Correlation study between CT imaging features and pathological diagnosis of subcentimeter pulmonary nodules
CT影像学特征与亚厘米肺结节病理诊断的相关性研究

摘要

目的 探究分析CT影像学特征与亚厘米肺结节病理诊断的相关性。方法 回顾性分析2022年1月至2024年12月期间本院收治的102例亚厘米肺小结节患者病例资料，以病理结果为基础，将患者分为A组（良性病变），B组（肺部不典型腺瘤样增生），C组（肺部原位癌），D组（肺部微浸润腺癌），E组（肺部浸润性腺癌），进一步整理患者CT以及增强CT检查资料，明确CT影像学特征，肺结节大小以及增强程度与病理诊断的关系。结果 102例患者均为单发结节，以形态特征差异为基础，将其分为五型：Ⅰ型44例，Ⅱ型18例，Ⅲ型8例，Ⅳ型25例，Ⅴ型7例。5组亚厘米肺小结节大小对比，E组亚厘米肺小结节最大，A组肺小结节最小，差异具有统计学意义（P＜0.05）。5组亚厘米肺小结节增强程度对比，E组肺结节增强程度最高，差异具有统计学意义（P＜0.05）。结论 CT影像学特征分类以及增强CT下肺结节大小、增强程度可协助医师更好的落实亚厘米小结节定性诊断，可为后续诊疗方案的制定提供有效的数据支持。

Abstract

Objective To explore and analyze the correlation between CT imaging features and pathological diagnosis of sub centimeter pulmonary nodules.
Methods A retrospective analysis was conducted on the case data of 102 patients with sub centimeter pulmonary nodules in the hospital from January 2023 to December 2024. Based on pathological results, the patients were divided into Group A (benign lesions), Group B (atypical adenomatous hyperplasia of the lungs), Group C (carcinoma in situ of the lungs), Group D (microinvasive adenocarcinoma of the lungs), and Group E (invasive adenocarcinoma of the lungs). CT and enhanced CT examination data were further organized to clarify the relationship between CT imaging characteristics, pulmonary nodule size, and enhancement degree and pathological diagnosis. The results showed that all 102 patients had a single nodule, which could be classified into four groups based on differences in morphological characteristics: 44 cases of type I, 18 cases of type II, 8 cases of type III, 25 cases of type IV, and 7 cases of type V. The comparison between the five groups was P<0.05. Comparison of size of 5 sub centimeter pulmonary nodules, P＜0.05. The size of sub centimeter pulmonary nodules in Group E is the largest, while the size of pulmonary nodules in Group A is the smallest, P＜0.05. Comparison of the enhancement degree of 5 groups of sub centimeter pulmonary nodules, P<0.05, with the highest enhancement ratio of pulmonary nodules in group E, P＜0.05.
Conclusion  : CT imaging feature classification, as well as the size and enhancement degree of lung nodules under enhanced CT, can assist physicians in better implementing qualitative diagnosis of sub centimeter nodules and provide effective data support for the formulation of subsequent diagnosis and treatment plans.