{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:37:28Z","timestamp":1786977448333,"version":"build-2736575974"},"reference-count":39,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T00:00:00Z","timestamp":1770249600000},"content-version":"vor","delay-in-days":4,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Numer Methods Biomed Eng"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Existing lumped arterial stenosis models struggle to accurately capture the pressure and flow relationship of complex lesion morphologies, thereby limiting their ability to accurately evaluate lesions. To overcome these limitations, we introduce a geometry\u2010informed, data\u2010driven lumped stenosis model that incorporates realistic lesion shapes using statistical shape modeling (SSM). By generating a large dataset of synthetic coronary stenoses, hence focusing on epicardial lesions, and evaluating them through high\u2010fidelity 3D computational fluid dynamics (CFD), we derived reference pressure drops across a diverse range of lesion geometries and flow regimes. These CFD\u2010derived pressures and flows, along with their corresponding shape coefficients, were used to train a lumped parameter model capable of rapidly estimating trans\u2010lesional pressure drops. Remarkably, only five shape modes were necessary to effectively describe the geometric variability, underscoring the efficiency of the approach. Compared to a conventional lumped model, our approach significantly improved pressure drop prediction accuracy, especially in the case of irregular stenosis morphologies. Integration of the new data\u2010driven lumped stenosis model within a 1D pulse wave propagation framework was also successful, aligning simulated pressure and flow waveforms much closer with high\u2010fidelity CFD\u2010coupled results. In turn, the estimation of the fractional flow reserve, a clinically validated index of lesion\u2010specific ischemia, also improved by 18% compared to a conventional lumped model. Although only validated using synthetic lesion data, the model's architecture allows easy integration of additional shape features and lesion\u2010specific parameters, paving the way for future validation on patient\u2010derived geometries.<\/jats:p>","DOI":"10.1002\/cnm.70138","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T04:38:13Z","timestamp":1770352693000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Statistical Shape Modeling Approach for the Derivation of a Data\u2010Driven Geometry\u2010Aware Lumped Arterial Stenosis Model"],"prefix":"10.1002","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1764-1536","authenticated-orcid":false,"given":"P. L. J.","family":"Hilhorst","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering Eindhoven University of Technology  Eindhoven the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1011-6627","authenticated-orcid":false,"given":"S. C. F. P. M.","family":"Verstraeten","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Eindhoven University of Technology  Eindhoven the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1393-8236","authenticated-orcid":false,"given":"K.","family":"Zaj\u0105c","sequence":"additional","affiliation":[{"name":"Sano Centre for Computational Medicine  Krak\u00f3w Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9666-5925","authenticated-orcid":false,"given":"R.","family":"Ganesan","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Eindhoven University of Technology  Eindhoven the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5006-0111","authenticated-orcid":false,"given":"M.","family":"van 't Veer","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Eindhoven University of Technology  Eindhoven the Netherlands"},{"name":"Department of Cardiology Catharina Hospital  Eindhoven the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4084-2064","authenticated-orcid":false,"given":"F. N.","family":"van de Vosse","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Eindhoven University of Technology  Eindhoven the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0779-4785","authenticated-orcid":false,"given":"W.","family":"Huberts","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Eindhoven University of Technology  Eindhoven the Netherlands"},{"name":"Computational Science Lab, Faculty of Science Institute for Informatics, University of Amsterdam  Amsterdam the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,2,5]]},"reference":[{"key":"e_1_2_11_2_1","article-title":"Towards Patient\u2010Specific Modeling of Coronary Hemodynamics in Healthy and Diseased State","volume":"2013","author":"Horst A.","year":"2013","journal-title":"Computational and Mathematical Methods in