Amide Proton Transfer Weighted Imaging Shows Differences in Multiple Sclerosis Lesions and White Matter Hyperintensities of Presumed Vascular Origin

To assess the ability of 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis to discriminate between multiple sclerosis lesions (MSL) and white matter hyperintensities of presumed vascular origin (WMH) and to compare APTw signal intensity of healthy white matter...

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Published inFrontiers in neurology Vol. 10; p. 1307
Main Authors Sartoretti, Elisabeth, Sartoretti, Thomas, Wyss, Michael, Becker, Anton S, Schwenk, Árpád, van Smoorenburg, Luuk, Najafi, Arash, Binkert, Christoph, Thoeny, Harriet C, Zhou, Jinyuan, Jiang, Shanshan, Graf, Nicole, Czell, David, Sartoretti-Schefer, Sabine, Reischauer, Carolin
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 10.12.2019
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Summary:To assess the ability of 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis to discriminate between multiple sclerosis lesions (MSL) and white matter hyperintensities of presumed vascular origin (WMH) and to compare APTw signal intensity of healthy white matter (healthy WM) with APTw signal intensity of MSL and WHM. A total of 27 patients (16 female, 11 males, mean age 39.6 years) with multiple sclerosis, 35 patients (17 females, 18 males, mean age 66.6 years) with small vessel disease (SVD) and 20 healthy young volunteers (9 females, 11 males, mean age 29 years) were included in the MSL, the WMH, and the healthy WM group. MSL and WMH were segmented on fluid attenuated inversion recovery (FLAIR) images underlaid onto APTw images. Histogram parameters (mean, median, 10th, 25th, 75th, 90th percentile) were calculated. Mean APTw signal intensity values in healthy WM were defined by "Region of interest" (ROI) measurements. Wilcoxon rank sum tests and receiver operating characteristics (ROC) curve analyses of clustered data were applied. All histogram parameters except the 75 and 90th percentile were significantly different between MSL and WMH ( = 0.018- = 0.034). MSL presented with higher median values in all parameters. The histogram parameters offered only low diagnostic performance in discriminating between MSL and WMH. The 10th percentile yielded the highest diagnostic performance with an AUC of 0.6245 (95% CI: [0.532, 0.717]). Mean APTw signal intensity values of MSL were significantly higher than mean values of healthy WM ( = 0.005). The mean values of WMH did not differ significantly from the values of healthy WM ( = 0.345). We found significant differences in APTw signal intensity, based on straightforward magnetization transfer analysis, between MSL and WMH and between MSL and healthy WM. Low AUC values from ROC analyses, however, suggest that it may be challenging to determine type of lesion with APTw imaging. More advanced analysis of the APT CEST signal may be helpful for further differentiation of MSL and WMH.
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Edited by: Itamar Ronen, Leiden University, Netherlands
These authors have contributed equally to this work and share first authorship
Reviewed by: Zhongliang Zu, Vanderbilt University, United States; Ece Ercan, Leiden University Medical Center, Netherlands
This article was submitted to Applied Neuroimaging, a section of the journal Frontiers in Neurology
ISSN:1664-2295
1664-2295
DOI:10.3389/fneur.2019.01307