Abstract #0985

Nested Habitat Analysis Based on MRI for Prediction of Progression-Free Survival in Aggressive Spinal Tumors

Yang Zhang¹, Qizheng Wang², Tongyu Wang³, Yongye Chen², Ruixin Yan², Ke Liu², Weili Zhao², Dapeng Hao³, Min-Ying Su⁴, and Ning Lang²

¹Department of Radiation Oncology, University of California, Irvine, CA, United States, ²Department of Radiology, Peking University Third Hospital, Beijing, China, ³Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China, ⁴Department of Radiological Sciences, University of California, Irvine, China

Synopsis

Keywords: Bone/Skeletal, Cancer

Motivation: The accurate prognosis of aggressive spinal tumors is crucial for treatment planning.

Goal(s): This study introduces a novel MRI-based nested habitat radiomics method, designed to identify the most aggressive regions within heterogeneous spinal tumors.

Approach: By analyzing a cohort of 259 patients with primary spinal tumors who underwent surgical resection, this method uses MRI features in a layered approach to predict progression-free survival (PFS).

Results: The model’s performance was validated with AUC of 0.88 with the habitat analysis outperforming traditional whole-tumor models. The nested habitat model could serve as a noninvasive prognostic tool, providing valuable insights for individualized surgical and post-surgical treatment plans.

Impact: This study's MRI-based nested habitat radiomics model enhances prediction accuracy of progression-free survival (PFS) in aggressive spinal tumors by focusing on the most aggressive regions, outperforming traditional models and providing valuable insights for personalized surgical and post-surgical treatment strategies.

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