Diffusion Tractography in Deep Brain Stimulation Surgery: A Review

Deep brain stimulation (DBS) is believed to exert its therapeutic effects through modulation of brain circuitry, yet conventional preoperative planning does not allow direct targeting or visualization of white matter pathways. Diffusion MRI tractography (DT) is virtually the only non-invasive method of visualizing structural connectivity in the brain, leading many to suggest its use to guide DBS targeting. DT-guided DBS not only has the potential to allow direct white matter targeting for established applications (e.g. Parkinson’s disease, essential tremor, dystonia), but may also aid in the discovery of new therapeutic targets for a variety of other neurologic and psychiatric diseases. Despite these exciting opportunities, DT lacks standardization and rigorous anatomic validation, raising significant concern for the use of such data in stereotactic brain surgery. This review covers the technical details, proposed methods, and initial clinical data for the use of DT in DBS surgery. Rather than focusing on specific disease applications, this review focuses on methods that can be applied to virtually any DBS target

Spinal cord gray matter segmentation using deep dilated convolutions

Gray matter (GM) tissue changes have been associated with a wide range of neurological disorders and was also recently found relevant as a biomarker for disability in amyotrophic lateral sclerosis. The ability to automatically segment the GM is, therefore, an important task for modern studies of the spinal cord. In this work, we devise a modern, simple and end-to-end fully automated human spinal cord gray matter segmentation method using Deep Learning, that works both on in vivo and ex vivo MRI acquisitions. We evaluate our method against six independently developed methods on a GM segmentation challenge and report state-of-the-art results in 8 out of 10 different evaluation metrics as well as major network parameter reduction when compared to the traditional medical imaging architectures such as U-Nets.Comment: 13 pages, 8 figure

Diffusion Tensor Imaging Biomarkers of Brain Development and Disease

<p>Understanding the structure of the brain has been a major goal of neuroscience research over the past century, driven in part by the understanding that brain structure closely follows function. Normative brain maps, or atlases, can be used to understand normal brain structure, and to identify structural differences resulting from disease. Recently, diffusion tensor magnetic resonance imaging has emerged as a powerful tool for brain atlasing; however, its utility is hindered by image resolution and signal limitations. These limitations can be overcome by imaging fixed ex-vivo specimens stained with MRI contrast agents, a technique known as diffusion tensor magnetic resonance histology (DT-MRH). DT-MRH represents a unique, quantitative tool for mapping the brain with unprecedented structural detail. This technique has engendered a new generation of 3D, digital brain atlases, capable of representing complex dynamic processes such as neurodevelopment. This dissertation explores the use of DT-MRH for quantitative brain atlasing in an animal model and initial work in the human brain. </p><p>Chapter 1 describes the advantages of the DT-MRH technique, and the motivations for generating a quantitative atlas of rat postnatal neurodevelopment. The second chapter covers optimization of the DT-MRH hardware and pulse sequence design for imaging the developing rat brain. Chapter 3 details the acquisition and curation of rat neurodevelopmental atlas data. Chapter 4 describes the creation and implementation of an ontology-based segmentation scheme for tracking changes in the developing brain. Chapters 5 and 6 pertain to analyses of volumetric changes and diffusion tensor parameter changes throughout rat postnatal neurodevelopment, respectively. Together, the first six chapters demonstrate many of the unique and scientifically valuable features of DT-MRH brain atlases in a popular animal model.</p><p>The final two chapters are concerned with translating the DT-MRH technique for use in human and non-human primate brain atlasing. Chapter 7 explores the validity of assumptions imposed by DT-MRH in the primate brain. Specifically, it analyzes computer models and experimental data to determine the extent to which intravoxel diffusion complexity exists in the rhesus macaque brain, a close model for the human brain. Finally, Chapter 8 presents conclusions and future directions for DT-MRH brain atlasing, and includes initial work in creating DT-MRH atlases of the human brain. In conclusion, this work demonstrates the utility of a DT-MRH brain atlasing with an atlas of rat postnatal neurodevelopment, and lays the foundation for creating a DT-MRH atlas of the human brain.</p>Dissertatio

Low-Volume and High-Volume Readers of Neurological and Musculoskeletal MRI: Achieving Subspecialization in Radiology.

ObjectiveDifferentiate high- versus low-volume radiologists who interpret neurological (Neuro) MRI or musculoskeletal (MSK) MRI and measure the proportion of Neuro and MSK MRIs read by low-volume radiologists.MethodsWe queried the 2015 Medicare Physician and Other Supplier Public Use File for radiologists who submitted claims for Neuro or MSK MRIs. Radiologists were classified as high-volume versus low-volume based on their work relative value units (wRVUs) focus or volume of studies interpreted using three different methodologies: Method 1, percentage of wRVUs in Neuro or MSK MRI; Method 2, absolute number of Neuro or MSK MRIs interpreted; and Method 3, both percentage and absolute number. Multiple thresholds with each methodology were tested, and the percentage of Neuro or MSK MRIs interpreted by low-volume radiologists was calculated for each threshold.ResultsWith Method 1, 33% of Neuro MRI and 50% of MSK MRI studies were interpreted by a radiologist whose wRVUs in Neuro or MSK MRI were less than 20% (Method 1). With Method 2, 22% of Neuro MRIs and 37% of MSK MRIs were interpreted by radiologists who read fewer than the mean number of Neuro or MSK MRIs interpreted by an "average full-time radiologist" whose wRVUs in Neuro or MSK MRI were approximately 20%. With Method 3, 38% of Neuro MRIs and 57% of MSK MRIs were interpreted by "low-volume" radiologists. If instead a 50% wRVU threshold is used for Methods One, Two, and Three, then 70%, 58%, and 77% of Neuro MRIs and 86%, 80%, and 90% of MSK MRIs are read by low-volume radiologists.DiscussionA large number of radiologists read a low volume of Neuro or MSK MRIs; these low-volume Neuro or MSK MRI radiologists&nbsp;read a substantial portion of Neuro or MSK MRIs. It is unknown which of the methods for distinguishing low-volume radiologists, combined with which threshold, may best correlate with high-performing or low-performing radiologists

