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The cohort of 250 CMR scans was divided into a derivation and validation cohort. A formula for calculating synthetic hematocrit (Hct syn) and synthetic extracellular volume (ECV syn) was derived and showed good results when validated against conventional Hct from blood sampling. Bias of ECV syn was comparable to bias from repeated Hct measurements. Use of published formulas for calculating ECV syn can lead to significant errors. Right panels: mean delta ± 1.96 * SD. [Display omitted] Calculation of extracellular volume fraction (ECV), a marker of myocardial fibrosis in cardiac magnetic resonance imaging (CMR), requires hematocrit (Hct). We aimed to correlate Hct levels with native blood T1 times, to derive a formula for estimating synthetic Hct (Hct syn) and synthetic ECV (ECV syn), to assess accuracy of ECV syn and to compare our model with published formulas. In this retrospective study, a cohort of 250 CMR scans with T1 mapping (3T, MOLLI 5(3)3, endsystolic aquisition), was divided into a derivation and validation cohort. Native T1 times of the left ventricular blood pool (T1 native,midLV) were correlated with Hct levels from blood sampling within 24 h (Hct 24h) and a formula for calculation of Hct syn was derived by linear regression. In the derivation cohort (n = 167), Hct 24h showed a good association with T1 native,midLV (r = −0.711, p < 0.001). The resulting regression equation was Hctsyn = 1/T1 native,midLV * 1355.52–0.310. In the validation cohort (n = 83), Hct syn and Hct 24h showed good correlation (r = 0.726, p < 0.001), while ECV syn , and ECV 24h demonstrated excellent correlation (r = 0.940, p < 0.001). ECV syn had a minimal bias of 0.28 % and the misclassification rate (8.8 %) was comparable to the variability introduced by repeated Hct measurements (misclassification in 7.5 %). Applying published formulas in our cohort resulted in incorrect classification in up to 60 %. We provide a formula for estimating Hct syn from native blood T1 on a 3T scanner. The measurement error of ECV syn is low and comparable to the error due to retest variability of conventional Hct. Scanner- and sequence-specific formulas should be used. [ABSTRACT FROM AUTHOR]

Background: Quantification of myocardial blood flow (MBF) from dynamic contrast‐enhanced (DCE) MRI can be performed using a signal intensity model that incorporates T1 values of blood and myocardium. Purpose: To assess the impact of T1 values on pixelwise MBF quantification, specifically to evaluate the influence of 1) study population‐averaged vs. subject‐specific, 2) diastolic vs. systolic, and 3) regional vs. global myocardial T1 values. Study Type: Prospective. Subjects: Fifteen patients with chronic coronary heart disease. Field Strength/Sequence: 3T; modified Look–Locker inversion recovery for T1 mapping and saturation recovery gradient echo for DCE imaging, both acquired in a mid‐ventricular short‐axis slice in systole and diastole. Assessment: MBF was estimated using Fermi modeling and signal intensity nonlinearity correction with different T1 values: study population‐averaged blood and myocardial, subject‐specific systolic and diastolic, and segmental T1 values. Myocardial segments with perfusion deficits were identified visually from DCE series. Statistical Tests: The relationships between MBF parameters derived by different methods were analyzed by Bland–Altman analysis; corresponding mean values were compared by t‐test. Results: Using subject‐specific diastolic T1 values, global diastolic MBF was 0.61 ± 0.13 mL/(min·g). It did not differ from global MBF derived from the study population‐averaged T1 (P = 0.88), but the standard deviation of differences was large (0.07 mL/(min·g), 11% of mean MBF). Global diastolic and systolic MBF did not differ (P = 0.12), whereas global diastolic MBF using systolic (0.62 ± 0.13 mL/(min·g)) and diastolic T1 values differed (P < 0.05). If regional instead of global T1 values were used, segmental MBF was lower in segments with perfusion deficits (bias = −0.03 mL/(min·g), −7% of mean MBF, P < 0.05) but higher in segments without perfusion deficits (bias = 0.01 mL/(min·g), 1% of mean MBF, P < 0.05). Data Conclusion: Whereas cardiac phase‐specific T1 values have a minor impact on MBF estimates, subject‐specific and myocardial segment‐specific T1 values substantially affect MBF quantification. Level of Evidence: 3 Technical Efficacy Stage: 3 [ABSTRACT FROM AUTHOR]

