Publications

2018
Nilsson M, Larsson J, Lundberg D, Szczepankiewicz F, Witzel T, Westin C-F, Bryskhe K, Topgaard D. Liquid Crystal Phantom for Validation of Microscopic Diffusion Anisotropy Measurements on Clinical MRI Systems. Magn Reson Med. 2018;79 (3) :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.
Schmidt EJ, Halperin HR. MRI use for Atrial Tissue Characterization in Arrhythmias and for EP Procedure Guidance. Int J Cardiovasc Imaging. 2018;34 (1) :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.
Jiang B, Gao W, Kacher D, Nevo E, Fetics B, Lee TC, Jayender J. Kalman Filter-based EM-optical Sensor Fusion for Needle Deflection Estimation. Int J Comput Assist Radiol Surg. 2018;13 (4) :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.
Zhang F, Wu W, Ning L, McAnulty G, Waber D, Gagoski B, Sarill K, Hamoda HM, Song Y, Cai W, et al. Suprathreshold Fiber Cluster Statistics: Leveraging White Matter Geometry to Enhance Tractography Statistical Analysis. Neuroimage. 2018;171 :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.
Toews M, Wells WM. Phantomless Auto-Calibration and Online Calibration Assessment for a Tracked Freehand 2-D Ultrasound Probe. IEEE Trans Med Imaging. 2018;37 (1) :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.
Black D, Unger M, Fischer N, Kikinis R, Hahn H, Neumuth T, Glaser B. Auditory Display as Feedback for a Novel Eye-tracking System for Sterile Operating Room Interaction. Int J Comput Assist Radiol Surg. 2018;13 (1) :37-45.Abstract
PURPOSE: The growing number of technical systems in the operating room has increased attention on developing touchless interaction methods for sterile conditions. However, touchless interaction paradigms lack the tactile feedback found in common input devices such as mice and keyboards. We propose a novel touchless eye-tracking interaction system with auditory display as a feedback method for completing typical operating room tasks. Auditory display provides feedback concerning the selected input into the eye-tracking system as well as a confirmation of the system response. METHODS: An eye-tracking system with a novel auditory display using both earcons and parameter-mapping sonification was developed to allow touchless interaction for six typical scrub nurse tasks. An evaluation with novice participants compared auditory display with visual display with respect to reaction time and a series of subjective measures. RESULTS: When using auditory display to substitute for the lost tactile feedback during eye-tracking interaction, participants exhibit reduced reaction time compared to using visual-only display. In addition, the auditory feedback led to lower subjective workload and higher usefulness and system acceptance ratings. CONCLUSION: Due to the absence of tactile feedback for eye-tracking and other touchless interaction methods, auditory display is shown to be a useful and necessary addition to new interaction concepts for the sterile operating room, reducing reaction times while improving subjective measures, including usefulness, user satisfaction, and cognitive workload.
Black D, Hahn HK, Kikinis R, Wårdell K, Haj-Hosseini N. Auditory Display for Fluorescence-guided Open Brain Tumor Surgery. Int J Comput Assist Radiol Surg. 2018;13 (1) :25-35.Abstract
PURPOSE: Protoporphyrin (PpIX) fluorescence allows discrimination of tumor and normal brain tissue during neurosurgery. A handheld fluorescence (HHF) probe can be used for spectroscopic measurement of 5-ALA-induced PpIX to enable objective detection compared to visual evaluation of fluorescence. However, current technology requires that the surgeon either views the measured values on a screen or employs an assistant to verbally relay the values. An auditory feedback system was developed and evaluated for communicating measured fluorescence intensity values directly to the surgeon. METHODS: The auditory display was programmed to map the values measured by the HHF probe to the playback of tones that represented three fluorescence intensity ranges and one error signal. Ten persons with no previous knowledge of the application took part in a laboratory evaluation. After a brief training period, participants performed measurements on a tray of 96 wells of liquid fluorescence phantom and verbally stated the perceived measurement values for each well. The latency and accuracy of the participants' verbal responses were recorded. The long-term memorization of sound function was evaluated in a second set of 10 participants 2-3 and 7-12 days after training. RESULTS: The participants identified the played tone accurately for 98% of measurements after training. The median response time to verbally identify the played tones was 2 pulses. No correlation was found between the latency and accuracy of the responses, and no significant correlation with the musical proficiency of the participants was observed on the function responses. Responses for the memory test were 100% accurate. CONCLUSION: The employed auditory display was shown to be intuitive, easy to learn and remember, fast to recognize, and accurate in providing users with measurements of fluorescence intensity or error signal. The results of this work establish a basis for implementing and further evaluating auditory displays in clinical scenarios involving fluorescence guidance and other areas for which categorized auditory display could be useful.
