Abstract #0369

Whole-Tumor Histogram Analysis of Synthetic MRI Predicts IDH mutation status in gliomas

Xin Ge¹, Ying shen², Yuhui Xiong³, Min Li³, Xiaodong Wang⁴, and Jing Zhang⁵

¹Second Clinical School, Lanzhou University, Lanzhou, China, ²Department of Rehabilitation Medicine, Second Affiliated Hospital of Air Force Military Medical University, Xi'an, China, ³GE Healthcare MR Research, Beijing, China, Beijing, China, ⁴Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China, ⁵Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China

Synopsis

Keywords: Tumors (Pre-Treatment), Brain, Gliomas, Isocitrate Dehydrogenase, Synthetic MRI, Histogram Analysis

Motivation: There is an urgent need to identify a novel, cost-effective, and non-invasive method for determining the IDH mutation status in differentiating between astrocytoma and glioblastoma.

Goal(s): To investigate the potential value of whole-tumor histogram metrics derived from synthetic MRI in distinguishing IDH mutation status.

Approach: Histogram metrics were extracted from the quantitative maps. Variables with statistical significance in univariate analysis were included in multivariate logistic regression analysis to develop the combined model. The AUC were used to assess the diagnostic performance of metrics and models.

Results: The combined model could be a valuable preoperative tool to distinguish IDH mutation status.

Impact: The current study proposes a combined model that comprises T1-10th, cT1-10th, and age. This model demonstrates differentiation between IDH-M astrocytoma and IDH-W glioblastoma. Moreover, it has the potential to decrease genetic testing expenses while offering treatment decision support for clinicians.

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