Three-dimensional analysis to predict recurrence of pure-solid non-small cell lung cancer after segmentectomy

The aim of this study was to assess the solid% using 3D-CT and analyze its potential value in selecting a segmentectomy as the surgical procedure.

A retrospective study was conducted on 198 NSCLC patients who underwent segmentectomy. Of these, 93 cases who were evaluated as pure-solid on 2D-CT scans were included in the analysis. Receiver operating characteristics analysis was used to calculate cut-off levels for prognostic markers. The univariate analysis included variables such as age, whole tumor size, smoking history, gender, 2D-mCT value, whole tumor volume, 3D-mCT value, solid%, solid volume, standardized uptake value, and carcinoembryonic antigen value. Multiple logistic regression analyses were performed to determine the independent variables for the prediction of tumor recurrence.

A cutoff of 71.1% yielded the maximum specificity and sensitivity to predict recurrence based on the solid%. In the group consisted of 62 cases with a solid% of 71.1% or higher on 3D-CT background-matched lobectomy group, the RFS was significantly better (p = 0.046) for the lobectomy group compared to the segmentectomy group. Preoperatively determined variables were used in multiple logistic regression models, revealing that the solid% (p = 0.04) and SUV (p = 0.03) were predictive and independent factors of tumor recurrence.

Solid % on 3D-CT has a potential to predict recurrence after segmentectomy in a group of cases rated as pure solid on 2D-CT. A future prospective study should be conducted to establish optimal treatment strategies for this disease.