The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers

Academic Radiology

Volumn 24, Issue 8, 2017, Pages 941-946

  Ash, Samuel Y ^a   Harmouche, Rola ^a   Ross, James C ^a   Diaz, Alejandro A ^a   Hunninghake, Gary M ^a   Putman, Rachel K ^a   Onieva, Jorge ^a   Martinez, Fernando J ^b   Choi, Augustine M ^b   Lynch, David A ^c   Hatabu, Hiroto ^a   Rosas, Ivan O ^a   Estepar, Raul San Jose ^a   Washko, George R ^a  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b WEILL CORNELL MEDICAL COLLEGE   (United States)

^c DEPARTMENT OF MEDICINE   (United States)

Author keywords

cigarettes; CT scanner; diffuse parenchymal lung diseases; idiopathic; interstitial; pneumonia; Pulmonary fibrosis; x ray

Indexed keywords

ADULT; ALGORITHM; ARTICLE; AUTOMATION; COHORT ANALYSIS; COMPUTED TOMOGRAPHY SCANNER; CONE BEAM COMPUTED TOMOGRAPHY; DIAGNOSTIC TEST ACCURACY STUDY; FEMALE; HISTOGRAM; HUMAN; IMAGE PROCESSING; INTERSTITIAL LUNG DISEASE; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; OBSERVATIONAL STUDY; PLEURA; PRIORITY JOURNAL; QUANTITATIVE DIAGNOSIS; SENSITIVITY AND SPECIFICITY; SMOKING; THORAX RADIOGRAPHY; AGED; CIGARETTE SMOKING; DIAGNOSTIC IMAGING; LUNG; PARENCHYMA; REPRODUCIBILITY; X-RAY COMPUTED TOMOGRAPHY;

AGED; CIGARETTE SMOKING; COHORT STUDIES; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LUNG; MALE; MIDDLE AGED; PARENCHYMAL TISSUE; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SMOKERS; TOMOGRAPHY, X-RAY COMPUTED;

EID: 85008400958     PISSN: 10766332     EISSN: 18784046     Source Type: Journal    
DOI: 10.1016/j.acra.2016.08.023     Document Type: Article

References (29)

