The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has developed a database built on XNAT housing over a quarter of a million scans. The database provides framework for (1) rapid prototyping, (2) large scale batch processing of images and (3) scalable project management. The system uses the web-based interfaces of XNAT and RedCAP to allow for graphical interaction. A python middleware layer, the Distributed Automation for XNAT (DAX) package, distributes computation across the Vanderbilt Advanced Computing Center for Research and Education high performance computing center. All software are made available in open source for use in combining portable batch scripting (PBS) grids and XNAT servers.

Abstract. The optic nerve (ON) plays a critical role in many devastating pathological conditions. Segmentation of the ON has the ability to provide understanding of anatomical development and progression of diseases of the ON. Recently, methods have been proposed to segment the ON but progress toward full automation has been limited. We optimize registration and fusion methods for a new multi-atlas framework for automated segmentation of the ONs, eye globes, and muscles on clinically acquired computed tomography (CT) data. Briefly, the multi-atlas approach consists of determining a region of interest within each scan using affine registration, followed by nonrigid registration on reduced field of view atlases, and performing statistical fusion on the results. We evaluate the robustness of the approach by segmenting the ON structure in 501 clinically acquired CT scan volumes obtained from 183 subjects from a thyroid eye disease patient population. A subset of 30 scan volumes was manually labeled to assess accuracy and guide method choice. Of the 18 compared methods, the ANTS Symmetric Normalization registration and nonlocal spatial simultaneous truth and performance level estimation statistical fusion resulted in the best overall performance, resulting in a median Dice similarity coefficient of 0.77, which is comparable with inter-rater (human) reproducibility at 0.73.

High-angular-resolution diffusion-weighted imaging (HARDI) MRI acquisitions have become common for use with higher order models of diffusion. Despite successes in resolving complex fiber configurations and probing microstructural properties of brain tissue, there is no common consensus on the optimal b-value and number of diffusion directions to use for these HARDI methods. While this question has been addressed by analysis of the diffusion-weighted signal directly, it is unclear how this translates to the information and metrics derived from the HARDI models themselves. Using a high angular resolution data set acquired at a range of b-values, and repeated 11 times on a single subject, we study how the b-value and number of diffusion directions impacts the reproducibility and precision of metrics derived from Q-ball imaging, a popular HARDI technique. We find that Q-ball metrics associated with tissue microstructure and white matter fiber orientation are sensitive to both the number of diffusion directions and the spherical harmonic representation of the Q-ball, and often are biased when under sampled. These results can advise researchers on appropriate acquisition and processing schemes, particularly when it comes to optimizing the number of diffusion directions needed for metrics derived from Q-ball imaging.

Purpose Our goal is to develop an accurate, automated tool to characterize the optic nerve (ON) and cerebrospinal fluid (CSF) to better understand ON changes in disease. Methods Multi-atlas segmentation is used to localize the ON and sheath on T2-weighted MRI (0.6 mm3 resolution). A sum of Gaussian distributions is fit to coronal slice-wise intensities to extract six descriptive parameters, and a regression forest is used to map the model space to radii. The model is validated for consistency using tenfold cross-validation and for accuracy using a high resolution (0.4 mm2 reconstructed to 0.15 mm2) in vivo sequence. We evaluated this model on 6 controls and 6 patients with multiple sclerosis (MS) and a history of optic neuritis. Results In simulation, the model was found to have an explanatory R-squared for both ON and sheath radii greater than 0.95. The accuracy of the method was within the measurement error on the highest possible in vivo resolution. Comparing healthy controls and patients with MS, significant structural differences were found near the ON head and the chiasm, and structural trends agreed with the literature. Conclusion This is a first demonstration that the ON can be exclusively, quantitatively measured and separated from the surrounding CSF using MRI.

BackgroundOptic neuritis (ON) is one of the most common presentations of multiple sclerosis (MS). Magnetic resonance imaging (MRI) of the optic nerves is challenging because of retrobulbar motion, orbital fat and susceptibility artifacts from maxillary sinuses; therefore, axonal loss is investigated with the surrogate measure of a single heuristically defined point along the nerve as opposed to volumetric investigation.ObjectiveThe objective of this paper is to derive optic nerve volumetrics along the entire nerve length in patients with MS and healthy controls in vivo using high-resolution, clinically viable MRI.MethodsAn advanced, isotropic T2-weighted turbo spin echo MRI was applied to 29 MS patients with (14 patients ON+) or without (15 patients ON–) history of ON and 42 healthy volunteers. An automated tool was used to estimate and compare whole optic nerve and surrounding cerebrospinal fluid radii along the length of the nerve.Results and conclusionOnly ON+ MS patients had a significantly reduced optic nerve radius compared to healthy controls in the central segment of the optic nerve. Using clinically available MRI methods, we show and quantify ON volume loss for the first time in MS patients.

Pathologies of the optic nerve and orbit impact millions of Americans and quantitative assessment of the orbital structures on 3-D imaging would provide objective markers to enhance diagnostic accuracy, improve timely intervention and eventually preserve visual function. Recent studies have shown that the multi-atlas methodology is suitable for identifying orbital structures, but challenges arise in the identification of the individual extraocular rectus muscles that control eye movement. This is increasingly problematic in diseased eyes, where these muscles often appear to fuse at the back of the orbit (at the resolution of clinical computed tomography imaging) due to inflammation or crowding. We propose the use of Kalman filters to track the muscles in three-dimensions to refine multi-atlas segmentation and resolve ambiguity due to imaging resolution, noise, and artifacts. The purpose of our study is to investigate a method of automatically generating orbital metrics from CT imaging and demonstrate the utility of the approach by correlating structural metrics of the eye orbit with clinical data and visual function measures in subjects with thyroid eye disease. The pilot study demonstrates that automatically calculated orbital metrics are strongly correlated with several clinical characteristics. Moreover, the superior, inferior, medial and lateral rectus muscles obtained using Kalman filters are each correlated with different categories of functional deficit. These findings serve as foundation for further investigation in the use of CT imaging in the study, analysis and diagnosis of ocular diseases, specifically thyroid eye disease.

Optic neuritis is a sudden inflammation of the optic nerve (ON) and is marked by pain on eye movement, and visual symptoms such as a decrease in visual acuity, color vision, contrast and visual field defects. The ON is closely linked with multiple sclerosis (MS) and patients have a 50% chance of developing MS within 15 years. Recent advances in multi-atlas segmentation methods have omitted volumetric assessment. In the past, measuring the size of the ON has been done by hand. We utilize a new method of automatically segmenting the ON to measure the radii of both the ON and surrounding cerebrospinal fluid (CSF) sheath to develop a normative distribution of healthy young adults. We examine this distribution for any trends and find that ON and CSF sheath radii do not vary between 20–35 years of age and between sexes. We evaluate how six patients suffering from optic neuropathy compare to this distribution of controls. We find that of these six patients, five of them qualitatively differ from the normative distribution which suggests this technique could be used in the future to distinguish between optic neuritis patients and healthy controls.

In this paper, spleen segmentation on MRI splenomegaly using MAS has been performed.