Abayazid M, Kato T, Silverman SG, Hata N. Using Needle Orientation Sensing as Surrogate Signal for Respiratory Motion Estimation in Rercutaneous Interventions. Int J Comput Assist Radiol Surg. 2018;13 (1) :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.
Stefanik L, Erdman L, Ameis SH, Foussias G, Mulsant BH, Behdinan T, Goldenberg A, O'Donnell LJ, Voineskos AN. Brain-Behavior Participant Similarity Networks Among Youth and Emerging Adults with Schizophrenia Spectrum, Autism Spectrum, or Bipolar Disorder and Matched Controls. Neuropsychopharmacology. 2018;43 (5) :1180-8.Abstract
There is considerable heterogeneity in social cognitive and neurocognitive performance among people with schizophrenia spectrum disorders (SSD), autism spectrum disorders (ASD), bipolar disorder (BD), and healthy individuals. This study used Similarity Network Fusion (SNF), a novel data-driven approach, to identify participant similarity networks based on relationships among demographic, brain imaging, and behavioral data. T1-weighted and diffusion-weighted magnetic resonance images were obtained for 174 adolescents and young adults (aged 16-35 years) with an SSD (n=51), an ASD without intellectual disability (n=38), euthymic BD (n=34), and healthy controls (n=51). A battery of social cognitive and neurocognitive tasks were administered. Data integration, cluster determination, and biological group formation were then obtained using SNF. We identified four new groups of individuals, each with distinct neural circuit-cognitive profiles. The most influential variables driving the formation of the new groups were robustly reliable across embedded resampling techniques. The data-driven groups showed considerably greater differentiation on key social and neurocognitive circuit nodes than groups generated by diagnostic analyses or dimensional social cognitive analyses. The data-driven groups were validated through functional outcome and brain network property measures not included in the SNF model. Cutting across diagnostic boundaries, our approach can effectively identify new groups of people based on a profile of neuroimaging and behavioral data. Our findings bring us closer to disease subtyping that can be leveraged toward the targeting of specific neural circuitry among participant subgroups to ameliorate social cognitive and neurocognitive deficits.Neuropsychopharmacology advance online publication, 6 December; doi:10.1038/npp.2017.274.
Zhang F, Savadjiev P, Cai W, Song Y, Rathi Y, Tunç B, Parker D, Kapur T, Schultz RT, Makris N, et al. Whole Brain White Matter Connectivity Analysis using Machine Learning: An Application to Autism. Neuroimage. 2018;172 :826-37.Abstract
In this paper, we propose an automated white matter connectivity analysis method for machine learning classification and characterization of white matter abnormality via identification of discriminative fiber tracts. The proposed method uses diffusion MRI tractography and a data-driven approach to find fiber clusters corresponding to subdivisions of the white matter anatomy. Features extracted from each fiber cluster describe its diffusion properties and are used for machine learning. The method is demonstrated by application to a pediatric neuroimaging dataset from 149 individuals, including 70 children with autism spectrum disorder (ASD) and 79 typically developing controls (TDC). A classification accuracy of 78.33% is achieved in this cross-validation study. We investigate the discriminative diffusion features based on a two-tensor fiber tracking model. We observe that the mean fractional anisotropy from the second tensor (associated with crossing fibers) is most affected in ASD. We also find that local along-tract (central cores and endpoint regions) differences between ASD and TDC are helpful in differentiating the two groups. These altered diffusion properties in ASD are associated with multiple robustly discriminative fiber clusters, which belong to several major white matter tracts including the corpus callosum, arcuate fasciculus, uncinate fasciculus and aslant tract; and the white matter structures related to the cerebellum, brain stem, and ventral diencephalon. These discriminative fiber clusters, a small part of the whole brain tractography, represent the white matter connections that could be most affected in ASD. Our results indicate the potential of a machine learning pipeline based on white matter fiber clustering.
