Spatially-variant image-based modeling of PSF deformations with application to a limited angle geometry from a dual-panel breast-PET imager

Abstract

Dual-panel PET system configuration can lead to spatially variable point-spread functions (PSF) of considerable deformations due to depth-of-interaction effects and limited angular coverage. If not modelled properly, these effects result in decreased and inconsistent recovery of lesion activity across the field-of-view (FOV), as well as mispositioning of lesions in the reconstructed image caused by strong PSF asymmetries. We implemented and evaluated models of such PSF deformations with spatially-variant image-based resolution modeling (IRM) within reconstruction (varRM) using the Direct Image REConstruction for Time-of-flight (DIRECT) method and within post-reconstruction deconvolution methods. In addition, DIRECT reconstruction was performed with a spatially-invariant IRM (invRM) and without resolution modeling (noRM) for comparison. The methods were evaluated using simulated data for a realistic breast model with a set of 5 mm lesions located throughout the FOV of a dual-panel Breast-PET scanner. We simulated high-count data to focus on the ability of each method to correctly recover the PSF deformations, and a clinically realistic count level to assess the impact of low count data on the quantitative performance of the evaluated techniques. Performance of the methods evaluated herein was assessed by comparing lesion activity recovery (%BIAS), consistency (%SD) across the FOV, overall error (%RMSE), and recovery of each lesion location. As expected, all techniques using IRM provide considerable improvement over the noRM reconstruction. For the high-count cases, the overall quantitative performance of all IRM techniques, whether within reconstruction or within post-reconstruction, is similar if the lesion location misplacements are ignored. However, invRM provides less consistent performance on activity across lesions and is not able to recover accurate lesion locations. For a clinically realistic count level, varRM reconstruction consistently outperforms all compared approaches, while the post-reconstruction IRM approaches exhibit higher %SD and %RMSE values due to being more affected by the data noise than the within-reconstruction IRM approaches.

Design and system evaluation of a dual-panel portable PET (DP-PET)

“…Breastdedicated PET imaging systems have been developed in recent years and demonstrate clinical feasibility [38][39][40]. The dual-panel geometry in breast-dedicated PET has been widely used due to the advantage of lower costs and potentially increased sensitivity [41][42][43]. There is a growing interest in developing breast PET/MR, and some simulation studies as well as prototypes have proved the increased sensitivity and specificity in the detection of small lesions [44,45].…”

Design and System Evaluation of a Dual-Panel Portable PET (DP-PET)

“…Breast-dedicated PET imaging systems have been developed in recent years and demonstrate the clinical feasibility [38][39][40]. The dual-panel geometry in breastdedicated PET has been widely used due to the advantage of lower costs and potentially increased sensitivity [41][42][43]. There is a growing interest in developing breast PET/MR, (a) (b)…”

Recovery of the spatially-variant deformations in dual-panel PET reconstructions using deep-learning

“…Both measured and synthetic (analytically simulated) data from the B-PET system underwent reconstruction using DIRECT-RAMLA, a reconstruction technique based on histo-image data partitioning, as described in prior work (Matej et al 2009, 2016, Gravel et al 2019. The data were histogrammed into histoimages with 1 × 1 × 1 mm 3 voxels, 60 transverse views with 3°steps, and 15 axial views (tilts) with 3.3°steps (due to the use of only half of the blocks in the z directions, the total axial acceptance angle was limited to 50°).…”

“…In our previous works, we investigated effects of the TOF modeling (Gravel et al 2020) and application of the image-based resolution models within the statistical image reconstruction modeling the limited angle and Depth-of-Interaction (DOI) effects on the PSF deformations (Matej et al 2016, Gravel et al 2019. Although reconstructions with the optimized TOF kernel widths and with the spatially-variant PSF models led to better and more uniform quantification of small lesions across the FOV, the efficacy of the image-based resolution models is limited to small objects, such as point-sources and small lesions.…”

“…In the first part of this work, we focus on investigations of the ability of DL approaches to capture and recover such deformations, employing image-based PSF deformation models generated for a generic dual-panel PET system (Gravel et al 2019). In these investigations we simulated the image-based deformations (see figure 1) for range of the objects, from simple point-sources in air up to lesions of more realistic shapes in warm background and also incorporated the presence of noise to reflect real-world conditions.…”