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Abstract #3771

Identification of Glioblastoma Infiltrative Areas in Peritumoral Edema Based on Expert Interaction Framework

Jiaqi Tu1, Chuyun Shen2, Jianpeng Liu1, Ji Xiong3, Xiangfeng Wang2, Bo Jin4, Fengping Zhu5, and Yuxin Li1
1Radiology, Huashan Hospital, Fudan University, Shanghai, China, 2School of Computer Science and Technology, East China Normal University, Shanghai, China, 3Pathology, Huashan Hospital, Fudan University, Shanghai, China, 4School of Software Engineering, Tongji University, Shanghai, China, 5Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China

Synopsis

Keywords: Diagnosis/Prediction, Brain

Motivation: Infiltration and recurrence of glioblastoma is typically fatal. Conventional imaging techniques are insufficient for identifying the infiltrated regions.

Goal(s): We aim to develop an interactive visualization method based on conventional MRI to identify the peri-tumor infiltration.

Approach: Glioblastoma infiltrating area detection interactive framework (GIADIF) consists of two steps: delineating peritumoral edema and extracting the voxels with low fractional anisotropy value as user-interactive input; using the P-Net from the DeepIGeoS framework to output the infiltrated maps, and validating in a prospective cohort.

Results: GIADIF showed reliable performance in identifying GBM-infiltrated regions (area under the receiver operating characteristic curve: 0.929 [95% CI 0.804–1.000]).

Impact: GIADIF utilizes the interactive information to the conventional MRI sequences to locate areas of GBM infiltration. Its excellent performance allows for the prompt and precise selection sites for surgery and radiotherapy.

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Keywords