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Automated quantification of radiologic patterns predicts survival in idiopathic pulmonary fibrosis

Fabien Maldonado, Teng Moua, Srinivasan Rajagopalan, Ronald A. Karwoski, Sushravya Raghunath, Paul A. Decker, Thomas E. Hartman, Brian J. Bartholmai, Richard A. Robb, Jay H. Ryu
European Respiratory Journal 2013; DOI: 10.1183/09031936.00071812
Fabien Maldonado
*Division of Pulmonary and Critical Care, Mayo Clinic Rochester
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  • For correspondence: Maldonado.Fabien@mayo.edu
Teng Moua
*Division of Pulmonary and Critical Care, Mayo Clinic Rochester
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Srinivasan Rajagopalan
¶Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester
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Ronald A. Karwoski
¶Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester
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Sushravya Raghunath
¶Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester
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Paul A. Decker
+Dept of Biomedical Statistics and Informatics
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Thomas E. Hartman
#Division of Radiology, Mayo Clinic Rochester
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Brian J. Bartholmai
#Division of Radiology, Mayo Clinic Rochester
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Richard A. Robb
¶Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester
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Jay H. Ryu
*Division of Pulmonary and Critical Care, Mayo Clinic Rochester
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Abstract

Accurate assessment of prognosis in idiopathic pulmonary fibrosis (IPF) remains elusive due to significant individual radiologic and physiologic variability. We hypothesized that short term radiologic changes may be predictive of survival.

We explored the use of CALIPER (Computer-Aided Lung Informatics for Pathology Evaluation and Rating), a novel software tool developed by the Biomedical Imaging Resource Lab at Mayo Clinic, for the analysis and quantification of parenchymal lung abnormalities on high-resolution computed tomography (HRCT). We assessed baseline and follow-up (time point 1 and 2, respectively) HRCT scans in 55 selected IPF patients and correlated CALIPER-quantified measurements with expert radiologists' assessments and clinical outcomes.

Findings of interval change (mean 289 days) in volume of reticular densities (HR 1.91, P=0.006), total volume of interstitial abnormalities (HR 1.70, P=0.003) and percent total interstitial abnormalities (HR 1.52, P=0.017) as quantified by CALIPER were predictive of survival after a median follow-up of 2.4 years. Radiologist interpretation of short term global ILD progression but not specific radiologic features was also predictive of mortality.

These data demonstrate the feasibility of quantifying interval short term changes on HRCT and their possible use as independent predictors of survival in IPF.

  • Computed tomography
  • idiopathic pulmonary fibrosis
  • survival
  • ERS
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European Respiratory Journal: 61 (1)
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Automated quantification of radiologic patterns predicts survival in idiopathic pulmonary fibrosis
Fabien Maldonado, Teng Moua, Srinivasan Rajagopalan, Ronald A. Karwoski, Sushravya Raghunath, Paul A. Decker, Thomas E. Hartman, Brian J. Bartholmai, Richard A. Robb, Jay H. Ryu
European Respiratory Journal Jan 2013, erj00718-2012; DOI: 10.1183/09031936.00071812

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Automated quantification of radiologic patterns predicts survival in idiopathic pulmonary fibrosis
Fabien Maldonado, Teng Moua, Srinivasan Rajagopalan, Ronald A. Karwoski, Sushravya Raghunath, Paul A. Decker, Thomas E. Hartman, Brian J. Bartholmai, Richard A. Robb, Jay H. Ryu
European Respiratory Journal Jan 2013, erj00718-2012; DOI: 10.1183/09031936.00071812
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