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    Online-Ressource
    Online-Ressource
    Oxford University Press (OUP) ; 2022
    In:  Interactive CardioVascular and Thoracic Surgery Vol. 35, No. 2 ( 2022-07-09)
    In: Interactive CardioVascular and Thoracic Surgery, Oxford University Press (OUP), Vol. 35, No. 2 ( 2022-07-09)
    Kurzfassung: OBJECTIVES We compared the computed tomographic (CT) volumetric analysis and anatomical segment counting (ASC) for predicting postoperative forced expiratory volume in 1 s (FEV1) and diffusing capacity for carbon monoxide (DLCO) in patients who had segmentectomy for early-stage lung cancer. METHODS A total of 175 patients who had segmentectomy for lung cancer and had postoperative pulmonary function test were included. CT volumetric analysis was performed by software, which could measure total lung and target segment volume from CT images. ASC and CT volumetric analysis were used to determine predicted postoperative (PPO) values and the concordance and difference of these values were assessed. The relationship between PPO values and actual postoperative values was also investigated. RESULTS The PPO-FEV1 and PPO-DLCO showed high concordance between 2 methods (concordance correlation coefficient = 0.96 for PPO-FEV1 and 0.95 for PPO-DLCO). There was no significant difference between PPO values as determined by 2 methods (P = 0.53 for PPO-FEV1, P = 0.25 for PPO-DLCO) and actual postoperative values [P = 0.77 (ASC versus actual) and P = 0.20 (CT versus actual) for FEV1; P = 0.41 (ASC versus actual) and P = 0.80 (CT versus actual) for DLCO]. We subdivided the patients according to poor pulmonary function test, the number of resected segments and the location of the resected lobe. All subgroup analyses revealed no significant difference between PPO values and actual postoperative values. CONCLUSIONS Both CT volumetric analysis and ASC showed high predictability for actual postoperative FEV1 and DLCO in segmentectomy.
    Materialart: Online-Ressource
    ISSN: 1569-9285
    Sprache: Englisch
    Verlag: Oxford University Press (OUP)
    Publikationsdatum: 2022
    ZDB Id: 2096257-5
    ZDB Id: 3167862-2
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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