Quantification of cerebral artery motion during the cardiac cycle.
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ABSTRACT:
SUBMITTER: Nishida T
PROVIDER: S-EPMC7964400 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Current protocols examining cerebral autoregulation (CA) parameters require participants to refrain from exercise for 12-24 hr, however there is sparse objective evidence examining the recovery trajectory of these measures following exercise across the cardiac cycle (diastole, mean, and systole). Therefore, this study sought to determine the duration acute exercise impacts CA and the within-day reproducibility of these measures. Nine participants performed squat-stand maneuvers at 0.05 and 0.10 Hz at baseline before three interventions: 45-min moderate-continuous exercise (at 50% heart-rate reserve), 30-min high-intensity intervals (ten, 1-min at 85% heart-rate reserve), and a control day (30-min quiet rest). Squat-stands were repeated at hours zero, one, two, four, six, and eight after each condition. Transcranial doppler ultrasound of the middle cerebral artery (MCA) and the posterior cerebral artery (PCA) was used to characterize CA parameters across the cardiac cycle. At baseline, the systolic CA parameters were different than mean and diastolic components (ps < 0.015), however following both exercise protocols in both frequencies this disappeared until hour four within the MCA (ps > 0.079). In the PCA, phase values were affected only following high-intensity intervals until hour four (ps > 0.055). Normalized gain in all cardiac cycle domains remained different following both exercise protocols (ps < 0.005) and across the control day (p < .050). All systolic differences returned by hour six across all measures (ps < 0.034). Future CA studies may use squat-stand maneuvers to assess the cerebral pressure-flow relationship 6 hr after exercise. Finally, CA measures under this paradigm appear to have negligible within-day variation, allowing for reproducible interpretations to be drawn.
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Project description:Measurement of microvascular perfusion with Intravoxel Incoherent Motion (IVIM) MRI is gaining interest. Yet, the physiological influences on the IVIM perfusion parameters ("pseudo-diffusion" coefficient D*, perfusion fraction f, and flow related parameter fD*) remain insufficiently characterized. In this article, we hypothesize that D* and fD*, which depend on blood speed, should vary during the cardiac cycle. We extended the IVIM model to include time dependence of D*?=?D*(t), and demonstrate in the healthy human brain that both parameters D* and fD* are significantly larger during systole than diastole, while the diffusion coefficient D and f do not vary significantly. The results non-invasively demonstrate the pulsatility of the brain's microvasculature.
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Project description:The quantification of cardiac motion using cardiac magnetic resonance imaging (CMR) has shown promise as an early-stage marker for cardiovascular diseases. Despite the growing popularity of CMR-based myocardial strain calculations, measures of complete spatiotemporal strains (i.e., three-dimensional strains over the cardiac cycle) remain elusive. Complete spatiotemporal strain calculations are primarily hampered by poor spatial resolution, with the rapid motion of the cardiac wall also challenging the reproducibility of such strains. We hypothesize that a super-resolution reconstruction (SRR) framework that leverages combined image acquisitions at multiple orientations will enhance the reproducibility of complete spatiotemporal strain estimation. Two sets of CMR acquisitions were obtained for five wild-type mice, combining short-axis scans with radial and orthogonal long-axis scans. Super-resolution reconstruction, integrated with tissue classification, was performed to generate full four-dimensional (4D) images. The resulting enhanced and full 4D images enabled complete quantification of the motion in terms of 4D myocardial strains. Additionally, the effects of SRR in improving accurate strain measurements were evaluated using an in-silico heart phantom. The SRR framework revealed near isotropic spatial resolution, high structural similarity, and minimal loss of contrast, which led to overall improvements in strain accuracy. In essence, a comprehensive methodology was generated to quantify complete and reproducible myocardial deformation, aiding in the much-needed standardization of complete spatiotemporal strain calculations.
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Project description:PurposeDevelop a novel 2D cardiac MR fingerprinting (MRF) approach to enable simultaneous T1, T2, T2*, and fat fraction (FF) myocardial tissue characterization in a single breath-hold scan.MethodsSimultaneous, co-registered, multi-parametric mapping of T1, T2, and FF has been recently achieved with cardiac MRF. Here, we further incorporate T2* quantification within this approach, enabling simultaneous T1, T2, T2*, and FF myocardial tissue characterization in a single breath-hold scan. T2* quantification is achieved with an eight-echo readout that requires a long cardiac acquisition window. A novel low-rank motion-corrected (LRMC) reconstruction is exploited to correct for cardiac motion within the long acquisition window. The proposed T1/T2/T2*/FF cardiac MRF was evaluated in phantom and in 10 healthy subjects in comparison to conventional mapping techniques.ResultsThe proposed approach achieved high quality parametric mapping of T1, T2, T2*, and FF with corresponding normalized RMS error (RMSE) T1 = 5.9%, T2 = 9.6% (T2 values <100 ms), T2* = 3.3% (T2* values <100 ms), and FF = 0.8% observed in phantom scans. In vivo, the proposed approach produced higher left-ventricular myocardial T1 values than MOLLI (1148 vs 1056 ms), lower T2 values than T2-GraSE (42.8 vs 50.6 ms), lower T2* values than eight-echo gradient echo (GRE) (35.0 vs 39.4 ms), and higher FF values than six-echo GRE (0.8 vs 0.3 %) reference techniques. The proposed approach achieved considerable reduction in motion artifacts compared to cardiac MRF without motion correction, improved spatial uniformity, and statistically higher apparent precision relative to conventional mapping for all parameters.ConclusionThe proposed cardiac MRF approach enables simultaneous, co-registered mapping of T1, T2, T2*, and FF in a single breath-hold for comprehensive myocardial tissue characterization, achieving higher apparent precision than conventional methods.
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