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Background: Studying the effects of medications on endpoints in an observational setting is an important yet challenging problem due to confounding by indication. The purpose of this study is to describe methodology for estimating such effects while including prevalent medication users. These techniques are illustrated in models relating statin use to cardiovascular disease (CVD) in a large multi-ethnic cohort study. Methods: The Multi-Ethnic Study of Atherosclerosis (MESA) includes 6814 participants aged 45-84 years free of CVD. Confounding by indication was mitigated using a two step approach: First, the untreated values of cholesterol were treated as missing data and the values imputed as a function of the observed treated value, dose and type of medication, and participant characteristics. Second, we construct a propensity-score modeling the probability of medication initiation as a function of measured covariates and estimated pre-treatment cholesterol value. The effect of statins on CVD endpoints were assessed using weighted Cox proportional hazard models using inverse probability weights based on the propensity score. Results: Based on a meta-analysis of randomized controlled trials (RCT) statins are associated with a reduced risk of CVD (relative risk ratio = 0.73, 95% CI: 0.70, 0.77). In an unweighted Cox model adjusting for traditional risk factors we observed little association of statins with CVD (hazard ratio (HR) = 0.97, 95% CI: 0.60, 1.59). Using weights based on a propensity model for statins that did not include the estimated pre-treatment cholesterol we observed a slight protective association (HR = 0.92, 95% CI: 0.54-1.57). Results were similar using a new-user design where prevalent users of statins are excluded (HR = 0.91, 95% CI: 0.45-1.80). Using weights based on a propensity model with estimated pre-treatment cholesterol the effects of statins (HR = 0.74, 95% CI: 0.38, 1.42) were consistent with the RCT literature. Conclusions: The imputation of pre-treated cholesterol levels for participants on medication at baseline in conjunction with a propensity score yielded estimates that were consistent with the RCT literature. These techniques could be useful in any example where inclusion of participants exposed at baseline in the analysis is desirable, and reasonable estimates of pre-exposure biomarker values can be estimated. [ABSTRACT FROM AUTHOR]

An abstract of the paper "Myocardial and Blood T1 Quantification in Normal Volunteers at 3T," by Christopher T. Sibley and colleagues, from the 2011 SCMR/Euro CMR Joint Scientific Sessions, held in Nice, France, from February 3-6, 2011, is presented.

Background: Cardiac magnetic resonance (CMR) T1 mapping has been used to characterize myocardial diffuse fibrosis. The aim of this study is to determine the reproducibility and sample size of CMR fibrosis measurements that would be applicable in clinical trials. Methods: A modified Look-Locker with inversion recovery (MOLLI) sequence was used to determine myocardial T1 values pre-, and 12 and 25min post-administration of a gadolinium-based contrast agent at 3 Tesla. For 24 healthy subjects (8 men; 29 ± 6 years), two separate scans were obtained a) with a bolus of 0.15mmol/kg of gadopentate dimeglumine and b) 0.1mmol/kg of gadobenate dimeglumine, respectively, with averaged of 51 ± 34 days between two scans. Separately, 25 heart failure subjects (12 men; 63 ± 14 years), were evaluated after a bolus of 0.15mmol/kg of gadopentate dimeglumine. Myocardial partition coefficient (λ) was calculated according to (ΔR1myocardium/ ΔR1blood), and ECV was derived from λ by adjusting (1-hematocrit). Results: Mean ECV and λ were both significantly higher in HF subjects than healthy (ECV: 0.287 ± 0.034 vs. 0.267 ± 0.028, p=0.002; &#03BB;: 0.481 ± 0.052 vs. 442 ± 0.037, p < 0.001, respectively). The inter-study ECV and λ variation were about 2.8 times greater than the intra-study ECV and λ variation in healthy subjects (ECV:0.017 vs. 0.006, λ:0.025 vs. 0.009, respectively). The estimated sample size to detect ECV change of 0.038 or λ change of 0.063 (corresponding to ~3% increase of histological myocardial fibrosis) with a power of 80% and an alpha error of 0.05 for heart failure subjects using a two group design was 27 in each group, respectively. Conclusion: ECV and λ quantification have a low variability across scans, and could be a viable tool for evaluating clinical trial outcome. [ABSTRACT FROM AUTHOR]

An abstract of the article "Sample size calculation for clinical trials using cardiac magnetic resonance partition coefficient and extracellular volume fraction for the assessment of diffuse myocardial fibrosis," by Songtao Liu and colleagues is presented.

