Faculty Bibliography

BACKGROUND: Non-Gaussian diffusion imaging by using diffusional kurtosis imaging (DKI) allows assessment of isotropic tissue as of gray matter (GM), an important limitation of diffusion tensor imaging (DTI). OBJECTIVE: In this study, we describe DKI and DTI metrics of GM in multiple sclerosis (MS) patients and their association with cognitive deficits. METHODS: Thirty-four patients with relapsing-remitting MS and 17 controls underwent MRI on a 3T scanner including a sequence for DKI with 30 diffusion directions and 3b values for each direction. Mean kurtosis (MK), mean diffusivity and fractional anisotropy (FA) of cortical and subcortical GM were measured using histogram analysis. Spearman rank correlations were used to characterize associations among imaging measures and clinical/neuropsychological scores. RESULTS: In cortical GM, a significant decrease of MK (0.68 vs. 0.73; p < 0.001) and increase of FA (0.16 vs. 0.13; p < 0.001) was found in patients compared to controls. Decreased cortical MK was correlated with poor performance on the Delis-Kaplan Executive Function System test (r = 0.66, p = 0.01). CONCLUSION: Mean kurtosis is sensitive to abnormality in GM of MS patients and can provide information that is complementary to that of conventional DTI-derived metrics. The association between MK and cognitive deficits suggests that DKI might serve as a clinically relevant biomarker for cortical injury.

Despite the increasing development and applications of iron imaging, the pathophysiology of iron accumulation in multiple sclerosis (MS), and its role in disease progression and development of clinical disability, is poorly understood. The aims of our study were to determine the presence and extent of iron in T2 visible lesions and gray and white matter using magnetic field correlation (MFC) MRI and correlate with microscopic white matter (WM) injury as measured by diffusion tensor imaging (DTI). This is a case-control study including a series of 31 patients with clinically definite MS. The mean age was 39 years [standard deviation (SD) = 9.55], they were 11 males and 20 females, with a disease duration average of 3 years (range 0-13) and a median EDSS of 2 (0-4.5). Seventeen healthy volunteers (6 males and 11 females) with a mean age of 36 years (SD = 11.4) were recruited. All subjects underwent MR imaging on a 3T scanner using T2-weighted sequence, 3D T1 MPRAGE, MFC, single-shot DTI and post-contrast T1. T2-lesion volumes, brain volumetry, DTI parameters and iron quantification were calculated and multiple correlations were exploited. Increased MFC was found in the putamen (p = 0.061), the thalamus (p = 0.123), the centrum semiovale (p = 0.053), globus pallidus (p = 0.008) and gray matter (GM) (p = 0.004) of MS patients compared to controls. The mean lesional MFC was 121 s-2 (SD = 67), significantly lower compared to the GM MFC (<0.0001). The GM mean diffusivity (MD) was inversely correlated with the MFC in the centrum semiovale (p < 0.001), and in the splenium of the corpus callosum (p < 0.001). Patients with MS have increased iron in the globus pallidus, putamen and centrum with a trend toward increased iron in all the brain structures. Quantitative iron evaluation of WM and GM may improve the understanding of MS pathophysiology, and might serve as a surrogate marker of disease progression.

Multiple Sclerosis (MS) is a chronic inflammatory/demyelinating and neurodegenerative disease of the central nervous system (CNS). Most patients experience a relapsing-remitting (RR) course, while about 15-20% of patients experience a primary progressive (PP) course. Cognitive impairment affects approximately 40-70% of all MS patients and differences in cognitive impairment between RR-MS and PP-MS have been found. We aimed to compare RR-MS and PP-MS patients in terms of cognitive performance, and to investigate the MRI correlates of cognitive impairment in the two groups using measures of brain volumes and cortical thickness. Fifty-seven patients (42 RR-MS, 15 PP-MS) and thirty-eight matched controls underwent neuropsychological (NP) testing and MRI. PP-MS patients scored lower than RR-MS patients on most of the NP tests in absence of any specific pattern. PP-MS patients showed significantly lower caudate volume. There was no significant difference in MRI correlates of cognitive impairment between the two groups except for a prevalent association with MRI measures of cortical GM injury in RR-MS patients and with MRI measures of subcortical GM injury in PP-MS patients. This suggests that although cognitive impairment results from several factors, cortical and subcortical GM injury may play a different role depending on the disease course.

