{"doi":"10.1016/j.jchf.2025.102753","title":"A Novel Computational Pipeline for Acquiring Pressure-Volume Hemodynamics of the Right Ventricle in Pulmonary Hypertension","abstract":"BACKGROUND: Load-independent indices of right ventricular (RV) dysfunction aid in the prognosis of patients with pulmonary hypertension (PH), but acquisition of these indices remains difficult. Simpler image-based tools could bring these metrics to everyday practice. OBJECTIVES: This study sought to develop a novel, artificial intelligence-based pipeline that estimates load-independent RV functional indices using a pressure-time waveform and stroke volume from clinical right-sided heart catheterization. METHODS: Clinical data and pressure-volume-time data were collected from 76 patients referred for right-sided heart catheterization for known or suspected PH from 3 centers. A computational pipeline was developed to determine the RV pressure-volume loop and extract load-independent RV indices using computer vision image processing and single-beat analysis. Agreement with gold standard single-beat analysis and prognostic value were evaluated. RESULTS: Strong concordance was observed between both methods for end-systolic elastance (Ees: R = 0.96; concordance correlation coefficient [CCC] = 0.58), effective arterial elastance (Ea: R = 0.97; CCC = 0.88), end-diastolic elastance (Eed: R = 0.87; CCC = 0.47), and Ees/Ea ratio (R = 0.93; CCC = 0.71) in both the validation and external cohorts. Prognostic analyses showed that calculated Ea (HR: 2.09; 95% CI: 1.04-4.20) and Ees/Ea (HR: 0.27; 95% CI: 0.08-0.87) were significant predictors of clinical outcomes. Cluster analysis using single-beat indices identified 2 RV subphenotypes with distinct hemodynamic features that were more predictive of poor outcomes than analysis using standard clinical features. CONCLUSIONS: Study investigators have developed a novel computational pipeline that digitizes and generates single-beat estimates of RV-pulmonary arterial coupling from an image of the RV pressure waveform and stroke volume. Its output correlates with single-beat methods and predicts clinical outcomes.","journal":"JACC Heart Failure","year":2025,"id":529223,"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":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9476,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":906195,"name":"Paul J. Scheel","orcid":"0000-0003-4268-516X","position":1,"is_corresponding":false},{"id":1408533,"name":"Maggie Montovano","orcid":null,"position":2,"is_corresponding":false},{"id":1048949,"name":"Milan Kaushik","orcid":"0000-0002-1860-5978","position":3,"is_corresponding":false},{"id":1097208,"name":"Cole Buchanan","orcid":null,"position":4,"is_corresponding":false},{"id":1269431,"name":"Samuel H. Friedman","orcid":"0000-0002-2301-1103","position":5,"is_corresponding":false},{"id":292471,"name":"Rebecca Vanderpool","orcid":"0000-0001-6038-0568","position":6,"is_corresponding":false},{"id":1408012,"name":"Tess Allan","orcid":"0000-0002-3384-1135","position":7,"is_corresponding":false},{"id":353424,"name":"Mohammed Aslam","orcid":"0000-0003-4560-8661","position":8,"is_corresponding":false},{"id":235992,"name":"Ryan J. Tedford","orcid":"0000-0001-9045-7722","position":9,"is_corresponding":false},{"id":536160,"name":"Monica Mukherjee","orcid":"0000-0001-6088-0773","position":10,"is_corresponding":false},{"id":1297880,"name":"Paul M. Hassoun","orcid":"0000-0003-4264-6435","position":11,"is_corresponding":false},{"id":449495,"name":"Vivek Jani","orcid":"0000-0002-3811-4973","position":12,"is_corresponding":false},{"id":683565,"name":"Steven Hsu","orcid":"0000-0002-8384-2638","position":13,"is_corresponding":false},{"id":1408011,"name":"Gyeongtae Moon","orcid":"0000-0002-4067-3627","position":0,"is_corresponding":true}],"reference_count":43,"raw_metadata":null,"created_at":"2026-07-19T02:50:56.971987Z","pmid":"41171248","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":[]}