Enhancement of Stopping Power Ratio (SPR) Estimation Accuracy through Image-Domain Dual-Energy Computer Tomography for Pencil Beam Scanning System: A Simulation Study.
Dong HanShuangyue ZhangSixia ChenHamed HooshangnejadFrancis YuKai DingHaibo LinPublished in: Cancers (2024)
Our study aims to quantify the impact of spectral separation on achieved theoretical prediction accuracy of proton-stopping power when the volume discrepancy between calibration phantom and scanned object is observed. Such discrepancy can be commonly seen in our CSI pediatric patients. One of the representative image-domain DECT models is employed on a virtual phantom to derive electron density and effective atomic number for a total of 34 ICRU standard human tissues. The spectral pairs used in this study are 90 kVp/140 kVp, without and with 0.1 mm to 0.5 mm additional tin filter. The two DECT images are reconstructed via a conventional filtered back projection algorithm (FBP) on simulated noiseless projection data. The best-predicted accuracy occurs at a spectral pair of 90 kVp/140 kVp with a 0.3 mm tin filter, and the root-mean-squared average error is 0.12% for tissue substitutes. The results reveal that the selected image-domain model is sensitive to spectral pair deviation when there is a discrepancy between calibration and scanning conditions. This study suggests that an optimization process may be needed for clinically available DECT scanners to yield the best proton-stopping power estimation.
Keyphrases
- dual energy
- image quality
- computed tomography
- deep learning
- optical coherence tomography
- high resolution
- electron microscopy
- magnetic resonance imaging
- machine learning
- contrast enhanced
- dna methylation
- endothelial cells
- gene expression
- electronic health record
- genome wide
- cross sectional
- working memory
- liquid chromatography
- low cost