Publications

Modern imaging techniques with computed tomography (CT) and magnetic resonance imaging (MRI) have revolutionized neuroimaging. While eliminating the risks of invasive procedures, new risks must now be considered before ordering neuroimaging. Advanced imaging techniques with CT may pose a risk of significant radiation exposure. Contrast may pose a risk in patients with pre-existing renal failure. MR is associated with risks related to the static magnetic field, to risks associated with the magnetic field gradients, and to risk from contrast media. Neurointervenional techniques allow for nonoperative treatment of a variety of intracranial and spinal pathologies, but with associated risks of embolization, radiation exposure, bleeding complications at the access site and a potential for contrast-related nephropathy.

Carotid and coronary vascular incidents are mostly caused by vulnerable plaques. Detection and characterization of vulnerable plaques are important for early disease diagnosis and treatment. For this purpose, the echomorphology and composition have been studied. Several distributions have been used to describe ultrasonic data depending on tissues, acquisition conditions, and equipment. Among them, the Rayleigh distribution is a one-parameter model used to describe the raw envelope RF ultrasound signal for its simplicity, whereas the Nakagami distribution (a generalization of the Rayleigh distribution) is the two-parameter model which is commonly accepted. However, it fails to describe B-mode images or Cartesian interpolated or subsampled RF images because linear filtering changes the statistics of the signal. In this work, a gamma mixture model (GMM) is proposed to describe the subsampled/interpolated RF images and it is shown that the parameters and coefficients of the mixture are useful descriptors of speckle pattern for different types of plaque tissues. This new model outperforms recently proposed probabilistic and textural methods with respect to plaque description and characterization of echogenic contents. Classification results provide an overall accuracy of 86.56% for four classes and 95.16% for three classes. These results evidence the classifier usefulness for plaque characterization. Additionally, the classifier provides probability maps according to each tissue type, which can be displayed for inspecting local tissue composition, or used for automatic filtering and segmentation.

BACKGROUND AND PURPOSE: Erythropoietin (EPO) has received growing attention because of its neuroregenerative properties. Preclinical and clinical evidence supports its therapeutic potential in brain conditions like stroke, multiple sclerosis, and schizophrenia. Also, in Friedreich ataxia, clinical improvement after EPO therapy was shown. The aim of this study was to assess possible therapy-associated brain white matter changes in these patients. METHODS: Nine patients with Friedreich ataxia underwent Diffusion Tensor Imaging (DTI) before and after EPO treatment. Tract-based spatial statistics was used for longitudinal comparison. RESULTS: We detected widespread longitudinal increase in fractional anisotropy and axial diffusivity (D||) in cerebral hemispheres bilaterally (P .05, corrected), while no changes were observed within the cerebellum, medulla oblongata, and pons. CONCLUSIONS: To the best of our knowledge, this is the first DTI study to investigate the effects of EPO in a neurodegenerative disease. Anatomically, the diffusivity changes appear disease unspecific, and their biological underpinnings deserve further study.

