BMC Medical Imaging最新文献

Background: This study aims to investigate the feasibility of coronary artery calcium scoring (CACS) calculating from PureCalcium virtual non-iodine algorithm on photon-counting detector CT (PCD-CT) and the potential impact of different section thickness, level of virtual monoenergetic images (VMIs), and quantum iterative reconstruction (QIR) on the accuracy of CACS quantification.

Materials and methods: A total of 123 patients who underwent coronary CT angiography on PCD-CT with a separate true non-contrast CACS (CACS_TNC) scan were prospectively included. Agatston scores were calculated from the PureCalcium algorithm (CACS_PC) using a section thickness of 3 mm-1.5 mm, different VMI (55-75 kilo-electron volt (keV)) and QIR (strength 1,4) levels, respectively. CACS_TNC at 70 keV and QIR 2 were used as reference standards. Differences in CACS of different reconstructions section thicknesses, various keV levels, and QIR strength were compared using the Wilcoxon rank sum test with Bonferroni correction. The intraclass correlation coefficients (ICCs) and Bland-Altman analysis were conducted to assessed the agreement. The agreement of plaque burden groups (based on CACS) at different reconstruction parameters was evaluated using weighted Cohen kappa.

Results: At all investigated section thickness, VMI, and QIR levels, the CACS_PC were strongly correlated with CACS_TNC (ICC: 0.94-0.98, P < 0.001 for all). There were no statistical differences in CACS between CACS_PC at 3 mm section thickness, 60/65 keV (QIR1/4), and at 1.5 mm section thickness with 55 keV (QIR1/4), compared with CACS_TNC. The smallest CACS bias was observed at a 1.5 mm section thickness, 55 keV, QIR 1, with mean bias of 2.4; LoA (IQR: -182.7, 187.4). CACS_PC correctly identified 105 of 123 participants (85.4%) into the corresponding plaque burden group using CACS_TNC as the referent standard (excellent agreement, κ = 0.904).

Conclusion: CACS derived from the PureCalcium algorithm with optimized reconstruction parameters shows excellent correlation with true non-contrast scans derived values. Thus, it is may possible to use the PureCalcium virtual non-iodine algorithm to replace the true non-contrast scans for CACS quantification, without additional radiation dose exposure.

Objectives: To evaluate the microstructure changes in thigh skeletal muscles of volunteers with knee pain and to explore their relationship with the proton density fat fraction (PDFF), utilizing neurite oriented diffusion and density imaging (NODDI).

Materials and methods: In this prospective study, we collected NODDI and mDIXON-quant images from the bilateral thigh skeletal muscles of 66 asymptomatic and 24 knee pain volunteers. To optimally match the raw data based on these variables and create asymptomatic group (HC, n = 24) and knee pain group (KP, n = 24), the MatchIt package was utilized.

Statistical tests: For the comparison of normally distributed data between the HC and KP groups, t-tests were utilized, while the Wilcoxon rank-sum test was applied for non-normally distributed data. Pearson coefficient was used to analyze the correlation between microstructure parameters of thigh skeletal muscle and PDFF.

Results: Statistically significant differences were observed in MD value of the left hamstrings between the HC and KP groups (p = 0.030), as well as in the FA value of the right quadriceps femoris (p = 0.026). Among volunteers experiencing knee pain, the V-intra value of the right hamstrings and the FA value of the right quadriceps femoris demonstrated a moderate positive correlation with PDFF (r = 0.661, p < 0.001; r = 0.724, p < 0.001).

Conclusion: Microstructure differences in thigh skeletal myofibrils were detected in volunteers with knee pain compared to asymptomatic volunteers, and were more closely related to intramuscular fat infiltration.