Publications

2017
Black D, Hettig J, Luz M, Hansen C, Kikinis R, Hahn H. Auditory Feedback to Support Image-Guided Medical Needle Placement. Int J Comput Assist Radiol Surg. 2017;12 (9) :1655-63.Abstract
PURPOSE: During medical needle placement using image-guided navigation systems, the clinician must concentrate on a screen. To reduce the clinician's visual reliance on the screen, this work proposes an auditory feedback method as a stand-alone method or to support visual feedback for placing the navigated medical instrument, in this case a needle. METHODS: An auditory synthesis model using pitch comparison and stereo panning parameter mapping was developed to augment or replace visual feedback for navigated needle placement. In contrast to existing approaches which augment but still require a visual display, this method allows view-free needle placement. An evaluation with 12 novice participants compared both auditory and combined audiovisual feedback against existing visual methods. RESULTS: Using combined audiovisual display, participants show similar task completion times and report similar subjective workload and accuracy while viewing the screen less compared to using the conventional visual method. The auditory feedback leads to higher task completion times and subjective workload compared to both combined and visual feedback. CONCLUSION: Audiovisual feedback shows promising results and establishes a basis for applying auditory feedback as a supplement to visual information to other navigated interventions, especially those for which viewing a patient is beneficial or necessary.
Kamran SC, Manuel MM, Catalano P, Cho L, Damato AL, Lee LJ, Schmidt EJ, Viswanathan AN. MR- versus CT-based High-dose-rate Interstitial Brachytherapy for Vaginal Recurrence of Endometrial Cancer. Brachytherapy. 2017;16 (6) :1159-68.Abstract
PURPOSE: To compare clinical outcomes of MR-based versus CT-based high-dose-rate interstitial brachytherapy (ISBT) for vaginal recurrence of endometrioid endometrial cancer (EC). METHODS AND MATERIALS: We reviewed 66 patients with vaginal recurrent EC; 18 had MR-based ISBT on a prospective clinical trial and 48 had CT-based treatment. Kaplan-Meier survival modeling was used to generate estimates for local control (LC), disease-free interval (DFI), and overall survival (OS), and multivariate Cox modeling was used to assess prognostic factors. Toxicities were evaluated and compared. RESULTS: Median followup was 33 months (CT 30 months, MR 35 months). Median cumulative equivalent dose in 2-Gy fractions was 75.5 Gy for MR-ISBT and 73.8 Gy for CT-ISBT (p = 0.58). MR patients were older (p = 0.03) and had larger tumor size (>4 cm vs. ≤ 4 cm) compared to CT patients (p = 0.04). For MR-based versus CT-based ISBT, 3-year KM rate for local control was 100% versus 78% (p = 0.04), DFI was 69% versus 55% (p = 0.1), and OS was 63% versus 75% (p = 0.81), respectively. On multivariate analysis, tumor Grade 3 was associated with worse OS (HR 3.57, 95% CI 1.25, 11.36) in a model with MR-ISBT (HR 0.56, 95% CI 0.16, 1.89). Toxicities were not significantly different between the two modalities. CONCLUSION: Despite worse patient prognostic features, MR-ISBT was associated with a significantly better (100%) 3-year local control, comparable survival, and improved DFI rates compared to CT. Toxicities did not differ compared to CT-ISBT patients. Tumor grade contributed as the most significant predictor for survival. Larger prospective studies are needed to assess the impact of MR-ISBT on survival outcomes.
de Arcos J, Schmidt EJ, Wang W, Tokuda J, Vij K, Seethamraju RT, Damato AL, Dumoulin CL, Cormack RA, Viswanathan AN. Prospective Clinical Implementation of a Novel Magnetic Resonance Tracking Device for Real-Time Brachytherapy Catheter Positioning. Int J Radiat Oncol Biol Phys. 2017;99 (3) :618-26.Abstract
PURPOSE: We designed and built dedicated active magnetic resonance (MR)-tracked (MRTR) stylets. We explored the role of MRTR in a prospective clinical trial. METHODS AND MATERIALS: Eleven gynecologic cancer patients underwent MRTR to rapidly optimize interstitial catheter placement. MRTR catheter tip location and orientation were computed and overlaid on images displayed on in-room monitors at rates of 6 to 16 frames per second. Three modes of actively tracked navigation were analyzed: coarse navigation to the approximate region around the tumor; fine-tuning, bringing the stylets to the desired location; and pullback, with MRTR stylets rapidly withdrawn from within the catheters, providing catheter trajectories for radiation treatment planning (RTP). Catheters with conventional stylets were inserted, forming baseline locations. MRTR stylets were substituted, and catheter navigation was performed by a clinician working inside the MRI bore, using monitor feedback. RESULTS: Coarse navigation allowed repositioning of the MRTR catheters tips by 16 mm (mean), relative to baseline, in 14 ± 5 s/catheter (mean ± standard deviation [SD]). The fine-tuning mode repositioned the catheter tips by a further 12 mm, in 24 ± 17 s/catheter. Pullback mode provided catheter trajectories with RTP point resolution of ∼1.5 mm, in 1 to 9 s/catheter. CONCLUSIONS: MRTR-based navigation resulted in rapid and optimal placement of interstitial brachytherapy catheters. Catheters were repositioned compared with the initial insertion without tracking. In pullback mode, catheter trajectories matched computed tomographic precision, enabling their use for RTP.
