Evaluation value of DECT energy spectrum curve slope combined with CT value on invasion of early lung adenocarcinoma

Objective To explore the value of dual-energy CT (DECT) energy spectrum curve slope (denoted by λHU) combined with CT values for the evaluation of the invasiveness of early-stage lung adenocarcinoma.

Methods A retrospective case-control study was conducted to analyze the clinical and DECT imaging data of 90 patients (44 males and 46 females, aged 34–84 years with a mean age of (57.9±11.5) years) admitted to Shaanxi Provincial People′s Hospital from January 2024 to October 2025. All patients underwent preoperative plain and enhanced chest DECT scans and were pathologically diagnosed with stage Ⅰ early-stage lung adenocarcinoma after surgery. The quantitative DECT parameters of lesions were measured and recorded. The patients were divided into three groups in accordance with postoperative histopathological results: adenocarcinoma in situ (AIS, n=19), minimally invasive adenocarcinoma (MIA, n=25), and invasive adenocarcinoma (IAC, n=46) groups. Differences in relevant parameters among the three groups were compared. Patients in the AIS and MIA groups were combined into the non-IAC group (n=44), which was further compared with the IAC group (n=46) in terms of general clinical data and DECT parameters. Comparisons between two groups were performed by using SNK-q test and independent-samples t-test. Comparisons among multiple groups were conducted through one-way analysis of variance and chi square test. Univariate and multivariate logistic regression analyses were performed to screen predictive factors for early-stage IAC. Receiver operating characteristic (ROC) curve analysis was adopted to evaluate the diagnostic efficacy of single parameters and the combined prediction model for IAC. The DeLong test was used to compare the differences in diagnostic efficacy among different parameters and combined model.

Results No significant difference in lesion location was found among the AIS, MIA, and IAC groups (χ²=0.226, P=0.893). However, significant differences were observed in the maximum lesion diameter, plain scan CT value, arterial- and venous-phase λHU, effective atomic number (denoted by Z_eff), iodine concentration (IC), and normalized iodine concentration (NIC) among the three groups (F=20.929–95.373, all P<0.001). No significant difference in lesion location was found between the IAC and non-IAC groups (χ²=0.206, P=0.650), whereas significant differences in maximum lesion diameter, plain scan CT value, arterial- and venous-phase λHU, IC, Z_eff, and NIC were found between the two groups (t=3.731–13.384, all P<0.001). Univariate logistic regression analysis showed that all the above imaging parameters were influencing factors for IAC (all P<0.05). Multivariate logistic regression analysis identified maximum lesion diameter, plain scan CT value, and arterial phase λHU as independent predictive factors for IAC (OR (95%CI): 1.280(1.138–1.440), 1.613(1.103–2.359), 0.165(0.067–0.403), all P<0.05). ROC curve analysis revealed that the AUC of plain scan CT values and arterial phase λHU were 0.857 and 0.932, respectively. The combined prediction model constructed by using the two parameters yielded an AUC of 0.966 for IAC prediction, with a sensitivity of 91.30% and specificity of 90.91%. DeLong test results confirmed that the diagnostic efficacy of the combined model was significantly superior to that of single imaging parameters (Z=3.082, 2.208; both P<0.05).

Conclusion Preoperative DECT scanning can assist in evaluating the invasiveness of early-stage lung adenocarcinoma. Plain scan CT values and arterial-phase λHU are effective indicators for predicting early-stage pulmonary IAC, and their combined evaluation can significantly improve the accuracy of preoperative diagnosis.