Estimating Postoperative Lung Function Using Three-Dimensional Segmental HRCT-Reconstruction: A Retrospective Pilot...

Background/Objectives: Can three-dimensional (3D) reconstruction software that simulates postoperative lung volumes more effectively identify suitable candidates for anatomical lung resection compared to conventional methods, particularly in personalized surgical planning? Patients/Methods: This single-center pilot study included 20 patients (10 females; age 68 ± 10 years) who underwent segmental or lobar VATS resection of the right upper lobe for NSCLC. Three-dimensional simulations from preoperative HRCT scans were correlated with measured pulmonary function and compared with predictions from the "5% per segment rule" and the model proposed by Brunelli et al. Results: Patients (8/20) with increased postoperative FEV1 [2.40 (0.56) vs. 2.30 (0.55)] had a lower proportion of healthy tissue [76 (18)% vs. 89 (10)%, p = 0.045] in 3D simulations than those with decreased FEV1. Mean postoperative FEV1 was 2.3 (0.54); the Brunelli model predicted 1.8 (0.36) and the "5% rule" 2.2 (0.54). Both models underestimated postoperative function, though the "5% rule" was more accurate. Conclusions: This pilot study suggests that 3D-HRCT reconstruction has the potential to facilitate patient-tailored identification of individuals who may derive greater benefit from surgical intervention compared to conventional methods. Further research is needed to determine whether this technology can more accurately predict postoperative pulmonary function in patients with severe COPD. Utilizing 3D-segmental-HRCT-reconstruction software, the advantages of lung resection in the context of NSCLC can be assessed on an individualized patient basis.