Optimal maximum standardized uptake value and nodal diameter cut-offs for predicting diagnostic sensitivity of endobronchial ultrasound-guided transbronchial needle aspiration

Background This study aimed to identify clinical predictors of diagnostic sensitivity for malignancy in endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and to determine optimal cut-off values for preoperative imaging parameters. We retrospectively reviewed 124 patients who underwent EBUS-TBNA for suspected thoracic malignancy between 2019 and 2022. Among 93 patients with available 18 F-fluorodeoxyglucose positron emission tomography/ computed tomography (FDG-PET/CT) and confirmed malignancy, the association between EBUS-TBNA diagnostic positivity and clinical factors, including CT nodal long-axis diameter and maximum standardized uptake value (SUVmax), was analyzed. Optimal cut-off values were determined using receiver operating characteristic (ROC) curve analysis. Results Of the 93 patients analyzed, 75 (80.6%) were diagnosed via EBUS-TBNA (EBUS-positive group), while 18 (19.4%) were false negatives (EBUS-false-negative group). Multivariable logistic regression analysis, treating parameters as continuous variables, identified both nodal size (odds ratio [OR]: 1.150; 95% confidence interval [CI]: 1.030–1.290; p = 0.016) and SUVmax (OR: 1.170; 95% CI: 1.020–1.330; p = 0.021) as significant independent predictors of EBUS-TBNA positivity. ROC analysis established optimal cut-offs of 21 mm for nodal size (AUC: 0.802) and 7.9 for SUVmax (AUC: 0.805). When both criteria (nodal size ≥ 21 mm and SUVmax ≥ 7.9) were met, the positive predictive value reached 95.7%, with a diagnostic accuracy of 64.5% and a negative predictive value of 34.0%. Conclusions The combination of high metabolic activity (SUVmax ≥ 7.9) and nodal size (≥ 21 mm) serves as a predictor of malignancy detection via EBUS-TBNA. Integrating these parameters can optimize preoperative staging and ensure sufficient diagnostic evaluation for personalized treatment planning in thoracic oncology.