Publications

2018
Andras Lasso, Hannah H Nam, Patrick V Dinh, Csaba Pinter, Jean-Christophe Fillion-Robin, Steve Pieper, Sankhesh Jhaveri, Jean-Baptiste Vimort, Ken Martin, Mark Asselin, Francis X McGowan, Ron Kikinis, Gabor Fichtinger, and Matthew A Jolley. 2018. “Interaction with Volume-Rendered Three-Dimensional Echocardiographic Images in Virtual Reality.” J Am Soc Echocardiogr, 31, 10, Pp. 1158-60.
Ye Wu, Fan Zhang, Nikos Makris, Yuping Ning, Isaiah Norton, Shenglin She, Hongjun Peng, Yogesh Rathi, Yuanjing Feng, Huawang Wu, and Lauren J O'Donnell. 2018. “Investigation into Local White Matter Abnormality in Emotional Processing and Sensorimotor Areas using an Automatically Annotated Fiber Clustering in Major Depressive Disorder.” Neuroimage, 181, Pp. 16-29.Abstract
This work presents an automatically annotated fiber cluster (AAFC) method to enable identification of anatomically meaningful white matter structures from the whole brain tractography. The proposed method consists of 1) a study-specific whole brain white matter parcellation using a well-established data-driven groupwise fiber clustering pipeline to segment tractography into multiple fiber clusters, and 2) a novel cluster annotation method to automatically assign an anatomical tract annotation to each fiber cluster by employing cortical parcellation information across multiple subjects. The novelty of the AAFC method is that it leverages group-wise information about the fiber clusters, including their fiber geometry and cortical terminations, to compute a tract anatomical label for each cluster in an automated fashion. We demonstrate the proposed AAFC method in an application of investigating white matter abnormality in emotional processing and sensorimotor areas in major depressive disorder (MDD). Seven tracts of interest related to emotional processing and sensorimotor functions are automatically identified using the proposed AAFC method as well as a comparable method that uses a cortical parcellation alone. Experimental results indicate that our proposed method is more consistent in identifying the tracts across subjects and across hemispheres in terms of the number of fibers. In addition, we perform a between-group statistical analysis in 31 MDD patients and 62 healthy subjects on the identified tracts using our AAFC method. We find statistical differences in diffusion measures in local regions within a fiber tract (e.g. 4 fiber clusters within the identified left hemisphere cingulum bundle (consisting of 14 clusters) are significantly different between the two groups), suggesting the ability of our method in identifying potential abnormality specific to subdivisions of a white matter structure.
Baichuan Jiang, Wenpeng Gao, Daniel Kacher, Erez Nevo, Barry Fetics, Thomas C Lee, and Jagadeesan Jayender. 2018. “Kalman Filter-based EM-optical Sensor Fusion for Needle Deflection Estimation.” Int J Comput Assist Radiol Surg, 13, 4, Pp. 573-83.Abstract
PURPOSE: In many clinical procedures such as cryoablation that involves needle insertion, accurate placement of the needle's tip at the desired target is the major issue for optimizing the treatment and minimizing damage to the neighboring anatomy. However, due to the interaction force between the needle and tissue, considerable error in intraoperative tracking of the needle tip can be observed as needle deflects. METHODS: In this paper, measurements data from an optical sensor at the needle base and a magnetic resonance (MR) gradient field-driven electromagnetic (EM) sensor placed 10 cm from the needle tip are used within a model-integrated Kalman filter-based sensor fusion scheme. Bending model-based estimations and EM-based direct estimation are used as the measurement vectors in the Kalman filter, thus establishing an online estimation approach. RESULTS: Static tip bending experiments show that the fusion method can reduce the mean error of the tip position estimation from 29.23 mm of the optical sensor-based approach to 3.15 mm of the fusion-based approach and from 39.96 to 6.90 mm, at the MRI isocenter and the MRI entrance, respectively. CONCLUSION: This work established a novel sensor fusion scheme that incorporates model information, which enables real-time tracking of needle deflection with MRI compatibility, in a free-hand operating setup.
