Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:3758-3763. doi: 10.1109/EMBC48229.2022.9870985.
Patients with advanced cancer undergoing chest wall resection may require reconstruction. Currently, rib prostheses are created by segmenting computed tomography images, which is time-consuming and labour intensive. The aim was to optimise the production of digital rib models based on a patient's age, weight, height and gender. A statistical shape model of human ribs was created and used to synthetise rib models, which were compared to the ones produced by segmentation and mirroring. The segmentation took 11.56±1.60 min compared to 0.027 ±0.009 min using the new technique. The average mesh error between the mirroring technique and segmentation was 0.58±0.25 mm (right ribs), and 0.87±0.18 mm (left ribs), compared to 1.37±0.66 mm ( ) and 1.68 ±0.77 mm ( ), respectively, for the new technique. The new technique is promising for the efficiency and ease-of-use in the clinical environment. Clinical Relevance- This is an optimised 3D modelling method providing clinicians with a time-efficient technique to create patient-specific rib prostheses, without any expertise or software knowledge required.
接受胸腔壁切除术的晚期癌症患者可能需要进行重建。目前，肋骨假体是通过对计算机断层扫描图像进行分段来创建的，这既耗时又费力。目的是基于患者的年龄、体重、身高和性别，优化数字肋骨模型的制作。创建了人体肋骨的统计形状模型，并用于综合肋骨模型，这些模型与分段和镜像生成的模型进行了比较。分段需要 11.56±1.60 分钟，而使用新技术只需 0.027 ±0.009 分钟。镜像技术和分段之间的平均网格误差为 0.58±0.25 毫米（右侧肋骨）和 0.87±0.18 毫米（左侧肋骨），而新技术的误差分别为 1.37±0.66 毫米（右侧肋骨）和 1.68 ±0.77 毫米（左侧肋骨）。新技术在临床环境中的效率和易用性具有很大的发展潜力。临床意义-这是一种优化的 3D 建模方法，为临床医生提供了一种高效的技术，可以创建患者特定的肋骨假体，而无需任何专业知识或软件知识。
