ArticleEuropean radiology2017
A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome.
Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06144762 (Precision Imaging for Early Detection and Targeted Treatment Monitoring in Pancreatic Cancer), which is not on this map. Cited by 76 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Precision Imaging for Early Detection and Targeted Treatment Monitoring in Pancreatic Cancer
Who cites it
76 citing papers in PubMed, 1 synthesis or guideline pooled it, 124 citations in OpenAlex.
- What Genetics Can Do for Oncological Imaging: A Systematic Review of the Genetic Validation Data Used in Radiomics Studies.International journal of molecular sciences · 2022Pooled it
- CT texture analysis in histological classification of epithelial ovarian carcinoma.European radiology · 2021Trial
- Objective responses to first-line neoadjuvant carboplatin-paclitaxel regimens for ovarian, fallopian tube, or primary peritoneal carcinoma (ICON8): post-hoc exploratory analysis of a randomised, phase 3 trial.The Lancet. Oncology · 2021Trial
- Spatiotemporal immune heterogeneity and precision immunotherapy for ovarian cancer.Clinical and translational medicine · 2026Review
- Preoperative prediction of cervical cancer recurrence using explainable MRI radiomics: a SHAP-Guided machine learning study.Abdominal radiology (New York) · 2026Article
- Role of Imaging Techniques in Ovarian Cancer Diagnosis: Current Approaches and Future Directions.Cancers · 2026Review
- Multimodal AI in high-grade serous ovarian cancer: integrated prediction and clinical decision-making.Frontiers in oncology · 2026Review
- A CT-based radiomics model for predicting progression-free survival in patients with epithelial ovarian cancer.BMC cancer · 2025Article
- Radiomics analysis of ultrasound images to discriminate between benign and malignant adnexal masses with solid morphology on ultrasound.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2025Observational
- Metastatic Lung Adenocarcinomas: Development and Evaluation of Radiomic-Based Methods to Measure Baseline Intra-Patient Inter-Tumor Lesion Heterogeneity.Journal of imaging informatics in medicine · 2025Article
- From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer.Military Medical Research · 2024Review
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- Radiomic-Based Approaches in the Multi-metastatic Setting: A Quantitative Review.medRxiv : the preprint server for health sciences · 2024Article
- Lymphadenectomy in clinically early epithelial ovarian cancer and survival analysis (LILAC): a Gynecologic Oncology Research Investigators Collaboration (GORILLA-3002) retrospective study.Journal of gynecologic oncology · 2024Article
- Survival time prediction in patients with high-grade serous ovarian cancer based onBMC cancer · 2024Article
- Contrast-enhanced CT radiomics for preoperative prediction of stage in epithelial ovarian cancer: a multicenter study.BMC cancer · 2024Article
- The Convergence of Radiology and Genomics: Advancing Breast Cancer Diagnosis with Radiogenomics.Cancers · 2024Review
- Identification of Precise 3D CT Radiomics for Habitat Computation by Machine Learning in Cancer.Radiology. Artificial intelligence · 2024Article
16 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
15 authors at 2 institutions in 4 countries.
Funding
Abstract
purposeTo evaluate the associations between clinical outcomes and radiomics-derived inter-site spatial heterogeneity metrics across multiple metastatic lesions on CT in patients with high-grade serous ovarian cancer (HGSOC).
methodsIRB-approved retrospective study of 38 HGSOC patients. All sites of suspected HGSOC involvement on preoperative CT were manually segmented. Gray-level correlation matrix-based textures were computed from each tumour site, and grouped into five clusters using a Gaussian Mixture Model. Pairwise inter-site similarities were computed, generating an inter-site similarity matrix (ISM). Inter-site texture heterogeneity metrics were computed from the ISM and compared to clinical outcomes.
resultsOf the 12 inter-site texture heterogeneity metrics evaluated, those capturing the differences in texture similarities across sites were associated with shorter overall survival (inter-site similarity entropy, similarity level cluster shade, and inter-site similarity level cluster prominence; p ≤ 0.05) and incomplete surgical resection (similarity level cluster shade, inter-site similarity level cluster prominence and inter-site cluster variance; p ≤ 0.05). Neither the total number of disease sites per patient nor the overall tumour volume per patient was associated with overall survival. Amplification of 19q12 involving cyclin E1 gene (CCNE1) predominantly occurred in patients with more heterogeneous inter-site textures.
conclusionQuantitative metrics non-invasively capturing spatial inter-site heterogeneity may predict outcomes in patients with HGSOC. KEY POINTS: • Calculating inter-site texture-based heterogeneity metrics was feasible • Metrics capturing texture similarities across HGSOC sites were associated with overall survival • Heterogeneity metrics were also associated with incomplete surgical resection of HGSOC.
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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.