Analysis of three-dimensional aerosol deposition in pharmacologically relevant terms: beyond black or white ROIs

Abstract

Background: This article presents a novel methodological approach to evaluate images of aerosol deposition taken with PET-CT cameras. Traditionally, Black-or-White (BW) Regions of Interest (ROIs) are created to cover Anatomical Regions (ARs) segmented from the high-resolution CT. Such ROIs do not usually consider blurring effects due to limited spatial resolution or breathing motion, and do not consider uncertainty in the AR position within the PET image. The new methodology presented here (Grayscale) addresses these issues, allows estimates of aerosol deposition within ARs, and expresses the deposition in terms of Tissue Dosing (in the lung periphery) and Inner Surface Concentration (in the larger airways).

Methods: Imaging data included a PET deposition image acquired during breathing and two CT scans acquired during breath holds at different lung volumes. The lungs were segmented into anatomically consistent ARs to allow unbiased comparisons across subjects and across lobes. The Grayscale method involves defining Voxel Influence Matrices (VIMs) to consider how average activity within each AR influences the measured activity within each voxel. The BW and Grayscale methods were used to analyze aerosol deposition in 14 bronchoconstricted asthmatics.

Results: Grayscale resulted in a closer description of the PET image than BW (p<0.0001) and exposed a seven-fold underestimation in measures of specific deposition. The Average Tissue Dosing was 2.11×10(-6) Total Lung Dose/mg. The average Inner Surface Concentration was 45×10(-6) Total Lung Dose/mm(2), with the left lower lobe having a lower ISC than lobes of the right lung (p<0.05). There was a strong lobar heterogeneity in these measures (COV=0.3).

Conclusion: The Grayscale approach is an improvement over the BW approach and provides a closer description of the PET image. It can be used to characterize heterogeneous concentrations throughout the lung and may be important in translational research and in the evaluation of aerosol delivery systems.

Keywords: PET-CT; ROIs; heterogeneity; motion correction; mucocilliary transport; partial volume effect; spillover effect; surface concentration; tissue dosing.

FIG. 1.

Panels illustrate the methods. (A) The TLC airway tree is trimmed to the sub-segmental generation to obtain a central airway tree ROI that is consistent across subjects. In light blue are umbrella-shaped cutting elements oriented with the segmental airways. In green are the trimmed portions of the tree. (B) The boundaries of the airways before and after the addition of sequential sources of blurring; the trimmed TLC @ MLV airway tree (purple), motion blur (light purple), PET blur (orange), including transformation and registration error (darker yellow), and the final PET mask discretized to the PET deposition image (light yellow). The boundaries represent the point where the voxel VI >0.1%. (C) The nine airway tree ARs (shown in saturated colors), and iso-contours of their corresponding VIMs in matching colors representing 10%, 1%, and 0.1% VI are drawn for each AR (the color legend is shown in panel G). (D) Effect of mapping airway tree from TLC to MLV: Front and lateral projections of the airway tree (Top) rendered from a CT acquired at TLC (red) and one at MLV (blue); (Bottom) the same as above, but with the TLC tree mapped to the MLV. (E) A Rendering of the 14 Anatomical Regions (ARs). The color legend is shown in panel G. The lobar central airways are color matched to the lobes that they feed. The 16 cm PET field of view and the typical placement of the PET image are shown with the rectangle. The lung volume for this subject was 4.7 L at MLV (average volume at MLV was 3.2 L). (F) The co-registration of the TLC (red) and MLV (blue) spines. The inset shows the variability in the Tanimoto Similarity Coefficient of the upper spines as the images are shifted relative to each other. The dark spot shows that the HRCT images are best co-registered when the blue spine is shifted up and to the left. (G) A visualization of the VIMs. Each color indicates the VIM of a single AR. VIMs estimate of how homogenous activity within an AR appears in the radionuclear image. Where in a conventional black or while ROI each voxel is assigned to a specific AR, the rectangle shows how the voxel is influences by many ARs.

FIG. 2.

Panels illustrate the results. (A) PET deposition images for three subjects (first column) contrasted with images of activity estimated with the two methods: BW and Grayscale. The estimated images are created by multiplying the ROIs used in each method by the estimated regional specific activities. The color scale within each row is kept constant with the darkest red corresponding to the point with highest activity. Both methods assume uniform deposition within the AR, which tends to diffuse hotspots in the estimated images. However, the Grayscale method tends to reproduce location and magnitude of hotspots better than the BW method. Note that the activity on the esophagus (present in the lower two PET images) is not represented in the projections since it was not defined as an AR (see discussion). (B) The coefficient of determination of the two methods. In all subjects the description of deposition with the Grayscale method is closer to the PET image (p<0.0001) than with the BW method. (C) (Left) Projections of the ARs (at CT resolution) in blue overlaid with a projection of the deposition image (at PET resolution) in red. (Right) Projection of the estimated activity within the ARs (at CT resolution) using the Grayscale method. (D) The PI, TD, and ISC using Grayscale across lobes. Individual subject data are connected with dashed lines. The solid line is the average lobar values. No statistical difference was observed between a given lobe's TD. The LLL showed lower ISC than the lobes of the right lung (the strength of the line between the lobes under STATS indicates the strength of the P value).