Meeting Banner
Abstract #4793

Radiogenomic Analysis using Dynamic Histogram Parameters of MR Perfusion-weighted Imaging in Glioblastoma

Kuan Chen1, Tzu-Wei Lee1, Chao-Wei Tso1, Larry Ying-Liang Lai2, Hui-Hsien Lin3, Fei-Ting Hsu4, and Hua-Shan Liu1
1Taipei Medical University, Taipei City, Taiwan, 2Taipei Medical University and National Health Research Institutes, Taipei City, Taiwan, 3CT/MR Division, Rotary Trading CO.,LTD, Taipei City, Taiwan, 4China Medical University, Taichung City, Taiwan

Imaging features contain information that reflects underlying pathophysiology but are distinct from that provided by assessments of tumor specimens, which can involve sampling errors because of selection bias of a localized sampling area. Most of the imaging assessment are based on the static and structural MRI and less has been done to perfusion-weighted imaging (PWI) which can reveal tumor vascularity. Time-dependent dynamic histogram parameters of PWI were derived and correlated with the survival rate and gene expression data. Our study demonstrated that the time-dependent information of dynamic histogram parameters can provide additional information regarding survival rate and GBM angiogenesis pathways.

This abstract and the presentation materials are available to 2020 meeting attendees and eLibrary customers only; a login is required.

Join Here