• Transmitral velocities derived from MR 4D flow are evaluation method dependent. • 4D flow allows accurate and precise evaluation of transmitral velocity parameters. • 4D flow allows accurate and precise evaluation of myocardial peak velocities. To compare agreement of different evaluation methods of magnetic resonance (MR) 4D flow-derived diastolic transmitral and myocardial peak velocities as well as their ratios, using echocardiography as reference. In this prospective study, 60 subjects without symptoms of cardiovascular disease underwent echocardiography and non-contrast 3 T MR 4D flow imaging of the heart. Early- (E) and late-diastolic (A) transmitral peak filling velocities were evaluated from 4D flow data using three different strategies: 1) at the mitral valve tips in short-axis orientation (SA-method), 2) between the mitral valve tips in 4-chamber orientation (4-chamber-method), and 3) as maximal velocities in the transmitral inflow volume (max-velocity-method). Septal, lateral and average early-diastolic myocardial peak velocities (e') were derived from the myocardial tissue in the vicinity of the mitral valve. 4D flow parameters were compared with echocardiography by correlation and Bland-Altman analysis. All 4D flow-derived E, A and E/A values correlated with echocardiography (r = 0.65–0.73, 0.75–0.83 and 0.74–0.86, respectively). While the SA- and 4-chamber-methods substantially underestimated E and A compared to echocardiography (p < 0.001), the max-velocity-method provided E (p = 0.13) and E/A (p = 0.07) without significant bias. Septal, lateral and average e' from 4D flow as well as the max-velocity-method-derived E/e' correlated with echocardiographic measurements (r = 0.64–0.81) and showed no significant bias (p = 0.26–0.54). MR 4D flow imaging allows precise and accurate evaluation of transmitral and myocardial peak velocities for characterization of LV diastolic function without significant bias to echocardiography, when transmitral velocities are assessed from the transmitral inflow volume. This enables the use of validated echocardiography threshold values. [ABSTRACT FROM AUTHOR]

The Tel2 (also known as Telo2) and Tti1 proteins control the cellular abundance of mammalian PIKKs and are integral components of mTORC1 and mTORC2. Here we report that Tel2 and Tti1 are targeted for degradation within mTORC1 by the SCFFbxo9 ubiquitin ligase to adjust mTOR signalling to growth factor availability. This process is primed by CK2, which translocates to the cytoplasm to mediate mTORC1-specific phosphorylation of Tel2/Tti1, subsequent to growth factor deprivation. As a consequence, mTORC1 is inactivated to restrain cell growth and protein translation whereas relief of feedback inhibition activates the PI(3)K/TORC2/Akt pathway to sustain survival. Significantly, primary human multiple myelomas exhibit high levels of Fbxo9. In this setting, PI(3)K/TORC2/Akt signalling and survival of multiple myeloma cells is dependent on Fbxo9 expression. Thus, mTORC1-specific degradation of the Tel2 and Tti1 proteins represents a central mTOR regulatory mechanism with implications in multiple myeloma, both in promoting survival and in providing targets for the specific treatment of multiple myeloma with high levels of Fbxo9 expression. [ABSTRACT FROM AUTHOR]

• Compared to healthy subjects RV-GLS, all RV systolic strain rates and the LV systolic longitudinal strain rate show lower magnitudes in PH. • Associations of LV and RV global peak strains with mPAP disappeared after adjustment with the respective ventricular ejection fraction. • In patients with pulmonary hypertension RV-GRS and the RV-GCS as well as the respective diastolic strain rates are associated with PAWP. To investigate associations of cardiac magnetic resonance feature-tracking-derived left (LV) and right ventricular (RV) global myocardial peak strains and strain rates with volumetric function and hemodynamic parameters to identify the major determinants of myocardial strain alterations in pulmonary hypertension (PH). Sixty-seven patients with PH or at risk of developing PH underwent right heart catheterization (RHC) and cine realtime imaging at 3 T. RHC parameters included mean pulmonary arterial pressure (mPAP), which was used for the diagnosis of PH. LV and RV volumetric function and feature-tracking-derived global radial, circumferential, and longitudinal (GLS) peak strains, together with their strain rates, were evaluated from cine images using routine software. Furthermore, myocardial strain parameters of 24 healthy subjects were evaluated as controls. Means were compared by t -test; relationships between parameters were investigated by correlation and regression analysis. Compared to controls, RV-GLS, all RV systolic strain rates and the LV systolic longitudinal strain rate showed lower magnitudes in PH (RV-GLS: −21 ± 4% vs. −16 ± 5%, p < 0.0001); the strongest univariate correlate to mPAP was the RV-GLS (r = 0.59). All LV and RV strain parameters yielded stronger correlations with their respective ejection fractions. In bi-linear models using mPAP and ejection fraction as predictors, mPAP remained significant only for diastolic LV radial and circumferential strain rates. Impairment of myocardial strains is more strongly associated with alterations in LV and RV volumetric function parameters than elevated mPAP, therefore limiting diagnostic information of myocardial strain parameters in PH. [ABSTRACT FROM AUTHOR]

