Browsing by Subject "virtual imaging trials"
- Results Per Page
- Sort Options
Item Open Access A systematic assessment and optimization of photon-counting CT for lung density quantifications.(Medical physics, 2024-02) Sotoudeh-Paima, Saman; Segars, W Paul; Ghosh, Dhrubajyoti; Luo, Sheng; Samei, Ehsan; Abadi, EhsanBackground
Photon-counting computed tomography (PCCT) has recently emerged into clinical use; however, its optimum imaging protocols and added benefits remains unknown in terms of providing more accurate lung density quantification compared to energy-integrating computed tomography (EICT) scanners.Purpose
To systematically assess the performance of a clinical PCCT scanner for lung density quantifications and compare it against EICT.Methods
This cross-sectional study involved a retrospective analysis of subjects scanned (August-December 2021) using a clinical PCCT system. The influence of altering reconstruction parameters was studied (reconstruction kernel, pixel size, slice thickness). A virtual CT dataset of anthropomorphic virtual subjects was acquired to demonstrate the correspondence of findings to clinical dataset, and to perform systematic imaging experiments, not possible using human subjects. The virtual subjects were imaged using a validated, scanner-specific CT simulator of a PCCT and two EICT (defined as EICT A and B) scanners. The images were evaluated using mean absolute error (MAE) of lung and emphysema density against their corresponding ground truth.Results
Clinical and virtual PCCT datasets showed similar trends, with sharper kernels and smaller voxel sizes increasing percentage of low-attenuation areas below -950 HU (LAA-950) by up to 15.7 ± 6.9% and 11.8 ± 5.5%, respectively. Under the conditions studied, higher doses, thinner slices, smaller pixel sizes, iterative reconstructions, and quantitative kernels with medium sharpness resulted in lower lung MAE values. While using these settings for PCCT, changes in the dose level (13 to 1.3 mGy), slice thickness (0.4 to 1.5 mm), pixel size (0.49 to 0.98 mm), reconstruction technique (70 keV-VMI to wFBP), and kernel (Qr48 to Qr60) increased lung MAE by 15.3 ± 2.0, 1.4 ± 0.6, 2.2 ± 0.3, 4.2 ± 0.8, and 9.1 ± 1.6 HU, respectively. At the optimum settings identified per scanner, PCCT images exhibited lower lung and emphysema MAE than those of EICT scanners (by 2.6 ± 1.0 and 9.6 ± 3.4 HU, compared to EICT A, and by 4.8 ± 0.8 and 7.4 ± 2.3 HU, compared to EICT B). The accuracy of lung density measurements was correlated with subjects' mean lung density (p < 0.05), measured by PCCT at optimum setting under the conditions studied.Conclusion
Photon-counting CT demonstrated superior performance in density quantifications, with its influences of imaging parameters in line with energy-integrating CT scanners. The technology offers improvement in lung quantifications, thus demonstrating potential toward more objective assessment of respiratory conditions.Item Open Access Impact of CT Simulation Parameters on the Realism of Virtual Imaging Trials(2023) Montero, Isabel SeraphinaVirtual imaging trials (VITs) provide the opportunity to conduct medical imaging experiments otherwise not feasible through patient images. The reliability of these virtual trials is directly dependent upon their ability to replicate clinical imaging experiments. The combined effect of various key simulation parameters on the closeness of virtual images to experimental images has not yet been explicitly quantified, which this sensitivity study aimed to address. To do so, a physical phantom, Mercury 3.0 (Sun Nuclear), was scanned using a clinical scanner (Siemens Force). Meanwhile, utilizing a validated CT simulator (DukeSim), a computational version of the Mercury 3.0 phantom was virtually imaged, emulating the same scanner model and imaging acquisition settings. The simulations were performed with varied parameters for the x-ray source, phantom model, and detector characteristics, evaluating their impact on the realism of the final reconstructed virtual images. Simulations were explicitly conducted and evaluated various source and detector subsampling (1 – 5 per side), phantom voxel resolution (0.1 mm – 0.5mm), anode heel severity (0% - 40% over anode-cathode axis), aluminum filtration (0.9cm - 1.1cm), and pixel-to-pixel detector crosstalk (0 – 10.5%, 0 – 15% per dimension). The real and simulated projections were then reconstructed, employing a vendor-specific reconstruction software (Siemens ReconCT), with identical reconstruction settings. The real and simulated images were then compared in terms of modulation transfer function (MTF), noise magnitude, noise power spectrum (NPS), and CT number accuracy. When the optimal simulation parameters were selected, the simulated images closely replicated real images (0.80% relative error in f50air metric). The error in the f50 measurements were highly sensitive to the variation of source and detector subsampling and phantom voxel size. The relative error in the noise magnitude measurements were not highly sensitive to the variation of source and detector subsampling or phantom voxel size but were sensitive to the modeling of the anode heel effect severity. The error in the nNPS measurements were not highly sensitive to the variation of source and detector subsampling, phantom voxel size, degree of anode heel severity, aluminum filtration, or detector cross talk. Finally, the error in the CT number accuracy measurements were not highly sensitive to the variation of source and detector subsampling, phantom voxel size, aluminum filtration, or degree of detector cross talk, but were sensitive to the modeling of anode heel severity. Through this study, the effects of various key simulation parameters on the realism of scanner-specific simulations were assessed. Certain simulation parameters, such as source and detector subsampling, and degree of anode heel severity, exert greater influence on simulation realism than others, thus they should be prioritized when exploring novel modeling avenues.