This is the authors' abstract. We don't add key points for this paper.
PurposeHigh soft-tissue contrast imaging is essential for effective radiotherapy treatment. This could potentially be realized using both megavoltage and kilovoltage x-ray sources available on some therapy treatment systems to perform “MV-kV” dual-energy (DE) computed tomography (CT). However, noisy megavoltage images obtained with existing energy-integrating detectors (EIDs) are a limiting factor for clinical translation. We explore the potential for non-spectral photon-counting detectors (PCDs) to improve MV-kV image quality simply by equally weighting all MV photons rather than up-weighting the less informative, lower contrast high-energy photons as in an EID.ApproachThree computational methods were applied to compare non-spectral PCDs with EIDs in MV-kV DE imaging. A single-line integral estimation theory approach was used to calculate the basis material signal-to-noise ratio (SNR) of tissue (1 to 50 cm) and bone (0.1 to 10 cm). CT images of a tissue cylinder with seven bone inserts (densities 1.0 to 2.2 g/cm3) were simulated to assess material decomposition accuracy. Multiple noisy simulations of an anthropomorphic phantom were performed to generate pixel-by-pixel noise profiles.ResultsPCDs yielded a 15% to 45% improvement in single-line integral SNR for both materials. In CT simulations, similar material decomposition accuracy was achieved, with both EIDs and PCDs slightly underestimating bone density. However, PCDs yield a higher contrast-to-noise ratio and more uniform noise texture than EIDs in virtual monoenergetic images.ConclusionsWe demonstrate the potential for improved MV-kV DE CT imaging using non-spectral PCDs and quantify the degree of improvement in a range of object compositions. This work motivates the experimental assessment of PCDs for megavoltage imaging and the potential clinical translation of PCDs to radiotherapy imaging.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Jadick et al. (2024) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: