Prediction of postoperative lung function has a key role in the proposed algorithm; however, we believe that the proposed method of performing this prediction, especially in case of lobectomy, is not optimal. The anatomic method based on the formula predicted postoperative FEV1 = preoperative FEV1 × (1 − y/z), where y is the functional or unobstructed lung segments to be removed, and z is the total functional segments, was proposed by Bolliger et al2 as a simpler alternative to the Nakahara formula (which took into account functional subsegments), since its predictive capability was equal to the latter. However, quantitative CT imaging has been tested in the prediction of postoperative lung function and has yielded more accurate predictions than the segment-counting method. Ueda et al3 demonstrated that volumetric analysis via quantitative CT imaging was better for estimating the functional contribution of a specific lung lobe, compared with segment counting, especially in cases where the functional contribution of every segment varies due to underlying diseases such as pulmonary emphysema or fibrosis, which may be heterogeneously distributed. Ohno et al4 demonstrated that the correlation coefficient was lower and the limits of agreement of the anatomic method were larger than those of quantitative CT imaging. Yoshimoto et al5 confirmed that the segment-counting method is inferior to quantitative CT imaging for predicting postoperative lung function after lobectomy.