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Title: SU-E-QI-14: Quantitative Variogram Detection of Mild, Unilateral Disease in Elastase-Treated Rats

Purpose: Determining the presence of mild or early disease in the lungs can be challenging and subjective. We present a rapid and objective method for evaluating lung damage in a rat model of unilateral mild emphysema based on a new approach to heterogeneity assessment. We combined octree decomposition (used in three-dimensional (3D) computer graphics) with variograms (used in geostatistics to assess spatial relationships) to evaluate 3D computed tomography (CT) lung images for disease. Methods: Male, Sprague-Dawley rats (232 ± 7 g) were intratracheally dosed with 50 U/kg of elastase dissolved in 200 μL of saline to a single lobe (n=6) or with saline only (n=5). After four weeks, 3D micro-CT images were acquired at end expiration on mechanically ventilated rats using prospective gating. Images were masked, and lungs were decomposed to homogeneous blocks of 2×2×2, 4×4×4, and 8×8×8 voxels using octree decomposition. The spatial variance – the square of the difference of signal intensity – between all pairs of the 8×8×8 blocks was calculated. Variograms – graphs of distance vs. variance - were made, and data were fit to a power law and the exponent determined. The mean HU values, coefficient of variation (CoV), and the emphysema index (EI) weremore » calculated and compared to the variograms. Results: The variogram analysis showed that significant differences between groups existed (p<0.01), whereas the mean HU (p=0.07), CoV (p=0.24), and EI (p=0.08) did not. Calculation time for the variogram for a typical 1000 block decomposition was ∼6 seconds, and octree decomposition took ∼2 minutes. Decomposing the images prior to variogram calculation resulted in a ∼700x decrease in time as compared to other published approaches. Conclusions: Our results suggest that the approach combining octree decomposition and variogram analysis may be a rapid, non-subjective, and sensitive imaging-based biomarker for quantitative characterization of lung disease.« less
Authors:
 [1] ;  [2]
  1. Pacific Northwest National Laboraory, Richland, WA (United States)
  2. Texas Advanced Computing Center, Austin, TX (United States)
Publication Date:
OSTI Identifier:
22402255
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 41; Journal Issue: 6; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; BIOLOGICAL MARKERS; CAT SCANNING; COMPARATIVE EVALUATIONS; COMPUTER GRAPHICS; EMPHYSEMA; LUNGS; RATS; THREE-DIMENSIONAL CALCULATIONS