Quantifying the Susceptibility Variation of Normal-Appearing White Matter in Multiple Sclerosis by Quantitative Susceptibility Mapping

Chen, Weiwei; Zhang, Yan; Mu, Ketao; Pan, Chu; Gauthier, Susan A.; Zhu, Wenzhen; Wang, Yi

doi:10.2214/ajr.16.16851

Cited by 18 publications

(15 citation statements)

References 30 publications

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“…A recent study reported increased NAWM QS in patients who had only non-enhancing lesions compared to HC subjects, and no significant difference in patients with enhancing lesions [44]. However, among patients in our study with only non-enhancing lesions, we found no significant QS difference between whole-brain NAWM compared to HCWM.…”

Section: Discussioncontrasting

confidence: 86%

“…Furthermore, iron content in NAWM may vary between different patients (i.e., relapsing–remitting versus primary progressive subtypes) as well as within the same patient over time [44]. With regard to the latter, Hametner et al found iron deposition in the NAWM of patients with acute MS similar to healthy populations, while patients with chronic disease exhibited iron depletion [38].…”

Section: Discussionmentioning

confidence: 99%

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Characterization of normal-appearing white matter in multiple sclerosis using quantitative susceptibility mapping in conjunction with diffusion tensor imaging

Chiang

Stephens

et al. 2018

Neuroradiology

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Purpose Quantitative susceptibility mapping (QSM) is influenced by iron as well as myelin, which makes interpretation of pathologic changes challenging. Concurrent acquisition of MR sequences that are sensitive to axonal/myelin integrity, such as diffusion tensor imaging (DTI), may provide context for interpreting quantitative susceptibility (QS) signal. The purpose of our study was to investigate alterations in normal-appearing white matter (NAWM) in multiple sclerosis (MS) using QSM in conjunction with DTI. Methods Twenty relapsing–remitting MS patients and 20 age-matched healthy controls (HC) were recruited for this prospective study. QS, radial diffusivity (RD), fractional anisotropy (FA), and R2* maps within the whole brain as well as individual tracts were generated for comparison between NAWM and HC white matter (HCWM). Results MS lesions demonstrated significant differences in QS, FA, RD, and R2* compared to HCWM (p < 0.03). These metrics did not show a significant difference between whole-brain NAWM and HCWM. Among NAWM tracts, the cingulate gyri demonstrated significantly decreased QS compared to HCWM (p = 0.004). The forceps major showed significant differences in FA and RD without corresponding changes in QS (p < 0.01). Conclusion We found discordant changes in QSM and DTI metrics within the cingulate gyri and forceps major. This may potentially reflect the influence of paramagnetic substrates such as iron, which could be decreased along these NAWM tracts. Our results point to the potential role of QSM as a unique biomarker, although additional validation studies are needed.

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Section: Discussioncontrasting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Characterization of normal-appearing white matter in multiple sclerosis using quantitative susceptibility mapping in conjunction with diffusion tensor imaging

Chiang

Stephens

et al. 2018

Neuroradiology

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“…Quantitative susceptibility mapping (QSM) enables the quantitative measurement of tissue magnetic susceptibility, which is a measure of how tissue responds to an external magnetic field . QSM has been used increasingly in clinical brain studies, particularly for visualizing and quantifying iron in brain diseases, including multiple sclerosis (MS), distinguishing calcifications and hemorrhage, and preoperative planning for deep brain stimulation . In the brain, QSM technology has advanced to a stage of high reproducibility as demonstrated by various groups .…”

Section: Introductionmentioning

confidence: 99%

Clinical Integration of Automated Processing for Brain Quantitative Susceptibility Mapping: Multi‐Site Reproducibility and Single‐Site Robustness

Spincemaille

Liu

Zhang

et al. 2019

Journal of Neuroimaging

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Quantitative susceptibility mapping (QSM) of the brain has become highly reproducible and has applications in an expanding array of diseases. To translate QSM from bench to bedside, it is important to automate its reconstruction immediately after data acquisition. In this work, a server system that automatically reconstructs QSM and exchange images with the scanner using the DICOM standard is demonstrated using a multi-site, multi-vendor reproducibility study and a large, single-site, multi-scanner image quality review study in a clinical environment. METHODS: A single healthy subject was scanned with a 3D multi-echo gradient echo sequence at nine sites around the world using scanners from three manufacturers. A high-resolution (HiRes, .5 × .5 × 1 mm 3 reconstructed) and standard-resolution (StdRes, .5 × .5 × 3 mm 3 ) protocol was performed. ROI analysis of various white matter and gray matter regions was performed to investigate reproducibility across sites. At one institution, a retrospective multi-scanner image quality review was carried out of all clinical QSM images acquired consecutively in 1 month. RESULTS: Reconstruction times using a GPU were 29 ± 22 seconds (StdRes) and 55 ± 39 seconds (HiRes). ROI standard deviation across sites was below 24 ppb (StdRes) and 17 ppb (HiRes). Correlations between ROI averages across sites were on average .92 (StdRes) and .96 (HiRes). Image quality review of 873 consecutive patients revealed diagnostic or excellent image quality in 96% of patients. CONCLUSION: Online QSM reconstruction for a variety of sites and scanner platforms with low cross-site ROI standard deviation is demonstrated. Image quality review revealed diagnostic or excellent image quality in 96% of 873 patients.