Background: Cardiac magnetic resonance (CMR) T1 mapping has been used to characterize myocardial diffuse fibrosis. The aim of this study is to determine the reproducibility and sample size of CMR fibrosis measurements that would be applicable in clinical trials., Methods: A modified Look-Locker with inversion recovery (MOLLI) sequence was used to determine myocardial T1 values pre-, and 12 and 25min post-administration of a gadolinium-based contrast agent at 3 Tesla. For 24 healthy subjects (8 men; 29 ± 6 years), two separate scans were obtained a) with a bolus of 0.15mmol/kg of gadopentate dimeglumine and b) 0.1mmol/kg of gadobenate dimeglumine, respectively, with averaged of 51 ± 34 days between two scans. Separately, 25 heart failure subjects (12 men; 63 ± 14 years), were evaluated after a bolus of 0.15mmol/kg of gadopentate dimeglumine. Myocardial partition coefficient (λ) was calculated according to (ΔR1myocardium/ΔR1blood), and ECV was derived from λ by adjusting (1-hematocrit)., Results: Mean ECV and λ were both significantly higher in HF subjects than healthy (ECV: 0.287 ± 0.034 vs. 0.267 ± 0.028, p=0.002; λ: 0.481 ± 0.052 vs. 442 ± 0.037, p < 0.001, respectively). The inter-study ECV and λ variation were about 2.8 times greater than the intra-study ECV and λ variation in healthy subjects (ECV:0.017 vs. 0.006, λ:0.025 vs. 0.009, respectively). The estimated sample size to detect ECV change of 0.038 or λ change of 0.063 (corresponding to ~3% increase of histological myocardial fibrosis) with a power of 80% and an alpha error of 0.05 for heart failure subjects using a two group design was 27 in each group, respectively., Conclusion: ECV and λ quantification have a low variability across scans, and could be a viable tool for evaluating clinical trial outcome.

Background: Myocardial T1 relaxation time (T1 time) and extracellular volume fraction (ECV) are altered in the presence of myocardial fibrosis. The purpose of this study was to evaluate acquisition factors that may result in variation of measured T1 time and ECV including magnetic field strength, cardiac phase and myocardial region., Methods: 31 study subjects were enrolled and underwent one cardiovascular MR exam at 1.5 T and two exams at 3 T, each on separate days. A Modified Look-Locker Inversion Recovery (MOLLI) sequence was acquired before and 5, 10, 12, 20, 25 and 30 min after administration of 0.15 mmol/kg gadopentetate dimeglumine (Gd-DTPA; Magnevist) at 1.5 T (exam 1). For exam 2, MOLLI sequences were acquired at 3 T both during diastole and systole, before and after administration of Gd-DTPA (0.15 mmol/kg Magnevist).Exam 3 was identical to exam 2 except gadobenate dimeglumine was administered (Gd-BOPTA; 0.1 mmol/kg Multihance). T1 times were measured in myocardium and blood. ECV was calculated by (ΔR1myocardium/ΔR1blood)*(1-hematocrit)., Results: Before gadolinium, T1 times of myocardium and blood were significantly greater at 3 T versus 1.5 T (28% and 31% greater, respectively, p < 0.001); after gadolinium, 3 T values remained greater than those at 1.5 T (14% and 12% greater for myocardium and blood at 3 T with Gd-DTPA, respectively, p < 0.0001 and 18% and 15% greater at 3 T with Gd-BOPTA, respectively, p < 0.0001). However, ECV did not vary significantly with field strength when using the same contrast agent at equimolar dose (p = 0.2). Myocardial T1 time was 1% shorter at systole compared to diastole pre-contrast and 2% shorter at diastole compared to systole post-contrast (p < 0.01). ECV values were greater during diastole compared to systole on average by 0.01 (p < 0.01 to p < 0.0001). ECV was significantly higher for the septum compared to the non-septal myocardium for all three exams (p < 0.0001-0.01) with mean absolute differences of 0.01, 0.004, and 0.07, respectively, for exams 1, 2 and 3., Conclusion: ECV is similar at field strengths of 1.5 T and 3 T. Due to minor variations in T1 time and ECV during the cardiac cycle and in different myocardial regions, T1 measurements should be obtained at the same cardiac phase and myocardial region in order to obtain consistent results.

