Development of a chest digital tomosynthesis R/F system and implementation of low-dose GPU-accelerated compressed-sensing (CS) image reconstruction.

PurposeThis work describes the hardware and software developments of a prototype chest digital tomosynthesis (CDT) R/F system. The purpose of this study was to validate the developed system for its possible clinical application on low-dose chest tomosynthesis imaging. MethodsThe prototype CDT R/F system was operated by carefully controlling the electromechanical subsystems through a synchronized interface. Once a command signal was delivered by the user, a tomosynthesis sweep started to acquire 81 projection views (PVs) in a limited angular range of 20 degrees. Among the full projection dataset of 81 images, several sets of 21 (quarter view) and 41 (half view) images with equally spaced angle steps were selected to represent a sparse view condition. GPU-accelerated and total-variation (TV) regularization strategy-based compressed sensing (CS) image reconstruction was implemented. The imaged objects were a flat-field using a copper filter to measure the noise power spectrum (NPS), a Catphan((R)) CTP682 quality assurance (QA) phantom to measure a task-based modulation transfer function (MTFTask) of three different cylinders' edge, and an anthropomorphic chest phantom with inserted lung nodules. The authors also verified the accelerated computing power over CPU programming by checking the elapsed time required for the CS method. The resultant absorbed and effective doses that were delivered to the chest phantom from two-view digital radiographic projections, helical computed tomography (CT), and the prototype CDT system were compared. ResultsThe prototype CDT system was successfully operated, showing little geometric error with fast rise and fall times of R/F x-ray pulse less than 2 and 10 ms, respectively. The in-plane NPS presented essential symmetric patterns as predicted by the central slice theorem. The NPS images from 21 PVs were provided quite different pattern against 41 and 81 PVs due to aliased noise. The voxel variance values which summed all NPS intensities were inversely proportional to the number of PVs, and the CS method gave much lower voxel variance by the factors of 3.97-6.43 and 2.28-3.36 compared to filtered backprojection (FBP) and 20 iterations of simultaneous algebraic reconstruction technique (SART). The spatial frequencies of the f(50) at which the MTFTask reduced to 50% were 1.50, 1.55, and 1.67 cycles/mm for FBP, SART, and CS methods, respectively, in the case of Bone 20% cylinder using 41 views. A variety of ranges of TV reconstruction parameters were implemented during the CS method and we could observe that the NPS and MTFTask preserved best when the regularization and TV smoothing parameters and were in a range of 0.001-0.1. For the chest phantom data, the signal difference to noise ratios (SDNRs) were higher in the proposed CS scheme images than in the FBP and SART, showing the enhanced rate of 1.05-1.43 for half view imaging. The total averaged reconstruction time during 20 iterations of the CS scheme was 124.68 s, which could match-up a clinically feasible time (<3 min). This computing time represented an enhanced speed 386 times greater than CPU programming. The total amounts of estimated effective doses were 0.12, 0.53 (half view), and 2.56 mSv for two-view radiographs, the prototype CDT system, and helical CT, respectively, showing 4.49 times higher than conventional radiography and 4.83 times lower than a CT exam, respectively. ConclusionsThe current work describes the development and performance assessment of both hardware and software for tomosynthesis applications. The authors observed reasonable outcomes by showing a potential for low-dose application in CDT imaging using GPU acceleration.