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术前三维肺容积测量可预测结直肠转移行大肝切除患者的肺部并发症。

Preoperative three-dimensional lung volumetry predicts respiratory complications in patients undergoing major liver resection for colorectal metastases.

机构信息

Department of General, Visceral, Pediatric, and Transplantation Surgery, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany.

Department of Operative Intensive Care and Intermediate Care, University Hospital RWTH Aachen, Aachen, Germany.

出版信息

Sci Rep. 2024 May 8;14(1):10594. doi: 10.1038/s41598-024-61386-8.

DOI:10.1038/s41598-024-61386-8
PMID:38719953
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11079043/
Abstract

Colorectal liver metastases (CRLM) are the predominant factor limiting survival in patients with colorectal cancer and liver resection with complete tumor removal is the best treatment option for these patients. This study examines the predictive ability of three-dimensional lung volumetry (3DLV) based on preoperative computerized tomography (CT), to predict postoperative pulmonary complications in patients undergoing major liver resection for CRLM. Patients undergoing major curative liver resection for CRLM between 2010 and 2021 with a preoperative CT scan of the thorax within 6 weeks of surgery, were included. Total lung volume (TLV) was calculated using volumetry software 3D-Slicer version 4.11.20210226 including Chest Imaging Platform extension ( http://www.slicer.org ). The area under the curve (AUC) of a receiver-operating characteristic analysis was used to define a cut-off value of TLV, for predicting the occurrence of postoperative respiratory complications. Differences between patients with TLV below and above the cut-off were examined with Chi-square or Fisher's exact test and Mann-Whitney U tests and logistic regression was used to determine independent risk factors for the development of respiratory complications. A total of 123 patients were included, of which 35 (29%) developed respiratory complications. A predictive ability of TLV regarding respiratory complications was shown (AUC 0.62, p = 0.036) and a cut-off value of 4500 cm was defined. Patients with TLV < 4500 cm were shown to suffer from significantly higher rates of respiratory complications (44% vs. 21%, p = 0.007) compared to the rest. Logistic regression analysis identified TLV < 4500 cm as an independent predictor for the occurrence of respiratory complications (odds ratio 3.777, 95% confidence intervals 1.488-9.588, p = 0.005). Preoperative 3DLV is a viable technique for prediction of postoperative pulmonary complications in patients undergoing major liver resection for CRLM. More studies in larger cohorts are necessary to further evaluate this technique.

摘要

结直肠癌肝转移(CRLM)是限制结直肠癌患者生存的主要因素,肝切除术联合完整肿瘤切除是此类患者的最佳治疗选择。本研究旨在探讨基于术前计算机断层扫描(CT)的三维肺容积(3DLV)对接受结直肠癌肝转移(CRLM)根治性肝切除术后肺部并发症的预测能力。

2010 年至 2021 年间,我们纳入了在手术前 6 周内行胸部 CT 检查的接受结直肠癌肝转移根治性肝切除术的患者。使用 3D-Slicer 版本 4.11.20210226 计算全肺容积(TLV),该软件包括 Chest Imaging Platform 扩展(http://www.slicer.org)。采用受试者工作特征曲线分析的曲线下面积(AUC)定义 TLV 截断值,以预测术后肺部并发症的发生。采用卡方检验、Fisher 确切概率法和 Mann-Whitney U 检验比较 TLV 截断值上下患者的差异,采用 logistic 回归分析确定发生肺部并发症的独立危险因素。

共纳入 123 例患者,其中 35 例(29%)发生肺部并发症。结果显示 TLV 对预测肺部并发症具有一定的预测能力(AUC 0.62,p=0.036),并定义截断值为 4500cm。与其余患者相比,TLV<4500cm 的患者肺部并发症发生率明显更高(44% vs. 21%,p=0.007)。Logistic 回归分析发现 TLV<4500cm 是发生肺部并发症的独立预测因素(比值比 3.777,95%置信区间 1.488-9.588,p=0.005)。

术前 3DLV 是预测结直肠癌肝转移患者行根治性肝切除术后肺部并发症的一种可行技术。需要更多的大样本队列研究进一步评估该技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40b/11079043/0a70e293909d/41598_2024_61386_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40b/11079043/4b3d5750abfc/41598_2024_61386_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40b/11079043/ed1a4417f7a7/41598_2024_61386_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40b/11079043/0a70e293909d/41598_2024_61386_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40b/11079043/4b3d5750abfc/41598_2024_61386_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40b/11079043/ed1a4417f7a7/41598_2024_61386_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40b/11079043/0a70e293909d/41598_2024_61386_Fig3_HTML.jpg

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