Evaluation of Normal Appearing White Matter in Multiple Sclerosis

Anık, Yonca; Demırcı, Ali; Efendı, Hüsnü; Bulut, Sema; Çelebi, İrfan; Komşuoğlu, Sezer

doi:10.1007/s00062-011-0091-4

Cited by 14 publications

(6 citation statements)

References 37 publications

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“…myelin) theoretically leads to an increase in free water diffusivity within damaged tissue compared to contralateral NAWM in patients or normal WM of healthy subjects. Several studies have confirmed an increase in water diffusivity within MS lesions [ 3 , 34 – 36 ], resulting from an increase in ‘free’ extracellular space either by extracellular edema at the acute inflammatory phase, or by demyelination at the chronic phase. However, the assumption that acute inflammation within enhanced lesions could display significantly different ADC values (or mean diffusivity values when diffusion tensor imaging is used) than within the chronic gliotic/demyelinated scar tissue of unenhanced lesions is still unverified and the reasons for variability in ADC value changes within enhanced lesions remain controversial [ 37 , 38 ].…”

Section: Discussionmentioning

confidence: 99%

Texture Analysis of T2-Weighted MR Images to Assess Acute Inflammation in Brain MS Lesions

et al. 2015

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Brain blood barrier breakdown as assessed by contrast-enhanced (CE) T1-weighted MR imaging is currently the standard radiological marker of inflammatory activity in multiple sclerosis (MS) patients. Our objective was to evaluate the performance of an alternative model assessing the inflammatory activity of MS lesions by texture analysis of T2-weighted MR images. Twenty-one patients with definite MS were examined on the same 3.0T MR system by T2-weighted, FLAIR, diffusion-weighted and CE-T1 sequences. Lesions and mirrored contralateral areas within the normal appearing white matter (NAWM) were characterized by texture parameters computed from the gray level co-occurrence and run length matrices, and by the apparent diffusion coefficient (ADC). Statistical differences between MS lesions and NAWM were analyzed. ROC analysis and leave-one-out cross-validation were performed to evaluate the performance of individual parameters, and multi-parametric models using linear discriminant analysis (LDA), partial least squares (PLS) and logistic regression (LR) in the identification of CE lesions. ADC and all but one texture parameter were significantly different within white matter lesions compared to within NAWM (p < 0.0167). Using LDA, an 8-texture parameter model identified CE lesions with a sensitivity Se = 70% and a specificity Sp = 76%. Using LR, a 10-texture parameter model performed better with Se = 86% / Sp = 84%. Using PLS, a 6-texture parameter model achieved the highest accuracy with Se = 88% / Sp = 81%. Texture parameter from T2-weighted images can assess brain inflammatory activity with sufficient accuracy to be considered as a potential alternative to enhancement on CE T1-weighted images.

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Section: Discussionmentioning

confidence: 99%

Texture Analysis of T2-Weighted MR Images to Assess Acute Inflammation in Brain MS Lesions

et al. 2015

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“…Mobile choline and phosphocholine exhibit high-intensity methyl singlets at 3.2 ppm with additional methylene multiplets at 4.1–4.3 and 3.5–3.6 ppm, while glycerophosphocholine demonstrates a range of complex resonances from 3.2 to 4.3 ppm (21). Creatine-referenced choline has demonstrated increases in mixed or unspecified multiple sclerosis group lesions (23–25, 34, 41, 138) and normal-appearing white matter (34, 41); in relapsing-remitting lesions (49, 139, 140), normal-appearing white matter (141), and spine (142); and in progressive lesions (78) and spine (76). Decreases, however, have also been shown in mixed multiple sclerosis lesions (29) and in relapsing-remitting lesions (143), normal-appearing white matter (66), gray matter (144), and mixed tissue (144, 145).…”

Section: Potential Small-molecule Diagnostic Biomarkers Of Multiple Smentioning

confidence: 99%

“…Almost half of the surveyed papers employed magnetic resonance spectroscopic imaging (MRSI) instead of single-voxel acquisition schemes, including echo-planar spectroscopic imaging (EPSI) (85, 89, 124, 144, 145, 221–223), and other CSI or spectroscopic imaging sequences encoded in two (25, 28, 30, 34, 36, 41, 43, 45, 50, 52, 54, 57, 60–62, 64–66, 68, 72, 73, 80, 81, 83, 87, 93, 94, 115, 119, 130, 131, 133, 135, 141, 159, 162–165, 167, 168, 174, 188, 191, 194, 204, 224–231) or three (102, 121, 122, 137, 202, 232, 233) spatial dimensions. MRSI offers the obvious advantage of enabling metabolic profiling over a large area of multiple tissue types, thereby enabling averaging over gray matter, white matter, and lesions within the same individual, enabling more robust estimates for the metabolic patterns of hypothetically pure tissue (102, 104, 163, 164).…”

