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在萎陷肺中描绘节段间线的新方法。

New method for delineation of the intersegmental line in a deflated lung.

作者信息

Okado Shoji, Kadomatsu Yuka, Nakao Megumi, Ueno Harushi, Fukumoto Koichi, Nakamura Shota, Chen-Yoshikawa Toyofumi Fengshi

机构信息

Department of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.

Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto, Japan.

出版信息

J Thorac Dis. 2023 Sep 28;15(9):4736-4744. doi: 10.21037/jtd-23-421. Epub 2023 Aug 22.

Abstract

BACKGROUND

Preoperative three-dimensional (3D) computed tomography (CT) images have been widely used as surgical guides in lung surgery; however, the lungs tend to be deflated during surgery. Discrepancies between the preoperatively constructed 3D image and the intraoperative view of the deflated lungs often require preoperative and/or intraoperative marking methods for sublobar pulmonary resection. We have developed a lung deflation simulation algorithm in which 3D CT images of the deflated lungs can be predicted only based on the preoperative CT taken in an inflated phase of respiration. Using this system, we conducted a preliminary study to retrospectively compare the intersegmental line predicted by our lung deflation simulation algorithm with the intersegmental line delineated by the intravenous administration of indocyanine green.

METHODS

Sixteen patients who underwent unilateral segmentectomy between January 1, 2020, and June 30, 2022, were included in the study. The identified intersegmental lines were confirmed intraoperatively using indocyanine green. These actual intersegmental lines were compared with those delineated on 3D images using the lung deflation simulation algorithm.

RESULTS

Of the 16 patients who underwent pulmonary segmentectomy, the consistency of these intersegmental lines was in complete agreement in twelve patients, partial agreement in three patients, and disagreement in one patient. The concordance rate of the intersegmental lines was 75%.

CONCLUSIONS

The lung deflation simulation algorithm provides a new surgical guide in addition to the currently utilized ones. Continuous innovation might lead to a less invasive surgical technique for delineating the intersegmental line.

摘要

背景

术前三维(3D)计算机断层扫描(CT)图像已在肺手术中广泛用作手术导航;然而,肺在手术过程中往往会萎陷。术前构建的3D图像与萎陷肺的术中视野之间的差异常常需要术前和/或术中标记方法来进行肺段以下肺切除术。我们开发了一种肺萎陷模拟算法,仅基于呼吸充气期拍摄的术前CT就能预测萎陷肺的3D CT图像。使用该系统,我们进行了一项初步研究,以回顾性比较我们的肺萎陷模拟算法预测的肺段间线与通过静脉注射吲哚菁绿描绘的肺段间线。

方法

纳入2020年1月1日至2022年6月30日期间接受单侧肺段切除术的16例患者。术中使用吲哚菁绿确认确定的肺段间线。将这些实际的肺段间线与使用肺萎陷模拟算法在3D图像上描绘的肺段间线进行比较。

结果

在接受肺段切除术的16例患者中,这些肺段间线的一致性在12例患者中完全一致,3例患者部分一致,1例患者不一致。肺段间线的符合率为75%。

结论

肺萎陷模拟算法除了现有的手术导航方法外,还提供了一种新的手术导航。持续创新可能会带来一种用于描绘肺段间线的侵入性较小的手术技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7771/10586991/fa6b535bccc1/jtd-15-09-4736-vid1.jpg

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