Trinh TW, Glazer DI, Sadow CA, Sahni AV, Geller NL, Silverman SG. Bladder Cancer Diagnosis with CT Urography: Test Characteristics and Reasons for False-positive and False-negative Results. Abdom Radiol (NY). 2018;43 (3) :663-71.Abstract
PURPOSE: To determine test characteristics of CT urography for detecting bladder cancer in patients with hematuria and those undergoing surveillance, and to analyze reasons for false-positive and false-negative results. METHODS: A HIPAA-compliant, IRB-approved retrospective review of reports from 1623 CT urograms between 10/2010 and 12/31/2013 was performed. 710 examinations for hematuria or bladder cancer history were compared to cystoscopy performed within 6 months. Reference standard was surgical pathology or 1-year minimum clinical follow-up. False-positive and false-negative examinations were reviewed to determine reasons for errors. RESULTS: Ninety-five bladder cancers were detected. CT urography accuracy: was 91.5% (650/710), sensitivity 86.3% (82/95), specificity 92.4% (568/615), positive predictive value 63.6% (82/129), and negative predictive value was 97.8% (568/581). Of 43 false positives, the majority of interpretation errors were due to benign prostatic hyperplasia (n = 12), trabeculated bladder (n = 9), and treatment changes (n = 8). Other causes include blood clots, mistaken normal anatomy, infectious/inflammatory changes, or had no cystoscopic correlate. Of 13 false negatives, 11 were due to technique, one to a large urinary residual, one to artifact. There were no errors in perception. CONCLUSION: CT urography is an accurate test for diagnosing bladder cancer; however, in protocols relying predominantly on excretory phase images, overall sensitivity remains insufficient to obviate cystoscopy. Awareness of bladder cancer mimics may reduce false-positive results. Improvements in CTU technique may reduce false-negative results.
Hassanzadeh E, Alessandrino F, Olubiyi OI, Glazer DI, Mulkern RV, Fedorov A, Tempany CM, Fennessy FM. Comparison of Quantitative Apparent Diffusion Coefficient Parameters with Prostate Imaging Reporting and Data System V2 Assessment for Detection of Clinically Significant Peripheral Zone Prostate Cancer. Abdom Radiol (NY). 2018;43 (5) :1237-44.Abstract
PURPOSE: To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. METHODS: We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean ADCT, mean ADCN, ADCratio (ADCT/ADCN) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). RESULTS: Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) ADCT (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) ADCT (0.86) was higher than ADCratio (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than ADCratio (0.56, p = 0.02). ADCT performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). ADCratio performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition. CONCLUSIONS: When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with ADCT providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than ADCratio. csPC definition did not affect PI-RADSv2 diagnostic performance.
2017
Chennubhotla C, Clarke LP, Fedorov A, Foran D, Harris G, Helton E, Nordstrom R, Prior F, Rubin D, Saltz JH, et al. An Assessment of Imaging Informatics for Precision Medicine in Cancer. Yearb Med Inform. 2017;26 (1) :110-9.Abstract
Precision medicine requires the measurement, quantification, and cataloging of medical characteristics to identify the most effective medical intervention. However, the amount of available data exceeds our current capacity to extract meaningful information. We examine the informatics needs to achieve precision medicine from the perspective of quantitative imaging and oncology. The National Cancer Institute (NCI) organized several workshops on the topic of medical imaging and precision medicine. The observations and recommendations are summarized herein. Recommendations include: use of standards in data collection and clinical correlates to promote interoperability; data sharing and validation of imaging tools; clinician's feedback in all phases of research and development; use of open-source architecture to encourage reproducibility and reusability; use of challenges which simulate real-world situations to incentivize innovation; partnership with industry to facilitate commercialization; and education in academic communities regarding the challenges involved with translation of technology from the research domain to clinical utility and the benefits of doing so. This article provides a survey of the role and priorities for imaging informatics to help advance quantitative imaging in the era of precision medicine. While these recommendations were drawn from oncology, they are relevant and applicable to other clinical domains where imaging aids precision medicine.
