The State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Shaanxi, China.
Institute of 3D Printing, Beijing City University, Beijing, China.
Med Biol Eng Comput. 2022 Oct;60(10):3029-3040. doi: 10.1007/s11517-022-02660-7. Epub 2022 Sep 2.
Accurate diagnosis and surgical selection of the double-outlet right ventricle (DORV) is both critical and difficult. Virtual models and three-dimensional (3D) printing have been used to provide morphological copies to doctors as reference. However, the existing methods have shortcomings in visualization of the surgical results, optimal surgical design, and accurate surgical scheme measurements. To overcome this problem, we performed surgical predictions by designing the intraventricular baffle and ventricular septal defect patch to evaluate surgical options and using 3D printing to guide the trimming of the baffle or patch. A complete set of processes including scanning, modeling, designing, 3D printing, and guiding the trimming of the baffle for the diagnosis and surgical planning of DORV was established. Six cases were used to evaluate the feasibility of this method. The average rate of misdiagnosis of the six cases by computed tomography and echocardiography was 42.5%, which was reduced to 4.6% when the diagnosis was established using the virtual models and 3D printing as auxiliary tools. The approach effectively improved diagnostic accuracy, guided the operation, and simplified the process of patch trimming. The proposed method can thus be used for improving the surgical simulation and guiding of the DORV surgery.
准确诊断和选择外科手术方法对双出口右心室（DORV）至关重要，但也极具挑战性。虚拟模型和三维（3D）打印已被用于为医生提供形态学副本作为参考。然而，现有的方法在可视化手术结果、优化手术设计和准确手术方案测量方面存在不足。为了克服这个问题，我们通过设计心室内隔板和室间隔缺损补片来进行手术预测，以评估手术方案，并使用 3D 打印来指导隔板或补片的修剪。建立了一套完整的流程，包括扫描、建模、设计、3D 打印和指导隔板修剪，用于 DORV 的诊断和手术规划。使用该方法评估了 6 例病例的可行性。6 例病例中，计算机断层扫描和超声心动图的平均误诊率为 42.5%，而使用虚拟模型和 3D 打印作为辅助工具进行诊断时，误诊率降低至 4.6%。该方法有效提高了诊断准确性，指导了手术，并简化了补片修剪过程。因此，该方法可用于改善 DORV 手术的模拟和指导。
