RATIONALE AND OBJECTIVES: This study evaluated the performance of computed tomography (CT)-derived biomechanical based features of lung function and the presence and severity of chronic obstructive pulmonary disease (COPD). It performed well when compared to CT-derived density and textural features of lung function and the presence and severity of COPD. MATERIALS AND METHODS: A total of 162 subjects (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stages 0-4 and nonsmokers) subjects with CT scan performed at total lung capacity or expiration to functional residual capacity were evaluated. CT-derived biomechanical, density, and textural feature sets were compared to forced expiratory volume in 1 second (FEV1)%, FEV1/forced vital capacity, and total St. George's respiratory questionnaire scores. The ability of these feature sets to assess the presence and severity of COPD was also evaluated. Optimal features are selected by linear forward feature selection and the classification is done using k nearest neighbor learning algorithm. RESULTS: The proposed biomechanical features showed good correlations with the pulmonary function tests and health status metrics. In COPD versus non-COPD classification, biomechanical feature set achieved an area under the curve (AUC) of 0.85 performing well in comparison to density (AUC = 0.83) and texture (AUC = 0.89) feature sets. Classifying the subjects into the severity of GOLD stage using biomechanical features (AUC = 0.81) performed better than the density- and texture-based feature sets, AUC = 0.76 and 0.73, respectively. The biomechanical features performed better alone than in combination with the other two feature sets. CONCLUSION: This study shows the effectiveness of CT-derived biomechanical measures in the assessment of airflow obstruction and quality of life in subjects with COPD. CT-derived biomechanical features performed well in assessing the presence and severity of COPD.
RATIONALE AND OBJECTIVES: This study evaluated the performance of computed tomography (CT)-derived biomechanical based features of lung function and the presence and severity of chronic obstructive pulmonary disease (COPD). It performed well when compared to CT-derived density and textural features of lung function and the presence and severity of COPD. MATERIALS AND METHODS: A total of 162 subjects (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stages 0-4 and nonsmokers) subjects with CT scan performed at total lung capacity or expiration to functional residual capacity were evaluated. CT-derived biomechanical, density, and textural feature sets were compared to forced expiratory volume in 1 second (FEV1)%, FEV1/forced vital capacity, and total St. George's respiratory questionnaire scores. The ability of these feature sets to assess the presence and severity of COPD was also evaluated. Optimal features are selected by linear forward feature selection and the classification is done using k nearest neighbor learning algorithm. RESULTS: The proposed biomechanical features showed good correlations with the pulmonary function tests and health status metrics. In COPD versus non-COPD classification, biomechanical feature set achieved an area under the curve (AUC) of 0.85 performing well in comparison to density (AUC = 0.83) and texture (AUC = 0.89) feature sets. Classifying the subjects into the severity of GOLD stage using biomechanical features (AUC = 0.81) performed better than the density- and texture-based feature sets, AUC = 0.76 and 0.73, respectively. The biomechanical features performed better alone than in combination with the other two feature sets. CONCLUSION: This study shows the effectiveness of CT-derived biomechanical measures in the assessment of airflow obstruction and quality of life in subjects with COPD. CT-derived biomechanical features performed well in assessing the presence and severity of COPD.
Authors: E Spaggiari; M Zompatori; A Verduri; A Chetta; C Bnà; F Ormitti; N Sverzellati; E Rabaiotti Journal: Radiol Med Date: 2005 Jan-Feb Impact factor: 3.469
Authors: R Uppaluri; E A Hoffman; M Sonka; P G Hartley; G W Hunninghake; G McLennan Journal: Am J Respir Crit Care Med Date: 1999-08 Impact factor: 21.405
Authors: M Mishima; T Hirai; H Itoh; Y Nakano; H Sakai; S Muro; K Nishimura; Y Oku; K Chin; M Ohi; T Nakamura; J H Bates; A M Alencar; B Suki Journal: Proc Natl Acad Sci U S A Date: 1999-08-03 Impact factor: 11.205
Authors: J W Gurney; K K Jones; R A Robbins; G L Gossman; K J Nelson; D Daughton; J R Spurzem; S I Rennard Journal: Radiology Date: 1992-05 Impact factor: 11.105
Authors: Kirsten L Boedeker; Michael F McNitt-Gray; Sarah R Rogers; Dao A Truong; Matthew S Brown; David W Gjertson; Jonathan G Goldin Journal: Radiology Date: 2004-07 Impact factor: 11.105
Authors: Klaus F Rabe; Suzanne Hurd; Antonio Anzueto; Peter J Barnes; Sonia A Buist; Peter Calverley; Yoshinosuke Fukuchi; Christine Jenkins; Roberto Rodriguez-Roisin; Chris van Weel; Jan Zielinski Journal: Am J Respir Crit Care Med Date: 2007-05-16 Impact factor: 21.405
Authors: Sandeep Bodduluri; Surya P Bhatt; Eric A Hoffman; John D Newell; Carlos H Martinez; Mark T Dransfield; Meilan K Han; Joseph M Reinhardt Journal: Thorax Date: 2017-01-02 Impact factor: 9.139
Authors: Surya P Bhatt; Sandeep Bodduluri; John D Newell; Eric A Hoffman; Jessica C Sieren; Meilan K Han; Mark T Dransfield; Joseph M Reinhardt Journal: Acad Radiol Date: 2016-04-04 Impact factor: 3.173
Authors: Marko Topalovic; Vasileios Exadaktylos; Marc Decramer; Thierry Troosters; Daniel Berckmans; Wim Janssens Journal: Med Biol Eng Comput Date: 2014-09-30 Impact factor: 2.602
Authors: Surya P Bhatt; Sandeep Bodduluri; Eric A Hoffman; John D Newell; Jessica C Sieren; Mark T Dransfield; Joseph M Reinhardt Journal: Am J Respir Crit Care Med Date: 2017-09-01 Impact factor: 21.405
Authors: Surya P Bhatt; George R Washko; Eric A Hoffman; John D Newell; Sandeep Bodduluri; Alejandro A Diaz; Craig J Galban; Edwin K Silverman; Raúl San José Estépar; David A Lynch Journal: Am J Respir Crit Care Med Date: 2019-02-01 Impact factor: 21.405