Li M, Narayan V, Gill RR, Jagannathan JP, Barile MF, Gao F, Bueno R, Jayender J. Computer-Aided Diagnosis of Ground-Glass Opacity Nodules Using Open-Source Software for Quantifying Tumor Heterogeneity. AJR Am J Roentgenol. 2017;209 (6) :1216-27.Abstract
OBJECTIVE: The purposes of this study are to develop quantitative imaging biomarkers obtained from high-resolution CTs for classifying ground-glass nodules (GGNs) into atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC); to evaluate the utility of contrast enhancement for differential diagnosis; and to develop and validate a support vector machine (SVM) to predict the GGN type. MATERIALS AND METHODS: The heterogeneity of 248 GGNs was quantified using custom software. Statistical analysis with a univariate Kruskal-Wallis test was performed to evaluate metrics for significant differences among the four GGN groups. The heterogeneity metrics were used to train a SVM to learn and predict the lesion type. RESULTS: Fifty of 57 and 51 of 57 heterogeneity metrics showed statistically significant differences among the four GGN groups on unenhanced and contrast-enhanced CT scans, respectively. The SVM predicted lesion type with greater accuracy than did three expert radiologists. The accuracy of classifying the GGNs into the four groups on the basis of the SVM algorithm was 70.9%, whereas the accuracy of the radiologists was 39.6%. The accuracy of SVM in classifying the AIS and MIA nodules was 73.1%, and the accuracy of the radiologists was 35.7%. For indolent versus invasive lesions, the accuracy of the SVM was 88.1%, and the accuracy of the radiologists was 60.8%. We found that contrast enhancement does not significantly improve the differential diagnosis of GGNs. CONCLUSION: Compared with the GGN classification done by the three radiologists, the SVM trained regarding all the heterogeneity metrics showed significantly higher accuracy in classifying the lesions into the four groups, differentiating between AIS and MIA and between indolent and invasive lesions. Contrast enhancement did not improve the differential diagnosis of GGNs.
Maier-Hein KH, Neher PF, Houde J-C, Côté M-A, Garyfallidis E, Zhong J, Chamberland M, Yeh F-C, Lin Y-C, Ji Q, et al. The Challenge of Mapping the Human Connectome Based on Diffusion Tractography. Nat Commun. 2017;8 (1) :1349.Abstract
Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.
Verma S, Choyke PL, Eberhardt SC, Oto A, Tempany CM, Turkbey B, Rosenkrantz AB. The Current State of MR Imaging-targeted Biopsy Techniques for Detection of Prostate Cancer. Radiology. 2017;285 (2) :343-56.Abstract
Systematic transrectal ultrasonography (US)-guided biopsy is the standard approach for histopathologic diagnosis of prostate cancer. However, this technique has multiple limitations because of its inability to accurately visualize and target prostate lesions. Multiparametric magnetic resonance (MR) imaging of the prostate is more reliably able to localize significant prostate cancer. Targeted prostate biopsy by using MR imaging may thus help to reduce false-negative results and improve risk assessment. Several commercial devices are now available for targeted prostate biopsy, including in-gantry MR imaging-targeted biopsy and real-time transrectal US-MR imaging fusion biopsy systems. This article reviews the current status of MR imaging-targeted biopsy platforms, including technical considerations, as well as advantages and challenges of each technique.
Norton I, Essayed WI, Zhang F, Pujol S, Yarmarkovich A, Golby AJ, Kindlmann G, Wasserman D, Estepar RSJ, Rathi Y, et al. SlicerDMRI: Open Source Diffusion MRI Software for Brain Cancer Research. Cancer Res. 2017;77 (21) :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.
