{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T19:47:15Z","timestamp":1781552835628,"version":"3.54.5"},"reference-count":48,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T00:00:00Z","timestamp":1709769600000},"content-version":"vor","delay-in-days":6,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Hematological Oncology"],"published-print":{"date-parts":[[2024,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>To recognize patients at high risk of refractory disease, the identification of novel prognostic parameters improving stratification of newly diagnosed Hodgkin Lymphoma (HL) is still needed. This study investigates the potential value of metabolic and texture features, extracted from baseline 18F\u2010FDG Positron Emission Tomography\/Computed Tomography (PET) and Contrast\u2010Enhanced Computed Tomography scan (CECT), together with clinical data, in predicting first\u2010line therapy refractoriness (R) of classical HL (cHL) with mediastinal bulk involvement. We reviewed 69 cHL patients who underwent staging PET and CECT. Lesion segmentation and texture parameter extraction were performed using the freeware software LIFEx 6.3. The prognostic significance of clinical and imaging features was evaluated in relation to the development of refractory disease. Receiver operating characteristic curve, Cox proportional hazard regression and Kaplan\u2010Meier analyses were performed to examine the potential independent predictors and to evaluate their prognostic value. Among clinical characteristics, only stage according to the German Hodgkin Group (GHSG) classification system significantly differed between R and not\u2010R. Among CECT variables, only parameters derived from second order matrices (gray\u2010level co\u2010occurrence matrix (GLCM) and gray\u2010level run length matrix (GLRLM) demonstrated significant prognostic power. Among PET variables, SUVmean, several variables derived from first (histograms, shape), and second order analyses (GLCM, GLRLM, NGLDM) exhibited significant predictive power. Such variables obtained accuracies greater than 70% at receiver operating characteristic analysis and their PFS curves resulted statistically significant in predicting refractoriness. At multivariate analysis, only HISTO_EntropyPET extracted from PET (HISTO_Entropy<jats:sub>PET<\/jats:sub>) and GHSG stage resulted as significant independent predictors. Their combination identified 4 patient groups with significantly different PFS curves, with worst prognosis in patients with higher HISTO_Entropy<jats:sub>PET<\/jats:sub> values, regardless of the stage. Imaging radiomics may provide a reference for prognostic evaluation of patients with mediastinal bulky cHL. The best prognostic value in the prediction of R versus not\u2010R disease was reached by combining HISTO_Entropy<jats:sub>PET<\/jats:sub> with GHSG stage.<\/jats:p>","DOI":"10.1002\/hon.3261","type":"journal-article","created":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T01:30:07Z","timestamp":1709861407000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Texture analysis of 18F\u2010FDG PET\/CT and CECT: Prediction of refractoriness of Hodgkin lymphoma with mediastinal bulk involvement"],"prefix":"10.1002","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9370-102X","authenticated-orcid":false,"given":"Elisabetta M.","family":"Abenavoli","sequence":"first","affiliation":[{"name":"Nuclear Medicine Unit Department of Experimental and Clinical Biomedical Sciences \u2018Mario Serio\u2019 University of Florence  Florence 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