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“…CNS abnormalities beyond obvious MS plaques are also well documented . The “normal‐appearing white matter” (NAWM) is a commonly described feature of white matter that appears normal on conventional MRI, but abnormalities can be detected using advanced MRI …”

Section: Introductionmentioning

confidence: 99%

“…[6][7][8] The "normal-appearing white matter" (NAWM) is a commonly described feature of white matter that appears normal on conventional MRI, but abnormalities can be detected using advanced MRI. [9][10][11][12][13][14][15][16][17] A less often reported, but still common, feature in MS is regions of white matter with signal intensity intermediate between NAWM and MS lesions on T 2 and proton density imaging, termed diffusely abnormal white matter (DAWM) 18,19 (Fig 1), formerly termed "dirty-appearing white matter." By definition, DAWM is diffuse with ill-defined borders and has signal intensity similar to gray matter on proton density and T 2 scans, but is found in white matter locations.…”

Section: Introductionmentioning

confidence: 99%

Diffusely Abnormal White Matter, T₂ Burden of Disease, and Brain Volume in Relapsing‐Remitting Multiple Sclerosis

Vertinsky

Vavasour

et al. 2018

Journal of Neuroimaging

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BACKGROUND AND PURPOSE Multiple sclerosis (MS) diffusely abnormal white matter (DAWM) is a mildly hyperintense magnetic resonance imaging abnormality distinct from typical lesions. Our goal was to investigate the prevalence and natural history of DAWM in a large cohort (n = 348) of relapsing–remitting MS (RRMS) patients. METHODS The presence of DAWM and relationship to changes in T2 burden of disease (BOD), brain volume (brain fractional ratio, BFR), and disability (Expanded Disability Status Scale, EDSS) were investigated at baseline and year 7–8 (long‐term follow‐up, LTF). RESULTS DAWM was present in 25.3% (88 of 348) of patients at baseline. At LTF, DAWM was unchanged in 69.3% (61 of 88), decreased in 28.4% (25 of 88), and increased in 2.3% (2 of 88) of patients. Baseline BOD and change in BOD did not significantly differ between patients with and without DAWM. DAWM was associated with greater reduction in BFR at LTF (P = .038). DAWM and DAWM change did not predict EDSS or EDSS progression. CONCLUSIONS DAWM is present in a quarter of RRMS patients, and rarely increases or develops de novo. DAWM predicts brain atrophy but does not predict physical disability. Because of its posterior periventricular location, further investigation is warranted to evaluate its relationship to other measures of disability, including visual spatial processing and cognitive function.

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Quantifying the Susceptibility Variation of Normal-Appearing White Matter in Multiple Sclerosis by Quantitative Susceptibility Mapping

Cited by 18 publications

References 30 publications

Characterization of normal-appearing white matter in multiple sclerosis using quantitative susceptibility mapping in conjunction with diffusion tensor imaging

Characterization of normal-appearing white matter in multiple sclerosis using quantitative susceptibility mapping in conjunction with diffusion tensor imaging

Clinical Integration of Automated Processing for Brain Quantitative Susceptibility Mapping: Multi‐Site Reproducibility and Single‐Site Robustness

Diffusely Abnormal White Matter, T₂ Burden of Disease, and Brain Volume in Relapsing‐Remitting Multiple Sclerosis

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Quantifying the Susceptibility Variation of Normal-Appearing White Matter in Multiple Sclerosis by Quantitative Susceptibility Mapping

Cited by 18 publications

References 30 publications

Characterization of normal-appearing white matter in multiple sclerosis using quantitative susceptibility mapping in conjunction with diffusion tensor imaging

Characterization of normal-appearing white matter in multiple sclerosis using quantitative susceptibility mapping in conjunction with diffusion tensor imaging

Clinical Integration of Automated Processing for Brain Quantitative Susceptibility Mapping: Multi‐Site Reproducibility and Single‐Site Robustness

Diffusely Abnormal White Matter, T2 Burden of Disease, and Brain Volume in Relapsing‐Remitting Multiple Sclerosis

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Diffusely Abnormal White Matter, T₂ Burden of Disease, and Brain Volume in Relapsing‐Remitting Multiple Sclerosis