Abstract
INTRODUCTION: Manual analysis of two-dimensional (2D) scintigraphy to evaluate aerosol deposition is usually subjective and has reduced sensitivity to quantify regional differences between central and distal airways. AIMS: (1) To present a method to analyze 2D scans based on three-dimensional (3D)-linked anatomically consistent regions of interest (ROIs); (2) to evaluate peripheral-to-central counts ratio (P/C(2D)) and penetration indices (PIs) for a set of 16 subjects with moderate-to-severe asthma; and (3) to compare the reproducibility of this method against one with manually traced ROIs. METHODS: Two-dimensional scans were analyzed using custom software that scaled onto 2D-projections' 3D anatomical features, obtained from population-averaged computed tomography (CT) chest scans. ROIs for a rectangular box (bROI) and an anatomically shaped ROI (aROI) were defined by computer and by manually tracing the standard rectangular box (manual ROI [mROI]). These ROIs were defined five nonconsecutive times for each scan and average value and variability of the P/C(2D) were estimated. Based on CT estimates of lung and airways, volumes lying under the bROI and aROI, a 2D penetration index (PI(2D)) and a 3D penetration index (PI(3D)), were defined as volume-normalized ratios of aerosol deposition in central and peripheral ROIs and in central and distal airways, respectively. RESULTS: P/C(2D) values and their variability, were influenced by the shape and method to define the ROIs: The P/C(2D) was systematically greater and more variable for mROI versus bROI (p < 0.005). The P/C(2D) for aROI was higher and its variability lower than those for the bROI (p < 0.001). The PI(2D) was in average the same for aROI and bROI, and is substantially (∼30 × ) greater than PI(3D) (p < 0.001). Both PI(2D) and PI(3D), obtained with our analysis, compared well with literature values obtained with two scans (deposition and volume). CONCLUSION: Our results demonstrate that 2D scintigraphy can be analyzed using anatomically based ROIs from 3D CT data, allowing objective and enhanced reproducibility values describing the distribution pattern of radioaerosol deposition in the tracheobronchial tree.