TY - JOUR
T1 - Amide Proton Transfer Weighted Imaging Shows Differences in Multiple Sclerosis Lesions and White Matter Hyperintensities of Presumed Vascular Origin
AU - Sartoretti, Elisabeth
AU - Sartoretti, Thomas
AU - Wyss, Michael
AU - Becker, Anton S.
AU - Schwenk, Árpád
AU - van Smoorenburg, Luuk
AU - Najafi, Arash
AU - Binkert, Christoph
AU - Thoeny, Harriet C.
AU - Zhou, Jinyuan
AU - Jiang, Shanshan
AU - Graf, Nicole
AU - Czell, David
AU - Sartoretti-Schefer, Sabine
AU - Reischauer, Carolin
N1 - Publisher Copyright:
© Copyright © 2019 Sartoretti, Sartoretti, Wyss, Becker, Schwenk, van Smoorenburg, Najafi, Binkert, Thoeny, Zhou, Jiang, Graf, Czell, Sartoretti-Schefer and Reischauer.
PY - 2019/12/10
Y1 - 2019/12/10
N2 - Objectives: 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. Materials and Methods: 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. Results: All histogram parameters except the 75 and 90th percentile were significantly different between MSL and WMH (p = 0.018–p = 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 (p = 0.005). The mean values of WMH did not differ significantly from the values of healthy WM (p = 0.345). Conclusions: 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.
AB - Objectives: 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. Materials and Methods: 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. Results: All histogram parameters except the 75 and 90th percentile were significantly different between MSL and WMH (p = 0.018–p = 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 (p = 0.005). The mean values of WMH did not differ significantly from the values of healthy WM (p = 0.345). Conclusions: 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.
KW - CEST
KW - amide proton transfer
KW - magnetic resonance imaging
KW - molecular imaging
KW - multiple sclerosis lesions
KW - white matter lesions
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U2 - 10.3389/fneur.2019.01307
DO - 10.3389/fneur.2019.01307
M3 - Article
C2 - 31920930
AN - SCOPUS:85077264842
SN - 1664-2295
VL - 10
JO - Frontiers in Neurology
JF - Frontiers in Neurology
M1 - 1307
ER -