Quantitative PCCT spectral parameters for noninvasive prediction of EGFR status and its subtypes in lung adenocarcinoma.

Abstract

Objective: To investigate the non-invasive predictive value of quantitative spectral parameters from photon-counting computed tomography (PCCT) for epidermal growth factor receptor (EGFR) mutation status and its predominant subtypes (19Del and L858R) in patients with lung adenocarcinoma.

Methods: A total of 72 patients with pathologically confirmed lung adenocarcinoma who underwent pretreatment PCCT were retrospectively enrolled. Arterial and venous CT attenuation values at 40 keV, 70 keV, and 100 keV (A/V-40 keV, A/V-70 keV, A/V-100 keV) were measured on virtual monoenergetic images, while arterial/venous iodine concentration (IC) and dual-energy index (DEI) of lesions were measured on iodine maps and spectral post-processing (SPP) images, respectively. Normalized iodine concentration (NIC) and spectral curve slope (λHU) were further calculated. Receiver operating characteristic (ROC) curve analysis and binary logistic regression were performed to evaluate the predictive performance and independent predictive value of PCCT parameters for discriminating EGFR-mutant vs. wild-type tumors, as well as 19Del vs. L858R subtypes.

Results: Of 72 patients, 37 (51.4%) harbored EGFR mutations, which correlated with female sex, never-smoking, reduced NSE, and lower monocyte count. The EGFR-mutant group showed significantly higher A-70 keV, A-100 keV, A-DEI, V-40 keV, V-70 keV, V-100 keV, V-λHU and V-DEI (all P < 0.05). Logistic regression identified female sex (P = 0.019, OR = 5.714, 95% CI: 1.336-24.442) and A-100 keV (P = 0.044, OR = 0.543, 95% CI: 0.300-0.983) as independent predictors. ROC analysis with bootstrap validation yielded: clinical model AUC 0.767 (optimism-corrected 0.762); PCCT model AUC 0.713 (optimism-corrected 0.707); combined model AUC 0.771 (optimism-corrected 0.768) (all P < 0.001). Between 19Del (n = 15) and L858R (n = 17) subgroups, A-40 keV and A-DEI showed significant discriminative performance in ROC analysis, with AUCs of 0.694 and 0.704 (optimism-corrected AUCs: 0.688 and 0.697, respectively).

Conclusions: Quantitative PCCT spectral parameters enable non-invasive prediction of EGFR mutation status and preliminary differentiation between 19Del and L858R subtypes in lung adenocarcinoma, though subtype-related findings require validation in larger cohorts. Female sex and A-100 keV are independent predictive factors. The combined model yielded a numerically higher AUC without statistically significant superiority, and PCCT parameters may provide auxiliary imaging evidence to inform individualized targeted therapy decisions in lung adenocarcinoma.