The myocardial perfusion reserve, defined as the ratio of hyperemic and basal myocardial blood flow, is a useful indicator of the functional significance of a coronary artery lesion. Rapid magnetic resonance (MR) imaging for the noninvasive detection of a bolus-injected contrast agent as a MR tracer is applied to the measurement of regional tissue perfusion during rest and hyperemia, in patients with microvascular dysfunction. A Fermi function model for the distribution of tracer residence times in the myocardium is used to fit the MR signal curves. The myocardial perfusion reserve is calculated from the impulse response amplitudes for rest and hyperemia. The assumptions of the model are tested with Monte Carlo simulations, using a multiple path, axially distributed mathematical model of blood tissue exchange, which allows for systematic variation of blood flow, vascular volume, and capillary permeability. For a contrast-to-noise ratio of 6:1, and over a range of flows from 0.5 to 4.0 ml/min per g of tissue, the ratio of the impulse response amplitudes for hyperemic and basal flows is linearly proportional to the ratio of model blood flows, if the mean transit time of the input function is shorter than approximately 9 s. The uncertainty in the blood flow reserve estimates grows both at low (< 1.0 ml/min/g) and high (> 3-4 ml/min/g) flows. The predictions of the Monte Carlo simulations agree with the results of MR first pass studies in patients without significant coronary artery lesions and microvascular dysfunction, where the perfusion reserve in the territory of the left anterior descending coronary artery (LAD) correlates linearly with the intracoronary Doppler ultrasound flow reserve in the LAD (r = 0.84), in agreement with previous PET studies.

The normal LV differs in volume and mass between sexes and among certain ethnic groups. When indexed by body surface area, LV mass was independent of age for both sexes. Studies that assess cardiovascular risk factors in relationship to cardiac function and structure need to account for these normal variations in the population.

Background-Two-dimensional echocardiography is currently the standard test for the clinical diagnosis of hypertrophic cardiomyopathy (HCM). The present study was undertaken to determine whether cardiac MRI (CMR) affords greater accuracy than echocardiography in establishing the diagnosis and assessing the magnitude of left ventricular (LV) hypertrophy in HCM. Methods and Results-Forty-eight patients (age 34Ϯ16 years) suspected of having HCM (or with a confirmed diagnosis)were imaged by both echocardiography and CMR to assess LV wall thickness in 8 anatomic segments (total nϭ384 segments) and compared in a blinded fashion. Maximum LV thickness was similar by echocardiography (21.7Ϯ9.1 mm) and CMR (22.5Ϯ9.6 mm; Pϭ0.21). However, in 3 (6%) of the 48 patients, echocardiography did not demonstrate LV hypertrophy, and CMR identified otherwise undetected areas of wall thickening in the anterolateral LV free wall (17 to 20 mm), which resulted in a new diagnosis of HCM. In the overall study group, compared with CMR, echocardiography also underestimated the magnitude of hypertrophy in the basal anterolateral free wall (by 20Ϯ6%; Pϭ0.001), as well as the presence of extreme LV wall thickness (Ն30 mm) in 10% of patients (PϽ0.05). Conclusions-CMR

OBJECTIVES This study sought to evaluate differential effects of visceral fat (VF) and subcutaneous fat and their effects on metabolic syndrome (MetS) risk across body mass index (BMI) categories. BACKGROUND The regional distribution of adipose tissue is an emerging risk factor for cardiometabolic disease, although serial changes in fat distribution have not been extensively investigated. VF and its alterations over time may be a better marker for risk than BMI in normal weight and overweight or obese individuals. METHODS We studied 1,511 individuals in the MESA (Multi-Ethnic Study of Atherosclerosis) with adiposity assessment by computed tomography (CT). A total of 253 participants without MetS at initial scan underwent repeat CT (median interval 3.3 years). We used discrete Cox regression with net reclassification to investigate whether baseline and changes in VF area are associated with MetS. RESULTS Higher VF was associated with cardiometabolic risk and coronary artery calcification, regardless of BMI. After adjustment, VF was more strongly associated with incident MetS than subcutaneous fat regardless of weight, with a 28% greater MetS hazard per 100 cm2/m VF area and significant net reclassification (net reclassification index: 0.44, 95% confidence interval [CI]: 0.29 to 0.60) over clinical risk. In individuals with serial imaging, initial VF (hazard ratio: 1.24 per 100 cm2/m, 95% CI: 1.08 to 1.44 per 100 cm2/m, p = 0.003) and change in VF (hazard ratio: 1.05 per 5% change, 95% CI: 1.01 to 1.08 per 5% change, p = 0.02) were associated with MetS after adjustment. Changes in subcutaneous fat were not associated with incident MetS after adjustment for clinical risk and VF area. CONCLUSIONS VF is modestly associated with BMI. However, across BMI, a single measure of and longitudinal change in VF predict MetS, even accounting for weight changes. Visceral adiposity is essential to assessing cardiometabolic risk, regardless of age, race, or BMI, and may serve as a marker and target of therapy in cardiometabolic disease.

CMR tissue characterization provides effective risk stratification in patients with suspected myocarditis.

In this cohort free of clinical cardiovascular disease, modifiable risk factors were associated with subclinical alterations in LV size and systolic function as detected by cardiac MRI.

Magnetic resonance (MR) imaging during the first pass of an injected contrast agent has been used to assess myocardial perfusion, but the quantification of blood flow has been generally judged as too complex for its clinical application. This study demonstrates the feasibility of applying model-independent deconvolution to the measured tissue residue curves to quantify myocardial perfusion. Model-independent approaches only require minimal user interaction or expertise in modeling. Monte Carlo simulations were performed with contrast-to-noise ratios typical of MR myocardial perfusion studies to determine the accuracy of the resulting blood flow estimates. With a B-spline representation of the tissue impulse response and Tikhonov regularization, the bias of blood flow estimates obtained by model-independent deconvolution was less than 1% in all cases for peak contrast to noise ratios in the range from 15:1 to 20:1. The relative dispersion of blood flow estimates in Monte Carlo simulations was less than 7%. Comparison of MR blood flow estimates against measurements with radio-isotope labeled microspheres indicated excellent linear correlation (R2 = 0.995, slope: 0.96, intercept: 0.06). It can be concluded from these studies that the application of myocardial blood flow quantification with MRI can be performed with model-independent methods, and this should support a more widespread use of blood flow quantification in the clinical environment.

The myocardial perfusion reserve can be quantified with first-pass MR imaging. In patients with microvascular dysfunction, the myocardial perfusion reserve matches the reduced coronary flow reserve.