{"doi":"10.1038/s41698-024-00790-9","title":"Novel radiogenomics approach to predict and characterize pneumonitis in stage III NSCLC","abstract":"Unresectable stage III NSCLC is now treated with chemoradiation (CRT) followed by immune checkpoint inhibitors (ICI). Pneumonitis, a common CRT complication, has heightened risk with ICI, potentially causing severe outcomes. Currently, there are no biomarkers to predict pneumonitis risk or differentiate between radiation-induced pneumonitis (RTP) and ICI-induced pneumonitis (IIP). This study analyzed 293 patients from two institutions, with 140 experiencing pneumonitis (RTP: 84, IIP: 56). Two models were developed: M1 predicted pneumonitis risk using seven radiomic features, achieving high accuracy across internal and external datasets (AUCs: 0.76 and 0.85). M2 differentiated RTP from IIP, with strong performance (AUCs: 0.86 and 0.81). Gene set enrichment analysis linked high pneumonitis risk to pathways such as ECM-receptor interaction and T-cell signaling, while high IIP risk correlated with MAPK and JAK-STAT pathways. Radiomic models show promise in early pneumonitis risk stratification and distinguishing pneumonitis types, potentially guiding personalized NSCLC treatment.","journal":"npj Precision Oncology","year":2024,"id":437538,"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":11,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9522,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":271231,"name":"Mohammadhadi Khorrami","orcid":"0000-0002-4141-8548","position":1,"is_corresponding":false},{"id":667225,"name":"Vidya Sankar Viswanathan","orcid":"0000-0003-1578-6248","position":2,"is_corresponding":false},{"id":861646,"name":"Khalid Jazieh","orcid":"0000-0002-3981-4293","position":3,"is_corresponding":false},{"id":1053062,"name":"Yifu Ding","orcid":"0000-0001-7779-7781","position":4,"is_corresponding":false},{"id":1247046,"name":"Pushkar Mutha","orcid":"0000-0002-5961-7131","position":5,"is_corresponding":false},{"id":841895,"name":"Kevin L. Stephans","orcid":"0000-0002-5554-8474","position":6,"is_corresponding":false},{"id":264728,"name":"Amit Gupta","orcid":"0000-0001-5345-6763","position":7,"is_corresponding":false},{"id":13914,"name":"Nathan A. Pennell","orcid":"0000-0002-1458-0064","position":8,"is_corresponding":false},{"id":264734,"name":"Pradnya D. Patil","orcid":"0000-0003-1304-3678","position":9,"is_corresponding":false},{"id":267372,"name":"Kristin Higgins","orcid":"0000-0003-1496-9878","position":10,"is_corresponding":false},{"id":237305,"name":"Anant Madabhushi","orcid":"0000-0002-5741-0399","position":11,"is_corresponding":false},{"id":428322,"name":"Lukas Delasos","orcid":"0000-0002-6409-2640","position":0,"is_corresponding":true}],"reference_count":51,"raw_metadata":null,"created_at":"2026-07-19T02:00:34.490087Z","pmid":"39719541","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":[]}