Four temporal and four spectral parameters of heart rate variability were compared after they were computed with two different time series generation methods: the RR intervals and the numerical values of heart rate provided by the Finapres. Recordings were obtained from 10 healthy subjects throughout five experimental conditions: supine, standing, controlled breathing, exercise and recovery. The mean and the RMS value of successive differences showed significant differences between the two methods. The spectral parameters were statistically different only during standing and exercise. The larger high frequency component and the lower HF/LF ratio by the Finapres method, observed during exercise, can be explained by the higher breathing influence on the peak-to-peak pressure intervals, in relation to RR intervals. Therefore, the high frequency component within mechanic intervals could possibly reflect the non-neural respiratory influence. In conclusion, values of heart rate provided by the Finapres are not completely interchangeable with those obtained from the ECG during the studied conditions.

The STELLR reconstruction approach of 3D radial sampling with mask subtraction provides a high-performance imaging technique for characterizing enhancing structures within the breast. It is capable of maintaining temporal fidelity, while visualizing breast lesions with high detail over a large FOV to include both breasts.

Purpose: Perfusion MRI with gadolinium-based contrast agents is useful for diagnosis and treatment response evaluation of brain tumors. Dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI are two gadolinium-based contrast agent perfusion imaging techniques that provide complementary information about the tumor vasculature. However, each requires a separate administration of a gadolinium-based contrast agent. The purpose of this retrospective study was to determine the feasibility of synthesizing relative cerebral blood volume (rCBV) maps, as computed from DSC MRI, from DCE MRI of brain tumors. Methods: One hundred nine brain-tumor patients underwent both DCE and DSC MRI. Relative CBV maps were computed from the DSC MRI, and blood plasma volume fraction maps were computed from the DCE MRIs. Conditional generative adversarial networks were developed to synthesize rCBV maps from the DCE MRIs. Tumor-to-white matter ratios were calculated from real rCBV, synthetic rCBV, and plasma volume fraction maps and compared using correlation analysis. Real and synthetic rCBV in white and gray matter regions were also compared. Results: Pearson correlation analysis showed that both the tumor rCBV and tumorto-white matter ratios in the synthetic and real rCBV maps were strongly correlated (ρ = 0.87, P < .05 and ρ = 0.86, P < .05, respectively). Tumor plasma volume fraction and real rCBV were not strongly correlated (ρ = 0.47). Bland-Altman analysis showed a mean difference between the synthetic and real rCBV tumor-to-white matter ratios of 0.20 with a 95% confidence interval of ±0.47. Conclusion: Realistic rCBV maps can be synthesized from DCE MRI and contain quantitative information, enabling robust brain-tumor perfusion imaging of DSC and DCE parameters with a single gadolinium-based contrast agent administration.

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The low exposures, unique x-ray beam geometry, and scanning design in dual-energy x-ray absorptiometry (DXA) make measurement and quality-control strategies different from traditional x-ray equipment. This study examines the dependence of measured entrance-air-kerma (EAK) on both dose sensor type and scan length. The feasibility of using EAK to compare scanner output between different scan modes, individual scanners, and scanner platforms was also established. Finally, the congruence between measured and vendor-reported EAK was analyzed. Methods: Four Hologic DXA scanners at two institutions and all four available scan modes were tested. EAK was measured directly by three types of Radcal dose sensors: 60-cc pancake ion-chamber (IC), 180-cc pancake IC, and solid-state detector. The coefficient of variation (COV) was used to assess the dependence of EAK on scan length. Variations in EAK between the types of dose sensors as well as measured versus vendor-reported values were evaluated using Bland-Altman analysis: mean ±95% prediction interval (PI): 1.96σ. Results: Dose sensor variations in EAK were minimal, with a −3.5 ± 3.5% (mean ±95% PI) percent difference between the two sizes of IC's. The solidstate detector produced highly similar measurements to the 180-cc IC. These small differences were consistent across all scanners and all scan modes tested. Neither measured nor vendor-reported EAK values were found to show relevant dependence on scan length, with all COV values ≤4%. Differences between measured and reported EAK were higher at −6 ± 48%. Likely errors in vendor-reported EAK calculations were also identified. Conclusion:It is feasible to quantify DXA scanner stability using EAK as a quality-control metric with a variety of solid-state and IC dose sensors, and the scan length used is not critical. Although vendor-reported EAK was consistent among scanners of the same platform, measured EAK varied significantly from scanner to scanner. As a result, measured and reported EAK may not always be comparable.