Ashar Asif, Andrew Iu Shearn, Mark S Turner, Maria V Ordoñez, Froso Sophocleous, Ana Mendez-Santos, Israel Valverde, Gianni D Angelini, Massimo Caputo, Mark Ck Hamilton, Giovanni Biglino
{"title":"通过3D打印和统计形状分析评估梗死后室间隔缺损。","authors":"Ashar Asif, Andrew Iu Shearn, Mark S Turner, Maria V Ordoñez, Froso Sophocleous, Ana Mendez-Santos, Israel Valverde, Gianni D Angelini, Massimo Caputo, Mark Ck Hamilton, Giovanni Biglino","doi":"10.2217/3dp-2022-0012","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Post-infarct ventricular septal defect (PIVSD) is a serious complication of myocardial infarction. We evaluated 3D-printing models in PIVSD clinical assessment and the feasibility of statistical shape modeling for morphological analysis of the defects.</p><p><strong>Methods: </strong>Models (n = 15) reconstructed from computed tomography data were evaluated by clinicians (n = 8). Statistical shape modeling was performed on 3D meshes to calculate the mean morphological configuration of the defects.</p><p><strong>Results: </strong>Clinicians' evaluation highlighted the models' utility in displaying defects for interventional/surgical planning, education/training and device development. However, models lack dynamic representation. Morphological analysis was feasible and revealed oval-shaped (n = 12) and complex channel-like (n = 3) defects.</p><p><strong>Conclusion: </strong>3D-PIVSD models can complement imaging data for teaching and procedural planning. Statistical shape modeling is feasible in this scenario.</p>","PeriodicalId":73578,"journal":{"name":"Journal of 3D printing in medicine","volume":"7 1","pages":"3DP3"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990116/pdf/","citationCount":"0","resultStr":"{\"title\":\"Assessment of post-infarct ventricular septal defects through 3D printing and statistical shape analysis.\",\"authors\":\"Ashar Asif, Andrew Iu Shearn, Mark S Turner, Maria V Ordoñez, Froso Sophocleous, Ana Mendez-Santos, Israel Valverde, Gianni D Angelini, Massimo Caputo, Mark Ck Hamilton, Giovanni Biglino\",\"doi\":\"10.2217/3dp-2022-0012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Post-infarct ventricular septal defect (PIVSD) is a serious complication of myocardial infarction. We evaluated 3D-printing models in PIVSD clinical assessment and the feasibility of statistical shape modeling for morphological analysis of the defects.</p><p><strong>Methods: </strong>Models (n = 15) reconstructed from computed tomography data were evaluated by clinicians (n = 8). Statistical shape modeling was performed on 3D meshes to calculate the mean morphological configuration of the defects.</p><p><strong>Results: </strong>Clinicians' evaluation highlighted the models' utility in displaying defects for interventional/surgical planning, education/training and device development. However, models lack dynamic representation. Morphological analysis was feasible and revealed oval-shaped (n = 12) and complex channel-like (n = 3) defects.</p><p><strong>Conclusion: </strong>3D-PIVSD models can complement imaging data for teaching and procedural planning. Statistical shape modeling is feasible in this scenario.</p>\",\"PeriodicalId\":73578,\"journal\":{\"name\":\"Journal of 3D printing in medicine\",\"volume\":\"7 1\",\"pages\":\"3DP3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990116/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of 3D printing in medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2217/3dp-2022-0012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of 3D printing in medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2217/3dp-2022-0012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Assessment of post-infarct ventricular septal defects through 3D printing and statistical shape analysis.
Background: Post-infarct ventricular septal defect (PIVSD) is a serious complication of myocardial infarction. We evaluated 3D-printing models in PIVSD clinical assessment and the feasibility of statistical shape modeling for morphological analysis of the defects.
Methods: Models (n = 15) reconstructed from computed tomography data were evaluated by clinicians (n = 8). Statistical shape modeling was performed on 3D meshes to calculate the mean morphological configuration of the defects.
Results: Clinicians' evaluation highlighted the models' utility in displaying defects for interventional/surgical planning, education/training and device development. However, models lack dynamic representation. Morphological analysis was feasible and revealed oval-shaped (n = 12) and complex channel-like (n = 3) defects.
Conclusion: 3D-PIVSD models can complement imaging data for teaching and procedural planning. Statistical shape modeling is feasible in this scenario.
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