Markus Nilsson, Johan Larsson, Dan Lundberg, Filip Szczepankiewicz, Thomas Witzel, Carl-Fredrik Westin, Karin Bryskhe, and Daniel Topgaard. 2018. “Liquid Crystal Phantom for Validation of Microscopic Diffusion Anisotropy Measurements on Clinical MRI Systems.” Magn Reson Med, 79, 3, Pp. 1817-28.Abstract
PURPOSE: To develop a phantom for validating MRI pulse sequences and data processing methods to quantify microscopic diffusion anisotropy in the human brain. METHODS: Using a liquid crystal consisting of water, detergent, and hydrocarbon, we designed a 0.5-L spherical phantom showing the theoretically highest possible degree of microscopic anisotropy. Data were acquired on the Connectome scanner using echo-planar imaging signal readout and diffusion encoding with axisymmetric b-tensors of varying magnitude, anisotropy, and orientation. The mean diffusivity, fractional anisotropy (FA), and microscopic FA (µFA) parameters were estimated. RESULTS: The phantom was observed to have values of mean diffusivity similar to brain tissue, and relaxation times compatible with echo-planar imaging echo times on the order of 100 ms. The estimated values of µFA were at the theoretical maximum of 1.0, whereas the values of FA spanned the interval from 0.0 to 0.8 as a result of varying orientational order of the anisotropic domains within each voxel. CONCLUSIONS: The proposed phantom can be manufactured by mixing three widely available chemicals in volumes comparable to a human head. The acquired data are in excellent agreement with theoretical predictions, showing that the phantom is ideal for validating methods for measuring microscopic diffusion anisotropy on clinical MRI systems. Magn Reson Med 79:1817-1828, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Martin T King, Paul L Nguyen, Ninjin Boldbaatar, Clare M Tempany, Robert A Cormack, Clair J Beard, Mark D Hurwitz, Warren W Suh, Anthony V D'Amico, and Peter F Orio. 2018. “Long-Term Outcomes of Partial Prostate Treatment with Magnetic Resonance Imaging-Guided Brachytherapy for Patients with Favorable-Risk Prostate Cancer.” Cancer, 124, 17, Pp. 3528-35.Abstract
BACKGROUND: Partial prostate treatment has emerged as a potential method for treating patients with favorable-risk prostate cancer while minimizing toxicity. The authors previously demonstrated poor rates of biochemical disease control for patients with National Comprehensive Cancer Network (NCCN) intermediate-risk disease using partial gland treatment with brachytherapy. The objective of the current study was to estimate the rates of distant metastasis and prostate cancer-specific mortality (PCSM) for this cohort. METHODS: Between 1997 and 2007, a total of 354 men with clinical T1c disease, a prostate-specific antigen (PSA) level < 15 ng/mL, and Gleason grade ≤3 + 4 prostate cancer underwent partial prostate treatment with brachytherapy to the peripheral zone under 0.5-Tesla magnetic resonance guidance. The cumulative incidences of metastasis and PCSM for the NCCN very low-risk, low-risk, and intermediate-risk groups were estimated. Fine and Gray competing risk regression was used to evaluate clinical factors associated with time to metastasis. RESULTS: A total of 22 patients developed metastases at a median of 11.0 years (interquartile range, 6.9-13.9 years). The 12-year metastasis rates for patients with very low-risk, low-risk, and intermediate-risk disease were 0.8% (95% confidence interval [95% CI], 0.1%-4.4%), 8.7% (95% CI, 3.4%-17.2%), and 15.7% (95% CI, 5.7%-30.2%), respectively, and the 12-year PCSM estimates were 1.6% (95% CI, 0.1%-7.6%), 1.4% (95% CI, 0.1%-6.8%), and 8.2% (95% CI, 1.9%-20.7%), respectively. On multivariate analysis, NCCN risk category (low risk: hazard ratio, 6.34 [95% CI, 1.18-34.06; P = .03] and intermediate risk: hazard ratio, 6.98 [95% CI, 1.23-39.73; P = .03]) was found to be significantly associated with the time to metastasis. CONCLUSIONS: Partial prostate treatment with brachytherapy may be associated with higher rates of distant metastasis and PCSM for patients with intermediate-risk disease after long-term follow-up. Treatment of less than the full gland may not be appropriate for this cohort. Cancer 2018. © 2018 American Cancer Society.
