Person:

Soman, Salil

Objective: Given the high prevalence and comorbidity of combat-related PTSD and TBI in Veterans, it is often difficult to disentangle the contributions of each disorder. Examining these pathologies separately may help to understand the neurobiological basis of memory impairment in PTSD and TBI independently of each other. Thus, we investigated whether a) PTSD and TBI are characterized by subcortical structural abnormalities by examining diffusion tensor imaging (DTI) metrics and volume and b) if these abnormalities were specific to PTSD versus TBI. Method We investigated whether individuals with PTSD or TBI display subcortical structural abnormalities in memory regions by examining DTI metrics and volume of the hippocampus and caudate in three groups of Veterans: Veterans with PTSD, Veterans with TBI, and Veterans with neither PTSD nor TBI (Veteran controls). Results: While our results demonstrated no macrostructural differences among the groups in these regions, there were significant alterations in microstructural DTI indices in the caudate for the PTSD group but not the TBI group compared to Veteran controls. Conclusions: The result of increased mean, radial, and axial diffusivity, and decreased fractional anisotropy in the caudate in absence of significant volume atrophy in the PTSD group suggests the presence of subtle abnormalities evident only at a microstructural level. The caudate is thought to play a role in the physiopathology of PTSD, and the habit-like behavioral features of the disorder could be due to striatal-dependent habit learning mechanisms. Thus, DTI appears to be a vital tool to investigate subcortical pathology, greatly enhancing the ability to detect subtle brain changes in complex disorders.

Carotid revascularization (endarterectomy, stenting) prevents stroke; however, procedure-related embolization is common and results in small brain lesions easily identified by diffusion weighted magnetic resonance imaging (DWI). A crucial barrier to understanding the clinical significance of these lesions has been the lack of a statistical approach to identify vulnerable brain areas. The problem is that the lesions are small, numerous, and non-overlapping. Here we address this problem with a new method, the Convergence Analysis of Micro-Lesions (CAML) technique, an extension of the Anatomic Likelihood Analysis (ALE). The method combines manual lesion tracing, constraints based on known lesion patterns, and convergence analysis to represent regions vulnerable to lesions as probabilistic brain atlases. Two studies were conducted over the course of 12 years in an active, vascular surgery clinic. An analysis in an initial group of 126 patients at 1.5 T MRI was cross-validated in a second group of 80 patients at 3T MRI. In CAML, lesions were manually defined and center points identified. Brains were aligned according to side of surgery since this factor powerfully determines lesion distribution. A convergence based analysis, was performed on each of these groups. Results indicated the most consistent region of vulnerability was in motor and premotor cortex regions. Smaller regions common to both groups included the dorsolateral prefrontal cortex and medial parietal regions. Vulnerability of motor cortex is consistent with previous work showing changes in hand dexterity associated with these procedures. The consistency of CAML also demonstrates the feasibility of this new approach to characterize small, diffuse, non-overlapping lesions in patients with multifocal pathologies.

Functional imaging provides hemodynamic and metabolic information and is increasingly being incorporated into clinical diagnostic and research studies. Typically functional images have reduced signal-to-noise ratio and spatial resolution compared to other non-functional cross sectional images obtained as part of a routine clinical protocol. We hypothesized that enhancing visualization and interpretation of functional images with anatomic information could provide preferable quality and superior diagnostic value. In this work, we implemented five methods (frequency addition, frequency multiplication, wavelet transform, non-subsampled contourlet transform and intensity-hue-saturation) and a newly proposed ShArpening by Local Similarity with Anatomic images (SALSA) method to enhance the visualization of functional images, while preserving the original functional contrast and quantitative signal intensity characteristics over larger spatial scales. Arterial spin labeling blood flow MR images of the brain were visualization enhanced using anatomic images with multiple contrasts. The algorithms were validated on a numerical phantom and their performance on images of brain tumor patients were assessed by quantitative metrics and neuroradiologist subjective ratings. The frequency multiplication method had the lowest residual error for preserving the original functional image contrast at larger spatial scales (55%–98% of the other methods with simulated data and 64%–86% with experimental data). It was also significantly more highly graded by the radiologists (p<0.005 for clear brain anatomy around the tumor). Compared to other methods, the SALSA provided 11%–133% higher similarity with ground truth images in the simulation and showed just slightly lower neuroradiologist grading score. Most of these monochrome methods do not require any prior knowledge about the functional and anatomic image characteristics, except the acquired resolution. Hence, automatic implementation on clinical images should be readily feasible.

Many Veterans exposed to physical and psychological trauma experience symptoms of posttraumatic stress disorder (PTSD). As the etiology of PTSD symptoms is complex, a better understanding of the underlying biological mechanisms may improve preventative care and treatment for PTSD. Recent findings from the fields of neuroimaging and epigenetics offer important insights into the potential brain structures and biochemical pathways of modified gene expression associated with PTSD. We combined neuroimaging and epigenetic measures to assess current PTSD symptoms by measuring overall hippocampal volume and methylation of the glucocorticoid receptor (GR) gene (promoter region). Multiple regression analyses indicated that the hippocampal volume/GR methylation interaction was a predictor of PTSD symptoms. Our findings suggest that neuroimaging and epigenetic measures contribute interactively to PTSD symptoms. Incorporation of these metrics may aid in the identification and treatment of PTSD patients.

Purpose To improve pseudo continuous arterial spin labeling (PCASL) robustness to off-resonance and pulsatile blood flow velocity.

Methods The Bloch equations were solved to evaluate the effect of labeling parameters in a pulsatile flow model for a range of off-resonance. Experimental confirmation was achieved in volunteers using linear phase increase between labeling pulses to approximate off-resonance errors. The location of the labeling plane was first assessed on four volunteers, then a range of parameters, including balanced and unbalanced gradients, were explored in five more volunteers at an optimal labeling plane location.

Results Simulations demonstrated that high velocities are vulnerable to off-resonance, that unbalanced PCASL outperforms balanced PCASL, that increased B1 and low average gradient improve the labeling efficiency for high velocity flow, and a low ratio of selective to average gradient improves off-resonance robustness. A good agreement between theory and experiment was observed.

Conclusion The robustness of PCASL can be increased by selecting an unbalanced scheme with a low average gradient (0.5mT/m), a low ratio (7x) of selective to average gradients and the highest feasible B1 (1.8uT). Placing the labeling plane above the carotid bifurcation and below the V3 segment, usually between the second and third vertebrae, produces robust results.