The differential computed tomography features between small benign and malignant solid solitary pulmonary nodules with different sizes.

ABSTRACT

Background: Computed tomography (CT) has been widely known to be the first choice for the diagnosis of solid solitary pulmonary nodules (SSPNs). However, the smaller the SSPN is, the less the differential CT signs between benign and malignant SSPNs there are, which brings great challenges to their diagnosis. Therefore, this study aimed to investigate the differential CT features between small (≤15 mm) benign and malignant SSPNs with different sizes. Methods: From May 2018 to November 2021, CT data of 794 patients with small SSPNs (≤15 mm) were retrospectively analyzed. SSPNs were divided into benign and malignant groups, and each group was further classified into three cohorts cohort I (diameter ≤6 mm), cohort II (6 mm < diameter ≤8 mm), and cohort III (8 mm < diameter ≤15 mm). The differential CT features of benign and malignant SSPNs in three cohorts were identified. Multivariable logistic regression analyses were conducted to identify independent factors of benign SSPNs. Results: In cohort I, polygonal shape and upper-lobe distribution differed significantly between groups (all P<0.05) and multiparametric analysis showed polygonal shape [adjusted odds ratio (OR) 12.165; 95% confidence interval (CI) 1.512-97.872; P=0.019] was the most effective variation for predicting benign SSPNs, with an area under the receiver operating characteristic curve (AUC) of 0.747 (95% CI 0.640-0.855; P=0.001). In cohort II, polygonal shape, lobulation, pleural retraction, and air bronchogram differed significantly between groups (all P<0.05), and polygonal shape (OR 8.870; 95% CI 1.096-71.772; P=0.041) and the absence of pleural retraction (OR 0.306; 95% CI 0.106-0.883; P=0.028) were independent predictors of benign SSPNs, with an AUC of 0.778 (95% CI 0.694-0.863; P<0.001). In cohort III, 12 CT features showed significant differences between groups (all P<0.05) and polygonal shape (OR 3.953; 95% CI 1.508-10.361; P=0.005); calcification (OR 3.710; 95% CI 1.305-10.551; P=0.014); halo sign (OR 6.237; 95% CI 2.838-13.710; P<0.001); satellite lesions (OR 6.554; 95% CI 3.225-13.318; P<0.001); and the absence of lobulation (OR 0.066; 95% CI 0.026-0.167; P<0.001), air space (OR 0.405; 95% CI 0.215-0.764; P=0.005), pleural retraction (OR 0.297; 95% CI 0.179-0.493; P<0.001), bronchial truncation (OR 0.165; 95% CI 0.090-0.303; P<0.001), and air bronchogram (OR 0.363; 95% CI 0.208-0.633; P<0.001) were independent predictors of benign SSPNs, with an AUC of 0.869 (95% CI 0.840-0.897; P<0.001). Conclusions: CT features vary between SSPNs with different sizes. Clarifying the differential CT features based on different diameter ranges may help to minimize ambiguities and discriminate the benign SSPNs from malignant ones.