Objectives: To develop a nomogram incorporating the quantity of tumor-related vessels (TRVs) and conventional CT features (CCTFs) for the preoperative differentiation of adenocarcinoma in situ (AIS) from minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) appearing as subsolid nodules.
Methods: High-resolution CT target scans of 274 subsolid nodules from 268 patients were included in this study and randomly assigned to the training and validation groups at a ratio of 7:3. A nomogram incorporating CCTFs with the category of TRVs (CTRVs, using TRVs as categorical variables) and a final nomogram combining the number of TRVs (QTRVs) and CCTFs were constructed using multivariable logistic regression analysis. The performance levels of the two nomograms were evaluated and validated on the training and validation datasets and then compared.
Results: The CCTF-QTRV nomogram incorporating abnormal air bronchogram, density, number of dilated and distorted vessels and number of adherent vessels showed more favorable predictive efficacy than the CCTF-CTRV nomogram (training cohort: area under the curve (AUC) = 0.893 vs. 0.844, validation cohort: AUC = 0.871 vs. 0.807). The net reclassification index (training cohort: 0.188, validation cohort: 0.326) and the integrated discrimination improvement values (training cohort: 0.091, validation cohort: 0.125) indicated that the CCTF-QTRV nomogram performed significantly better discriminative ability than the CCTF-CTRV nomogram (all p-value < 0.05).
Conclusions: The nomogram incorporating the QTRVs and CCTFs showed favorable predictive efficacy for differentiating AIS from MIA-IAC appearing as subsolid nodules and may serve as a potential tool to provide individual care for these patients.
Keywords: Lung Adenocarcinoma; Nomogram; Subsolid Nodule; Target High Resolution CT; Tumor-Related Vessel.
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