{"doi":"10.1101/2020.12.18.20248364","title":"Deep Learning to Estimate Cardiac Magnetic Resonance-Derived Left Ventricular Mass","abstract":"ABSTRACT Background Cardiac magnetic resonance (CMR) is the gold standard for left ventricular hypertrophy (LVH) diagnosis. CMR-derived LV mass can be estimated using proprietary algorithms (e.g., inlineVF), but their accuracy and availability may be limited. Objective To develop an open-source deep learning model to estimate CMR-derived LV mass. Methods Within participants of the UK Biobank prospective cohort undergoing CMR, we trained two convolutional neural networks to estimate LV mass. The first (ML4H reg ) performed regression informed by manually labeled LV mass (available in 5,065 individuals), while the second (ML4H seg ) performed LV segmentation informed by inlineVF contours. We compared ML4H reg , ML4H seg , and inlineVF against manually labeled LV mass within an independent holdout set using Pearson correlation and mean absolute error (MAE). We assessed associations between CMR-derived LVH and prevalent cardiovascular disease using logistic regression adjusted for age and sex. Results We generated CMR-derived LV mass estimates within 38,574 individuals. Among 891 individuals in the holdout set, ML4H seg reproduced manually labeled LV mass more accurately (r=0.864, 95% CI 0.847-0.880; MAE 10.41g, 95% CI 9.82-10.99) than ML4H reg (r=0.843, 95% CI 0.823-0.861; MAE 10.51, 95% CI 9.86-11.15, p=0.01) and inlineVF (r=0.795, 95% CI 0.770-0.818; MAE 14.30, 95% CI 13.46-11.01, p<0.01). LVH defined using ML4H seg demonstrated the strongest associations with hypertension (odds ratio 2.76, 95% CI 2.51-3.04), atrial fibrillation (1.75, 95% CI 1.37-2.20), and heart failure (4.53, 95% CI 3.16-6.33). Conclusions ML4H seg is an open-source deep learning model providing automated quantification of CMR-derived LV mass. Deep learning models characterizing cardiac structure may facilitate broad cardiovascular discovery.","journal":"medRxiv","year":2020,"id":125737,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.6169,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":236909,"name":"Sam Friedman","orcid":"0000-0002-0688-2169","position":1,"is_corresponding":false},{"id":902,"name":"James P. Pirruccello","orcid":"0000-0001-6088-4037","position":2,"is_corresponding":false},{"id":464102,"name":"Paolo Di Achille","orcid":"0000-0001-9256-0678","position":3,"is_corresponding":false},{"id":18141,"name":"Nathaniel Diamant","orcid":"0000-0002-1738-304X","position":4,"is_corresponding":false},{"id":274758,"name":"Christopher D. Anderson","orcid":"0000-0002-0053-2002","position":5,"is_corresponding":false},{"id":896,"name":"Patrick T. Ellinor","orcid":"0000-0002-2067-0533","position":6,"is_corresponding":false},{"id":552484,"name":"Puneet Batra","orcid":"0000-0001-6822-0593","position":7,"is_corresponding":false},{"id":892,"name":"Jennifer E. Ho","orcid":"0000-0002-7987-4768","position":8,"is_corresponding":false},{"id":27305,"name":"Anthony Philippakis","orcid":"0000-0001-6953-3794","position":9,"is_corresponding":false},{"id":1083,"name":"Steven A. Lubitz","orcid":"0000-0002-9599-4866","position":10,"is_corresponding":false},{"id":552483,"name":"Shaan Khurshid","orcid":"0000-0002-2840-4539","position":0,"is_corresponding":true}],"reference_count":20,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:15:19.482428Z","pmid":null,"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":[]}