Section: Spectral Acquisition and Processingmentioning

confidence: 99%

Quantifying the Metabolic Signature of Multiple Sclerosis by in vivo Proton Magnetic Resonance Spectroscopy: Current Challenges and Future Outlook in the Translation From Proton Signal to Diagnostic Biomarker

et al. 2019

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Proton magnetic resonance spectroscopy (1H-MRS) offers a growing variety of methods for querying potential diagnostic biomarkers of multiple sclerosis in living central nervous system tissue. For the past three decades, 1H-MRS has enabled the acquisition of a rich dataset suggestive of numerous metabolic alterations in lesions, normal-appearing white matter, gray matter, and spinal cord of individuals with multiple sclerosis, but this body of information is not free of seeming internal contradiction. The use of 1H-MRS signals as diagnostic biomarkers depends on reproducible and generalizable sensitivity and specificity to disease state that can be confounded by a multitude of influences, including experiment group classification and demographics; acquisition sequence; spectral quality and quantifiability; the contribution of macromolecules and lipids to the spectroscopic baseline; spectral quantification pipeline; voxel tissue and lesion composition; T1 and T2 relaxation; B1 field characteristics; and other features of study design, spectral acquisition and processing, and metabolite quantification about which the experimenter may possess imperfect or incomplete information. The direct comparison of 1H-MRS data from individuals with and without multiple sclerosis poses a special challenge in this regard, as several lines of evidence suggest that experimental cohorts may differ significantly in some of these parameters. We review the existing findings of in vivo 1H-MRS on central nervous system metabolic abnormalities in multiple sclerosis and its subtypes within the context of study design, spectral acquisition and processing, and metabolite quantification and offer an outlook on technical considerations, including the growing use of machine learning, by future investigations into diagnostic biomarkers of multiple sclerosis measurable by 1H-MRS.

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“…We did not identify any abnormalities in CHO. Although several studies have previously reported CHO increases in MS, 43,[48][49][50] others have reported decreases, [51][52][53][54][55] and no study has been able to resolve this discrepancy. 16 It is possible that CHO abnormalities in MS are limited to certain stages of the disease, or to areas of active demyelination.…”

Section: Discussionmentioning

confidence: 93%

Whole-Brain Metabolic Abnormalities Are Associated With Mobility in Older Adults With Multiple Sclerosis

Mueller

Baird

Motl

2022

Neurorehabil Neural Repair

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Background Older adults with multiple sclerosis (MS) experience mobility impairments, but conventional brain imaging is a poor predictor of walking abilities in this population. Objective To test whether brain metabolites measured with Magnetic Resonance Spectroscopy (MRS) are associated with walking performance in older adults with MS. Methods Fifteen older adults with MS (mean age: 60.9, SD: 5.1) and 22 age-matched healthy controls (mean age: 64.2, SD: 5.7) underwent whole-brain MRS and mobility testing. Levels of N-acetylaspartate (NAA), myo-inositol (MI), choline (CHO), and temperature in 47 brain regions were compared between groups and correlated with walking speed (Timed 25 Foot Walk) and walking endurance (Six-Minute Walk). Results Older adults with MS had higher MI in 23 areas, including the bilateral frontal (right: t (21.449) = −2.605, P = .016; left: t (35) = −2.434, P = .020), temporal (right: t (35) = −3.063, P = .004; left: t (35) = −3.026, P = .005), and parietal lobes (right: t (21.100) = −2.886, P = .009; left: t (35) = −2.507, P = .017), and right thalamus (t (35) = −2.840, P = .007). MI in eleven regions correlated with walking speed, and MI in twelve regions correlated with walking endurance. NAA was lower in MS in the bilateral thalami (right: t (35) = 3.449, P < .001; left: t (35) = 2.061, P = .047), caudate nuclei (right: t (33) = 2.828, P = .008; left: t (32) = 2.132, P = .041), and posterior cingulum (right: t (35) = 3.077, P = .004; left: t (35) = 2.972, P = .005). NAA in four regions correlated with walking speed and endurance. Brain temperature was higher in MS patients in four regions, but did not correlate with mobility measures. There were no group differences in CHO. Conclusion MI and NAA may be useful imaging end-points for walking ability as a clinical outcome in older adults with MS.

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Evaluation of Normal Appearing White Matter in Multiple Sclerosis

Abstract: The MS, MTR and MR spectroscopy findings were found to be useful for detecting subtle abnormalities in NAWM. Although ADC values were significantly altered in plaque and periplaque regions a significance difference was not found in NAWM.

Cited by 14 publications

References 37 publications

Texture Analysis of T2-Weighted MR Images to Assess Acute Inflammation in Brain MS Lesions

Texture Analysis of T2-Weighted MR Images to Assess Acute Inflammation in Brain MS Lesions

Quantifying the Metabolic Signature of Multiple Sclerosis by in vivo Proton Magnetic Resonance Spectroscopy: Current Challenges and Future Outlook in the Translation From Proton Signal to Diagnostic Biomarker

Whole-Brain Metabolic Abnormalities Are Associated With Mobility in Older Adults With Multiple Sclerosis

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