Iterative image reconstruction algorithm analysis for optical CT radiochromic gel dosimetry

Abstract

Background: Gel dosimeters are a potential tool for measuring the complex dose distributions that characterize modern radiotherapy. A prototype tabletop solid-tank fan-beam optical CT scanner for readout of gel dosimeters was recently developed. This scanner does not have a straight raypath from source to detector, thus images cannot be reconstructed using filtered backprojection (FBP) and iterative techniques are required. 

Purpose: To compare a subset of top performing algorithms in terms of image quality and quantitatively determine the optimal algorithm while accounting for refraction within the optical CT system.

Methods: A ray tracing simulator was developed to track the path of light rays as they traverse the different mediums of the optical CT scanner. Two clinical phantoms and several synthetic phantoms were produced and used to evaluate the reconstruction techniques under known conditions. Reconstructed images were analyzed in terms of spatial resolution, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), signal non-uniformity (SNU) and mean relative difference (MRD). We developed an image quality based method to find the optimal stopping iteration window for each algorithm. Imaging data from the prototype optical CT scanner was reconstructed and analysed to determine the optimal algorithm for this application. 

Results/Conclusions: The optimal algorithms found through the quantitative scoring metric were FISTA-TV and S-CG-2-NA. Both algorithms are stable from over iterating and have excellent edge detection. FISTA-TV had the greatest noise reduction, however low spatial resolution makes FISTA-TV only viable for large field dosimetry. S-CG-2-NA has better spatial resolution than FISTA-TV but less noise reduction. S-CG-2-NA still maintains good SNR, CNR, and SNU values thus, is a well rounded reconstruction algorithm that would be the preferable choice for small field dosimetry.