Luo M, Frisken SF, Weis JA, Clements LW, Unadkat P, Thompson RC, Golby AJ, Miga MI. Retrospective Study Comparing Model-Based Deformation Correction to Intraoperative Magnetic Resonance Imaging for Image-Guided Neurosurgery. J Med Imaging (Bellingham). 2017;4 (3) :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.
Niethammer M, Pohl KM, Janoos F, Wells WM. Active Mean Fields for Probabilistic Image Segmentation: Connections with Chan-Vese and Rudin-Osher-Fatemi Models. SIAM J. Imaging Sci. 2017;10 (3) :1069–1103.Abstract
Segmentation is a fundamental task for extracting semantically meaningful regions from an image. The goal of segmentation algorithms is to accurately assign object labels to each image location. However, image noise, shortcomings of algorithms, and image ambiguities cause uncertainty in label assignment. Estimating this uncertainty is important in multiple application domains, such as segmenting tumors from medical images for radiation treatment planning. One way to estimate these uncertainties is through the computation of posteriors of Bayesian models, which is computationally prohibitive for many practical applications. However, most computationally efficient methods fail to estimate label uncertainty. We therefore propose in this paper the active mean fields (AMF) approach, a technique based on Bayesian modeling that uses a mean-field approximation to efficiently compute a segmentation and its corresponding uncertainty. Based on a variational formulation, the resulting convex model combines any label-likelihood measure with a prior on the length of the segmentation boundary. A specific implementation of that model is the Chan-Vese segmentation model, in which the binary segmentation task is defined by a Gaussian likelihood and a prior regularizing the length of the segmentation boundary. Furthermore, the Euler-Lagrange equations derived from the AMF model are equivalent to those of the popular Rudin-Osher-Fatemi (ROF) model for image denoising. Solutions to the AMF model can thus be implemented by directly utilizing highly efficient ROF solvers on log-likelihood ratio fields. We qualitatively assess the approach on synthetic data as well as on real natural and medical images. For a quantitative evaluation, we apply our approach to the tt icgbench dataset.
Ghafoorian M, Mehrtash A, Kapur T, Karssemeijer N, Marchiori E, Pesteie M, Guttmann CRG, de Leeuw F-E, Tempany CMC, van Ginneken B, et al. Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation. Int Conf Med Image Comput Comput Assist Interv. 2017;20 (Pt3) :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
Glazer DI, Tatli S, Shyn PB, Vangel MG, Tuncali K, Silverman SG. Percutaneous Image-Guided Cryoablation of Hepatic Tumors: Single-Center Experience with Intermediate to Long-Term Outcomes. AJR Am J Roentgenol. 2017;209 (6) :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.
Mastmeyer A, Pernelle G, Ma R, Barber L, Kapur T. Accurate Model-based Segmentation of Gynecologic Brachytherapy Catheter Collections in MRI-images. Med Image Anal. 2017;42 :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.
Todd N, Josephs O, Zeidman P, Flandin G, Moeller S, Weiskopf N. Functional Sensitivity of 2D Simultaneous Multi-Slice Echo-Planar Imaging: Effects of Acceleration on g-factor and Physiological Noise. Front Neurosci. 2017;11 :158.Abstract
Accelerated data acquisition with simultaneous multi-slice (SMS) imaging for functional MRI studies leads to interacting and opposing effects that influence the sensitivity to blood oxygen level-dependent (BOLD) signal changes. Image signal to noise ratio (SNR) is decreased with higher SMS acceleration factors and shorter repetition times (TR) due to g-factor noise penalties and saturation of longitudinal magnetization. However, the lower image SNR is counteracted by greater statistical power from more samples per unit time and a higher temporal Nyquist frequency that allows for better removal of spurious non-BOLD high frequency signal content. This study investigated the dependence of the BOLD sensitivity on these main driving factors and their interaction, and provides a framework for evaluating optimal acceleration of SMS-EPI sequences. functional magnetic resonance imaging (fMRI) data from a scenes/objects visualization task was acquired in 10 healthy volunteers at a standard neuroscience resolution of 3 mm on a 3T MRI scanner. SMS factors 1, 2, 4, and 8 were used, spanning TRs of 2800 ms to 350 ms. Two data processing methods were used to equalize the number of samples over the SMS factors. BOLD sensitivity was assessed using g-factors maps, temporal SNR (tSNR), and t-score metrics. tSNR results show a dependence on SMS factor that is highly non-uniform over the brain, with outcomes driven by g-factor noise amplification and the presence of high frequency noise. The t-score metrics also show a high degree of spatial dependence: the lower g-factor noise area of V1 shows significant improvements at higher SMS factors; the moderate-level g-factor noise area of the parahippocampal place area shows only a trend of improvement; and the high g-factor noise area of the ventral-medial pre-frontal cortex shows a trend of declining t-scores at higher SMS factors. This spatial variability suggests that the optimal SMS factor for fMRI studies is region dependent. For task fMRI studies done with similar parameters as were used here (3T scanner, 32-channel RF head coil, whole brain coverage at 3 mm isotropic resolution), we recommend SMS accelerations of 4x (conservative) to 8x (aggressive) for most studies and a more conservative acceleration of 2x for studies interested in anterior midline regions.
