Diagnostic Performance of Imaging Methods in Predicting Lung Cancer Metastases

Abstract

Objective: This study aimed to investigate the possibility of distant organ metastasis using an algorithm developed to evaluate the morphology and localization of lung masses. Methods: Patients diagnosed with lung cancer between 2016 and 2023 were included. The lesion's morphological characteristics, proximity to important structures, and maximum standardized uptake value were recorded. Six common metastatic sites were identified: the contralateral lung, liver, brain, adrenal glands, bone, and other regions. The relationship between the characteristics of the mass and the metastatic location was investigated. Results: A total of 383 patients (260 men, 68%) with malignant lung lesions with a mean ± SD age of 65.50 ± 12.34 years (range: 36–74 years) were included in the study. Among them, 242 were diagnosed with primary lung cancer, and 106 (43.8%) exhibited metastases to other organs with primary lung tumors. Distant organ metastases were most frequently detected in the bones (n = 45, 42.5%) and were more frequent in male patients and lesions adjacent to the ribs and bronchi, those involving mediastinal lymph nodes, irregular contours, and maximum standardized uptake values above 11.15 ± 5.67 (mean ± SD). Conclusions: Evaluating radiological imaging of malignant lesions in patients with lung cancer using an algorithm that considers morphological and neighborhood characteristics can provide predictive information regarding the possibility of metastasis of malignant lung lesions and the metastatic location. Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.