Keywords: Tumors (Pre-Treatment), Tumor, Glioma,Tumor habitat,prognosis
Motivation: High-grade glioma (HGG) is a highly invasive neoplasm characterized by significant intra-tumoral spatial heterogeneity. However, the clinical relevance of the observed spatial and physical imaging characteristics remains unknown.
Goal(s): To identify tumor subregions and quantify their image-based habitat characteristics associated with survival time.
Approach: We retrospectively analyzed quantitative tumor habitat based on initial MRI scans in 2 groups (long-term and short-term survivals) of patients diagnosed with HGGs. Kmeans clustering, Univariate and multivariate logistic and survival analysis were used.
Results: The features of the high MK and low FLAIR habitat was most effective for predicting survival groups (AUC 0.91, Sensitivity 0.844, Specificity 0.867).
Impact: Tumor habitat is a novel method and It’s an earlier attempt to use habitats from diffusion and T1 based perfuison to predict the survival time of HGG. It has high prediction capabilities for prognosis.
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