Background: Quantification of myocardial blood flow (MBF) from dynamic contrast-enhanced (DCE) MRI can be performed using a signal intensity model that incorporates T 1 values of blood and myocardium., Purpose: To assess the impact of T 1 values on pixelwise MBF quantification, specifically to evaluate the influence of 1) study population-averaged vs. subject-specific, 2) diastolic vs. systolic, and 3) regional vs. global myocardial T 1 values., Study Type: Prospective., Subjects: Fifteen patients with chronic coronary heart disease., Field Strength/sequence: 3T; modified Look-Locker inversion recovery for T 1 mapping and saturation recovery gradient echo for DCE imaging, both acquired in a mid-ventricular short-axis slice in systole and diastole., Assessment: MBF was estimated using Fermi modeling and signal intensity nonlinearity correction with different T 1 values: study population-averaged blood and myocardial, subject-specific systolic and diastolic, and segmental T 1 values. Myocardial segments with perfusion deficits were identified visually from DCE series., Statistical Tests: The relationships between MBF parameters derived by different methods were analyzed by Bland-Altman analysis; corresponding mean values were compared by t-test., Results: Using subject-specific diastolic T 1 values, global diastolic MBF was 0.61 ± 0.13 mL/(min·g). It did not differ from global MBF derived from the study population-averaged T 1 (P = 0.88), but the standard deviation of differences was large (0.07 mL/(min·g), 11% of mean MBF). Global diastolic and systolic MBF did not differ (P = 0.12), whereas global diastolic MBF using systolic (0.62 ± 0.13 mL/(min·g)) and diastolic T 1 values differed (P < 0.05). If regional instead of global T 1 values were used, segmental MBF was lower in segments with perfusion deficits (bias = -0.03 mL/(min·g), -7% of mean MBF, P < 0.05) but higher in segments without perfusion deficits (bias = 0.01 mL/(min·g), 1% of mean MBF, P < 0.05)., Data Conclusion: Whereas cardiac phase-specific T 1 values have a minor impact on MBF estimates, subject-specific and myocardial segment-specific T 1 values substantially affect MBF quantification., Level of Evidence: 3 TECHNICAL EFFICACY STAGE: 3., (© 2020 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background:  Cardiac magnetic resonance imaging (MRI) represents the established reference standard method for the assessment of cardiac function and non-invasive evaluation of myocardial tissue in a variety of clinical questions, wherein quantification of cardiac parameters gains growing diagnostic and differential-diagnostic importance. This review aims to summarize established and newly emerging quantitative parameters, which are assessed in routine cardiac MRI. Interrelations and interdependencies between metrics are explained, and common factors affecting quantitative results are discussed., Method:  The review is based on a PubMed literature research using the search terms "cardiac magnetic resonance" and "quantification", "recommendations", "quantitative evaluation/assessment", "reference method", "reference/normal values", "pitfalls" or "artifacts" published between 2000-2019., Results and Conclusion:  Quantitative functional, phase contrast, and perfusion imaging, as well as relaxation time mapping techniques give opportunity for assessment of a large number of quantitative cardiac MRI parameters in clinical routine. Application of these techniques allows for characterization of function, morphology and perfusion of the heart beyond visual analysis of images, either in primary evaluation and comparison to normal values or in patients' follow-up and treatment monitoring. However, with implementation of quantitative parameters in clinical routine, standardization is of particular importance as different acquisition and evaluation strategies and algorithms may substantially influence results, though not always immediately apparent., Key Points:   · Clinical cardiac MRI provides numerous functional and morphological quantitative parameters.. · Quantitative cardiac MRI enables assessment of diffuse and global myocardial alterations.. · Standardized data acquisition/evaluation is the prerequisite for diagnostic use of quantitative cardiac MRI parameters.., Citation Format: · Reiter U, Reiter C, Kräuter C et al. Quantitative Clinical Cardiac Magnetic Resonance Imaging. Fortschr Röntgenstr 2020; 192: 246 - 256., Competing Interests: Gert Reiter is employee of Research & Developement, Siemens Healthcare Diagnostics GmbH., (© Georg Thieme Verlag KG Stuttgart · New York.)