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Previous studies in psychosis patients have shown hippocampal volume deficits across anterior and posterior regions or across subfields, but subfield specific changes in volume along the hippocampal long axis have not been examined. Here, we tested the hypothesis that volume changes exist across the hippocampus in chronic psychosis but only the anterior CA region is affected in early psychosis patients. We analyzed structural MRI data from 179 patients with a non-affective psychotic disorder (94 chronic psychosis; 85 early psychosis) and 167 heathy individuals demographically matched to the chronic and early psychosis samples respectively (82 matched to chronic patients; 85 matched to early patients). We measured hippocampal volumes using Freesurfer 6-derived automated segmentation of both anterior and posterior regions and the CA, dentate gyrus, and subiculum subfields. We found a hippocampal volume deficit in both anterior and posterior regions in chronic psychosis, but this deficit was limited to the anterior hippocampus in early psychosis patients. This volume change was more pronounced in the anterior CA subfield of early psychosis patients than in the dentate gyrus or subiculum. Our findings support existing models of psychosis implicating initial CA dysfunction with later progression to other hippocampal regions and suggest that the anterior hippocampus may be an important target for early interventions.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
PURPOSE - The non-uniform fast Fourier transform (NUFFT) involves interpolation of non-uniformly sampled Fourier data onto a Cartesian grid, an interpolation that is slowed by complex, non-local data access patterns. A faster NUFFT would increase the clinical relevance of the plethora of advanced non-Cartesian acquisition methods.
METHODS - Here we customize the NUFFT procedure for a radial trajectory and GPU architecture to eliminate the bottlenecks encountered when allowing for arbitrary trajectories and hardware. We call the result TRON, for TRajectory Optimized NUFFT. We benchmark the speed and accuracy TRON on a Shepp-Logan phantom and on whole-body continuous golden-angle radial MRI.
RESULTS - TRON was 6-30× faster than the closest competitor, depending on test data set, and was the most accurate code tested.
CONCLUSIONS - Specialization of the NUFFT algorithm for a particular trajectory yielded significant speed gains. TRON can be easily extended to other trajectories, such as spiral and PROPELLER. TRON can be downloaded at http://github.com/davidssmith/TRON.
© 2018 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Diffusion MRI fiber tractography is widely used to probe the structural connectivity of the brain, with a range of applications in both clinical and basic neuroscience. Despite widespread use, tractography has well-known pitfalls that limits the anatomical accuracy of this technique. Numerous modern methods have been developed to address these shortcomings through advances in acquisition, modeling, and computation. To test whether these advances improve tractography accuracy, we organized the 3-D Validation of Tractography with Experimental MRI (3D-VoTEM) challenge at the ISBI 2018 conference. We made available three unique independent tractography validation datasets - a physical phantom and two ex vivo brain specimens - resulting in 176 distinct submissions from 9 research groups. By comparing results over a wide range of fiber complexities and algorithmic strategies, this challenge provides a more comprehensive assessment of tractography's inherent limitations than has been reported previously. The central results were consistent across all sub-challenges in that, despite advances in tractography methods, the anatomical accuracy of tractography has not dramatically improved in recent years. Taken together, our results independently confirm findings from decades of tractography validation studies, demonstrate inherent limitations in reconstructing white matter pathways using diffusion MRI data alone, and highlight the need for alternative or combinatorial strategies to accurately map the fiber pathways of the brain.
Copyright © 2018 Elsevier Inc. All rights reserved.
PURPOSE - Functional magnetic resonance imaging with BOLD contrast is widely used for detecting brain activity in the cortex. Recently, several studies have described anisotropic correlations of resting-state BOLD signals between voxels in white matter (WM). These local WM correlations have been modeled as functional-correlation tensors, are largely consistent with underlying WM fiber orientations derived from diffusion MRI, and appear to change during functional activity. However, functional-correlation tensors have several limitations. The use of only nearest-neighbor voxels makes functional-correlation tensors sensitive to noise. Furthermore, adjacent voxels tend to have higher correlations than diagonal voxels, resulting in orientation-related biases. Finally, the tensor model restricts functional correlations to an ellipsoidal bipolar-symmetric shape, and precludes the ability to detect complex functional orientation distributions (FODs).
