Observational studyCancer imaging : the official publication of the International Cancer Imaging Society2026
CT predictors of visceral pleural invasion in subsolid nodular pulmonary adenocarcinoma: differences between direct and indirect tumor-pleura contact.
Observational study in Cancer imaging : the official publication of the International Cancer Imaging Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Ultrasound assessment of pleural invasion via visceral pleura interruption and arch distance-to-tumour diameter ratio in a rabbit model of subpleural lung cancer.Translational lung cancer research · 2026Article
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Abstract
backgroundPreoperative accurate prediction of visceral pleural invasion (VPI) in subsolid nodular pulmonary adenocarcinoma (PA) can provide guidance for the surgical method of early lung cancer. The aim of this study is to explore the value of CT features in predicting VPI in clinical stage IA subsolid nodular peripheral PA with contact with the pleura.
methodsA total of 464 patients across three hospitals were retrospectively analyzed. The internal dataset (n = 363) was divided into training cohort (n = 244) and internal validation cohort (n = 119) based on examination time, using a 7:3 ratio. Patients were categorized into VPI-positive and VPI-negative groups according to the pathological diagnosis. The CT features were analyzed, including pleural end characteristics, tumor signs, and tumor-pleural features. Multivariate logistic regression analyses were performed to screen the optimal combination of variables for predicting VPI. Based on these variables, a predictive model and corresponding nomogram were developed, and their predictive performance was evaluated using external validation cohort (n = 101). According to the type of tumor-pleural contact, it was divided into indirect and direct contact types. Subgroup analyses were subsequently performed for each category to identify CT features indicative of VPI.
resultsMultivariable logistic regression analysis identified the optimal combination of predictor variables, including solid component diameter, tumor-pleura relationship, vacuole sign, vascular convergence sign, and soft tissue density shadow of pleural end. Among them, solid component diameter (OR = 1.17), the Type III classification of the tumor-pleura relationship (OR = 7.43), Type IV (OR = 37.22), and Type V (OR = 13.62) were independent risk factors. The AUC values of the model for predicting VPI in three cohorts were 0.833, 0.781, and 0.796, respectively. Subgroup analysis further revealed that solid component diameter (OR = 1.12), Type IV tumor-pleura relationship (OR = 27.63), vascular convergence sign (OR = 10.68) and soft tissue density shadow of pleural end (OR = 10.48) were independent risk factors for indirect contact type, whereas solid component diameter (OR = 1.15), Type V tumor-pleura relationship (OR = 4.44), and solid component contact pleura (OR = 6.23) were independent risk factors for direct contact type.
conclusionsThe model based on CT features demonstrated acceptable diagnostic efficacy in predicting VPI. The types of tumor-pleural contact are different, and there are differences in CT predictive variables.
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