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BioMed Research International
Volume 2016 (2016), Article ID 9578139, 9 pages
http://dx.doi.org/10.1155/2016/9578139
Research Article

Characterization of Enhancing MS Lesions by Dynamic Texture Parameter Analysis of Dynamic Susceptibility Perfusion Imaging

1Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, 3010 Bern, Switzerland
2Tiefenau Hospital, Institute of Radiology, Spital-Netz Bern, 3004 Bern, Switzerland
3Department of Neurology, Inselspital, University of Bern, 3010 Bern, Switzerland

Received 31 August 2015; Accepted 3 December 2015

Academic Editor: Guang Jia

Copyright © 2016 Rajeev K. Verma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose. The purpose of this study was to investigate statistical differences with MR perfusion imaging features that reflect the dynamics of Gadolinium-uptake in MS lesions using dynamic texture parameter analysis (DTPA). Methods. We investigated 51 MS lesions (25 enhancing, 26 nonenhancing lesions) of 12 patients. Enhancing lesions () were prestratified into enhancing lesions with increased permeability (EL+; ) and enhancing lesions with subtle permeability (EL−; ). Histogram-based feature maps were computed from the raw DSC-image time series and the corresponding texture parameters were analyzed during the inflow, outflow, and reperfusion time intervals. Results. Significant differences () were found between EL+ and EL− and between EL+ and nonenhancing inactive lesions (NEL). Main effects between EL+ versus EL− and EL+ versus NEL were observed during reperfusion (mainly in mean and standard deviation (SD): EL+ versus EL− and EL+ versus NEL), while EL− and NEL differed only in their SD during outflow. Conclusion. DTPA allows grading enhancing MS lesions according to their perfusion characteristics. Texture parameters of EL− were similar to NEL, while EL+ differed significantly from EL− and NEL. Dynamic texture analysis may thus be further investigated as noninvasive endogenous marker of lesion formation and restoration.