OBJECT: Cingulotomy and limbic leucotomy are lesioning surgeries with demonstrated benefit for medically intractable psychiatric illnesses. They represent significant refinements of the prefrontal lobotomy used from the 1930s through the 1950s. However, the associations between anatomical characterization of these lesions and outcome data are not well understood. To elucidate these procedures and associations, the authors sought to define and compare the neuroanatomy of cingulotomy and limbic leucotomy and to test a method that uses neuroanatomical data and voxel-based lesion-symptom mapping (VLSM) to reveal potential refinements to modern psychiatric neurosurgical procedures. METHODS: T1-weighted MR images of patients who had undergone cingulotomy and limbic leucotomy were segmented and registered onto the Montreal Neurological Institute T1-weighted template brain MNI152. Using an atlas-based approach, the authors calculated, by case, the percentage of each anatomical structure affected by the lesion. Because of the infrequency of modern lesion procedures and the requirement for higher-resolution clinical imaging, the sample size was small. The pilot study correlated cingulotomy and limbic leucotomy lesion characteristics with clinical outcomes for patients with obsessive-compulsive disorder. For this study, preoperative and postoperative Yale-Brown Obsessive Compulsive Scale scores for 11 cingulotomy patients and 8 limbic leucotomy patients were obtained, and lesion masks were defined and compared anatomically by using an atlas-based method. Statistically significant voxels were additionally calculated by using VLSM techniques that correlated lesion characteristics with postoperative scores. RESULTS: Mean lesion volumes were 13.3 ml for cingulotomy and 11.8 ml for limbic leucotomy. As expected, cingulotomy was isolated to the anterior cingulum. The subcaudate tractotomy portion of limbic leucotomy additionally affected Brodmann area 25, the medial orbitofrontal cortex, and the nucleus accumbens. Initial results indicated that the dorsolateral regions of the cingulotomy lesion and the posteroventral regions of the subcaudate tractotomy lesion were associated with improved postoperative Yale-Brown Obsessive Compulsive Scale scores. CONCLUSIONS: Cingulotomy and limbic leucotomy are lesioning surgeries that target pathological circuits implicated in psychiatric disease. Lesion analysis and VLSM contextualize outcome data and have the potential to be useful for improving lesioning neurosurgical procedures.

We propose a fully 3-D methodology for the computation of myocardial nonviable tissue transmurality in contrast enhanced magnetic resonance images. The outcome is a continuous map defined within the myocardium where not only current state-of-the-art measures of transmurality can be calculated, but also information on the location of nonviable tissue is preserved. The computation is done by means of a partial differential equation framework we have called multi-stencil streamline fast marching. Using it, the myocardial and scarred tissue thickness is simultaneously computed. Experimental results show that the proposed 3-D method allows for the computation of transmurality in myocardial regions where current 2-D methods are not able to as conceived, and it also provides more robust and accurate results in situations where the assumptions on which current 2-D methods are based-i.e., there is a visible endocardial contour and its corresponding epicardial points lie on the same slice-, are not met.

Despite the fact that several theories link cortical development and function to the development of white matter and its geometrical structure, the relationship between gray and white matter morphology has not been widely researched. In this paper, we propose a novel framework for investigating this relationship. Given a set of fiber tracts which connect to a particular cortical region, the key idea is to compute two scalar fields that represent geometrical characteristics of the white matter and of the surface of the cortical region. The distributions of these scalar values are then linked via Mutual Information, which results in a quantitative marker that can be used in the study of normal and pathological brain structure and development. We apply this framework to a population study on autism spectrum disorder in children.

A significant percentage of individuals diagnosed with mild traumatic brain injury (mTBI) experience persistent post-concussive symptoms (PPCS). Little is known about the pathology of these symptoms and there is often no radiological evidence based on conventional clinical imaging. We aimed to utilize methods to evaluate microstructural tissue changes and to determine whether or not a link with PPCS was present. A novel analysis method was developed to identify abnormalities in high-resolution diffusion tensor imaging (DTI) when the location of brain injury is heterogeneous across subjects. A normative atlas with 145 brain regions of interest (ROI) was built from 47 normal controls. Comparing each subject’s diffusion measures to the atlas generated subject-specific profiles of injury. Abnormal ROIs were defined by absolute z-score values above a given threshold. The method was applied to 11 PPCS patients following mTBI and 11 matched controls. Z-score information for each individual was summarized with two location-independent measures: "load" (number of abnormal regions) and "severity" (largest absolute z-score). Group differences were then computed using Wilcoxon rank sum tests. Results showed statistically significantly higher load (p = 0.018) and severity (p = 0.006) for fractional anisotropy (FA) in patients compared with controls. Subject-specific profiles of injury evinced abnormally high FA regions in gray matter (30 occurrences over 11 patients), and abnormally low FA in white matter (3 occurrences over 11 subjects). Subject-specific profiles provide important information regarding the pathology associated with PPCS. Increased gray matter (GM) anisotropy is a novel in-vivo finding, which is consistent with an animal model of brain trauma that associates increased FA in GM with pathologies such as gliosis. In addition, the individualized analysis shows promise for enhancing the clinical care of PPCS patients as it could play a role in the diagnosis of brain injury not revealed using conventional imaging.