Junichi Tokuda, Laurent Chauvin, Brian Ninni, Takahisa Kato, Franklin King, Kemal Tuncali, and Nobuhiko Hata. 2018. “Motion Compensation for MRI-compatible Patient-mounted Needle Guide Device: Estimation of Targeting Accuracy in MRI-guided Kidney Cryoablations.” Phys Med Biol, 63, 8, Pp. 085010.Abstract
Patient-mounted needle guide devices for percutaneous ablation are vulnerable to patient motion. The objective of this study is to develop and evaluate a software system for an MRI-compatible patient-mounted needle guide device that can adaptively compensate for displacement of the device due to patient motion using a novel image-based automatic device-to-image registration technique. We have developed a software system for an MRI-compatible patient-mounted needle guide device for percutaneous ablation. It features fully-automated image-based device-to-image registration to track the device position, and a device controller to adjust the needle trajectory to compensate for the displacement of the device. We performed: (a) a phantom study using a clinical MR scanner to evaluate registration performance; (b) simulations using intraoperative time-series MR data acquired in 20 clinical cases of MRI-guided renal cryoablations to assess its impact on motion compensation; and (c) a pilot clinical study in three patients to test its feasibility during the clinical procedure. FRE, TRE, and success rate of device-to-image registration were [Formula: see text] mm, [Formula: see text] mm, and 98.3% for the phantom images. The simulation study showed that the motion compensation reduced the targeting error for needle placement from 8.2 mm to 5.4 mm (p  <  0.0005) in patients under general anesthesia (GA), and from 14.4 mm to 10.0 mm ([Formula: see text]) in patients under monitored anesthesia care (MAC). The pilot study showed that the software registered the device successfully in a clinical setting. Our simulation study demonstrated that the software system could significantly improve targeting accuracy in patients treated under both MAC and GA. Intraprocedural image-based device-to-image registration was feasible.
JP Guenette, RT Seethamraju, J Jayender, CE Corrales, and TC Lee. 2018. “MR Imaging of the Facial Nerve through the Temporal Bone at 3T with a Noncontrast Ultrashort Echo Time Sequence.” AJNR Am J Neuroradiol, 39, 10, Pp. 1903-6.Abstract
The pointwise encoding time reduction with radial acquisition (PETRA) ultrashort echo time MR imaging sequence at 3T enables visualization of the facial nerve from the brain stem, through the temporal bone, to the stylomastoid foramen without intravenous contrast. Use of the PETRA sequence, or other ultrashort echo time sequences, should be considered in the MR imaging evaluation of certain skull base tumors and perhaps other facial nerve and temporal bone pathologies.
Ehud J Schmidt and Henry R Halperin. 2018. “MRI use for Atrial Tissue Characterization in Arrhythmias and for EP Procedure Guidance.” Int J Cardiovasc Imaging, 34, 1, Pp. 81-95.Abstract
We review the utilization of magnetic resonance imaging methods for classifying atrial tissue properties that act as a substrate for common cardiac arrhythmias, such as atrial fibrillation. We then review state-of-the-art methods for mapping this substrate as a predicate for treatment, as well as methods used to ablate the electrical pathways that cause arrhythmia and restore patients to sinus rhythm.
