{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["14(16)"],"submitter":["De Bari B"],"pubmed_abstract":["Background: We evaluated the value of pre-treatment positron-emission tomography−computed tomography (PET-CT)-based radiomic features in predicting the locoregional progression-free survival (LR-PFS) of patients with inoperable or unresectable oesophageal cancer. Material and Methods: Forty-six patients were included and 230 radiomic parameters were extracted. After a principal component analysis (PCA), we identified the more robust radiomic parameters, and we used them to develop a heatmap. Finally, we correlated these radiomic features with LR-PFS. Results: The median follow-up time was 17 months. The two-year LR-PFS and PFS rates were 35.9% (95% CI: 18.9−53.3) and 21.6% (95%CI: 10.0−36.2), respectively. After the correlation analysis, we identified 55 radiomic parameters that were inclu"],"journal":["Cancers"],"pagination":["4043"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9406583"],"repository":["biostudies-literature"],"pubmed_title":["Could 18-FDG PET-CT Radiomic Features Predict the Locoregional Progression-Free Survival in Inoperable or Unresectable Oesophageal Cancer?"],"pmcid":["PMC9406583"],"pubmed_authors":["De Bari B","Gatta R","Borg C","Mathieu P","Valentini V","Dinapoli N","Boulahdour H","Lefevre L","Boldrini L","Vernerey D","Henriques J","Falcoz A"],"additional_accession":[]},"is_claimable":false,"name":"Could 18-FDG PET-CT Radiomic Features Predict the Locoregional Progression-Free Survival in Inoperable or Unresectable Oesophageal Cancer?","description":"Background: We evaluated the value of pre-treatment positron-emission tomography−computed tomography (PET-CT)-based radiomic features in predicting the locoregional progression-free survival (LR-PFS) of patients with inoperable or unresectable oesophageal cancer. Material and Methods: Forty-six patients were included and 230 radiomic parameters were extracted. After a principal component analysis (PCA), we identified the more robust radiomic parameters, and we used them to develop a heatmap. Finally, we correlated these radiomic features with LR-PFS. Results: The median follow-up time was 17 months. The two-year LR-PFS and PFS rates were 35.9% (95% CI: 18.9−53.3) and 21.6% (95%CI: 10.0−36.2), respectively. After the correlation analysis, we identified 55 radiomic parameters that were inclu","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Aug","modification":"2026-04-08T04:04:19.89Z","creation":"2025-02-19T00:34:12.32Z"},"accession":"S-EPMC9406583","cross_references":{"pubmed":["36011035"],"doi":["10.3390/cancers14164043"]}}