154-9.Abstract

PURPOSE: To determine the accuracy of in-bore transperineal 3-Tesla (T) magnetic resonance (MR) imaging-guided prostate biopsies for predicting final Gleason grades in patients who subsequently underwent radical prostatectomy (RP). METHODS: A retrospective review of men who underwent transperineal MR imaging-guided prostate biopsy (tpMRGB) with subsequent radical prostatectomy within 1 year was conducted from 2010 to 2015. All patients underwent a baseline 3-T multiparametric MRI (mpMRI) with endorectal coil and were selected for biopsy based on MR findings of a suspicious prostate lesion and high degree of clinical suspicion for cancer. Spearman correlation was performed to assess concordance between tpMRGB and final RP pathology among patients with and without previous transrectal ultrasound (TRUS)-guided biopsies. RESULTS: A total of 24 men met all eligibility requirements, with a median age of 65 years (interquartile range [IQR] 11.7). The median time from biopsy to RP was 85 days (IQR 50.5). Final pathology revealed Gleason 3 + 4 = 7 in 12 patients, 4 + 3 = 7 in 10 patients, and 4 + 4 = 8 in 2 patients. A strong correlation (ρ: +0.75, p < 0.001) between tpMRGB and RP results was observed, with Gleason scores concordant in 17 cases (71%). 16 of the 24 patients underwent prior TRUS biopsies. Subsequent tpMRGB revealed Gleason upgrading in 88% of cases, which was concordant with RP Gleason scores in 69% of cases (ρ: +0.75, p < 0.001). CONCLUSION: Final Gleason scores diagnosed by tpMRGB at 3-T correlate strongly with final RP surgical pathology. This may facilitate prostate cancer diagnosis, particularly in patients with negative or low-grade TRUS biopsy results in whom clinically significant cancer is suspected or detected on mpMRI.

Daniel I Glazer, Servet Tatli, Paul B Shyn, Mark G Vangel, Kemal Tuncali, and Stuart G Silverman. 2017. “Percutaneous Image-Guided Cryoablation of Hepatic Tumors: Single-Center Experience with Intermediate to Long-Term Outcomes.” AJR Am J Roentgenol, 209, 6, Pp. 1381-9.Abstract
OBJECTIVE: The purpose of this article is to report our intermediate to long-term outcomes with image-guided percutaneous hepatic tumor cryoablation and to evaluate its technical success, technique efficacy, local tumor progression, and adverse event rate. MATERIALS AND METHODS: Between 1998 and 2014, 299 hepatic tumors (243 metastases and 56 primary tumors; mean diameter, 2.5 cm; median diameter, 2.2 cm; range, 0.3-7.8 cm) in 186 patients (95 women; mean age, 60.9 years; range, 29-88 years) underwent cryoablation during 236 procedures using CT (n = 126), MRI (n = 100), or PET/CT (n = 10) guidance. Technical success, technique efficacy at 3 months, local tumor progression (mean follow-up, 2.5 years; range, 2 months to 14.6 years), and adverse event rates were calculated. RESULTS: The technical success rate was 94.6% (279/295). The technique efficacy rate was 89.5% (231/258) and was greater for tumors smaller than 4 cm (93.4%; 213/228) than for larger tumors (60.0%; 18/30) (p < 0.0001). Local tumor progression occurred in 23.3% (60/258) of tumors and was significantly more common after the treatment of tumors 4 cm or larger (63.3%; 19/30) compared with smaller tumors (18.0%; 41/228) (p < 0.0001). Adverse events followed 33.8% (80/236) of procedures and were grade 3-5 in 10.6% (25/236) of cases. Grade 3 or greater adverse events more commonly followed the treatment of larger tumors (19.5%; 8/41) compared with smaller tumors (8.7%; 17/195) (p = 0.04). CONCLUSION: Image-guided percutaneous cryoablation of hepatic tumors is efficacious; however, tumors smaller than 4 cm are more likely to be treated successfully and without an adverse event.
Ma Luo, Sarah F Frisken, Jared A Weis, Logan W Clements, Prashin Unadkat, Reid C Thompson, Alexandra J Golby, and Michael I Miga. 2017. “Retrospective Study Comparing Model-Based Deformation Correction to Intraoperative Magnetic Resonance Imaging for Image-Guided Neurosurgery.” J Med Imaging (Bellingham), 4, 3, Pp. 035003.Abstract
Brain shift during tumor resection compromises the spatial validity of registered preoperative imaging data that is critical to image-guided procedures. One current clinical solution to mitigate the effects is to reimage using intraoperative magnetic resonance (iMR) imaging. Although iMR has demonstrated benefits in accounting for preoperative-to-intraoperative tissue changes, its cost and encumbrance have limited its widespread adoption. While iMR will likely continue to be employed for challenging cases, a cost-effective model-based brain shift compensation strategy is desirable as a complementary technology for standard resections. We performed a retrospective study of [Formula: see text] tumor resection cases, comparing iMR measurements with intraoperative brain shift compensation predicted by our model-based strategy, driven by sparse intraoperative cortical surface data. For quantitative assessment, homologous subsurface targets near the tumors were selected on preoperative MR and iMR images. Once rigidly registered, intraoperative shift measurements were determined and subsequently compared to model-predicted counterparts as estimated by the brain shift correction framework. When considering moderate and high shift ([Formula: see text], [Formula: see text] measurements per case), the alignment error due to brain shift reduced from [Formula: see text] to [Formula: see text], representing [Formula: see text] correction. These first steps toward validation are promising for model-based strategies.
2016
Mao Li, Karol Miller, Grand Roman Joldes, Ron Kikinis, and Adam Wittek. 2016. “Biomechanical Model for Computing Deformations for Whole-body Image Registration: A Meshless Approach.” Int J Numer Method Biomed Eng, 32, 12.Abstract