Medicine"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0022112007005344"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9290(92)90060-E"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1115\/1.4042184"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9290(73)90099-7"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9290(73)90012-2"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa0807611"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1115\/1.2891404"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0266727"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbiomech.2019.05.030"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1161\/01.CIR.80.3.636"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/cnm.3518"},{"key":"e_1_2_11_14_1","first-page":"464","article-title":"Generation of Synthetic Aortic Valve Stenosis Geometries for In Silico Trials","volume":"40","author":"Verstraeten S.","year":"2023","journal-title":"International Journal for Numerical Methods in Biomedical Engineering"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13239-023-00679-x"},{"issue":"4","key":"e_1_2_11_16_1","first-page":"784","article-title":"On the Distribution of Points in a Cube and the Approximate Evaluation of Integrals","volume":"7","author":"Sobol' I. M.","year":"1967","journal-title":"Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.06.043"},{"key":"e_1_2_11_18_1","volume-title":"Springer Series in Statistics","author":"Jolliffe I. T.","year":"2002"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/cnm.70126"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.1098\/rsta.2024.0230"},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.1253\/circj.CJ-16-0623"},{"key":"e_1_2_11_22_1","first-page":"10","article-title":"Normal Values of Thermodilution\u2010Derived Absolute Coronary Blood Flow and Microvascular Resistance in Humans","volume":"17","author":"Fournier S.","year":"2020","journal-title":"EuroIntervention: Journal OF EuroPCR in Collaboration With the Working Group on Interventional Cardiology of the European Society of Cardiology"},{"key":"e_1_2_11_23_1","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehv626"},{"key":"e_1_2_11_24_1","volume-title":"Adaptive Computation and Machine Learning","author":"Rasmussen C. E.","year":"2006"},{"key":"e_1_2_11_25_1","doi-asserted-by":"crossref","unstructured":"T.Akiba S.Sano T.Yanase T.Ohta andM.Koyama \u201cOptuna: A Next\u2010Generation Hyperparameter Optimization Framework \u201d2019 InProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.","DOI":"10.1145\/3292500.3330701"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.envsoft.2013.12.008"},{"key":"e_1_2_11_27_1","doi-asserted-by":"crossref","unstructured":"L.NuytsandJ.Davis \u201cThe When and How of Target Variable Transformations \u201d2025.","DOI":"10.1007\/978-3-031-91398-3_9"},{"key":"e_1_2_11_28_1","volume-title":"Cardiovascular Physiology Concepts","author":"Klabunde R. E.","year":"2022"},{"key":"e_1_2_11_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-36021-3_2"},{"key":"e_1_2_11_30_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12938-023-01121-y"},{"key":"e_1_2_11_31_1","doi-asserted-by":"publisher","DOI":"10.1152\/japplphysiol.00752.2015"},{"key":"e_1_2_11_32_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1011055"},{"key":"e_1_2_11_33_1","doi-asserted-by":"publisher","DOI":"10.1017\/jfm.2015.286"},{"key":"e_1_2_11_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10439-010-0083-6"},{"key":"e_1_2_11_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12572-016-0161-6"},{"key":"e_1_2_11_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbiomech.2014.03.028"},{"key":"e_1_2_11_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2024.109420"},{"key":"e_1_2_11_38_1","first-page":"74","volume-title":"Advances in Neural Networks","author":"Chen Z.","year":"2020"},{"key":"e_1_2_11_39_1","doi-asserted-by":"publisher","DOI":"10.3389\/fbioe.2023.1089113"},{"key":"e_1_2_11_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2012.6235797"}],"container-title":["International Journal for Numerical Methods in Biomedical Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cnm.70138","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/cnm.70138","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cnm.70138","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T23:30:02Z","timestamp":1773012602000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/cnm.70138"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":39,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["10.1002\/cnm.70138"],"URL":"https:\/\/doi.org\/10.1002\/cnm.70138","archive":["Portico"],"relation":{},"ISSN":["2040-7939","2040-7947"],"issn-type":[{"value":"2040-7939","type":"print"},{"value":"2040-7947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2]]},"assertion":[{"value":"2025-07-25","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-02","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-05","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70138"}}