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Abstract #0244

Habitat analysis based on mean apparent propagator-MRI for differentiating between glioblastoma and solitary brain metastasis

Guohua Zhao1, Mengyang He2, Xiaoyue Ma1, Eryuan Gao1, Yufei Gao2, Xingyu Liu2, Jie Bai1, Mengzhu Wang3, Yong Zhang1, and Jingliang Cheng1
1The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, 2Zhengzhou University, Zhengzhou, China, 3Siemens Healthineers Ltd., Zhengzhou, China

Synopsis

Keywords: Diagnosis/Prediction, Tumors

Motivation: Accurate preoperative differentiation between glioblastoma (Gb) and solitary brain metastasis (SBM) is crucial for formulating treatment plans.

Goal(s): This study aims to explore the utility of habitat analysis using MAP-MRI in differentiating between Gb and SBM.

Approach: Five habitat sub-regions are delineated based on MAP-MRI parametric maps, and radiomic features are extracted. Subsequently, classification models are constructed separately to predict Gb and SBM, and the performance of models for each habitat sub-region is evaluated.

Results: The ABV sub-region model achieved the best discriminative ability in differentiating between glioblastoma (Gb) and solitary brain metastasis (SBM).

Impact: Morphological MRI often struggles to differentiate between glioblastoma (Gb) and solitary brain metastasis (SBM). This study seeks to identify differences between these two types of tumors through advanced diffusion imaging, with the aim of contributing to clinical practice.

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Keywords