David C Newitt, Dariya Malyarenko, Thomas L Chenevert, Chad C Quarles, Laura Bell, Andriy Fedorov, Fiona Fennessy, Michael A Jacobs, Meiyappan Solaiyappan, Stefanie Hectors, Bachir Taouli, Mark Muzi, Paul E Kinahan, Kathleen M Schmainda, Melissa A Prah, Erin N Taber, Christopher Kroenke, Wei Huang, Lori R Arlinghaus, Thomas E Yankeelov, Yue Cao, Madhava Aryal, Yi-Fen Yen, Jayashree Kalpathy-Cramer, Amita Shukla-Dave, Maggie Fung, Jiachao Liang, Michael Boss, and Nola Hylton. 2018. “Multisite Concordance of Apparent Diffusion Coefficient Measurements across the NCI Quantitative Imaging Network.” J Med Imaging (Bellingham), 5, 1, Pp. 011003.Abstract
Diffusion weighted MRI has become ubiquitous in many areas of medicine, including cancer diagnosis and treatment response monitoring. Reproducibility of diffusion metrics is essential for their acceptance as quantitative biomarkers in these areas. We examined the variability in the apparent diffusion coefficient (ADC) obtained from both postprocessing software implementations utilized by the NCI Quantitative Imaging Network and online scan time-generated ADC maps. Phantom and breast studies were evaluated for two ([Formula: see text]) and four ([Formula: see text]) [Formula: see text]-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and [Formula: see text], with relative biases [Formula: see text] ([Formula: see text]) and [Formula: see text] (phantom [Formula: see text]) but with higher deviations in ADC at the lowest phantom ADC values. [Formula: see text] concordance was good, with typical biases of [Formula: see text] to 3% but higher for online maps. Multiple -value ADC implementations were separated into two groups determined by the fitting algorithm. Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for [Formula: see text] data. Some higher deviations were found for individual implementations and online parametric maps. Despite generally good concordance, implementation biases in ADC measures are sometimes significant and may be large enough to be of concern in multisite studies.
Inês Machado, Matthew Toews, Jie Luo, Prashin Unadkat, Walid Essayed, Elizabeth George, Pedro Teodoro, Herculano Carvalho, Jorge Martins, Polina Golland, Steve Pieper, Sarah Frisken, Alexandra Golby, and William Wells. 2018. “Non-rigid Registration of 3D Ultrasound for Neurosurgery using Automatic Feature Detection and Matching.” Int J Comput Assist Radiol Surg, 13, 10, Pp. 1525-38.Abstract
PURPOSE: The brain undergoes significant structural change over the course of neurosurgery, including highly nonlinear deformation and resection. It can be informative to recover the spatial mapping between structures identified in preoperative surgical planning and the intraoperative state of the brain. We present a novel feature-based method for achieving robust, fully automatic deformable registration of intraoperative neurosurgical ultrasound images. METHODS: A sparse set of local image feature correspondences is first estimated between ultrasound image pairs, after which rigid, affine and thin-plate spline models are used to estimate dense mappings throughout the image. Correspondences are derived from 3D features, distinctive generic image patterns that are automatically extracted from 3D ultrasound images and characterized in terms of their geometry (i.e., location, scale, and orientation) and a descriptor of local image appearance. Feature correspondences between ultrasound images are achieved based on a nearest-neighbor descriptor matching and probabilistic voting model similar to the Hough transform. RESULTS: Experiments demonstrate our method on intraoperative ultrasound images acquired before and after opening of the dura mater, during resection and after resection in nine clinical cases. A total of 1620 automatically extracted 3D feature correspondences were manually validated by eleven experts and used to guide the registration. Then, using manually labeled corresponding landmarks in the pre- and post-resection ultrasound images, we show that our feature-based registration reduces the mean target registration error from an initial value of 3.3 to 1.5 mm. CONCLUSIONS: This result demonstrates that the 3D features promise to offer a robust and accurate solution for 3D ultrasound registration and to correct for brain shift in image-guided neurosurgery.
