PDF(Pubmed)
Abstract：
In recent years, preoperative planning has undergone significant advancements, with a dual focus: improving the accuracy of implant placement and enhancing the prediction of functional outcomes. These breakthroughs have been made possible through the development of advanced processing methods for 3D preoperative images. These methods not only offer novel visualization techniques but can also be seamlessly integrated into computer-aided design models. Additionally, the refinement of motion capture systems has played a pivotal role in this progress. These \"markerless\" systems are more straightforward to implement and facilitate easier data analysis. Simultaneously, the emergence of machine learning algorithms, utilizing artificial intelligence, has enabled the amalgamation of anatomical and functional data, leading to highly personalized preoperative plans for patients. The shift in preoperative planning from 2D towards 3D, from static to dynamic, is closely linked to technological advances, which will be described in this instructional review. Finally, the concept of 4D planning, encompassing periarticular soft tissues, will be introduced as a forward-looking development in the field of orthopedic surgery.
摘要：
近年来,术前规划有了重大进步，具有双重重点：提高植入物放置的准确性和增强功能结局的预测。通过开发3D术前图像的先进处理方法，这些突破已经成为可能。这些方法不仅提供了新颖的可视化技术，而且还可以无缝地集成到计算机辅助设计模型中。此外,动作捕捉系统的完善在这一进展中发挥了关键作用。这些“无标记”系统更容易实现和简化数据分析。同时,机器学习算法的出现，利用人工智能，实现了解剖和功能数据的融合，导致患者高度个性化的术前计划。术前规划从2D向3D的转变，从静态到动态，与技术进步密切相关，这将在本指导审查中进行描述。最后,4D规划的概念，包括关节周围软组织，将作为骨科手术领域的前瞻性发展。