1. Rosas, I.O., Dellaripa, P.F., Lederer, D.J., et al. Interstitial lung disease: NHLBI workshop on the primary prevention of chronic lung diseases. Ann Am Thorac Soc 11:suppl 3 (2014), S169–S177.
2. King, T.E. Jr, Bradford, W.Z., Castro-Bernardini, S., et al. A phase 3 trial of pirfenidone in patients with idiopathic pulmonary fibrosis. N Engl J Med 370 (2014), 2083–2092.
3. Richeldi, L., du Bois, R.M., Raghu, G., et al. Efficacy and safety of nintedanib in idiopathic pulmonary fibrosis. N Engl J Med 370 (2014), 2071–2082.
4. Putman, R.K., Hatabu, H., Araki, T., et al. Association between interstitial lung abnormalities and all-cause mortality. JAMA 315 (2016), 672–681.
5. Washko, G.R., Hunninghake, G.M., Fernandez, I.E., et al. Lung volumes and emphysema in smokers with interstitial lung abnormalities. N Engl J Med 364 (2011), 897–906.
6. Doyle, T.J., Dellaripa, P.F., Batra, K., et al. Functional impact of a spectrum of interstitial lung abnormalities in rheumatoid arthritis. Chest 146 (2014), 41–50.
7. Washko, G.R., Lynch, D.A., Matsuoka, S., et al. Identification of early interstitial lung disease in smokers from the COPDGene Study. Acad Radiol 17 (2010), 48–53.
8. Jin, G.Y., Lynch, D., Chawla, A., et al. Interstitial lung abnormalities in a CT lung cancer screening population: prevalence and progression rate. Radiology 268 (2013), 563–571.
9. Bankier, A.A., De Maertelaer, V., Keyzer, C., et al. Pulmonary emphysema: subjective visual grading versus objective quantification with macroscopic morphometry and thin-section CT densitometry. Radiology 211 (1999), 851–858.
10. Xu, Y., Sonka, M., McLennan, G., et al. MDCT-based 3-D texture classification of emphysema and early smoking related lung pathologies. IEEE Trans Med Imaging 25 (2006), 464–475.
11. Matsuoka, S., Yamashiro, T., Matsushita, S., et al. Quantitative CT evaluation in patients with combined pulmonary fibrosis and emphysema: correlation with pulmonary function. Acad Radiol 22 (2015), 626–631.
12. Iwasawa, T., Asakura, A., Sakai, F., et al. Assessment of prognosis of patients with idiopathic pulmonary fibrosis by computer-aided analysis of CT images. J Thorac Imaging 24 (2009), 216–222.
13. Best, A.C., Lynch, A.M., Bozic, C.M., et al. Quantitative CT indexes in idiopathic pulmonary fibrosis: relationship with physiologic impairment. Radiology 228 (2003), 407–414.
14. Rosas, I.O., Yao, J., Avila, N.A., et al. Automated quantification of high-resolution CT scan findings in individuals at risk for pulmonary fibrosis. Chest 140 (2011), 1590–1597.
15. Bartholmai, B.J., Raghunath, S., Karwoski, R.A., et al. Quantitative computed tomography imaging of interstitial lung diseases. J Thorac Imaging 28 (2013), 298–307.
16. Mendoza, C.S., Washko, G.R., Ross, J.C., et al. Emphysema quantification in a multi-scanner HRCT cohort using local intensity distributions. Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro IEEE International Symposium on Biomedical Imaging, 2012, 474–477.
17. Regan, E.A., Hokanson, J.E., Murphy, J.R., et al. Genetic epidemiology of COPD (COPDGene) study design. COPD 7 (2010), 32–43.
18. Castaldi, P.J., San Jose Estepar, R., Mendoza, C.S., et al. Distinct quantitative computed tomography emphysema patterns are associated with physiology and function in smokers. Am J Respir Crit Care Med 188 (2013), 1083–1090.
19. Ross, J.C., San Jose Estepar, R., Kindlmann, G., et al. Automatic lung lobe segmentation using particles, thin plate splines, and maximum a posteriori estimation. Med Image Comput Comput Assist Interv 13 (2010), 163–171.
20. Botev, Z.I., Grotowski, J.F., Kroese, D.P., Kernel density estimation via diffusion. Ann Stat, 2010, 2916–2957.
21. Snoek, J., Larochelle, H., Adams, R.P., Practical Bayesian optimization of machine learning algorithms. 2012, 2951–2959.
22. Ley, B., Collard, H.R., King, T.E. Jr, Clinical course and prediction of survival in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 183 (2011), 431–440.
23. Raghu, G., Collard, H.R., Egan, J.J., et al. An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med 183 (2011), 788–824.
24. Best, A.C., Meng, J., Lynch, A.M., et al. Idiopathic pulmonary fibrosis: physiologic tests, quantitative CT indexes, and CT visual scores as predictors of mortality. Radiology 246 (2008), 935–940.
25. Coxson, H.O., Hogg, J.C., Mayo, J.R., et al. Quantification of idiopathic pulmonary fibrosis using computed tomography and histology. Am J Respir Crit Care Med 155 (1997), 1649–1656.
26. Hartley, P.G., Galvin, J.R., Hunninghake, G.W., et al. High-resolution CT-derived measures of lung density are valid indexes of interstitial lung disease. J Appl Physiol 76 (1994), 271–277.
27. Kim, H.J., Brown, M.S., Chong, D., et al. Comparison of the quantitative CT imaging biomarkers of idiopathic pulmonary fibrosis at baseline and early change with an interval of 7 months. Acad Radiol 22 (2015), 70–80.
28. Sverzellati, N., Calabro, E., Chetta, A., et al. Visual score and quantitative CT indices in pulmonary fibrosis: relationship with physiologic impairment. Radiol Med (Torino) 112 (2007), 1160–1172.
29. Xu, Y., van Beek, E.J., Hwanjo, Y., et al. Computer-aided classification of interstitial lung diseases via MDCT: 3D adaptive multiple feature method (3D AMFM). Acad Radiol 13 (2006), 969–978.