METHODS - We introduce high-angular-resolution functional-correlation imaging (HARFI) to address these limitations. In the same way that high-angular-resolution diffusion imaging (HARDI) techniques provide more information than diffusion tensors, we show that the HARFI model is capable of characterizing complex FODs expected to be present in WM.
RESULTS - We demonstrate that the unique radial and angular sampling strategy eliminates orientation biases present in tensor models. We further show that HARFI FODs are able to reconstruct known WM pathways. Finally, we show that HARFI allows asymmetric "bending" and "fanning" distributions, and propose asymmetric and functional indices which may increase fiber tracking specificity, or highlight boundaries between functional regions.
CONCLUSIONS - The results suggest the HARFI model could be a robust, new way to evaluate anisotropic BOLD signal changes in WM.
© 2018 International Society for Magnetic Resonance in Medicine.
For two decades diffusion fiber tractography has been used to probe both the spatial extent of white matter pathways and the region to region connectivity of the brain. In both cases, anatomical accuracy of tractography is critical for sound scientific conclusions. Here we assess and validate the algorithms and tractography implementations that have been most widely used - often because of ease of use, algorithm simplicity, or availability offered in open source software. Comparing forty tractography results to a ground truth defined by histological tracers in the primary motor cortex on the same squirrel monkey brains, we assess tract fidelity on the scale of voxels as well as over larger spatial domains or regional connectivity. No algorithms are successful in all metrics, and, in fact, some implementations fail to reconstruct large portions of pathways or identify major points of connectivity. The accuracy is most dependent on reconstruction method and tracking algorithm, as well as the seed region and how this region is utilized. We also note a tremendous variability in the results, even though the same MR images act as inputs to all algorithms. In addition, anatomical accuracy is significantly decreased at increased distances from the seed. An analysis of the spatial errors in tractography reveals that many techniques have trouble properly leaving the gray matter, and many only reveal connectivity to adjacent regions of interest. These results show that the most commonly implemented algorithms have several shortcomings and limitations, and choices in implementations lead to very different results. This study should provide guidance for algorithm choices based on study requirements for sensitivity, specificity, or the need to identify particular connections, and should serve as a heuristic for future developments in tractography.
Copyright © 2018 Elsevier Inc. All rights reserved.
Substance use may confound the study of brain structure in schizophrenia. We used voxel-based morphometry (VBM) to examine whether differences in regional gray matter volumes exist between schizophrenia patients with (n = 92) and without (n = 66) clinically significant cannabis and/or alcohol use histories compared to 88 healthy control subjects. Relative to controls, patients with schizophrenia had reduced gray matter volume in the bilateral precentral gyrus, right medial frontal cortex, right visual cortex, right occipital pole, right thalamus, bilateral amygdala, and bilateral cerebellum regardless of substance use history. Within these regions, we found no volume differences between patients with schizophrenia and a history of cannabis and/or alcohol compared to patients with schizophrenia without a clinically significant substance use history. Our data support the idea that a clinically meaningful history of alcohol or cannabis use does not significantly compound the gray matter deficits associated with schizophrenia.
Copyright © 2018. Published by Elsevier B.V.
OBJECTIVE - Because of the high prevalence of silent cerebral infarcts (SCIs) in adults with sickle cell anemia (SCA) and lack of information to guide treatment strategies, we evaluated the risk of recurrent SCIs and overt stroke in adults with SCA with preexisting SCI.
METHODS - This observational study included adults with SCA (HbSS or Sβ thalassemia) aged 18 to 40 years. Participants received 3-tesla brain MRI and a detailed neurologic examination. Time-to-event analysis assessed those with or without baseline SCI and with new or progressive infarcts. The incidence rate of new events was compared by log-rank test. Univariable Cox regression assessed the association of SCI with infarct progression.
RESULTS - Among adults with SCA with 2 MRIs and at least 6 months between MRIs (n = 54, mean interval = 2.5 years), 43% had SCI at baseline. Of participants with baseline SCI, 30% had new or progressive SCI over 2.5 years compared to 6% with no SCI at baseline; no participant had an overt stroke. New SCIs at follow-up were present in 12.9 per 100 patient-years with existing SCI compared with 2.4 per 100 patient-years without prior SCI (log-rank test, = 0.021). No statistically significant differences were seen among those with or without baseline SCI in use of hydroxyurea therapy, hydroxyurea dose, or other stroke risk factors. The presence of SCI was associated with increased hazard of a new or progressive infarct (hazard ratio 5.27, 95% confidence interval 1.09-25.51, = 0.039).
