{"doi":"10.3390/diagnostics13081391","title":"Baseline 18F-FDG PET/CT Radiomics in Classical Hodgkin’s Lymphoma: The Predictive Role of the Largest and the Hottest Lesions","abstract":"This study investigated the predictive role of baseline 18F-FDG PET/CT (bPET/CT) radiomics from two distinct target lesions in patients with classical Hodgkin’s lymphoma (cHL). cHL patients examined with bPET/CT and interim PET/CT between 2010 and 2019 were retrospectively included. Two bPET/CT target lesions were selected for radiomic feature extraction: Lesion_A, with the largest axial diameter, and Lesion_B, with the highest SUVmax. Deauville score at interim PET/CT (DS) and 24-month progression-free-survival (PFS) were recorded. Mann–Whitney test identified the most promising image features (p < 0.05) from both lesions with regards to DS and PFS; all possible radiomic bivariate models were then built through a logistic regression analysis and trained/tested with a cross-fold validation test. The best bivariate models were selected based on their mean area under curve (mAUC). A total of 227 cHL patients were included. The best models for DS prediction had 0.78 ± 0.05 maximum mAUC, with a predominant contribution of Lesion_A features to the combinations. The best models for 24-month PFS prediction reached 0.74 ± 0.12 mAUC and mainly depended on Lesion_B features. bFDG-PET/CT radiomic features from the largest and hottest lesions in patients with cHL may provide relevant information in terms of early response-to-treatment and prognosis, thus representing an earlier and stronger decision-making support for therapeutic strategies. External validations of the proposed model are planned.","journal":"Diagnostics","year":2023,"id":342534,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":14,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8027,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":103887,"name":"Roberto Gatta","orcid":"0000-0002-4716-9925","position":1,"is_corresponding":false},{"id":1079075,"name":"Elena Maiolo","orcid":"0000-0001-8956-7502","position":2,"is_corresponding":false},{"id":1079076,"name":"Marco De Summa","orcid":"0009-0000-5951-0177","position":3,"is_corresponding":false},{"id":103878,"name":"Luca Boldrini","orcid":"0000-0002-5631-1575","position":4,"is_corresponding":false},{"id":284209,"name":"Marius E. Mayerhoefer","orcid":"0000-0001-8786-8686","position":5,"is_corresponding":false},{"id":1079077,"name":"Stefan Hohaus","orcid":"0000-0002-5534-7197","position":6,"is_corresponding":false},{"id":336772,"name":"Lorenzo Nardo","orcid":"0000-0002-0266-2708","position":7,"is_corresponding":false},{"id":1079078,"name":"David Morland","orcid":"0000-0001-8738-4841","position":8,"is_corresponding":false},{"id":1079079,"name":"Salvatore Annunziata","orcid":"0000-0003-3241-1501","position":9,"is_corresponding":false},{"id":1079074,"name":"Elizabeth Katherine Anna Triumbari","orcid":"0000-0001-6932-2276","position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":null,"created_at":"2026-07-19T01:11:12.506815Z","pmid":"37189492","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}