Importance: Cerebrovascular reactivity (CVR) is an inherent indicator of the dilatory capacity of cerebral arterioles for a vasomotor stimulus for maintaining a spontaneous and instant increase of cerebral blood flow (CBF) in response to neural activation. The integrity of this mechanism is essential to preserving healthy neurovascular coupling; however, to our knowledge, no studies have investigated whether there are CVR abnormalities in multiple sclerosis (MS). Objective: To use hypercapnic perfusion magnetic resonance imaging to assess CVR impairment in patients with MS. Design, Setting, and Participants: A total of 19 healthy volunteers and 19 patients with MS underwent perfusion magnetic resonance imaging based on pseudocontinuous arterial spin labeling to measure CBF at normocapnia (ie, breathing room air) and hypercapnia. The hypercapnia condition is achieved by breathing 5% carbon dioxide gas mixture, which is a potent vasodilator causing an increase of CBF. Main Outcomes and Measures: Cerebrovascular reactivity was calculated as the percent increase of normocapnic to hypercapnic CBF normalized by the change in end-tidal carbon dioxide, which was recorded during both conditions. Group analysis was performed for regional and global CVR comparison between patients and controls. Regression analysis was also performed between CVR values, lesion load, and brain atrophy measures in patients with MS. Results: A significant decrease of mean (SD) global gray matter CVR was found in patients with MS (3.56 [0.81]) compared with healthy controls (5.08 [1.56]; P = .001). Voxel-by-voxel analysis showed diffuse reduction of CVR in multiple regions of patients with MS. There was a significant negative correlation between gray matter CVR and lesion volume (R = 0.6, P = .004) and a significant positive correlation between global gray matter CVR and gray matter atrophy index (R = 0.5, P = .03). Conclusions and Relevance: Our quantitative imaging findings suggest impairment in functional cerebrovascular pathophysiology, by measuring a diffuse decrease in CVR, which may be the underlying cause of neurodegeneration in MS.

OBJECTIVE: The purpose of this study was to develop an algorithm incorporating MRI metrics to classify patients with mild traumatic brain injury (mTBI) and controls. METHODS: This was an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant prospective study. We recruited patients with mTBI and healthy controls through the emergency department and general population. We acquired data on a 3.0T Siemens Trio magnet including conventional brain imaging, resting-state fMRI, diffusion-weighted imaging, and magnetic field correlation (MFC), and performed multifeature analysis using the following MRI metrics: mean kurtosis (MK) of thalamus, MFC of thalamus and frontal white matter, thalamocortical resting-state networks, and 5 regional gray matter and white matter volumes including the anterior cingulum and left frontal and temporal poles. Feature selection was performed using minimal-redundancy maximal-relevance. We used classifiers including support vector machine, naive Bayesian, Bayesian network, radial basis network, and multilayer perceptron to test maximal accuracy. RESULTS: We studied 24 patients with mTBI and 26 controls. Best single-feature classification uses thalamic MK yielding 74% accuracy. Multifeature analysis yields 80% accuracy using the full feature set, and up to 86% accuracy using minimal-redundancy maximal-relevance feature selection (MK thalamus, right anterior cingulate volume, thalamic thickness, thalamocortical resting-state network, thalamic microscopic MFC, and sex). CONCLUSION: Multifeature analysis using diffusion-weighted imaging, MFC, fMRI, and volumetrics may aid in the classification of patients with mTBI compared with controls based on optimal feature selection and classification methods. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that classification algorithms using multiple MRI features accurately identifies patients with mTBI as defined by American Congress of Rehabilitation Medicine criteria compared with healthy controls.