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Purpose: Guidelines recommend measuring myocardial extracellular volume (ECV) using T1‐mapping before and 10–30 min after contrast agent administration. Data are then analyzed using a linear model (LM), which assumes fast water exchange (WX) between the ECV and cardiomyocytes. We investigated whether limited WX influences ECV measurements in patients with severe aortic stenosis (AS). Methods: Twenty‐five patients with severe AS and 5 healthy controls were recruited. T1 measurements were made on a 3 T Siemens system using a multiparametric saturation‐recovery single‐shot acquisition (a) before contrast; (b) 4 min post 0.05 mmol/kg gadobutrol; and (c) 4 min, (d) 10 min, and (e) 30 min after an additional gadobutrol dose (0.1 mmol/kg). Three LM‐based ECV estimates, made using paired T1 measurements (a and b), (a and d), and (a and e), were compared to ECV estimates made using all 5 T1 measurements and a two‐site exchange model (2SXM) accounting for WX. Results: Median (range) ECV estimated using the 2SXM model was 25% (21%–39%) for patients and 26% (22%–29%) for controls. ECV estimated in patients using the LM at 10 min following a cumulative contrast dose of 0.15 mmol/kg was 21% (17%–32%) and increased significantly to 22% (19%–35%) at 30 min (p = 0.0001). ECV estimated using the LM was highest following low dose gadobutrol, 25% (19%–38%). Conclusion: Current guidelines on contrast agent dose for ECV measurements may lead to underestimated ECV in patients with severe AS because of limited WX. Use of a lower contrast agent dose may mitigate this effect. [ABSTRACT FROM AUTHOR]

Purpose: DTI characterizes tissue microstructure and provides proxy measures of nerve health. Echo‐planar imaging is a popular method of acquiring DTI but is susceptible to various artifacts (e.g., susceptibility, motion, and eddy currents), which may be ameliorated via preprocessing. There are many pipelines available but limited data comparing their performance, which provides the rationale for this study. Methods: DTI was acquired from the upper limb of heathy volunteers at 3T in blip‐up and blip‐down directions. Data were independently corrected using (i) FSL's TOPUP & eddy, (ii) FSL's TOPUP, (iii) DSI Studio, and (iv) TORTOISE. DTI metrics were extracted from the median, radial, and ulnar nerves and compared (between pipelines) using mixed‐effects linear regression. The geometric similarity of corrected b = 0 images and the slice matched T1‐weighted (T1w) images were computed using the Sörenson‐Dice coefficient. Results: Without preprocessing, the similarity coefficient of the blip‐up and blip‐down datasets to the T1w was 0·80 and 0·79, respectively. Preprocessing improved the geometric similarity by 1% with no difference between pipelines. Compared to TOPUP & eddy, DSI Studio and TORTOISE generated 2% and 6% lower estimates of fractional anisotropy, and 6% and 13% higher estimates of radial diffusivity, respectively. Estimates of anisotropy from TOPUP & eddy versus TOPUP were not different but TOPUP reduced radial diffusivity by 3%. The agreement of DTI metrics between pipelines was poor. Conclusions: Preprocessing DTI from the upper limb improves geometric similarity but the choice of the pipeline introduces clinically important variability in diffusion parameter estimates from peripheral nerves. [ABSTRACT FROM AUTHOR]

Purpose: Diffusion‐weighted MRI is sensitive to incoherent tissue motion, which may confound the measured signal and subsequent analysis. We propose a "motion‐compensated" gradient waveform design for tensor‐valued diffusion encoding that negates the effects bulk motion and incoherent motion in the ballistic regime. Methods: Motion compensation was achieved by constraining the magnitude of gradient waveform moment vectors. The constraint was incorporated into a numerical optimization framework, along with existing constraints that account for b‐tensor shape, hardware restrictions, and concomitant field gradients. We evaluated the efficacy of encoding and motion compensation in simulations, and we demonstrated the approach by linear and planar b‐tensor encoding in a healthy heart in vivo. Results: The optimization framework produced asymmetric motion‐compensated waveforms that yielded b‐tensors of arbitrary shape with improved efficiency compared with previous designs for tensor‐valued encoding, and equivalent efficiency to previous designs for linear (conventional) encoding. Technical feasibility was demonstrated in the heart in vivo, showing vastly improved data quality when using motion compensation. The optimization framework is available online in open source. Conclusion: Our gradient waveform design is both more flexible and efficient than previous methods, facilitating tensor‐valued diffusion encoding in tissues in which motion would otherwise confound the signal. The proposed design exploits asymmetric encoding times, a single refocusing pulse or multiple refocusing pulses, and integrates compensation for concomitant gradient effects throughout the imaging volume. [ABSTRACT FROM AUTHOR]

