Lucía Fernández-Rodríguez1, Isabel Torres1, Delia Romera2, Raúl Galera3, Raquel Casitas3, Elisabet Martínez-Cerón3, Prudencio Díaz-Agero4, Cristina Utrilla1, Francisco García-Río5. 1. Servicio de Radiodiagnóstico, Hospital Universitario La Paz, Madrid, Spain. 2. Servicio de Neumología, Hospital Universitario La Paz, IdiPAZ, Madrid, Spain. 3. Servicio de Neumología, Hospital Universitario La Paz, IdiPAZ, Madrid, Spain; CIBER de Enfermedades Respiratorias, Madrid, Spain. 4. Servicio de Cirugía Torácica, Hospital Universitario La Paz, IdiPAZ, Madrid, Spain. 5. Servicio de Neumología, Hospital Universitario La Paz, IdiPAZ, Madrid, Spain; CIBER de Enfermedades Respiratorias, Madrid, Spain; Facultad de Medicina, Universidad Autónoma de Madrid, Madrid, Spain. Electronic address: fgr01m@gmail.com.
Abstract
OBJECTIVES: The study objectives were to assess the accuracy of volumetric computed tomography to predict postoperative lung function in patients with lung cancer in relation to anatomic segments counting and perfusion scintigraphy, to generate specific predictive equations for each functional parameter, and to evaluate accuracy and precision of these in a validation cohort. METHODS: We assessed pulmonary functions preoperatively and 3 to 4 months postoperatively after lung resection for lung cancer (n = 114). Absolute and relative lung volumes (total and upper/middle/lower) were determined using volumetric software analysis for staging thoracic computed tomography scans. Predicted postoperative function was calculated by segments counting, scintigraphy, and volumetric computed tomography. RESULTS: Volumetric computed tomography achieves a higher correlation and precision with measured postoperative lung function than segments counting or scintigraphy (correlation and intraclass correlation coefficients, 0.779-0.969 and 0.776-0.969; 0.573-0.887 and 0.552-0.882; and 0.578-0.834 and 0.532-0.815, respectively), as well as greater accuracy, determined by narrower agreement coefficients for forced vital capacity, forced expiratory volume in 1 second, lung diffusing capacity, and peak oxygen uptake. After validation in an independent cohort (n = 43), adjusted linear regression including volumetric estimation of decreased postoperative ventilation for postoperative lung function parameters explains 98% to 99% of variance. CONCLUSIONS: Volumetric computed tomography is a reliable and accurate method to predict postoperative lung function in patients undergoing lung resection that provides better accuracy than conventional procedures. Because lung computed tomography is systematically performed in the staging of patients with suspected lung cancer, this volumetric analysis might simultaneously provide the information necessary to evaluate operability.
OBJECTIVES: The study objectives were to assess the accuracy of volumetric computed tomography to predict postoperative lung function in patients with lung cancer in relation to anatomic segments counting and perfusion scintigraphy, to generate specific predictive equations for each functional parameter, and to evaluate accuracy and precision of these in a validation cohort. METHODS: We assessed pulmonary functions preoperatively and 3 to 4 months postoperatively after lung resection for lung cancer (n = 114). Absolute and relative lung volumes (total and upper/middle/lower) were determined using volumetric software analysis for staging thoracic computed tomography scans. Predicted postoperative function was calculated by segments counting, scintigraphy, and volumetric computed tomography. RESULTS: Volumetric computed tomography achieves a higher correlation and precision with measured postoperative lung function than segments counting or scintigraphy (correlation and intraclass correlation coefficients, 0.779-0.969 and 0.776-0.969; 0.573-0.887 and 0.552-0.882; and 0.578-0.834 and 0.532-0.815, respectively), as well as greater accuracy, determined by narrower agreement coefficients for forced vital capacity, forced expiratory volume in 1 second, lung diffusing capacity, and peak oxygen uptake. After validation in an independent cohort (n = 43), adjusted linear regression including volumetric estimation of decreased postoperative ventilation for postoperative lung function parameters explains 98% to 99% of variance. CONCLUSIONS: Volumetric computed tomography is a reliable and accurate method to predict postoperative lung function in patients undergoing lung resection that provides better accuracy than conventional procedures. Because lung computed tomography is systematically performed in the staging of patients with suspected lung cancer, this volumetric analysis might simultaneously provide the information necessary to evaluate operability.