Jagadeesan Jayender, Brian Xavier, Franklin King, Ahmed Hosny, David Black, Steve Pieper, and Ali Tavakkoli. 2018. “A Novel Mixed Reality Navigation System for Laparoscopy Surgery.” Med Image Comput Comput Assist Interv, 11073, Pp. 72-80.Abstract
OBJECTIVE: To design and validate a novel mixed reality head-mounted display for intraoperative surgical navigation. DESIGN: A mixed reality navigation for laparoscopic surgery (MRNLS) system using a head mounted display (HMD) was developed to integrate the displays from a laparoscope, navigation system, and diagnostic imaging to provide context-specific information to the surgeon. Further, an immersive auditory feedback was also provided to the user. Sixteen surgeons were recruited to quantify the differential improvement in performance based on the mode of guidance provided to the user (laparoscopic navigation with CT guidance (LN-CT) versus mixed reality navigation for laparoscopic surgery (MRNLS)). The users performed three tasks: (1) standard peg transfer, (2) radiolabeled peg identification and transfer, and (3) radiolabeled peg identification and transfer through sensitive wire structures. RESULTS: For the more complex task of peg identification and transfer, significant improvements were observed in time to completion, kinematics such as mean velocity, and task load index subscales of mental demand and effort when using the MRNLS (p < 0.05) compared to the current standard of LN-CT. For the final task of peg identification and transfer through sensitive structures, time taken to complete the task and frustration were significantly lower for MRNLS compared to the LN-CT approach. CONCLUSIONS: A novel mixed reality navigation for laparoscopic surgery (MRNLS) has been designed and validated. The ergonomics of laparoscopic procedures could be improved while minimizing the necessity of additional monitors in the operating room.
Matthew Toews and William M Wells. 2018. “Phantomless Auto-Calibration and Online Calibration Assessment for a Tracked Freehand 2-D Ultrasound Probe.” IEEE Trans Med Imaging, 37, 1, Pp. 262-72.Abstract
This paper presents a method for automatically calibrating and assessing the calibration quality of an externally tracked 2-D ultrasound (US) probe by scanning arbitrary, natural tissues, as opposed a specialized calibration phantom as is the typical practice. A generative topic model quantifies the posterior probability of calibration parameters conditioned on local 2-D image features arising from a generic underlying substrate. Auto-calibration is achieved by identifying the maximum a-posteriori image-to-probe transform, and calibration quality is assessed online in terms of the posterior probability of the current image-to-probe transform. Both are closely linked to the 3-D point reconstruction error (PRE) in aligning feature observations arising from the same underlying physical structure in different US images. The method is of practical importance in that it operates simply by scanning arbitrary textured echogenic structures, e.g., in-vivo tissues in the context of the US-guided procedures, without requiring specialized calibration procedures or equipment. Observed data take the form of local scale-invariant features that can be extracted and fit to the model in near real-time. Experiments demonstrate the method on a public data set of in vivo human brain scans of 14 unique subjects acquired in the context of neurosurgery. Online calibration assessment can be performed at approximately 3 Hz for the US images of pixels. Auto-calibration achieves an internal mean PRE of 1.2 mm and a discrepancy of [2 mm, 6 mm] in comparison to the calibration via a standard phantom-based method.
