Comparison of maximal myocardial blood flow during adenosine infusion with that of intravenous dipyridamole in normal men

AbstractObjective. This study compared quantitatively the efficacy of intravenous adenosine and dipyridamole for pharmacologic induction of myocardial hyperemia.Background. Pharmacologic vasodilation is used increasingly for induction of myocardial hyperemia in conjunction with radionuclide imaging of myocardial blood flow. Although both intravenous dipyridamole and adenosine have been used, the magnitude of hyperemia induced by these agents and the hyperemia to baseline blood flow ratios have not been quantified and compared.Methods. Twenty normal volunteers were studied with dynamic positron emission tomography (PET) and intravenous nitrogen-13 ammonia. Myocardial blood flow was quantified with a two-compartment tracer kinetic model.Results. Myocardial blood flow at rest averaged 1.1 ± 0.2 ml/min per g and increased significantly to 4.4 ± 0.9 ml/min per g during adenosine and 43 ± 1.3 ml/min per g after dipyridamole administration. Hyperemia to baseline flow ratios averaged 4.3 ± 1.6 for adenosine and 4.0 ± 1.3 for dipyridamole. The average flow ratios and the maximal flows achieved were similar for both agents, but there was considerable variation in the individual response to these agents, as indicated by the range of hyperemia to baseline flow ratios (from 2.0 to 8.4 for adenosine and from 1.5 to 5.8 for dipyridamole). in addition, the hyperemic responses to dipyridamole and to adenosine differed by > 1 ml/min per g in nine subjects.Conclusions. Despite these inter- and istraindividual differences, we conclude that both agents are equally effective in producing myocardial hyperemia

Deoxyglucose method for the estimation of local myocardial glucose metabolism with positron computed tomography

The deoxyglucose method originally developed for measurements of the local cerebral metabolic rate for glucose has been investigated in terms of its application to studies of the heart with positron computed tomography (PCT) and FDG. Studies were performed in dogs to measure the tissue kinetics of FDG with PCT and by direct arterial-venous sampling. The operational equation developed in our laboratory as an extension of the Sokoloff model was used to analyze the data. The FDG method accurately predicted the true MMRGlc even when the glucose metabolic rate was normal but myocardial blood flow (MBF) was elevated 5 times the control value or when metabolism was reduced to 10% of normal and MBF increased 5 times normal. Improvements in PCT resolution are required to improve the accuracy of the estimates of the rate constants and the MMRGlc

Quantification and parametric imaging of renal cortical blood flow in vivo based on Patlak graphical analysis

Quantification and parametric imaging of renal cortical blood flow in vivo based on Patlak graphical analysis. Patlak graphical analysis was applied to quantify renal cortical blood flow with N-13 ammonia and dynamic positron emission tomography. Measurements were made in a swine model of kidney transplantation with a wide range of normal and abnormal renal blood flows (N = 57 studies) and in 20 healthy human volunteers (N = 45 studies). Estimates of renal cortical blood flow by the Patlak method were compared to those from a two-compartment model for N-13 ammonia. In addition, estimates of renal cortical blood flow by the N-13 ammonia PET approach were compared in 10 normal human volunteers to estimates by the metabolically inert, freely diffusible O-15 water and a one-compartment model. Patlak graphical analysis estimates of renal cortical blood flow correlated linearly with the standard two-compartment model in pigs (y = -0.05 + 1.01x, r = 0.99) and in humans (y = 0.57 + 0.88x, r = 0.93). Estimates of renal cortical blood flow by O-15 water in human volunteers were also linearly correlated with those by N-13 ammonia and the Patlak graphical analysis (y = 0.71 + 0.84x, r = 0.86). Renal cortical blood flow estimates were highly reproducible both with N-13 ammonia and O-15 water measurements in humans. It is concluded that the Patlak graphical analysis with N-13 ammonia dynamic positron emission tomographic imaging renders accurate and reproducible estimates of renal cortical blood flow. Moreover, the graphical analysis approach is 1,000 times faster than the standard model fitting approach and suitable for generating parametric images of renal blood flow in the clinical setting

Simplifying cardiovascular magnetic resonance pulse sequence terminology.

