ArticleEuropean journal of nuclear medicine and molecular imaging2026
Predicting the early response to neoadjuvant chemotherapy in high-grade serous ovarian cancer by intratumoral habitat heterogeneity based on
Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive performance of MRI and CT radiomics in predicting the response to induction chemotherapy in nasopharyngeal carcinoma: a network meta-analysis.Frontiers in oncology · 2025Pooled it
- Heterogeneity Analyzed by CT-Based Habitat Analysis for Clinical Management of Cancers: A Narrative Review.The Kaohsiung journal of medical sciences · 2026Review
- Development and validation of a CT-based habitat radiomics model for predicting pathological grading in non-small cell lung cancer.Frontiers in medicine · 2026Article
- Electroacupuncture modulates electroencephalographic microstate dynamics to alleviate chronic insomnia: a machine learning approach for predicting individual treatment response.Frontiers in neurologyArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
objectiveTo explore the predictive value of intratumoral habitat heterogeneity for the early therapeutic response to neoadjuvant chemotherapy (NACT) in patients with high-grade serous ovarian cancer (HGSOC). MATERIALS AND
methodsA total of 258 patients with HGSOC receiving [
resultsThe automatic segmentation model had a Dice coefficient of 0.82 and showed excellent performance in the validation cohort. The predictive efficacy of the subregion model in the test dataset was significantly better than that of the traditional model [Area Under the Curve (AUC): 0.83 vs. 0.71, P = 0.007. There was no statistically significant difference between the union model and the subregion model (AUC: 0.89 vs. 0.83, P = 0.077). Radiomics features involved in the modeling were significantly correlated with Ki67 before NACT (pre-Ki67) and the change value of Ki67 before NACT-after IDS(ΔKi67) respectively (P < 0.05).
conclusionThe PET/CT radiomics model based on habitat analysis can effectively predict the early response to NACT in patients with HGSOC, which can be explained by the tumor proliferative activity and provide reliable imaging biomarkers for individualized treatment decisions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.