Department of Industrial Engineering, University of Trento, Via Sommarive, 9, 38123, Trento, Italy; Department of Physics, University of Trento, Via Sommarive, 14, 38123, Trento, Italy.
Department of Neurosciences, School of Dentistry, University of Padua, Via Giustiniani, 5, 35128, Padua, Italy.
Comput Biol Med. 2019 Nov;114:103435. doi: 10.1016/j.compbiomed.2019.103435. Epub 2019 Sep 5.
Intraoral autologous bone grafting represents a preferential choice for alveolar reconstruction prior to dental implant placement. Bone block harvesting guided by a computer-planned lithographic template is a novel and promising technique for optimizing the volume of harvested material, while controlling the osteotomy 3D position with respect to delicate anatomical structures. We provide a quantitative framework to non-invasively estimate the accuracy of this technique. In the proposed framework, the planned osteotomy geometry was compared to the real outcome of the procedure, obtained by segmentation of post-procedural cone beam computed tomography data. The comparison required the rigid registration between pre and post-procedural mandibular models, which was automatically accomplished by minimizing the sum of squared distances via a stochastic multi-trial iterative closest point algorithm. Bone harvesting accuracy was quantified by calculating a set of angular and displacement errors between the planned and real planes which characterized the excision block. The application of the framework to four cases showed its capability to quantify the tolerance associated with computer-guided bone harvesting techniques with submillimetric accuracy (<0.4 mm), within the limits of native image resolution. The validation methodology proved suitable for defining the safety margins of osteotomy surgical planning.
口腔自体骨移植是牙种植前牙槽骨重建的首选方法。计算机规划的光刻模板引导的骨块采集是一种优化采集材料体积的新技术,同时可以控制相对于精细解剖结构的骨切开术 3D 位置。我们提供了一个定量框架来非侵入性地估计该技术的准确性。在提出的框架中,将计划的骨切开术几何形状与通过对术后锥形束计算机断层扫描数据进行分割获得的实际手术结果进行比较。比较需要通过通过随机多试验迭代最近点算法最小化平方距离之和来自动完成术前和术后下颌模型之间的刚性配准。通过计算一组角度和位移误差来量化骨采集的准确性,这些误差用于描述切除块的计划和实际平面之间的关系。该框架在四个案例中的应用表明,它能够以亚毫米精度(<0.4mm)量化与计算机引导骨采集技术相关的容差,其精度在原生图像分辨率范围内。验证方法学证明适用于定义骨切开术手术计划的安全裕度。