Investigating the tradeoffs between spatial resolution and diffusion sampling for brain mapping with diffusion tractography: Time well spent?: Spatial vs. Q-Space Sampling for Tractography

Interest in mapping white matter pathways in the brain has peaked with the recognition that altered brain connectivity may contribute to a variety of neurologic and psychiatric diseases. Diffusion tractography has emerged as a popular method for postmortem brain mapping initiatives, including the ex-vivo component of the human connectome project, yet it remains unclear to what extent computer-generated tracks fully reflect the actual underlying anatomy. Of particular concern is the fact that diffusion tractography results vary widely depending on the choice of acquisition protocol. The two major acquisition variables that consume scan time, spatial resolution, and diffusion sampling, can each have profound effects on the resulting tractography. In this analysis we determined the effects of the temporal tradeoff between spatial resolution and diffusion sampling on tractography in the ex-vivo rhesus macaque brain, a close primate model for the human brain. We used the wealth of autoradiography-based connectivity data available for the rhesus macaque brain to assess the anatomic accuracy of six time-matched diffusion acquisition protocols with varying balance between spatial and diffusion sampling. We show that tractography results vary greatly, even when the subject and the total acquisition time are held constant. Further, we found that focusing on either spatial resolution or diffusion sampling at the expense of the other is counterproductive. A balanced consideration of both sampling domains produces the most anatomically accurate and consistent results

A diffusion tensor MRI atlas of the postmortem rhesus macaque brain

The rhesus macaque (Macaca mulatta) is the most widely used nonhuman primate for modeling the structure and function of the brain. Brain atlases, and particularly those based on magnetic resonance imaging (MRI), have become important tools for understanding normal brain structure, and for identifying structural abnormalities resulting from disease states, exposures, and/or aging. Diffusion tensor imaging (DTI) -based MRI brain atlases are widely used in both human and macaque brain imaging studies because of the unique contrasts, quantitative diffusion metrics, and diffusion tractography that they can provide. Previous MRI and DTI atlases of the rhesus brain have been limited by low contrast and/or low spatial resolution imaging. Here we present a microscopic resolution MRI/DTI atlas of the rhesus brain based on 10 postmortem brain specimens. The atlas includes both structural MRI and DTI image data, a detailed three-dimensional segmentation of 241 anatomic structures, diffusion tractography, cortical thickness estimates, and maps of anatomic variability amongst atlas specimens. This atlas incorporates many useful features from previous work, including anatomic label nomenclature and ontology, data orientation, and stereotaxic reference frame, and further extends prior analyses with the inclusion of high-resolution multi-contrast image data

The University of California San Francisco, Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset

The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) dataset is a public, clinical, multimodal brain MRI dataset consisting of 560 brain MRIs from 412 patients with expert annotations of 5136 brain metastases. Data consists of registered and skull stripped T1 post-contrast, T1 pre-contrast, FLAIR and subtraction (T1 pre-contrast - T1 post-contrast) images and voxelwise segmentations of enhancing brain metastases in NifTI format. The dataset also includes patient demographics, surgical status and primary cancer types. The UCSF-BSMR has been made publicly available in the hopes that researchers will use these data to push the boundaries of AI applications for brain metastases.Comment: 15 pages, 2 tables, 2 figure

The Brain Tumor Sequence Registration Challenge: Establishing Correspondence between Pre-Operative and Follow-up MRI scans of diffuse glioma patients

Registration of longitudinal brain Magnetic Resonance Imaging (MRI) scans containing pathologies is challenging due to tissue appearance changes, and still an unsolved problem. This paper describes the first Brain Tumor Sequence Registration (BraTS-Reg) challenge, focusing on estimating correspondences between pre-operative and follow-up scans of the same patient diagnosed with a brain diffuse glioma. The BraTS-Reg challenge intends to establish a public benchmark environment for deformable registration algorithms. The associated dataset comprises de-identified multi-institutional multi-parametric MRI (mpMRI) data, curated for each scan's size and resolution, according to a common anatomical template. Clinical experts have generated extensive annotations of landmarks points within the scans, descriptive of distinct anatomical locations across the temporal domain. The training data along with these ground truth annotations will be released to participants to design and develop their registration algorithms, whereas the annotations for the validation and the testing data will be withheld by the organizers and used to evaluate the containerized algorithms of the participants. Each submitted algorithm will be quantitatively evaluated using several metrics, such as the Median Absolute Error (MAE), Robustness, and the Jacobian determinant

CMB-S4 Science Book, First Edition

This book lays out the scientific goals to be addressed by the next-generation ground-based cosmic microwave background experiment, CMB-S4, envisioned to consist of dedicated telescopes at the South Pole, the high Chilean Atacama plateau and possibly a northern hemisphere site, all equipped with new superconducting cameras. CMB-S4 will dramatically advance cosmological studies by crossing critical thresholds in the search for the B-mode polarization signature of primordial gravitational waves, in the determination of the number and masses of the neutrinos, in the search for evidence of new light relics, in constraining the nature of dark energy, and in testing general relativity on large scales