Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve
BackgroundObstruction within the left anterior descending coronary artery (LAD) is prevalent, serving as a prominent and independent predictor of mortality. Invasive Fractional flow reserve (FFR) is the gold standard for Coronary Artery Disease risk assessment. Despite advances in computational and...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2025.1438253/full |
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| author | Arshia Eskandari Sara Malek Alireza Jabbari Kian Javari Nima Rahmati Behrad Nikbakhtian Bahram Mohebbi Seyed Ehsan Parhizgar Mona Alimohammadi |
| author_facet | Arshia Eskandari Sara Malek Alireza Jabbari Kian Javari Nima Rahmati Behrad Nikbakhtian Bahram Mohebbi Seyed Ehsan Parhizgar Mona Alimohammadi |
| author_sort | Arshia Eskandari |
| collection | DOAJ |
| description | BackgroundObstruction within the left anterior descending coronary artery (LAD) is prevalent, serving as a prominent and independent predictor of mortality. Invasive Fractional flow reserve (FFR) is the gold standard for Coronary Artery Disease risk assessment. Despite advances in computational and imaging techniques, no definitive methodology currently assures clinicians of reliable, non-invasive strategies for future planning.MethodThe present research encompassed a cohort of 150 participants who were admitted to the Rajaie Cardiovascular, Medical, and Research Center. The method includes a three-dimensional geometry reconstruction, computational fluid dynamics simulations, and methodology optimization for the computation time. Four patients are analyzed within this study to showcase the proposed methodology. The invasive FFR results reported by the clinic have validated the optimized model.ResultsThe computational FFR data derived from all methodologies are compared with those reported by the clinic for each case. The chosen methodology has yielded virtual FFR values that exhibit remarkable proximity to the clinically reported patient-specific FFR values, with the MSE of 6.186e-7 and R2 of 0.99 (p = 0.00434).ConclusionThis approach has shown reliable results for all 150 patients. The results are both computationally and clinically user-friendly, with the accumulative pre and post-processing time of 15 min on a desktop computer (Intel i7 processor, 16 GB RAM). The proposed methodology has the potential to significantly assist clinicians with diagnosis. |
| format | Article |
| id | doaj-art-e1fb87fa30f347ccb313ac3319844d40 |
| institution | Kabale University |
| issn | 2296-4185 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj-art-e1fb87fa30f347ccb313ac3319844d402025-01-27T06:41:00ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852025-01-011310.3389/fbioe.2025.14382531438253Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserveArshia Eskandari0Sara Malek1Alireza Jabbari2Kian Javari3Nima Rahmati4Behrad Nikbakhtian5Bahram Mohebbi6Seyed Ehsan Parhizgar7Mona Alimohammadi8Department of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, IranDepartment of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, IranDepartment of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, IranDepartment of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, IranDepartment of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, IranDepartment of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, IranRajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, IranRajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, IranDepartment of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, IranBackgroundObstruction within the left anterior descending coronary artery (LAD) is prevalent, serving as a prominent and independent predictor of mortality. Invasive Fractional flow reserve (FFR) is the gold standard for Coronary Artery Disease risk assessment. Despite advances in computational and imaging techniques, no definitive methodology currently assures clinicians of reliable, non-invasive strategies for future planning.MethodThe present research encompassed a cohort of 150 participants who were admitted to the Rajaie Cardiovascular, Medical, and Research Center. The method includes a three-dimensional geometry reconstruction, computational fluid dynamics simulations, and methodology optimization for the computation time. Four patients are analyzed within this study to showcase the proposed methodology. The invasive FFR results reported by the clinic have validated the optimized model.ResultsThe computational FFR data derived from all methodologies are compared with those reported by the clinic for each case. The chosen methodology has yielded virtual FFR values that exhibit remarkable proximity to the clinically reported patient-specific FFR values, with the MSE of 6.186e-7 and R2 of 0.99 (p = 0.00434).ConclusionThis approach has shown reliable results for all 150 patients. The results are both computationally and clinically user-friendly, with the accumulative pre and post-processing time of 15 min on a desktop computer (Intel i7 processor, 16 GB RAM). The proposed methodology has the potential to significantly assist clinicians with diagnosis.https://www.frontiersin.org/articles/10.3389/fbioe.2025.1438253/fullcoronary artery diseasefractional flow reservemyocardial infarctionnoninvasive imagingcomputational fluid dynamicsvirtual surgery |
| spellingShingle | Arshia Eskandari Sara Malek Alireza Jabbari Kian Javari Nima Rahmati Behrad Nikbakhtian Bahram Mohebbi Seyed Ehsan Parhizgar Mona Alimohammadi Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve Frontiers in Bioengineering and Biotechnology coronary artery disease fractional flow reserve myocardial infarction noninvasive imaging computational fluid dynamics virtual surgery |
| title | Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve |
| title_full | Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve |
| title_fullStr | Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve |
| title_full_unstemmed | Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve |
| title_short | Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve |
| title_sort | enhancing cardiac assessments accurate and efficient prediction of quantitative fractional flow reserve |
| topic | coronary artery disease fractional flow reserve myocardial infarction noninvasive imaging computational fluid dynamics virtual surgery |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2025.1438253/full |
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