3 resultados para POWER-FLOW CONTROLLER

em Université de Lausanne, Switzerland


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Rb-82cardiac PET has been used to non-invasively assess myocardial blood flow (MBF)and myocardial flow reserve (MFR). The impact of MBF and MFR for predictingmajor adverse cardiovascular events (MACE) has not been investigated in aprospective study, which was our aim. MATERIAL AND METHODS: In total, 280patients (65±10y, 36% women) with known or suspected CAD were prospectivelyenrolled. They all underwent both a rest and adenosine stress Rb-82 cardiacPET/CT. Dynamic acquisitions were processed with the FlowQuant 2.1.3 softwareand analyzed semi-quantitatively (SSS, SDS) and quantitatively (MBF, MFR) andreported using the 17-segment AHA model. Patients were stratified based on SDS,stress MBF and MFR and allocated into tertiles. For each group, annualizedevent rates were computed by dividing the number of annualized MACE (cardiacdeath, myocardial infarction, revascularisation or hospitalisation forcardiac-related event) by the sum of individual follow-up periods in years.Outcome were analysed for each group using Kaplan-Meier event-free survivalcurves and compared using the log-rank test. Multivariate analysis wasperformed in a stepwise fashion using Cox proportional hazards regressionmodels (p<0.05 for model inclusion). RESULTS: In a median follow-up of 256days (range 168-440d), 44 MACE were observed. Ischemia (SDS≥2) was observed in95 patients who had higher annualized MACE rate as compared to those without(55% vs. 9.8%, p<0.0001). The group with the lowest MFR tertile (MFR<1.76)had higher MACE rate than the two highest tertiles (51% vs. 9% and 14%,p<0.0001). Similarly, the group with the lowest stress MBF tertile(MBF<1.78mL/min/g) had the highest annualized MACE rate (41% vs. 26% and 6%,p=0.0002). On multivariate analysis, the addition of MFR or stress MBF to SDSsignificantly increased the global χ2 (from 56 to 60, p=0.04; and from56 to 63, p=0.01). The best prognostic power was obtained in a model combiningSDS (p<0.001) and stress MBF (p=0.01). Interestingly, the integration ofstress MBF enhanced risk stratification even in absence of ischemia.CONCLUSIONS: Quantification of MBF or MFR in Rb-82 cardiac PET/CT providesindependent and incremental prognostic information over semi-quantitativeassessment with SDS and is of value for risk stratification.

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AIMS: We studied the respective added value of the quantitative myocardial blood flow (MBF) and the myocardial flow reserve (MFR) as assessed with (82)Rb positron emission tomography (PET)/CT in predicting major adverse cardiovascular events (MACEs) in patients with suspected myocardial ischaemia. METHODS AND RESULTS: Myocardial perfusion images were analysed semi-quantitatively (SDS, summed difference score) and quantitatively (MBF, MFR) in 351 patients. Follow-up was completed in 335 patients and annualized MACE (cardiac death, myocardial infarction, revascularization, or hospitalization for congestive heart failure or de novo stable angor) rates were analysed with the Kaplan-Meier method in 318 patients after excluding 17 patients with early revascularizations (<60 days). Independent predictors of MACEs were identified by multivariate analysis. During a median follow-up of 624 days (inter-quartile range 540-697), 35 MACEs occurred. An annualized MACE rate was higher in patients with ischaemia (SDS >2) (n = 105) than those without [14% (95% CI = 9.1-22%) vs. 4.5% (2.7-7.4%), P < 0.0001]. The lowest MFR tertile group (MFR <1.8) had the highest MACE rate [16% (11-25%) vs. 2.9% (1.2-7.0%) and 4.3% (2.1-9.0%), P < 0.0001]. Similarly, the lowest stress MBF tertile group (MBF <1.8 mL/min/g) had the highest MACE rate [14% (9.2-22%) vs. 7.3% (4.2-13%) and 1.8% (0.6-5.5%), P = 0.0005]. Quantitation with stress MBF or MFR had a significant independent prognostic power in addition to semi-quantitative findings. The largest added value was conferred by combining stress MBF to SDS. This holds true even for patients without ischaemia. CONCLUSION: Perfusion findings in (82)Rb PET/CT are strong MACE outcome predictors. MBF quantification has an added value allowing further risk stratification in patients with normal and abnormal perfusion images.

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BACKGROUND: So far, none of the existing methods on Murray's law deal with the non-Newtonian behavior of blood flow although the non-Newtonian approach for blood flow modelling looks more accurate. MODELING: In the present paper, Murray's law which is applicable to an arterial bifurcation, is generalized to a non-Newtonian blood flow model (power-law model). When the vessel size reaches the capillary limitation, blood can be modeled using a non-Newtonian constitutive equation. It is assumed two different constraints in addition to the pumping power: the volume constraint or the surface constraint (related to the internal surface of the vessel). For a seek of generality, the relationships are given for an arbitrary number of daughter vessels. It is shown that for a cost function including the volume constraint, classical Murray's law remains valid (i.e. SigmaR(c) = cste with c = 3 is verified and is independent of n, the dimensionless index in the viscosity equation; R being the radius of the vessel). On the contrary, for a cost function including the surface constraint, different values of c may be calculated depending on the value of n. RESULTS: We find that c varies for blood from 2.42 to 3 depending on the constraint and the fluid properties. For the Newtonian model, the surface constraint leads to c = 2.5. The cost function (based on the surface constraint) can be related to entropy generation, by dividing it by the temperature. CONCLUSION: It is demonstrated that the entropy generated in all the daughter vessels is greater than the entropy generated in the parent vessel. Furthermore, it is shown that the difference of entropy generation between the parent and daughter vessels is smaller for a non-Newtonian fluid than for a Newtonian fluid.