Purpose: Myocardial T1 relaxation time (T1 time) and extracellular volume fraction (ECV) are altered in patients with diffuse myocardial fibrosis. The purpose of this study was to perform an intra-individual assessment of normal T1 time and ECV for two different contrast agents., Methods: A modified Look-Locker Inversion Recovery (MOLLI) sequence was acquired at 3 T in 24 healthy subjects (8 men; 28 ± 6 years) at mid-ventricular short axis pre-contrast and every 5 min between 5-45 min after injection of a bolus of 0.15 mmol/kg gadopentetate dimeglumine (Gd-DTPA; Magnevist®) (exam 1) and 0.1 mmol/kg gadobenate dimeglumine (Gd-BOPTA; Multihance®) (exam 2) during two separate scanning sessions. T1 times were measured in myocardium and blood on generated T1 maps. ECVs were calculated as ΔR1 myocardium/ΔR1 blood*1-hematocrit., Results: Mean pre-contrast T1 relaxation times for myocardium and blood were similar for both the first and second CMR exam (p > 0.5). Overall mean post-contrast myocardial T1 time was 15 ± 2 ms (2.5 ± 0.7%) shorter for Gd-DTPA at 0.15 mmol/kg compared to Gd-BOPTA at 0.1 mmol/kg (p < 0.01) while there was no significant difference for T1 time of blood pool (p > 0.05). Between 5 and 45 minutes after contrast injection, mean ECV values increased linearly with time for both contrast agents from 0.27 ± 0.03 to 0.30 ± 0.03 (p < 0.0001). Mean ECV values were slightly higher (by 0.01, p < 0.05) for Gd-DTPA compared to Gd-BOPTA. Inter-individual variation of ECV was higher (CV 8.7% [exam 1, Gd-DTPA] and 9.4% [exam 2, Gd-BOPTA], respectively) compared to variation of pre-contrast myocardial T1 relaxation time (CV 4.5% [exam 1] and 3.0% [exam 2], respectively). ECV with Gd-DTPA was highly correlated to ECV by Gd-BOPTA (r = 0.803; p < 0.0001)., Conclusion: In comparison to pre-contrast myocardial T1 relaxation time, variation in ECV values of normal subjects is larger. However, absolute differences in ECV between Gd-DTPA and Gd-BOPTA were small and rank correlation was high. There is a small and linear increase in ECV over time, therefore ideally images should be acquired at the same delay after contrast injection.

Background: To compare 11 heartbeat (HB) and 17 HB modified lock locker inversion recovery (MOLLI) pulse sequence at 3T and to establish preliminary reference values for myocardial T1 and the extracellular volume fraction (ECV)., Methods: Both phantoms and normal volunteers were scanned at 3T using 11 HB and 17 HB MOLLI sequence with the following parameters: spatial resolution = 1.75 × 1.75 × 10 mm on a 256 × 180 matrix, TI initial = 110 ms, TI increment = 80 ms, flip angle = 35°, TR/TE = 1.9/1.0 ms. All volunteers were administered Gadolinium-DTPA (Magnevist, 0.15 mmol/kg), and multiple post-contrast MOLLI scans were performed at the same pre-contrast position from 3.5-23.5 minutes after a bolus contrast injection. Late gadolinium enhancement (LGE) images were also acquired 12-30 minutes after the gadolinium bolus., Results: T1 values of 11 HB and 17 HB MOLLI displayed good agreement in both phantom and volunteers. The average pre-contrast myocardial and blood T1 was 1315 ± 39 ms and 2020 ± 129 ms, respectively. ECV was stable between 8.5 to 23.5 minutes post contrast with an average of 26.7 ± 1.0%., Conclusion: The 11 HB MOLLI is a faster method for high-resolution myocardial T1 mapping at 3T. ECV fractions are stable over a wide time range after contrast administration.