Diffusion-Tensor MR Imaging of Cortical Lesions in Multiple Sclerosis: Initial Findings

Poonawalla, Aziz H.; Hasan, Khader M.; Gupta, Rakesh K.; Ahn, Chul; Nelson, Flavia; Wolinsky, Jerry S.; Narayana, Ponnada A.

doi:10.1148/radiol.2463070486

Cited by 57 publications

(44 citation statements)

References 26 publications

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“…These results are similar to others presented earlier (Cifelli et al, 2002; Fabiano et al, 2003; Inglese et al, 2004; Poonawalla et al, 2008; Dineen et al, 2009; Roosendaal et al, 2009; Raz et al, 2010; Kern et al, 2011; Yu et al, 2012). However it is important to point out that we also found a signature of extensive demyelination in the normal appearing white matter, which was only rarely described in former diffusion tensor imaging studies.…”

Section: Discussionsupporting

confidence: 92%

Gray Matter Atrophy Is Primarily Related to Demyelination of Lesions in Multiple Sclerosis: A Diffusion Tensor Imaging MRI Study

et al. 2017

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Objective: Cortical pathology, periventricular demyelination, and lesion formation in multiple sclerosis (MS) are related (Hypothesis 1). Factors in the cerebrospinal fluid close to these compartments could possibly drive the parallel processes. Alternatively, the cortical atrophy could be caused by remote axonal transection (Hypothesis 2). Since MRI can differentiate between demyelination and axon loss, we used this imaging modality to investigate the correlation between the pattern of diffusion parameter changes in the periventricular- and deep white matter and the gray matter atrophy.Methods: High-resolution T1-weighted, FLAIR, and diffusion MRI images were acquired in 52 RRMS patients and 50 healthy, age-matched controls. We used EDSS to estimate the clinical disability. We used Tract Based Spatial Statistics to compare diffusion parameters (fractional anisotropy, mean, axial, and radial diffusivity) between groups. We evaluated global brain, white, and gray matter atrophy with SIENAX. Averaged, standard diffusion parameters were calculated in four compartment: periventricular lesioned and normal appearing white matter, non-periventricular lesioned and normal appearing white matter. PLS regression was used to identify which diffusion parameter and in which compartment best predicts the brain atrophy and clinical disability.Results: In our diffusion tensor imaging study compared to controls we found extensive alterations of fractional anisotropy, mean and radial diffusivity and smaller changes of axial diffusivity (maximal p > 0.0002) in patients that suggested demyelination in the lesioned and in the normal appearing white matter. We found significant reduction in total brain, total white, and gray matter (patients: 718.764 ± 14.968, 323.237 ± 7.246, 395.527 ± 8.050 cm3, controls: 791.772 ± 22.692, 355.350 ± 10.929, 436.422 ± 12.011 cm3; mean ± SE), (p < 0.015; p < 0.0001; p < 0.009; respectively) of patients compared to controls. The PLS analysis revealed a combination of demyelination-like diffusion parameters (higher mean and radial diffusivity in patients) in the lesions and in the non-lesioned periventricular white matter, which best predicted the gray matter atrophy (p < 0.001). Similarly, EDSS was best predicted by the radial diffusivity of the lesions and the non-lesioned periventricular white matter, but axial diffusivity of the periventricular lesions also contributed significantly (p < 0.0001).Interpretation: Our investigation showed that gray matter atrophy and white matter demyelination are related in MS but white matter axonal loss does not significantly contribute to the gray matter pathology.

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Section: Discussionsupporting

confidence: 92%

Gray Matter Atrophy Is Primarily Related to Demyelination of Lesions in Multiple Sclerosis: A Diffusion Tensor Imaging MRI Study

et al. 2017

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“…4,21 This increase of FA has been attributed to the specific characteristics of cortical lesions within the examined GM. Cortical lesions are characterized by low inflammatory demyelination, microglia proliferation and activation as well as loss of dendritic arborization 22 distinguishing them from WM lesions.…”

Section: Discussionmentioning

confidence: 92%

Non-Gaussian diffusion MRI of gray matter is associated with cognitive impairment in multiple sclerosis

et al. 2014

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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 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 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.

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“…Recently, Poonawalla et al ( 86 ) found increased FA values in intracortical MS lesions, which might refl ect increased tissue structural coherence due to reduced dendritic arborization, or increased activation of microglia with extended processes that sheathe neuronal cell bodies and dendrites.…”

Section: Diffusion-tensor Mr Imagingmentioning

confidence: 99%

MR Imaging of Multiple Sclerosis

2011

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Owing to its ability to depict the pathologic features of multiple sclerosis (MS) in exquisite detail, conventional magnetic resonance (MR) imaging has become an established tool in the diagnosis of this disease and in monitoring its evolution. MR imaging has been formally included in the diagnostic work-up of patients who present with a clinically isolated syndrome suggestive of MS, and ad hoc diagnostic criteria have been proposed and are updated on a regular basis. In patients with established MS and in those participating in treatment trials, examinations performed with conventional MR pulse sequences provide objective measures to monitor disease activity and progression; however, they have a limited prognostic role. This has driven the application of newer MR imaging technologies, including higher-field-strength MR units, to estimate overall MS burden and mechanisms of recovery in patients at different stages of the disease. These techniques have allowed in vivo assessment of the heterogeneity of MS pathologic features in focal lesions and in normal-appearing tissues. More recently, some of the finer details of MS, including macrophage infiltration and abnormal iron deposition, have become quantifiable with MR imaging. The utility of these modern MR techniques in clinical trial monitoring and in the assessment of the individual patient's response to treatment still need to be evaluated.

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Diffusion-Tensor MR Imaging of Cortical Lesions in Multiple Sclerosis: Initial Findings

Abstract: DIR and PSIR combined with nonlinear image registration allowed direct focal measurement of FA and MD in cortical lesions.

Cited by 57 publications

References 26 publications

Gray Matter Atrophy Is Primarily Related to Demyelination of Lesions in Multiple Sclerosis: A Diffusion Tensor Imaging MRI Study

Gray Matter Atrophy Is Primarily Related to Demyelination of Lesions in Multiple Sclerosis: A Diffusion Tensor Imaging MRI Study

Non-Gaussian diffusion MRI of gray matter is associated with cognitive impairment in multiple sclerosis

MR Imaging of Multiple Sclerosis

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