Fraunhofer Institute for Medical Image Computing - MEVIS, Am Fallturm 1, 28359, Bremen, Germany.
Charité - University Medicine Berlin, Berlin, Germany.
Int J Comput Assist Radiol Surg. 2019 Feb;14(2):357-371. doi: 10.1007/s11548-018-1868-6. Epub 2018 Oct 6.
Various options are available for the treatment of mitral valve insufficiency, including reconstructive approaches such as annulus correction through ring implants. The correct choice of general therapy and implant is relevant for an optimal outcome. Additional to guidelines, decision support systems (DSS) can provide decision aid by means of virtual intervention planning and predictive simulations. Our approach on virtual downsizing is one of the virtual intervention tools that are part of the DSS workflow. It allows for emulating a ring implantation based on patient-specific lumen geometry and vendor-specific implants.
Our approach is fully automatic and relies on a lumen mask and an annulus contour as inputs. Both are acquired from previous DSS workflow steps. A virtual surface- and contour-based model of a vendor-specific ring design (26-40 mm) is generated. For each case, the ring geometry is positioned with respect to the original, patient-specific annulus and additional anatomical landmarks. The lumen mesh is parameterized to allow for a vertex-based deformation with respect to the user-defined annulus. Derived from post-interventional observations, specific deformation schemes are applied to atrium and ventricle and the lumen mesh is altered with respect to the ring location.
For quantitative evaluation, the surface distance between the deformed lumen mesh and segmented post-operative echo lumen close to the annulus was computed for 11 datasets. The results indicate a good agreement. An arbitrary subset of six datasets was used for a qualitative evaluation of the complete lumen. Two domain experts compared the deformed lumen mesh with post-interventional echo images. All deformations were deemed plausible.
Our approach on virtual downsizing allows for an automatic creation of plausible lumen deformations. As it takes only a few seconds to generate results, it can be added to a virtual intervention toolset without unnecessarily increasing the pipeline complexity.
二尖瓣关闭不全的治疗方法有多种选择,包括通过环植入物进行环矫正等重建方法。选择合适的综合治疗和植入物对于获得最佳效果至关重要。除了指南外,决策支持系统 (DSS) 还可以通过虚拟干预规划和预测模拟提供决策辅助。我们的虚拟缩小方法是 DSS 工作流程中虚拟干预工具之一。它允许根据患者特定的管腔几何形状和供应商特定的植入物模拟环植入。
我们的方法是全自动的,依赖于管腔蒙版和环轮廓作为输入。两者都是从前一个 DSS 工作流程步骤中获得的。生成供应商特定环设计(26-40 毫米)的虚拟基于表面和基于轮廓的模型。对于每个病例,根据原始患者特定的环和附加解剖学标记定位环几何形状。管腔网格进行参数化,以便根据用户定义的环进行基于顶点的变形。根据介入后的观察结果,应用特定的变形方案到心房和心室,并相对于环位置改变管腔网格。
对于定量评估,计算了 11 个数据集上变形管腔网格与接近环的术后回声管腔之间的表面距离。结果表明吻合度良好。使用六个数据集的任意子集对完整管腔进行定性评估。两位领域专家将变形的管腔网格与介入后的回声图像进行比较。所有变形都被认为是合理的。
我们的虚拟缩小方法允许自动创建合理的管腔变形。由于生成结果只需要几秒钟,因此可以将其添加到虚拟干预工具集中,而不会不必要地增加管道的复杂性。