Am. J. Respir. Crit. Care Med., Volume 159, Number 2, February 1999, 519-525

Interstitial Lung Disease
A Quantitative Study Using the Adaptive Multiple Feature Method

RENUKA UPPALURI, ERIC A. HOFFMAN, MILAN SONKA, GARY W. HUNNINGHAKE, and GEOFFREY MCLENNAN

Department of Electrical and Computer Engineering, Department of Radiology, Biomedical Engineering, Department of Internal Medicine, University of Iowa, Iowa City, Iowa

We have previously described an adaptive multiple feature method (AMFM) for the objective assessment of global and regional changes in pulmonary parenchyma to detect emphysema. This computerized method uses a combination of statistical and fractal texture features for characterization of lung tissues based upon high resolution computed tomography (HRCT) scans. This present study was a substantial extension of the AMFM to simultaneously discriminate between multiple pulmonary disease processes. Normal subjects and those with emphysema, idiopathic pulmonary fibrosis (IPF), or sarcoidosis were studied. The AMFM was compared with two currently utilized computer-based methods: mean lung density (MLD) and the histogram analysis (HIST). Globally, when comparing two-subject groups the AMFM overall accuracy was 2 to 18% better than the overall accuracy of MLD and as much as 36% better than the accuracy of the HIST methods. In three-subject group discrimination tasks, the AMFM performed 7 to 27% better than the MLD and 4 to 36% better than the HIST methods. Finally, in discriminating all four subject groups at a time, the AMFM overall accuracy was 81%, which was 21% better than the MLD and 25% better than the HIST method. In most three-subject group comparisons and in the four-subject group comparison, the AMFM was significantly (p < 0.01) better than the MLD and HIST methods. Next, the AMFM was applied to local discrimination between normal and each disease group individually. The normal versus emphysema, normal versus IPF, and normal versus sarcoidosis samples were discriminated with an accuracy of 95, 86, and 77%, respectively. The AMFM is an objective quantitative method that can be adapted for successful discrimination of multiple parenchymal lung diseases.

This article has been cited by other articles:

				C. S. Rogers, W. M. Abraham, K. A. Brogden, J. F. Engelhardt, J. T. Fisher, P. B. McCray Jr., G. McLennan, D. K. Meyerholz, E. Namati, L. S. Ostedgaard, et al. The porcine lung as a potential model for cystic fibrosis Am J Physiol Lung Cell Mol Physiol, August 1, 2008; 295(2): L240 - L263. [Abstract] [Full Text] [PDF]

				A. C. Best, J. Meng, A. M. Lynch, C. M. Bozic, D. Miller, G. K. Grunwald, and D. A. Lynch Idiopathic Pulmonary Fibrosis: Physiologic Tests, Quantitative CT Indexes, and CT Visual Scores as Predictors of Mortality Radiology, March 1, 2008; 246(3): 935 - 940. [Abstract] [Full Text] [PDF]

				M. Cazzola, W. MacNee, F. J. Martinez, K. F. Rabe, L. G. Franciosi, P. J. Barnes, V. Brusasco, P. S. Burge, P. M. A. Calverley, B. R. Celli, et al. Outcomes for COPD pharmacological trials: from lung function to biomarkers Eur. Respir. J., February 1, 2008; 31(2): 416 - 469. [Abstract] [Full Text] [PDF]

				E. A. Hoffman, B. A. Simon, and G. McLennan State of the Art. A Structural and Functional Assessment of the Lung via Multidetector-Row Computed Tomography: Phenotyping Chronic Obstructive Pulmonary Disease Proceedings of the ATS, August 1, 2006; 3(6): 519 - 532. [Abstract] [Full Text] [PDF]

				D G Parr, B C Stoel, J Stolk, and R A Stockley Validation of computed tomographic lung densitometry for monitoring emphysema in {alpha}1-antitrypsin deficiency Thorax, June 1, 2006; 61(6): 485 - 490. [Abstract] [Full Text] [PDF]

				S. Misumi and D. A. Lynch Idiopathic pulmonary fibrosis/usual interstitial pneumonia: imaging diagnosis, spectrum of abnormalities, and temporal progression. Proceedings of the ATS, January 1, 2006; 3(4): 307 - 314. [Abstract] [Full Text] [PDF]

				D. A. Lynch, J. D. Godwin, S. Safrin, K. M. Starko, P. Hormel, K. K. Brown, G. Raghu, T. E. King Jr., W. Z. Bradford, D. A. Schwartz, et al. High-Resolution Computed Tomography in Idiopathic Pulmonary Fibrosis: Diagnosis and Prognosis Am. J. Respir. Crit. Care Med., August 15, 2005; 172(4): 488 - 493. [Abstract] [Full Text] [PDF]

				R. M. Summers Road Maps for Advancement of Radiologic Computer-aided Detection in the 21st Century Radiology, October 1, 2003; 229(1): 11 - 13. [Full Text] [PDF]

				K. R. Flaherty, J. A. Mumford, S. Murray, E. A. Kazerooni, B. H. Gross, T. V. Colby, W. D. Travis, A. Flint, G. B. Toews, J. P. Lynch III, et al. Prognostic Implications of Physiologic and Radiographic Changes in Idiopathic Interstitial Pneumonia Am. J. Respir. Crit. Care Med., September 1, 2003; 168(5): 543 - 548. [Abstract] [Full Text] [PDF]

				A. C. Best, A. M. Lynch, C. M. Bozic, D. Miller, G. K. Grunwald, and D. A. Lynch Quantitative CT Indexes in Idiopathic Pulmonary Fibrosis: Relationship with Physiologic Impairment Radiology, August 1, 2003; 228(2): 407 - 414. [Abstract] [Full Text] [PDF]

				N.L. Muller Advances in imaging Eur. Respir. J., November 1, 2001; 18(5): 867 - 871. [Abstract] [Full Text] [PDF]

				E. A. Kazerooni High-Resolution CT of the Lungs Am. J. Roentgenol., September 1, 2001; 177(3): 501 - 519. [Full Text] [PDF]

				R. UPPALURI, E. A. HOFFMAN, M. SONKA, P. G. HARTLEY, G. W. HUNNINGHAKE, and G. MCLENNAN Computer Recognition of Regional Lung Disease Patterns Am. J. Respir. Crit. Care Med., August 1, 1999; 160(2): 648 - 654. [Abstract] [Full Text]