ArticleAnnals of clinical and translational neurology2024
Diffusion kurtosis imaging-based habitat analysis identifies high-risk molecular subtypes and heterogeneity matching in diffuse gliomas.
Article in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Integrating Multimodal MRI Habitat and Transformer-Based Pathomics to Predict High-Risk Molecular Subtypes and Explore Biological Mechanisms in Adult Diffuse Gliomas.CNS neuroscience & therapeutics · 2026Article
- Advancing precision risk stratification in adult diffuse gliomas through DSC-MRI-based habitat analysis.BMC medical imaging · 2026Article
- Prediction of Ki-67 expression in hepatocellular carcinoma: a dual-center study based on T2-weighted imaging habitat analysis.Radiology and oncology · 2026Article
- Development of a Prediction Model for Progression Risk in High-Grade Gliomas Based on Habitat Radiomics and Pathomics.Annals of clinical and translational neurology · 2026Article
- AI-derived prognostic model identifies high-risk gene signatures in pediatric gliomas.Frontiers in immunology · 2026Article
- Pre-treatment CEMRI habitat radiomics and deep learning for noninvasive prediction of the VETC pattern in hepatocellular carcinoma: an exploratory radiogenomic analysis.Frontiers in oncology · 2026Article
- Parameter-driven habitat imaging based on intravoxel incoherent motion MRI for preoperative prediction of muscle invasion in bladder cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Integrating deep learning and radiomics for preoperative glioma grading using multi-center MRI data.Scientific reports · 2025Article
- Development and validation of radiopathomics models for predicting molecular subtypes and WHO grades in adult-type diffuse gliomas: a multicenter study.Journal of translational medicine · 2025Article
- Preoperative prediction of WHO/ISUP grade of ccRCC using intratumoral and peritumoral habitat imaging: multicenter study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Contrast-enhanced MRI-based intratumoral heterogeneity assessment for predicting lymph node metastasis in resectable pancreatic ductal adenocarcinoma.Insights into imaging · 2025Article
- MRI transformer deep learning and radiomics for predicting IDH wild type TERT promoter mutant gliomas.NPJ precision oncology · 2025Article
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10 authors.
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Abstract
objectiveHigh-risk types of diffuse gliomas in adults include isocitrate dehydrogenase (IDH) wild-type glioblastomas and grade 4 astrocytomas. Achieving noninvasive prediction of high-risk molecular subtypes of gliomas is important for personalized and precise diagnosis and treatment.
methodsWe retrospectively collected data from 116 patients diagnosed with adult diffuse gliomas. Multiple high-risk molecular markers were tested, and various habitat models and whole-tumor models were constructed based on preoperative routine and diffusion kurtosis imaging (DKI) sequences to predict high-risk molecular subtypes of gliomas. Feature selection and model construction utilized Least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM). Finally, the Wilcoxon rank-sum test was employed to explore the correlation between habitat quantitative features (intra-tumor heterogeneity score,ITH score) and heterogeneity, as well as high-risk molecular subtypes.
resultsThe results showed that the habitat analysis model based on DKI performed remarkably well (with AUC values reaching 0.977 and 0.902 in the training and test sets, respectively). The model's performance was further enhanced when combined with clinical variables. (The AUC values were 0.994 and 0.920, respectively.) Additionally, we found a close correlation between ITH score and heterogeneity, with statistically significant differences observed between high-risk and non-high-risk molecular subtypes.
interpretationThe habitat model based on DKI is an ideal means for preoperatively predicting high-risk molecular subtypes of gliomas, holding significant value for noninvasively alerting malignant gliomas and those with malignant transformation potential.
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