Zhang M, Wells WM, Golland P. Probabilistic Modeling of Anatomical Variability using a Low Dimensional Parameterization of Diffeomorphisms. Med Image Anal. 2017;41 :55-62.Abstract
We present an efficient probabilistic model of anatomical variability in a linear space of initial velocities of diffeomorphic transformations and demonstrate its benefits in clinical studies of brain anatomy. To overcome the computational challenges of the high dimensional deformation-based descriptors, we develop a latent variable model for principal geodesic analysis (PGA) based on a low dimensional shape descriptor that effectively captures the intrinsic variability in a population. We define a novel shape prior that explicitly represents principal modes as a multivariate complex Gaussian distribution on the initial velocities in a bandlimited space. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than the state-of-the-art method such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA) that operate in the high dimensional image space.
Liao R, Ning L, Chen Z, Rigolo L, Gong S, Pasternak O, Golby AJ, Rathi Y, O'Donnell LJ, ckovic JV. Performance of Unscented Kalman Filter Tractography in Edema: Analysis of the Two-tensor Model. Neuroimage Clin. 2017;15 :819-31.Abstract
Diffusion MRI tractography is increasingly used in pre-operative neurosurgical planning to visualize critical fiber tracts. However, a major challenge for conventional tractography, especially in patients with brain tumors, is tracing fiber tracts that are affected by vasogenic edema, which increases water content in the tissue and lowers diffusion anisotropy. One strategy for improving fiber tracking is to use a tractography method that is more sensitive than the traditional single-tensor streamline tractography. We performed experiments to assess the performance of two-tensor unscented Kalman filter (UKF) tractography in edema. UKF tractography fits a diffusion model to the data during fiber tracking, taking advantage of prior information from the previous step along the fiber. We studied UKF performance in a synthetic diffusion MRI digital phantom with simulated edema and in retrospective data from two neurosurgical patients with edema affecting the arcuate fasciculus and corticospinal tracts. We compared the performance of several tractography methods including traditional streamline, UKF single-tensor, and UKF two-tensor. To provide practical guidance on how the UKF method could be employed, we evaluated the impact of using various seed regions both inside and outside the edematous regions, as well as the impact of parameter settings on the tractography sensitivity. We quantified the sensitivity of different methods by measuring the percentage of the patient-specific fMRI activation that was reached by the tractography. We expected that diffusion anisotropy threshold parameters, as well as the inclusion of a free water model, would significantly influence the reconstruction of edematous WM fiber tracts, because edema increases water content in the tissue and lowers anisotropy. Contrary to our initial expectations, varying the fractional anisotropy threshold and including a free water model did not affect the UKF two-tensor tractography output appreciably in these two patient datasets. The most effective parameter for increasing tracking sensitivity was the generalized anisotropy (GA) threshold, which increased the length of tracked fibers when reduced to 0.075. In addition, the most effective seeding strategy was seeding in the whole brain or in a large region outside of the edema. Overall, the main contribution of this study is to provide insight into how UKF tractography can work, using a two-tensor model, to begin to address the challenge of fiber tract reconstruction in edematous regions near brain tumors.
Glazer DI, Mayo-Smith WW, Sainani NI, Sadow CA, Vangel MG, Tempany CM, Dunne RM. 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. 2017;209 (3) :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.
Fischer K, Ohori S, Meral FC, Uehara M, Giannini S, Ichimura T, Smith RN, Jolesz FA, Guleria I, Zhang Y, et al. Testing the Efficacy of Contrast-Enhanced Ultrasound in Detecting Transplant Rejection using a Murine Model of Heart Transplantation. Am J Transplant. 2017;17 (7) :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.
