The encouraging performance of DLCT quantitative parameters in this study demonstrated that they could provide valid information regarding the EGFR mutation status of NSCLC, with NIC(VP) and INW(AP) identified as key factors. NIC(VP) had the highest predictive efficacy, even higher than that found in previous studies [19, 20].

Previous studies have attempted to detect EGFR mutations in patients with NSCLC using radiomics, specific tumor markers, and morphological features via traditional CT scans [21,22,23]. The present study found no significant differences in the size, location, density, or morphological features of NSCLC lesions between the two groups, deviating from findings in earlier research [24]. Such inconsistencies could stem from the constrained sample size and potential patient selection bias in this investigation. Clinical features also can provide valuable information about the tumor. The 75.0% EGFR mutation rate among patients with NSCLC and all the mutations being in exons 18 to 21 in this study exceeds the findings of prior reports, likely due to the small sample and the preponderance of early-stage cases compared to the established 40–50% prevalence in Asian lung adenocarcinoma populations [10]. In addition to ethnicity, EGFR mutations in lung cancer are also associated with female sex and non-smoking status [25, 26], consistent with our results. Contrary to prior findings, this study identified no significant difference in sex or smoking history between the two groups [20, 27].

Several malignancies have been noted to show high or abnormal EGFR expression, thereby precipitating sustained activation and amplification of downstream signaling pathways, stimulating physiological and pathological angiogenesis to enhance blood supply to the tumor [28, 29]. Therefore, dynamic contrast-enhanced CT imaging provides additional information about EGFR-mutated NSCLC lesions relative to non-enhanced CT scans. Tacelli et al [30] showed that perfusion CT scanning holds potential as a predictive tool for assessing tumor responsiveness to antiangiogenic therapeutics, yet its utility is limited by variability in patient-specific vascular perfusion characteristics and concerns regarding substantial radiation exposure. The present study showed that ED in the mutated EGFR group was significantly higher than that in the wild-type EGFR group. The VNC images here were obtained by inhibiting iodine in conventional contrast-enhanced CT images. Theoretically, if the quality of the VNC image is good enough, it can replace the true non-contrast image [31], which is of great significance for optimizing the scanning process and reducing the radiation dose.

The present study demonstrated that NIC(VP) exhibited optimal performance in predicting EGFR mutation status. Because iodine is the main component of CT contrast agent, IC can faithfully represent the lesion’s enhancement characteristics, providing a precise evaluation of the angiogenic activity and perfusion status in lung cancer, in contrast to ED. The blood supply of lesions may be increased in NSCLC with EGFR mutations, which could be reflected by IC. This study identified more quantitative parameters that were significantly different between the mutated and wild-type EGFR groups in the VP scans than in the AP scans. The enhanced reliability of the VP scans may be attributable to a more consistent hemodynamic profile in patients, minimizing imaging inconsistencies and yielding more precise quantitative parameters, thereby offering a stable basis for diagnosis. NIC, which calibrates the tumor’s iodine uptake to that of the thoracic aorta, mitigates interpatient hemodynamic variability, enhancing precise EGFR mutation status prediction.

Univariate analysis showed that INW(AP), INW(VP), Zeff(VP), λHU(AP), and λHU(VP) were significantly higher in the EGFR mutated group than in the wild-type EGFR group, although NIC, IC, and ED were not, this is consistent with results of previous studies [19, 20]. INW is indicative of the vascular supply of lung tumors, whereas Zeff reflects the effective atomic number of inorganic constituents within the tumor. ΛHU, the slope of the spectral curve obtained by 40 keV–200 keV levels VMI of DLCT, represents the unique linear attenuation coefficient of X-rays by different substances. All three quantitative parameters mentioned above can be used to identify different materials [32, 33], indicating a similar potential to evaluate EGFR mutation status in patients with NSCLC. However, there were no significant differences in VMI(40keV) or VMI(100keV) between the two groups. While low-energy levels of VMI improve lesion delineation, they fail to provide additional diagnostic information beyond that of conventional CT images. Nonetheless, these results need to be further verified through studies with a larger sample size.

Studies have shown quantitative color mapping of the AEF, the ratio of CT value between the AP and the portal venous phase, could increase the diagnostic performance of hepatocellular carcinoma [34]. However, few studies have investigated the clinical value of AEF or NAEF, defined as the ratio of IC or NIC in the arteriovenous phase. For example, AEF could be used to identify and evaluate the function of mediastinal lymph nodes in lung cancer [35, 36]. Wen et al [37] discerned that the NAEF yielded limited utility in discriminating between benign and malignant solid pulmonary nodules. This study marked the inaugural presentation of the NAEF map derived from NIC value; however, it revealed that neither AEF nor NAEF exhibited a significant correlation with EGFR mutation status in NSCLC. Subsequent research with a larger sample size is imperative for validation.

Our study has several limitations. First, it is based on a small sample size from a single-center institution, potentially introducing selection bias. Second, the representation of patients with advanced-stage NSCLC is limited, and investigations into other oncogenic driver mutations, including ALK or KRAS, were not undertaken in this study. Multicenter recruitment is essential to enhance the robustness and generalizability of the findings. Third, the heterogeneity of NSCLC may mean that those quantitative parameters of the two-dimensional spectral DLCT images do not comprehensively represent the biological complexity of the entire tumor, and the potential relevance of quantitative parameters from the tumor’s periphery to the EGFR mutation status was not assessed. Finally, future research should delve into the relationship between the quantitative parameters of DLCT and the efficacy of targeted treatments in lung cancer patients harboring EGFR mutations.

In conclusion, this study demonstrated that quantitative parameters of DLCT were correlated with EGFR mutation status in patients with NSCLC. NIC(VP) might be a potential predictor of EGFR mutation status, which could help to select appropriate and individualized treatment for these patients.