Robust imaging approach for precise prediction of postoperative lung function in lung cancer patients prior to curative operation

Abstract

AbstractBackgroundTo create a combined variable integrating both ventilation and perfusion as measured by preoperative dual‐energy computed tomography (DECT), compare the results with predicted postoperative (PPO) lung function as estimated using conventional methods, and assess agreement with actual postoperative lung function.MethodsA total of 33 patients with lung cancer who underwent curative surgery after DECT and perfusion scan were selected. Ventilation and perfusion values were generated from DECT data. In the “combined variable method,” these two variables and clinical variables were linearly regressed to estimate PPO lung function. Six PPO lung function parameters (segment counting, perfusion scan, volume analysis, ventilation map, perfusion map, and combined variable) were compared with actual postoperative lung function using an intraclass correlation coefficient (ICC).ResultsThe segment counting method produced the highest ICC for forced vital capacity (FVC) at 0.93 (p < 0.05), while the segment counting and perfusion map methods produced the highest ICC for forced expiratory volume in 1 second (FEV1; both 0.89, p < 0.05). The highest ICC value when using the combined variable method was for FEV1/FVC (0.75, p < 0.05) and diffusing capacity of the lung for carbon monoxide (DLco; 0.80, p < 0.05) when using the perfusion map method. Overall, the perfusion map and ventilation map provided the best performance, followed by volume analysis, segment counting, perfusion scan, and the combined variable.ConclusionsUse of DECT image processing to predict postoperative lung function produced better agreement with actual postoperative lung function than conventional methods. The combined variable method produced ICC values of 0.8 or greater for FVC and FEV1.