We propose a set of simplified terms to describe applied Cardiovascular Magnetic Resonance (CMR) pulse sequence techniques in clinical reports, scientific articles and societal guidelines or recommendations. Rather than using various technical details in clinical reports, the description of the technical approach should be based on the purpose of the pulse sequence. In scientific papers or other technical work, this should be followed by a more detailed description of the pulse sequence and settings. The use of a unified set of widely understood terms would facilitate the communication between referring physicians and CMR readers by increasing the clarity of CMR reports and thus improve overall patient care. Applied in research articles, its use would facilitate non-expert readers' understanding of the methodology used and its clinical meaning

Precision measurement of cardiac structure and function in cardiovascular magnetic resonance using machine learning

BACKGROUND: Measurement of cardiac structure and function from images (e.g. volumes, mass and derived parameters such as left ventricular (LV) ejection fraction [LVEF]) guides care for millions. This is best assessed using cardiovascular magnetic resonance (CMR), but image analysis is currently performed by individual clinicians, which introduces error. We sought to develop a machine learning algorithm for volumetric analysis of CMR images with demonstrably better precision than human analysis. METHODS: A fully automated machine learning algorithm was trained on 1923 scans (10 scanner models, 13 institutions, 9 clinical conditions, 60,000 contours) and used to segment the LV blood volume and myocardium. Performance was quantified by measuring precision on an independent multi-site validation dataset with multiple pathologies with n = 109 patients, scanned twice. This dataset was augmented with a further 1277 patients scanned as part of routine clinical care to allow qualitative assessment of generalization ability by identifying mis-segmentations. Machine learning algorithm ('machine') performance was compared to three clinicians ('human') and a commercial tool (cvi42, Circle Cardiovascular Imaging). FINDINGS: Machine analysis was quicker (20 s per patient) than human (13 min). Overall machine mis-segmentation rate was 1 in 479 images for the combined dataset, occurring mostly in rare pathologies not encountered in training. Without correcting these mis-segmentations, machine analysis had superior precision to three clinicians (e.g. scan-rescan coefficients of variation of human vs machine: LVEF 6.0% vs 4.2%, LV mass 4.8% vs. 3.6%; both P < 0.05), translating to a 46% reduction in required trial sample size using an LVEF endpoint. CONCLUSION: We present a fully automated algorithm for measuring LV structure and global systolic function that betters human performance for speed and precision

Myocardial extravascular extracellular volume fraction measurement by gadolinium cardiovascular magnetic resonance in humans: slow infusion versus bolus

<p>Abstract</p> <p>Background</p> <p>Myocardial extravascular extracellular volume fraction (Ve) measures quantify diffuse fibrosis not readily detectable by conventional late gadolinium (Gd) enhancement (LGE). Ve measurement requires steady state equilibrium between plasma and interstitial Gd contrast. While a constant infusion produces steady state, it is unclear whether a simple bolus can do the same. Given the relatively slow clearance of Gd, we hypothesized that a bolus technique accurately measures Ve, thus facilitating integration of myocardial fibrosis quantification into cardiovascular magnetic resonance (CMR) workflow routines. Assuming equivalence between techniques, we further hypothesized that Ve measures would be reproducible across scans.</p> <p>Methods</p> <p>In 10 volunteers (ages 20-81, median 33 yr, 3 females), we compared serial Ve measures from a single short axis slice from two scans: first, during a constant infusion, and second, 12-50 min after a bolus (0.2 mmol/kg gadoteridol) on another day. Steady state during infusion was defined when serial blood and myocardial T1 data varied <5%. We measured T1 on a 1.5 T Siemens scanner using a single-shot modified Look Locker inversion recovery sequence (MOLLI) with balanced SSFP. To shorten breath hold times, T1 values were measured with a shorter sampling scheme that was validated with spin echo relaxometry (TR = 15 sec) in CuSO4-Agar phantoms. Serial infusion vs. bolus Ve measures (n = 205) from the 10 subjects were compared with generalized estimating equations (GEE) with exchangeable correlation matrices. LGE images were also acquired 12-30 minutes after the bolus.</p> <p>Results</p> <p>No subject exhibited LGE near the short axis slices where Ve was measured. The Ve range was 19.3-29.2% and 18.4-29.1% by constant infusion and bolus, respectively. In GEE models, serial Ve measures by constant infusion and bolus did not differ significantly (difference = 0.1%, p = 0.38). For both techniques, Ve was strongly related to age (p < 0.01 for both) in GEE models, even after adjusting for heart rate. Both techniques identically sorted older individuals with higher mean Ve values.</p> <p>Conclusion</p> <p>Myocardial Ve can be measured reliably and accurately 12-50 minutes after a simple bolus. Ve measures are also reproducible across CMR scans. Ve estimation can be integrated into CMR workflow easily, which may simplify research applications involving the quantification of myocardial fibrosis.</p

[11C]acetate PET/CT Visualizes Skeletal Muscle Exercise Participation, Impaired Function, and Recovery after Hip Arthroplasty; First Results

Based on skeletal muscle acetate physiology we aimed studying muscle function after hip arthroplasty with [(11)C]acetate PET