Parametric response mapping monitors temporal changes on lung CT scans in the subpopulations and intermediate outcome measures in COPD Study (SPIROMICS).

[1]  P. Paré,et al.  The Diagnosis of Emphysema , 2015 .

[2]  Eric A Hoffman,et al.  Variation in the percent of emphysema-like lung in a healthy, nonsmoking multiethnic sample. The MESA lung study. , 2014, Annals of the American Thoracic Society.

[3]  Raúl San José Estépar,et al.  Distinct quantitative computed tomography emphysema patterns are associated with physiology and function in smokers. , 2013, American journal of respiratory and critical care medicine.

[4]  Lisa M LaVange,et al.  Design of the Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS) , 2013, Thorax.

[5]  David A Lynch,et al.  Quantitative Computed Tomography in Chronic Obstructive Pulmonary Disease , 2013, Journal of thoracic imaging.

[6]  Raúl San José Estépar,et al.  Computed tomographic measures of pulmonary vascular morphology in smokers and their clinical implications. , 2013, American journal of respiratory and critical care medicine.

[7]  P. Barnes.  New anti-inflammatory targets for chronic obstructive pulmonary disease , 2013, Nature Reviews Drug Discovery.

[8]  Henrietta Creasy,et al.  Pulmonary arterial enlargement and acute exacerbations of COPD , 2013, Thorax.

[9]  C. Hsia,et al.  Quantifying heterogeneity in emphysema from high-resolution computed tomography: a lung tissue research consortium study. , 2013, Academic radiology.

[10]  F. Martinez,et al.  Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. , 2007, American journal of respiratory and critical care medicine.

[11]  Joyce D. Schroeder,et al.  Automated texture-based quantification of centrilobular nodularity and centrilobular emphysema in chest CT images. , 2012, Academic radiology.

[12]  A. Bankier,et al.  Chronic obstructive pulmonary disease: CT quantification of airways disease. , 2012, Radiology.

[13]  P F Judy,et al.  Reference standard and statistical model for intersite and temporal comparisons of CT attenuation in a multicenter quantitative lung study. , 2012, Medical physics.

[14]  Ella A. Kazerooni,et al.  CT-based Biomarker Provides Unique Signature for Diagnosis of COPD Phenotypes and Disease Progression , 2012, Nature Medicine.

[15]  Marleen de Bruijne,et al.  Toward automatic regional analysis of pulmonary function using inspiration and expiration thoracic CT. , 2012, Medical physics.

[16]  B. van Ginneken,et al.  Computed tomography-quantified emphysema distribution is associated with lung function decline , 2012, European Respiratory Journal.

[17]  Warren B. Gefter,et al.  The n e w e n g l a n d j o u r n a l of m e d i c i n e , 2011 .

[18]  B. Celli,et al.  Addressing the complexity of chronic obstructive pulmonary disease: from phenotypes and biomarkers to scale-free networks, systems biology, and P4 medicine. , 2011, American journal of respiratory and critical care medicine.

[19]  E. V. van Beek,et al.  Heterogeneity of pulmonary perfusion as a mechanistic image-based phenotype in emphysema susceptible smokers , 2010, Proceedings of the National Academy of Sciences.

[20]  Raúl San José Estépar,et al.  Quantitative CT measurement of cross-sectional area of small pulmonary vessel in COPD: correlations with emphysema and airflow limitation. , 2010, Academic radiology.

[21]  Ulrike Held,et al.  Expansion of the prognostic assessment of patients with chronic obstructive pulmonary disease: the updated BODE index and the ADO index , 2009, The Lancet.

[22]  E. Hoffman,et al.  A multivariate analysis of risk factors for the air-trapping asthmatic phenotype as measured by quantitative CT analysis. , 2009, Chest.

[23]  Eric A. Hoffman,et al.  Registration-based estimates of local lung tissue expansion compared to xenon CT measures of specific ventilation , 2008, Medical Image Anal..

[24]  Kunihiro Yagihashi,et al.  Quantitative assessment of air trapping in chronic obstructive pulmonary disease using inspiratory and expiratory volumetric MDCT. , 2008, AJR. American journal of roentgenology.

[25]  P. Barnes.  Immunology of asthma and chronic obstructive pulmonary disease , 2008, Nature Reviews Immunology.

[26]  D. Mannino,et al.  Global burden of COPD: risk factors, prevalence, and future trends , 2007, The Lancet.

[27]  D. Morrow,et al.  Benchmarks for the Assessment of Novel Cardiovascular Biomarkers , 2007, Circulation.

[28]  J. Bousquet,et al.  [Global alliance against chronic respiratory diseases]. , 2006, Pneumonologia i alergologia polska.

[29]  Ye Xu,et al.  MDCT-based 3-D texture classification of emphysema and early smoking related lung pathologies , 2006, IEEE Transactions on Medical Imaging.

[30]  J. Janssens.  Aging of the respiratory system: impact on pulmonary function tests and adaptation to exertion. , 2005, Clinics in chest medicine.

[31]  Ciro Casanova,et al.  The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. , 2004, The New England journal of medicine.

[32]  P. Paré,et al.  Computed tomographic measurements of airway dimensions and emphysema in smokers. Correlation with lung function. , 2000, American journal of respiratory and critical care medicine.

[33]  B Suki,et al.  Complexity of terminal airspace geometry assessed by lung computed tomography in normal subjects and patients with chronic obstructive pulmonary disease. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[34]  D. Lynch,et al.  Quantitative computed tomography detects air trapping due to asthma. , 1994, Chest.

[35]  P. Paré,et al.  The diagnosis of emphysema. A computed tomographic-pathologic correlation. , 1986, The American review of respiratory disease.

[36]  J. Mead,et al.  Elasticity of human lungs in relation to age. , 1968, Journal of applied physiology.