Pouch AM, Aly AH, Lasso A, Nguyen AV, Scanlan AB, McGowan FX, Fichtinger G, Gorman RC, Gorman JH, Yushkevich PA, et al. Image Segmentation and Modeling of the Pediatric Tricuspid Valve in Hypoplastic Left Heart Syndrome. Funct Imaging Model Heart. 2017;10263 :95-105.Abstract
Hypoplastic left heart syndrome (HLHS) is a single-ventricle congenital heart disease that is fatal if left unpalliated. In HLHS patients, the tricuspid valve is the only functioning atrioventricular valve, and its competence is therefore critical. This work demonstrates the first automated strategy for segmentation, modeling, and morphometry of the tricuspid valve in transthoracic 3D echocardiographic (3DE) images of pediatric patients with HLHS. After initial landmark placement, the automated segmentation step uses multi-atlas label fusion and the modeling approach uses deformable modeling with medial axis representation to produce patient-specific models of the tricuspid valve that can be comprehensively and quantitatively assessed. In a group of 16 pediatric patients, valve segmentation and modeling attains an accuracy (mean boundary displacement) of 0.8 ± 0.2 mm relative to manual tracing and shows consistency in annular and leaflet measurements. In the future, such image-based tools have the potential to improve understanding and evaluation of tricuspid valve morphology in HLHS and guide strategies for patient care.
Herrlich M, Tavakol P, Black D, Wenig D, Rieder C, Malaka R, Kikinis R. Instrument-mounted Displays for Reducing Cognitive Load During Surgical Navigation. Int J Comput Assist Radiol Surg. 2017;12 (9) :1599-1605.Abstract
PURPOSE: Surgical navigation systems rely on a monitor placed in the operating room to relay information. Optimal monitor placement can be challenging in crowded rooms, and it is often not possible to place the monitor directly beside the situs. The operator must split attention between the navigation system and the situs. We present an approach for needle-based interventions to provide navigational feedback directly on the instrument and close to the situs by mounting a small display onto the needle. METHODS: By mounting a small and lightweight smartwatch display directly onto the instrument, we are able to provide navigational guidance close to the situs and directly in the operator's field of view, thereby reducing the need to switch the focus of view between the situs and the navigation system. We devise a specific variant of the established crosshair metaphor suitable for the very limited screen space. We conduct an empirical user study comparing our approach to using a monitor and a combination of both. RESULTS: Results from the empirical user study show significant benefits for cognitive load, user preference, and general usability for the instrument-mounted display, while achieving the same level of performance in terms of time and accuracy compared to using a monitor. CONCLUSION: We successfully demonstrate the feasibility of our approach and potential benefits. With ongoing technological advancements, instrument-mounted displays might complement standard monitor setups for surgical navigation in order to lower cognitive demands and for improved usability of such systems.
Silva MA, See AP, Essayed WI, Golby AJ, Tie Y. Challenges and Techniques for Presurgical Brain Mapping with Functional MRI. Neuroimage Clin. 2017;17 :794-803.Abstract
Functional magnetic resonance imaging (fMRI) is increasingly used for preoperative counseling and planning, and intraoperative guidance for tumor resection in the eloquent cortex. Although there have been improvements in image resolution and artifact correction, there are still limitations of this modality. In this review, we discuss clinical fMRI's applications, limitations and potential solutions. These limitations depend on the following parameters: foundations of fMRI, physiologic effects of the disease, distinctions between clinical and research fMRI, and the design of the fMRI study. We also compare fMRI to other brain mapping modalities which should be considered as alternatives or adjuncts when appropriate, and discuss intraoperative use and validation of fMRI. These concepts direct the clinical application of fMRI in neurosurgical patients.
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.

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