CONCLUSIONS - Silent infarcts in adults with SCA are common and are a significant risk factor for future silent infarcts.
© 2018 American Academy of Neurology.
OBJECTIVE - While epilepsy studies rarely examine brainstem, we sought to examine the hypothesis that temporal lobe epilepsy (TLE) leads to subcortical arousal center dysfunction, contributing to neocortical connectivity and neurocognitive disturbances.
METHODS - In this case-control study of 26 adult patients with TLE and 26 controls, we used MRI to measure structural and functional connectivity of the cuneiform/subcuneiform nuclei (CSC), pedunculopontine nucleus, and ventral tegmental area. Ascending reticular activating system connectivity patterns were related to neuropsychological and disease measures.
RESULTS - Compared to controls, patients with TLE demonstrated reductions in ascending reticular activating system structural and functional connectivity, most prominently to neocortical regions ( < 0.05, unpaired tests, corrected). While reduced CSC structural connectivity was related to impaired performance IQ and visuospatial memory, diminished CSC functional connectivity was associated with impaired verbal IQ and language abilities ( < 0.05, Spearman ρ, tests). Finally, CSC structural connectivity decreases were quantitatively associated with consciousness-impairing seizure frequency ( < 0.05, Spearman ρ) and the presence of generalized seizures ( < 0.05, unpaired test), suggesting a relationship to disease severity.
CONCLUSIONS - Connectivity perturbations in brainstem arousal centers are present in TLE and may contribute to neurocognitive problems. These studies demonstrate the underappreciated role of brainstem networks in epilepsy and may lead to novel neuromodulation targets to treat or prevent deleterious brain network effects of seizures in TLE.
© 2018 American Academy of Neurology.
BACKGROUND - The American Thyroid Association (ATA) recommends fine-needle aspiration (FNA) biopsy of nodules measuring >1.5 cm with low-suspicion sonographic patterns or >1.0 cm with high/intermediate-suspicion features. Routine biopsy of nodules <1 cm is not recommended. However, despite these recommendations, subcentimeter nodules are often referred for FNA biopsy.
METHODS - This was a retrospective chart review of consecutive thyroid FNAs during an 18-month period (1157 patients, 1491 nodules, 2016-2017) to evaluate age, sex, medical history, diagnoses, and follow-up. Radiographic information was used to identify 61 subcentimeter nodules (4%) from 57 patients. Ultrasound studies were re-evaluated using criteria according to the American College of Radiology Thyroid Imaging, Reporting, and Data System (TI-RADS).
RESULTS - Reported reasons for biopsy included a larger companion nodule (44%), a personal or family history of cancer (26%), or a suspicious sonogram, including calcification and/or irregular contours (16%). FNA diagnoses included: 69% benign (42 of 61 nodules), 10% papillary thyroid carcinoma (PTC) (6 of 61 nodules), and 15% atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS) (9 of 61 nodules). Seven percent of nodules were unsatisfactory/nondiagnostic (4 of 61 nodules) compared with a 3% nondiagnostic rate for all sized nodules. Fifty-one nodules had an ultrasound available for re-review using the TI-RADS scoring system. A high TI-RADS score (4-5) was indicative of PTC in 29.4% of nodules. A low TI-RADS score (1-2) was indicative of PTC in 0% of nodules (P < .01). High and intermediate TI-RADS scores (3 and 4-5, respectively) were indicative of PTC/AUS/FLUS in 32% of nodules compared with 0% in those with low TI-RADS scores (P < .01).
CONCLUSIONS - The current results demonstrate successful use of the TI-RADS scoring system in evaluation of the risk of malignancy in subcentimeter nodules. Larger studies will be necessary to determine whether biopsy is warranted for TI-RADS high-subcentimeter nodules. Cancer Cytopathol 2018. © 2018 American Cancer Society.
© 2018 American Cancer Society.
High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software development and expansion, and (3) scalable spider deployment compatible with HPC clusters and local workstations.