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基于虚拟3D影像和病理学表现的早期肺腺癌大小测量及肺段切除术切缘:一项初步相关性研究

Size Measurement and Segmentectomy Resection Margin of Early-Stage Lung Adenocarcinoma Manifesting on Virtual 3D Imagery and Pathology: A Pilot Correlation Study.

作者信息

Lin Ching-Min, Tai Hui-Chun, Cheng Ya-Fu, Ke Pei-Cing, Liu Chia-Chi, Wang Bing-Yen

机构信息

Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 500209, Taiwan.

Department of Pathology, Changhua Christian Hospital, Changhua 500209, Taiwan.

出版信息

J Clin Med. 2022 Oct 19;11(20):6155. doi: 10.3390/jcm11206155.

Abstract

BACKGROUND

The objective of our study was to assess if 3D reconstructed images could be extrapolated to reflect pathologies, as evaluated by early-stage lung adenocarcinoma tumor size and simulated segmentectomy resection margin.

METHODS

Retrospectively selected patients ( = 18) who underwent segmentectomy at Changhua Christian Hospital between 2012 and 2018 and then had pulmonary 3D reconstruction using Ziostation2 were included in our study. Tumor size and simulated segmentectomy resection distance on a 3D model were measure and compared to pathology.

RESULTS

Both tumor size and segmentectomy resection margin showed positive correlations between 3D image measurements and pathological measurements. The resection margin showed a stronger correlation and was beneficial in pre-operative planning.

CONCLUSIONS

A 3D reconstructed model aided understanding of pulmonary anatomy, prompting confidence in surgical approaches and ensured segmentectomy outcome success. Regardless of age and pulmonary function, 3D simulation can accurately mimic segmentectomy, making it a simple, effective and feasible pre-operative planning tool.

摘要

背景

我们研究的目的是评估三维重建图像是否能够外推以反映病变情况,这通过早期肺腺癌肿瘤大小和模拟肺段切除术切缘来评估。

方法

回顾性选取2012年至2018年期间在彰化基督教医院接受肺段切除术并随后使用Ziostation2进行肺部三维重建的患者(n = 18)纳入我们的研究。在三维模型上测量肿瘤大小和模拟肺段切除术切除距离,并与病理结果进行比较。

结果

肿瘤大小和肺段切除术切缘在三维图像测量与病理测量之间均显示出正相关。切缘显示出更强的相关性,并且在术前规划中有益。

结论

三维重建模型有助于理解肺部解剖结构,增强对手术方法的信心并确保肺段切除术结果成功。无论年龄和肺功能如何,三维模拟都能准确模拟肺段切除术,使其成为一种简单、有效且可行的术前规划工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca8/9605571/8622dc6d547b/jcm-11-06155-g001.jpg

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