Annika Kurreck, Lindsey A Vandergrift, Taylor L Fuss, Piet Habbel, Nathalie YR Agar, and Leo L Cheng. 2018. “Prostate Cancer Diagnosis and Characterization with Mass Spectrometry Imaging.” Prostate Cancer Prostatic Dis, 21, 3, Pp. 297-305.Abstract
BACKGROUND: Prostate cancer (PCa), the most common cancer and second leading cause of cancer death in American men, presents the clinical challenge of distinguishing between indolent and aggressive tumors for proper treatment. PCa presents significant alterations in metabolic pathways that can potentially be measured using techniques like mass spectrometry (MS) or MS imaging (MSI) and used to characterize PCa aggressiveness. MS quantifies metabolomic, proteomic, and lipidomic profiles of biological systems that can be further visualized for their spatial distributions through MSI. METHODS: PubMed was queried for all publications relating to MS and MSI in human PCa from April 2007 to April 2017. With the goal of reviewing the utility of MSI in diagnosis and prognostication of human PCa, MSI articles that reported investigations of PCa-specific metabolites or metabolites indicating PCa aggressiveness were selected for inclusion. Articles were included that covered MS and MSI principles, limitations, and applications in PCa. RESULTS: We identified nine key studies on MSI in intact human prostate tissue specimens that determined metabolites which could either differentiate between benign and malignant prostate tissue or indicate PCa aggressiveness. These MSI-detected biomarkers show promise in reliably identifying PCa and determining disease aggressiveness. CONCLUSIONS: MSI represents an innovative technique with the ability to interrogate cancer biomarkers in relation to tissue pathologies and investigate tumor aggressiveness. We propose MSI as a powerful adjuvant histopathology imaging tool for prostate tissue evaluations, where clinical translation of this ex vivo technique could make possible the use of MSI for personalized medicine in diagnosis and prognosis of PCa. Moreover, the knowledge provided from this technique can majorly contribute to the understanding of molecular pathogenesis of PCa and other malignant diseases.
Wenpeng Gao, Baichuan Jiang, Daniel F Kacher, Barry Fetics, Erez Nevo, Thomas C Lee, and Jagadeesan Jayender. 2018. “Real-time Probe Tracking using EM-optical Sensor for MRI-guided Cryoablation .” Int J Med Robot, 14, 1.Abstract
BACKGROUND: A method of real-time, accurate probe tracking at the entrance of the MRI bore is developed, which, fused with pre-procedural MR images, will enable clinicians to perform cryoablation efficiently in a large workspace with image guidance. METHODS: Electromagnetic (EM) tracking coupled with optical tracking is used to track the probe. EM tracking is achieved with an MRI-safe EM sensor working under the scanner's magnetic field to compensate the line-of-sight issue of optical tracking. Unscented Kalman filter-based probe tracking is developed to smooth the EM sensor measurements when occlusion occurs and to improve the tracking accuracy by fusing the measurements of two sensors. RESULTS: Experiments with a spine phantom show that the mean targeting errors using the EM sensor alone and using the proposed method are 2.21 mm and 1.80 mm, respectively. CONCLUSION: The proposed method achieves more accurate probe tracking than using an EM sensor alone at the MRI scanner entrance.
Fan Zhang, Weining Wu, Lipeng Ning, Gloria McAnulty, Deborah Waber, Borjan Gagoski, Kiera Sarill, Hesham M Hamoda, Yang Song, Weidong Cai, Yogesh Rathi, and Lauren J O'Donnell. 2018. “Suprathreshold Fiber Cluster Statistics: Leveraging White Matter Geometry to Enhance Tractography Statistical Analysis.” Neuroimage, 171, Pp. 341-54.Abstract
This work presents a suprathreshold fiber cluster (STFC) method that leverages the whole brain fiber geometry to enhance statistical group difference analyses. The proposed method consists of 1) a well-established study-specific data-driven tractography parcellation to obtain white matter tract parcels and 2) a newly proposed nonparametric, permutation-test-based STFC method to identify significant differences between study populations. The basic idea of our method is that a white matter parcel's neighborhood (nearby parcels with similar white matter anatomy) can support the parcel's statistical significance when correcting for multiple comparisons. We propose an adaptive parcel neighborhood strategy to allow suprathreshold fiber cluster formation that is robust to anatomically varying inter-parcel distances. The method is demonstrated by application to a multi-shell diffusion MRI dataset from 59 individuals, including 30 attention deficit hyperactivity disorder patients and 29 healthy controls. Evaluations are conducted using both synthetic and in-vivo data. The results indicate that the STFC method gives greater sensitivity in finding group differences in white matter tract parcels compared to several traditional multiple comparison correction methods.
