ArticleEuropean radiology2020
Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis.
Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 44 citations in OpenAlex.
- Opportunities and challenges in application of VASARI features in neuro-oncology.Neuro-oncology practice · 2025Review
- CT-based radiomics model to predict platinum sensitivity in epithelial ovarian carcinoma: a multicentre study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- CT-based radiomic analysis for categorization of ovarian sex cord-stromal tumors and epithelial ovarian cancers.Abdominal radiology (New York) · 2024Article
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- Imaging of Peritoneal Metastases in Ovarian Cancer Using MDCT, MRI, and FDG PET/CT: A Systematic Review and Meta-Analysis.Cancers · 2024Review
- Survival time prediction in patients with high-grade serous ovarian cancer based onBMC cancer · 2024Article
- Radiogenomic landscape: Assessment of specific phagocytosis regulators in lower-grade gliomas.Experimental biology and medicine (Maywood, N.J.) · 2023Article
- Ovarian cancer beyond imaging: integration of AI and multiomics biomarkers.European radiology experimental · 2023Review
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- Ovarian imaging radiomics quality score assessment: an EuSoMII radiomics auditing group initiative.European radiology · 2023Article
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- The Evaluation Value of CT in the Efficacy of Neoadjuvant Chemotherapy in Ovarian Cancer Patients.Contrast media & molecular imaging · 2022Article
- Habitat radiomics analysis of pet/ct imaging in high-grade serous ovarian cancer: Application to Ki-67 status and progression-free survival.Frontiers in physiology · 2022Article
- Radioproteomics in patients with ovarian cancer.The British journal of radiology · 2021Review
- Radiomics in cervical and endometrial cancer.The British journal of radiology · 2021Review
- Radiomics and radiogenomics in ovarian cancer: a literature review.Abdominal radiology (New York) · 2021Review
- Radiogenomics Map Reveals the Landscape of m6A Methylation Modification Pattern in Bladder Cancer.Frontiers in immunology · 2021Article
- Integrated Multi-Tumor Radio-Genomic Marker of Outcomes in Patients with High Serous Ovarian Carcinoma.Cancers · 2020Article
- Integrative radiogenomics for virtual biopsy and treatment monitoring in ovarian cancer.Insights into imaging · 2020Review
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Authors and funding
18 authors at 10 institutions in 4 countries.
Funding
Abstract
objectivesTo investigate the association between CT imaging traits and texture metrics with proteomic data in patients with high-grade serous ovarian cancer (HGSOC).
methodsThis retrospective, hypothesis-generating study included 20 patients with HGSOC prior to primary cytoreductive surgery. Two readers independently assessed the contrast-enhanced computed tomography (CT) images and extracted 33 imaging traits, with a third reader adjudicating in the event of a disagreement. In addition, all sites of suspected HGSOC were manually segmented texture features which were computed from each tumor site. Three texture features that represented intra- and inter-site tumor heterogeneity were used for analysis. An integrated analysis of transcriptomic and proteomic data identified proteins with conserved expression between primary tumor sites and metastasis. Correlations between protein abundance and various CT imaging traits and texture features were assessed using the Kendall tau rank correlation coefficient and the Mann-Whitney U test, whereas the area under the receiver operating characteristic curve (AUC) was reported as a metric of the strength and the direction of the association. P values < 0.05 were considered significant.
resultsFour proteins were associated with CT-based imaging traits, with the strongest correlation observed between the CRIP2 protein and disease in the mesentery (p < 0.001, AUC = 0.05). The abundance of three proteins was associated with texture features that represented intra-and inter-site tumor heterogeneity, with the strongest negative correlation between the CKB protein and cluster dissimilarity (p = 0.047, τ = 0.326).
conclusionThis study provides the first insights into the potential associations between standard-of-care CT imaging traits and texture measures of intra- and inter-site heterogeneity, and the abundance of several proteins. KEY POINTS: • CT-based texture features of intra- and inter-site tumor heterogeneity correlate with the abundance of several proteins in patients with HGSOC. • CT imaging traits correlate with protein abundance in patients with HGSOC.
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