A preliminary attempt to visualize nigrosome 1 in the substantia nigra for Parkinson's disease at 3T: An efficient susceptibility map-weighted imaging (SMWI) with quantitative susceptibility mapping using deep neural network (QSMnet).

Journal: Medical physics
Published Date:

Abstract

PURPOSE: Visibility of nigrosome 1 in the substantia nigra (SN) is used as an MR imaging biomarker for Parkinson's disease. Because of lower susceptibility induced tissue contrast and SNR visualization of the SN pars compacta (SNPC) using conventional imaging technique in the clinical field strength (≤3T) has been limited. Susceptibility map-weighted imaging (SMWI) has been proposed to visualize SNPC at 3T. To better visualize nigrosome 1 and SN areas using SMWI, accurate estimation of the quantitative susceptibility mapping (QSM) map is essential. In SMWI processing, however, QSM processing time using conventional algorithms is the most time-consuming step and may limit clinical use. In this study, we introduce an efficient SMWI processing approach using the deep neural network (QSMnet). To improve the processing speed of SMWI while maintaining similar image quality to that obtained with the conventional method, QSMnet was applied to generate a susceptibility mask for SMWI processing.

Authors

  • Minju Jo
    Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
  • Se-Hong Oh
    Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea.