biostudies-literatureLiu TDong HuangJie WeiYang Liu978https://www.ebi.ac.uk/biostudies/studies/S-EPMC12467337biostudies-literatureUnknown12(9)<h4>Background</h4>Glioblastoma (GBM) is a highly aggressive and heterogeneous primary malignancy of the central nervous system, with a median overall survival (OS) of approximately 15 months. Achieving accurate and generalizable OS prediction across multi-center settings is essential for clinical application.<h4>Methods</h4>We propose a Personalized Habitat-aware Survival Prediction Network (PHSP-Net) that integrates multiparametric MRI with an adaptive habitat partitioning strategy. The network combines deep convolutional feature extraction and interpretable visualization modules to perform patient-specific subregional segmentation and survival prediction. A total of 1084 patients with histologically confirmed WHO grade IV GBM from four centers (UPENN-GBM, UCSF-PDGM, LUMIERE and TCGA-GBMBioengineering (Basel, Switzerland)PHSP-Net: Personalized Habitat-Aware Deep Learning for Multi-Center Glioblastoma Survival Prediction Using Multiparametric MRI.PMC12467337LHJJ24YG01LHJJ24YG13LHJJ24YG078247205362403473624015702025SF-YBXM-324Liu YZheng YHuang DFeng YLiu TChen CWei JfalsePHSP-Net: Personalized Habitat-Aware Deep Learning for Multi-Center Glioblastoma Survival Prediction Using Multiparametric MRI.<h4>Background</h4>Glioblastoma (GBM) is a highly aggressive and heterogeneous primary malignancy of the central nervous system, with a median overall survival (OS) of approximately 15 months. Achieving accurate and generalizable OS prediction across multi-center settings is essential for clinical application.<h4>Methods</h4>We propose a Personalized Habitat-aware Survival Prediction Network (PHSP-Net) that integrates multiparametric MRI with an adaptive habitat partitioning strategy. The network combines deep convolutional feature extraction and interpretable visualization modules to perform patient-specific subregional segmentation and survival prediction. A total of 1084 patients with histologically confirmed WHO grade IV GBM from four centers (UPENN-GBM, UCSF-PDGM, LUMIERE and TCGA-GBM2025-01-01T00:00:00Z2025 Sep2026-05-02T03:09:30.602Z2026-05-02T03:07:36.744ZS-EPMC124673374100722410.3390/bioengineering12090978