磨玻璃结节样肺癌的最大尺寸:计算机断层成像与切除病理标本的比较。

IF 1.3
Jingyi Gao, Xiaoran Chen, Yingying Zheng, Xia Yang, Guoliang Xue, Nan Wang, Zhichao Li, Qing Sun, Ping Zhou, Qingshi Zeng, Xin Ye
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引用次数: 0

摘要

目的:肿瘤的最大尺寸(LDT)仍然是局部肿瘤控制的关键决定因素,无论手术切除,放疗,和图像引导热消融。本前瞻性研究旨在通过比较磨玻璃结节(GGN)样肺癌的计算机断层扫描(CT)图像与切除病理标本来确定LDT的一致性。材料与方法:2023年5月至2024年7月,共163例ggn样肺癌患者(男54例,女109例,平均年龄56.2±10.9岁)163个病灶(最大尺寸≤20 mm,纯ggn 49例,混合ggn 114例)行手术切除,所有患者病理类型均为腺癌。通过二维(2D) CT成像(横断面,2D-LDT)、三维(3D)重建系统(3D-LDT)和病理标本(P-LDT)评估每位ggn样肺癌患者的LDT。采用R 4.2.1版软件进行统计分析。结果:测量所有ggn样肺癌病变的2D-LDT、3D-LDT和P-LDT的中位LDT分别为10.0 mm、11.6 mm和11.7 mm。2D-LDT与3D-LDT比较差异有统计学意义(P = 0.0002), 2D-LDT与P- ldt比较差异有统计学意义(P = 0.0000118), 3D-LDT与P- ldt比较差异无统计学意义(P = 0.7394)。结论:3D-LDT与P-LDT对≤20mm的ggn样肺癌的诊断一致性较高。术前2D-CT与病理浸润性LDT相比可能被低估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Largest dimension of ground-glass nodule-like lung cancer: Comparison of computed tomography imaging and resected pathological specimens.

Purpose: The largest dimension of the tumor (LDT) remains a key determinant of local tumor control regardless of surgical resection, radiotherapy, and image-guided thermal ablation. This prospective study aimed to determine the consistency of LDT by comparing computed tomography (CT) images of ground-glass nodule (GGN)-like lung cancer with resected pathological specimens.

Materials and methods: A total of 163 patients (54 males and 109 females, a mean age of 56.2 ± 10.9 years) with 163 lesions demonstrating GGN-like lung cancer (the largest dimension of ≤20 mm, pure GGNs in 49 and mixed GGNs in 114) underwent surgical resection from May 2023 to July 2024, with adenocarcinoma as the pathology type of all included patients. LDT for each patient with GGN-like lung cancer was evaluated by two-dimensional (2D) CT imaging (cross-section, 2D-LDT), a three-dimensional (3D) reconstruction system (3D-LDT), and pathological specimens (P-LDT). R version 4.2.1 software was used for statistical analyses.

Results: The median LDT for measuring all lesions with GGN-like lung cancer were 10.0 mm, 11.6 mm, and 11.7 mm in 2D-LDT, 3D-LDT, and P-LDT, respectively. A significant difference was observed in the 2D-LDT compared with the 3D-LDT (P = 0.0002) as well as between the 2D-LDT and P-LDT (P = 0.0000118), but no statistically significant difference was found between the 3D-LDT and P-LDT (P = 0.7394).

Conclusions: 3D-LDT demonstrated high consistency with P-LDT for determining GGN-like lung cancer of ≤20 mm. Preoperative 2D-CT may be underestimated in comparison with pathological invasive LDT.

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