{"doi":"10.1101/2023.09.05.23295066","title":"Non-invasive estimation of pressure drop across aortic coarctations: validation of 0D and 3D computational models with <i>in vivo</i> measurements","abstract":"Abstract Purpose Blood pressure gradient ( Δ P) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of Δ P estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Methods Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N=17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. Δ P across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. Results The 0D simulations were extremely efficient ( ∼ 15 secs computation time) compared to 3D simulations ( ∼ 30 hrs computation time on a cluster). However, the 0D Δ P estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as Δ P ≥ 20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Conclusion Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.","journal":"medRxiv","year":2023,"id":397226,"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":0.9654,"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":689315,"name":"Martin R. Pfaller","orcid":"0000-0001-5760-2617","position":1,"is_corresponding":false},{"id":688105,"name":"Seraina A. Dual","orcid":"0000-0001-6867-8270","position":2,"is_corresponding":false},{"id":771793,"name":"Doff B. McElhinney","orcid":"0000-0001-7242-0934","position":3,"is_corresponding":false},{"id":338800,"name":"Daniel B. Ennis","orcid":"0000-0001-7435-1311","position":4,"is_corresponding":false},{"id":268892,"name":"Alison L. Marsden","orcid":"0000-0003-1902-171X","position":5,"is_corresponding":false},{"id":1172816,"name":"Priya J. Nair","orcid":"0000-0001-6326-9777","position":0,"is_corresponding":true}],"reference_count":30,"raw_metadata":null,"created_at":"2026-07-19T01:19:35.497854Z","pmid":"37732242","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":[]}