Assessment of post-infarct ventricular septal defects through 3D printing and statistical shape analysis.

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
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Abstract

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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通过3D打印和统计形状分析评估梗死后室间隔缺损。
背景:梗死后室间隔缺损(PIVSD)是心肌梗死的严重并发症。我们评估了3d打印模型在PIVSD临床评估中的应用,以及统计形状建模用于缺陷形态学分析的可行性。方法:临床医生对计算机断层数据重建的模型(n = 15)进行评估(n = 8)。在三维网格上进行统计形状建模,计算缺陷的平均形态构型。结果:临床医生的评价突出了模型在显示介入/手术计划、教育/培训和设备开发缺陷方面的效用。然而,模型缺乏动态表示。形态学分析是可行的,发现椭圆形(n = 12)和复杂的沟道状(n = 3)缺陷。结论:3D-PIVSD模型可作为影像资料的补充,为教学和手术规划提供依据。统计形状建模在这种情况下是可行的。
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