Dariya Malyarenko, Andriy Fedorov, Laura Bell, Melissa Prah, Stefanie Hectors, Lori Arlinghaus, Mark Muzi, Meiyappan Solaiyappan, Michael Jacobs, Maggie Fung, Amita Shukla-Dave, Kevin McManus, Michael Boss, Bachir Taouli, Thomas E Yankeelov, Christopher Chad Quarles, Kathleen Schmainda, Thomas L Chenevert, and David C Newitt. 2018. “Toward Uniform Implementation of Parametric Map Digital Imaging and Communication in Medicine Standard in Multisite Quantitative Diffusion Imaging Studies.” J Med Imaging (Bellingham), 5, 1, Pp. 011006.Abstract
This paper reports on results of a multisite collaborative project launched by the MRI subgroup of Quantitative Imaging Network to assess current capability and provide future guidelines for generating a standard parametric diffusion map Digital Imaging and Communication in Medicine (DICOM) in clinical trials that utilize quantitative diffusion-weighted imaging (DWI). Participating sites used a multivendor DWI DICOM dataset of a single phantom to generate parametric maps (PMs) of the apparent diffusion coefficient (ADC) based on two models. The results were evaluated for numerical consistency among models and true phantom ADC values, as well as for consistency of metadata with attributes required by the DICOM standards. This analysis identified missing metadata descriptive of the sources for detected numerical discrepancies among ADC models. Instead of the DICOM PM object, all sites stored ADC maps as DICOM MR objects, generally lacking designated attributes and coded terms for quantitative DWI modeling. Source-image reference, model parameters, ADC units and scale, deemed important for numerical consistency, were either missing or stored using nonstandard conventions. Guided by the identified limitations, the DICOM PM standard has been amended to include coded terms for the relevant diffusion models. Open-source software has been developed to support conversion of site-specific formats into the standard representation.
Seiji Arai, Oliver Jonas, Matthew A Whitman, Eva Corey, Steven P Balk, and Sen Chen. 2018. “Tyrosine Kinase Inhibitors Increase MCL1 Degradation and in Combination with BCLXL/BCL2 Inhibitors Drive Prostate Cancer Apoptosis.” Clin Cancer Res, 24, 21, Pp. 5458-5470.Abstract
Clinically available BH3 mimetic drugs targeting BCLXL and/or BCL2 (navitoclax and venetoclax, respectively) are effective in some hematologic malignancies, but have limited efficacy in solid tumors. This study aimed to identify combination therapies that exploit clinical BH3 mimetics for prostate cancer. Prostate cancer cells or xenografts were treated with BH3 mimetics as single agents or in combination with other agents, and effects on MCL1 and apoptosis were assessed. MCL1 was also targeted directly using RNAi, CRISPR, or an MCL1-specific BH3 mimetic, S63845. We initially found that MCL1 depletion or inhibition markedly sensitized prostate cancer cells to apoptosis mediated by navitoclax, but not venetoclax, and , indicating that they are primed to undergo apoptosis and protected by MCL1 and BCLXL. Small-molecule EGFR kinase inhibitors (erlotinib, lapatinib) also dramatically sensitized to navitoclax-mediated apoptosis, and this was associated with markedly increased proteasome-dependent degradation of MCL1. This increased MCL1 degradation appeared to be through a novel mechanism, as it was not dependent upon GSK3β-mediated phosphorylation and subsequent ubiquitylation by the ubiquitin ligases βTRCP and FBW7, or through other previously identified MCL1 ubiquitin ligases or deubiquitinases. Inhibitors targeting additional kinases (cabozantinib and sorafenib) similarly caused GSK3β-independent MCL1 degradation, and in combination with navitoclax drove apoptosis and These results show that prostate cancer cells are primed to undergo apoptosis and that cotargeting BCLXL and MCL1, directly or indirectly through agents that increase MCL1 degradation, can induce dramatic apoptotic responses. .
