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智能电磁导航系统在机器人辅助下颌骨肿瘤切除术中的应用:模型实验。

Intelligent electromagnetic navigation system for robot-assisted intraoral osteotomy in mandibular tumor resection: a model experiment.

机构信息

Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China.

Department of Stomatology, the First Affiliated Hospital of Soochow University, Suzhou, China.

出版信息

Front Immunol. 2024 Jul 25;15:1436276. doi: 10.3389/fimmu.2024.1436276. eCollection 2024.

DOI:10.3389/fimmu.2024.1436276
PMID:39119338
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11306084/
Abstract

BACKGROUND

Mandibular tumor surgery necessitates precise osteotomies based on tumor boundaries; however, conventional osteotomies often lack accuracy in predicting osteotomy positions and planes, potentially leading to excessive resection of normal bone tissues or residual tumors, thus compromising postoperative quality of life and clinical outcomes. Robotic-assisted surgery (RAS) augmented with artificial intelligence (AI) offers precise localization capabilities, aiding surgeons in achieving accurate osteotomy positioning. This study aimed to evaluate the feasibility and accuracy of a robotic magnetic navigation system for positioning and osteotomy in an intraoral surgical trial of a mandibular tumor model.

METHODS

Patient computed tomography (CT) imaging data of mandibular chin and body tumors were utilized to create 3D printed models, serving as study subjects for mandibular tumor resection. Ten pairs of models were printed for the experimental and control groups. The experimental group (EG) underwent osteotomy using a robot-assisted surgical navigation system, performing osteotomy under robotic navigation following alignment based on preoperative design. The control group (CG) underwent traditional surgery, estimating osteotomy position empirically according to preoperative design. Postoperative CT scans were conducted on both models, and actual postoperative results were compared to preoperative design. Osteotomy accuracy was evaluated by positional and angular errors between preoperatively designed and actual osteotomy planes.

RESULTS

For ten randomly selected spots on the left and right sides, respectively, the EG group had mean distance errors of 0.338 mm and 0.941 mm. These values were obtained from the EG group. In the EG group, on the left side, the mean angular errors were 14.741 degrees, while on the right side, they were 13.021 degrees. For the 10 randomly selected spots on the left and right sides, respectively, the CG had mean distance errors of 1.776 mm and 2.320 mm. This is in contrast to the results obtained by the EG. It was determined that the left side had a mean angle error of 16.841 degrees, while the right side had an error of 18.416 degrees in the CG group. The above results indicated significantly lower point errors of bilateral osteotomy planes in the experimental group compared to the control group.

CONCLUSION

This study demonstrates the feasibility of electromagnetic navigation robot-assisted intraoral osteotomy for mandibular tumors and suggests that this approach can enhance the precision of clinical surgery.

摘要

背景

下颌骨肿瘤手术需要根据肿瘤边界进行精确的截骨术;然而,传统截骨术往往缺乏对截骨位置和平面的精确预测能力,可能导致正常骨组织切除过多或肿瘤残留,从而影响术后生活质量和临床效果。机器人辅助手术(RAS)与人工智能(AI)相结合,具有精确的定位能力,有助于外科医生实现精确的截骨定位。本研究旨在评估机器人磁导航系统在口腔内下颌骨肿瘤模型手术中定位和截骨的可行性和准确性。

方法

利用患者下颌颏部和体部肿瘤的计算机断层扫描(CT)影像数据制作 3D 打印模型,作为下颌骨肿瘤切除的研究对象。共打印 10 对模型,分别用于实验组(EG)和对照组(CG)。EG 组采用机器人辅助手术导航系统进行截骨,根据术前设计进行机器人导航下的截骨。CG 组采用传统手术,根据术前设计经验估计截骨位置。对两组模型进行术后 CT 扫描,并将实际术后结果与术前设计进行比较。通过术前设计与实际截骨平面之间的位置和角度误差评估截骨准确性。

结果

在左侧和右侧各随机选择 10 个点,EG 组的平均距离误差分别为 0.338mm 和 0.941mm。在 EG 组,左侧的平均角度误差为 14.741 度,右侧为 13.021 度。在左侧和右侧各随机选择 10 个点,CG 组的平均距离误差分别为 1.776mm 和 2.320mm。左侧的平均角度误差为 16.841 度,右侧为 18.416 度。以上结果表明,实验组双侧截骨平面的点误差明显低于对照组。

结论

本研究表明,电磁导航机器人辅助口腔内下颌骨肿瘤截骨术具有可行性,并提示该方法可以提高临床手术的精度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/3f6ab3964748/fimmu-15-1436276-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/b0295c948247/fimmu-15-1436276-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/e9c4e021a624/fimmu-15-1436276-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/7508874e267d/fimmu-15-1436276-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/dc8371b57984/fimmu-15-1436276-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/76cc8d139fa5/fimmu-15-1436276-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/487ab1832238/fimmu-15-1436276-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/e0048dac607d/fimmu-15-1436276-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/3f6ab3964748/fimmu-15-1436276-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/b0295c948247/fimmu-15-1436276-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/e9c4e021a624/fimmu-15-1436276-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/7508874e267d/fimmu-15-1436276-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/dc8371b57984/fimmu-15-1436276-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/76cc8d139fa5/fimmu-15-1436276-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/487ab1832238/fimmu-15-1436276-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/e0048dac607d/fimmu-15-1436276-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/825c/11306084/3f6ab3964748/fimmu-15-1436276-g008.jpg

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