Nishino M, Sacher AG, Gandhi L, Chen Z, Akbay E, Fedorov A, Westin CF, Hatabu H, Johnson BE, Hammerman P, et al. Co-clinical Quantitative Tumor Volume Imaging in ALK-rearranged NSCLC Treated with Crizotinib. Eur J Radiol. 2017;88 :15-20.Abstract
PURPOSE: To evaluate and compare the volumetric tumor burden changes during crizotinib therapy in mice and human cohorts with ALK-rearranged non-small-cell lung cancer (NSCLC). METHODS: Volumetric tumor burden was quantified on serial imaging studies in 8 bitransgenic mice with ALK-rearranged adenocarcinoma treated with crizotinib, and in 33 human subjects with ALK-rearranged NSCLC treated with crizotinib. The volumetric tumor burden changes and the time to maximal response were compared between mice and humans. RESULTS: The median tumor volume decrease (%) at the maximal response was -40.4% (range: -79.5%-+11.7%) in mice, and -72.9% (range: -100%-+72%) in humans (Wilcoxon p=0.03). The median time from the initiation of therapy to maximal response was 6 weeks in mice, and 15.7 weeks in humans. Overall volumetric response rate was 50% in mice and 97% in humans. Spider plots of tumor volume changes during therapy demonstrated durable responses in the human cohort, with a median time on therapy of 13.1 months. CONCLUSION: The present study described an initial attempt to evaluate quantitative tumor burden changes in co-clinical imaging studies of genomically-matched mice and human cohorts with ALK-rearranged NSCLC treated with crizotinib. Differences are noted in the degree of maximal volume response between the two cohorts in this well-established paradigm of targeted therapy, indicating a need for further studies to optimize co-clinical trial design and interpretation.
Essayed WI, Zhang F, Unadkat P, Cosgrove RG, Golby AJ, O'Donnell LJ. White Matter Tractography for Neurosurgical Planning: A Topography-based Review of the Current State of the Art. Neuroimage Clin. 2017;15 :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.
Fedorov A, Vangel MG, Tempany CM, Fennessy FM. Multiparametric Magnetic Resonance Imaging of the Prostate: Repeatability of Volume and Apparent Diffusion Coefficient Quantification. Invest Radiol. 2017;52 (9) :538-46.Abstract
OBJECTIVES: The aim of this study was to evaluate the repeatability of a region of interest (ROI) volume and mean apparent diffusion coefficient (ADC) in standard-of-care 3 T multiparametric magnetic resonance imaging (mpMRI) of the prostate obtained with the use of endorectal coil. MATERIALS AND METHODS: This prospective study was Health Insurance Portability and Accountability Act compliant, with institutional review board approval and written informed consent. Men with confirmed or suspected treatment-naive prostate cancer scheduled for mpMRI were offered a repeat mpMRI within 2 weeks. Regions of interest corresponding to the whole prostate gland, the entire peripheral zone (PZ), normal PZ, and suspected tumor ROI (tROI) on axial T2-weighted, dynamic contrast-enhanced subtract, and ADC images were annotated and assessed using Prostate Imaging Reporting and Data System (PI-RADS) v2. Repeatability of the ROI volume for each of the analyzed image types and mean ROI ADC was summarized with repeatability coefficient (RC) and RC%. RESULTS: A total of 189 subjects were approached to participate in the study. Of 40 patients that gave initial agreement, 15 men underwent 2 mpMRI examinations and completed the study. Peripheral zone tROIs were identified in 11 subjects. Tumor ROI volume was less than 0.5 mL in 8 of 11 subjects. PI-RADS categories were identical between baseline-repeat studies in 11/15 subjects and differed by 1 point in 4/15. Peripheral zone tROI volume RC (RC%) was 233 mm (71%) on axial T2-weighted, 422 mm (112%) on ADC, and 488 mm (119%) on dynamic contrast-enhanced subtract. Apparent diffusion coefficient ROI mean RC (RC%) were 447 × 10 mm/s (42%) in PZ tROI and 471 × 10 mm/s (30%) in normal PZ. Significant difference in repeatability of the tROI volume across series was observed (P < 0.005). The mean ADC RC% was lower than volume RC% for tROI ADC (P < 0.05). CONCLUSIONS: PI-RADS v2 overall assessment was highly repeatable. Multiparametric magnetic resonance imaging sequences differ in volume measurement repeatability. The mean tROI ADC is more repeatable compared with tROI volume in ADC. Repeatability of prostate ADC is comparable with that in other abdominal organs.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

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