Predicting invasiveness of ground-glass nodules in lung adenocarcinoma: based on preoperative 18F-fluorodeoxyglucose PET/computed tomography and high-resolution computed tomography

医学 标准摄取值 核医学 磨玻璃样改变 放射科 腺癌 计算机断层摄影术 断层摄影术 氟脱氧葡萄糖 高分辨率计算机断层扫描 癌症 内科学
作者
Ximei Wang,Chunyan Yang,Xue-Wei Wang,Dalong Wang
出处
期刊:Nuclear Medicine Communications [Lippincott Williams & Wilkins]
标识
DOI:10.1097/mnm.0000000000001898
摘要

Objective This study was conducted to explore the differential diagnostic value of PET/computed tomography (PET/CT) combined with high-resolution computed tomography (HRCT) in predicting the invasiveness of ground-glass nodules (GGNs). Materials and methods This retrospective analysis included 67 patients (mean age 62.5 ± 8.4, including 45 females and 22 males) with GGNs who underwent preoperative 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/CT and HRCT examinations between January 2018 and October 2022. Based on the postoperative pathological results of lung adenocarcinoma, the patients were classified into two groups: invasive adenocarcinoma (IAC) and non-IAC. Besides, the clinical and imaging information of these patients was collected. HRCT signs include the existence of air bronchial signals, vascular convergence, pleural indentation, lobulation, and spiculation. Moreover, the diameter of solid components (D Solid ), diameter of ground-glass nodules (D GGN ), and computed tomography values of ground-glass nodules (CT GGN ) were measured concurrently. Furthermore, the mean standardized uptake value, maximal standardized uptake value (SUVmax), metabolic tumor volume, and total lesion glycolysis were assessed during PET/CT. Associations between invasiveness and these factors were evaluated using univariate and multivariate analyses. Results The results of logistic regression analysis demonstrated that D GGN , D Solid , consolidation tumor ratio (CTR), CT GGN , and SUVmax were independent predictors in the IAC group. The combined diagnosis based on these five predictors revealed that area under the curve was 0.825. Conclusion The D GGN , D Solid , CTR, CT GGN , and SUVmax in GGNs were independent predictors of IAC, and combining 18 F-FDG PET/CT metabolic parameters with HRCT may improve the predictive value of pathological classification in lung adenocarcinoma.

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