Prediction of post-operative pulmonary function after lobectomy for primary lung cancer: A comparison among counting method, effective lobar volume, and lobar collapsibility using inspiratory/expiratory CT

Hidetake Yabuuchi, Satoshi Kawanami, Takeshi Kamitani, Masato Yonezawa, Yuzo Yamasaki, Torahiko Yamanouchi, Michinobu Nagao, Tatsuro Okamoto, Hiroshi Honda

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7 Citations (Scopus)

Abstract

Purpose To compare the predictabilities of postoperative pulmonary function after lobectomy for primary lung cancer among counting method, effective lobar volume, and lobar collapsibility. Methods Forty-nine patients who underwent lobectomy for primary lung cancer were enrolled. All patients underwent inspiratory/expiratory CT and pulmonary function tests 2 weeks before surgery and postoperative pulmonary function tests 6–7 months after surgery. Pulmonary function losses (ΔFEV1.0 and ΔVC) were calculated from the pulmonary function tests. Predictive postoperative pulmonary function losses (ppoΔFEV1.0 and ppoΔVC) were calculated using counting method, effective volume, and lobar collapsibility. Correlations and agreements between ΔFEV1.0 and ppoFEV1.0 and those between ΔVC and ppoΔVC were tested among three methods using Spearman's correlation coefficient and Bland-Altman plots. Results ΔFEV1.0 and ppoΔFEV1.0insp-exp were strongly correlated (r = 0.72), whereas ΔFEV1.0 and ppoΔFEV1.0count and ΔFEV1.0 and Pred. ΔFEV1.0eff.vol. were moderately correlated (r = 0.50, 0.56). ΔVC and ppoΔVCeff.vol. (r = 0.71) were strongly correlated, whereas ΔVC and ppoΔVCcount, and ΔVC and ppoΔVC insp-exp were moderately correlated (r = 0.55, 0.42). Conclusions Volumetry from inspiratory/expiratory CT data could be useful to predict postoperative pulmonary function after lobectomy for primary lung cancer.

Original languageEnglish
Pages (from-to)1956-1962
Number of pages7
JournalEuropean Journal of Radiology
Volume85
Issue number11
DOIs
Publication statusPublished - Nov 1 2016

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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