In image segmentation, we are often interested in using certain quantities to characterize the object, and perform the classification based on criteria such as mean intensity, gradient magnitude, and responses to certain predefined filters. Unfortunately, in many cases such quantities are not adequate to model complex textured objects. Along a different line of research, the sparse characteristic of natural signals has been recognized and studied in recent years. Therefore, how such sparsity can be utilized, in a non-parametric way, to model the object texture and assist the textural image segmentation process is studied in this paper, and a segmentation scheme based on the sparse representation of the texture information is proposed. More explicitly, the texture is encoded by the dictionaries constructed from the user initialization. Then, an active contour is evolved to optimize the fidelity of the representation provided by the dictionary of the target. In doing so, not only a non-parametric texture modeling technique is provided, but also the sparsity of the representation guarantees the computation efficiency. The experiments are carried out on the publicly available image data sets which contain a large variety of texture images, to analyze the user interaction, performance statistics, and to highlight the algorithm’s capability of robustly extracting textured regions from an image.

CNTNAP2 is a gene on chromosome 7 that has shown associations with autism and schizophrenia, and there is evidence that it plays an important role for neuronal synchronization and brain connectivity. In this study, we assessed the relationship between Diffusion Tensor Imaging (DTI), a putative marker of anatomical brain connectivity, and multiple single nucleotide polymorphisms (SNPs) spread out over this large gene. 81 healthy controls and 44 patients with schizophrenia (all Caucasian) underwent DTI and genotyping of 31 SNPs within CNTNAP2. We employed Tract-based Spatial Statistics (TBSS) for inter-subject brain registration and computed average diffusivity values for six major white matter tracts. Analyses of Covariance (ANCOVAs) were computed to test for possible associations with genotypes. The strongest association, which survived rigorous Bonferroni correction, was between rs2710126 genotype and Fractional Anisotropy (FA) in the uncinate fasciculus (p = .00003). This anatomical location is particularly interesting given the enriched fronto-temporal expression of CNTNAP2 in the developing brain. For this SNP, no phenotype association has been reported before. There were several further genotype-DTI associations that were nominally significant but did not survive Bonferroni correction, including an association between axial diffusivity in the dorsal cingulum bundle and a region in intron 13 (represented by rs2710102, rs759178, rs2538991), which has previously been reported to be associated with anterior-posterior functional connectivity. We present new evidence about the effects of CNTNAP2 on brain connectivity, whose disruption has been hypothesized to be central to schizophrenia pathophysiology.

Patients with 22q11.2 deletion syndrome (22q11.2DS) represent a population at high risk for developing schizophrenia, as well as learning disabilities. Deficits in visuo-spatial memory are thought to underlie some of the cognitive disabilities. Neuronal substrates of visuo-spatial memory include the inferior fronto-occipital fasciculus (IFOF) and the inferior longitudinal fasciculus (ILF), two tracts that comprise the ventral visual stream. Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) is an established method to evaluate white matter (WM) connections in vivo. DT-MRI scans of nine 22q11.2DS young adults and nine matched healthy subjects were acquired. Tractography of the IFOF and the ILF was performed. DT-MRI indices, including Fractional anisotropy (FA, measure of WM changes), axial diffusivity (AD, measure of axonal changes) and radial diffusivity (RD, measure of myelin changes) of each of the tracts and each group were measured and compared. The 22q11.2DS group showed statistically significant reductions of FA in IFOF in the left hemisphere. Additionally, reductions of AD were found in the IFOF and the ILF in both hemispheres. These findings might be the consequence of axonal changes, which is possibly due to fewer, thinner, or less organized fibers. No changes in RD were detected in any of the tracts delineated, which is in contrast to findings in schizophrenia patients where increases in RD are believed to be indicative of demyelination. We conclude that reduced axonal changes may be key to understanding the underlying pathology of WM leading to the visuo-spatial phenotype in 22q11.2DS.