Alexander J Kim, Sankha Basu, Carolyn Glass, Edgar L Ross, Nathalie Agar, Qing He, and David Calligaris. 2018. “Unique Intradural Inflammatory Mass Containing Precipitated Morphine: Confirmatory Analysis by LESA-MS and MALDI-MS.” Pain Pract, 18, 7, Pp. 889-94.Abstract
Opioids are often used for analgesia via continuous intrathecal delivery by implantable devices. A higher concentration and daily dose of opioid have been postulated as risk factors for intrathecal granuloma formation. We present a 42-year-old female patient with chronic abdominal pain from refractory pancreatitis, with an intrathecal drug delivery device implanted 21 years prior, delivering continuous intrathecal morphine. After many years without concerning physical signs or complaints, with gradual increases in daily morphine dose, she presented with rapidly progressive neurologic deficits, including lower extremity, bladder, and bowel symptoms. These symptoms were determined to be secondary to mass effect and local inflammation related to an intrathecal catheter tip granuloma, detected on magnetic resonance imaging of the spine. The mass was urgently resected. On histopathologic examination, this granuloma was found to be unique, in that in addition to the expected inflammatory components, it appeared to contain precipitated nonpolarizable crystals. These were identified as precipitated morphine using liquid extraction surface analysis-tandem mass spectrometry (LESA-MS/MS) and matrix-assisted laser desorption ionization-Fourier transform ion cyclotron resonance-mass spectrometry imaging (MALDI-FTICR-MSI). In addition to the unique finding of precipitated morphine crystals, the long-term follow-up of both morphine concentration and daily dose increases provides insight into the formation of intrathecal granulomas.
Momen Abayazid, Takahisa Kato, Stuart G Silverman, and Nobuhiko Hata. 2018. “Using Needle Orientation Sensing as Surrogate Signal for Respiratory Motion Estimation in Rercutaneous Interventions.” Int J Comput Assist Radiol Surg, 13, 1, Pp. 125-33.Abstract
PURPOSE: To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen. MATERIALS AND METHODS: The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time. RESULTS: The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor. CONCLUSION: The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.
Jie Luo, Sarah Frisken, Ines Machado, Miaomiao Zhang, Steve Pieper, Polina Golland, Matthew Toews, Prashin Unadkat, Alireza Sedghi, Haoyin Zhou, Alireza Mehrtash, Frank Preiswerk, Cheng-Chieh Cheng, Alexandra Golby, Masashi Sugiyama, and William M Wells. 2018. “Using the Variogram for Vector Outlier Screening: Application to Feature-based Image Registration.” Int J Comput Assist Radiol Surg, 13, 12, Pp. 1871-80.Abstract
PURPOSE: Matching points that are derived from features or landmarks in image data is a key step in some medical imaging applications. Since most robust point matching algorithms claim to be able to deal with outliers, users may place high confidence in the matching result and use it without further examination. However, for tasks such as feature-based registration in image-guided neurosurgery, even a few mismatches, in the form of invalid displacement vectors, could cause serious consequences. As a result, having an effective tool by which operators can manually screen all matches for outliers could substantially benefit the outcome of those applications. METHODS: We introduce a novel variogram-based outlier screening method for vectors. The variogram is a powerful geostatistical tool for characterizing the spatial dependence of stochastic processes. Since the spatial correlation of invalid displacement vectors, which are considered as vector outliers, tends to behave differently than normal displacement vectors, they can be efficiently identified on the variogram. RESULTS: We validate the proposed method on 9 sets of clinically acquired ultrasound data. In the experiment, potential outliers are flagged on the variogram by one operator and further evaluated by 8 experienced medical imaging researchers. The matching quality of those potential outliers is approximately 1.5 lower, on a scale from 1 (bad) to 5 (good), than valid displacement vectors. CONCLUSION: The variogram is a simple yet informative tool. While being used extensively in geostatistical analysis, it has not received enough attention in the medical imaging field. We believe there is a good deal of potential for clinically applying the proposed outlier screening method. By way of this paper, we also expect researchers to find variogram useful in other medical applications that involve motion vectors analyses.

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