Patient-specific biomechanical models have been advocated as a tool for predicting deformations of soft body organs/tissue for medical image registration (aligning two sets of images) when differences between the images are large. However, complex and irregular geometry of the body organs makes generation of patient-specific biomechanical models very time-consuming. Meshless discretisation has been proposed to solve this challenge. However, applications so far have been limited to 2D models and computing single organ deformations. In this study, 3D comprehensive patient-specific nonlinear biomechanical models implemented using meshless Total Lagrangian explicit dynamics algorithms are applied to predict a 3D deformation field for whole-body image registration. Unlike a conventional approach that requires dividing (segmenting) the image into non-overlapping constituents representing different organs/tissues, the mechanical properties are assigned using the fuzzy c-means algorithm without the image segmentation. Verification indicates that the deformations predicted using the proposed meshless approach are for practical purposes the same as those obtained using the previously validated finite element models. To quantitatively evaluate the accuracy of the predicted deformations, we determined the spatial misalignment between the registered (i.e. source images warped using the predicted deformations) and target images by computing the edge-based Hausdorff distance. The Hausdorff distance-based evaluation determines that our meshless models led to successful registration of the vast majority of the image features. Copyright © 2016 John Wiley & Sons, Ltd.

Jeffrey P Guenette, Nathan Himes, Andreas A Giannopoulos, Tatiana Kelil, Dimitris Mitsouras, and Thomas C Lee. 2016. “Computer-Based Vertebral Tumor Cryoablation Planning and Procedure Simulation Involving Two Cases using MRI-Visible 3D Printing and Advanced Visualization.” AJR Am J Roentgenol, 207, 5, Pp. 1128-31.Abstract

OBJECTIVE: We report the development and use of MRI-compatible and MRI-visible 3D printed models in conjunction with advanced visualization software models to plan and simulate safe access routes to achieve a theoretic zone of cryoablation for percutaneous image-guided treatment of a C7 pedicle osteoid osteoma and an L1 lamina osteoblastoma. Both models altered procedural planning and patient care. CONCLUSION: Patient-specific MRI-visible models can be helpful in planning complex percutaneous image-guided cryoablation procedures.

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