Purpose: Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization. Methods: Proposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixel‐wise mapping. A distributed kinetics model, blood‐tissue exchange model, is implemented, computing pixel‐wise maps of myocardial blood flow (mL/min/g), permeability‐surface‐area product (mL/min/g), blood volume (mL/g), and interstitial volume (mL/g). Results: Thirty healthy subjects (11 men; 26.4 ± 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 ± 0.4 for stress and 3.7 ± 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (P < 1e‐6), 0.87 ± 0.05 for stress and 0.86 ± 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 ± 1.3 mmol/L at stress and 5.2 ± 1.5 mmol/L at rest. Mean myocardial blood flow at stress and rest were 2.82 ± 0.47 mL/min/g and 0.68 ± 0.16 mL/min/g, respectively. The permeability‐surface‐area product was 1.32 ± 0.26 mL/min/g at stress and 1.09 ± 0.21 mL/min/g at rest (P < 1e‐3). Blood volume was 12.0 ± 0.8 mL/100 g at stress and 9.7 ± 1.0 mL/100 g at rest (P < 1e‐9), indicating good adenosine vasodilation response. Interstitial volume was 20.8 ± 2.5 mL/100 g at stress and 20.3 ± 2.9 mL/100 g at rest (P = 0.50). Conclusions: An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates this fully automated solution for the respiratory MOCO, arterial input function left ventricle mask detection, and pixel‐wise mapping, from free‐breathing myocardial perfusion imaging. [ABSTRACT FROM AUTHOR]

Purpose To compare methods designed to minimize or correct signal nonlinearity in quantitative myocardial dynamic contrast-enhanced (DCE) MRI. Methods DCE-MRI studies were simulated and data acquired in eight volunteers. Signal nonlinearity was corrected using either a dual-bolus approach or model-based correction using proton-density weighted imaging (conventional or dual-sequence acquisition) or T1 data (native or bookend). Scanning of healthy and infarcted myocardium at 3 T was simulated, including noise, saturation imperfection and T1 measurement error. Data were analyzed using model-based deconvolution with a one-compartment (mono-exponential) model. Results Substantial variation between methods was demonstrated in volunteers. In simulations the dual-bolus method proved stable for realistic levels of saturation efficiency but demonstrated bias due to residual nonlinearity. Model-based methods performed ideally in the absence of confounding error sources and were generally robust to noise or saturation imperfection, except for native T1 based correction which was highly sensitive to the latter. All methods demonstrated large variation in accuracy above an over-saturation level where baseline signal was nulled. For the dual-sequence approach this caused substantial bias at the saturation efficiencies observed in volunteers. Conclusion The choice of nonlinearity correction method in myocardial DCE-MRI impacts on accuracy and precision of estimated parameters, particularly in the presence of nonideal saturation. Magn Reson Med 75:1290-1300, 2016. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

T1 maps obtained with modified Look-Locker inversion recovery (MOLLI) can be used to measure myocardial T1. We aimed to evaluate the potential of MOLLI T1 mapping for the assessment of acute and chronic myocardial infarction (MI). A total of 24 patients with a first MI underwent MRI within 8 days and after 6 months. T1 mapping was performed at baseline and at selected intervals between 2-20 min following administration of gadopentetate dimeglumine (Gd-DTPA). Delayed-enhancement (DE) imaging served as the reference standard for delineation of the infarct zone. On T1 maps the myocardial T1 relaxation time was assessed in hyperenhanced areas, hypoenhanced infarct cores, and remote myocardium. The planimetric size of myocardial areas with standardized T1 threshold values was measured. Acute and chronic MI exhibited different T1 changes. Precontrast threshold T1 maps detected segmental abnormalities caused by acute MI with 96% sensitivity and 91% specificity. Agreement between measurements of infarct size from T1 mapping and DE imaging was higher in chronic than in acute infarcts. Precontrast T1 maps enable the detection of acute MI. Acute and chronic MI show different patterns of T1 changes. Standardized T1 thresholds provide the potential to dichotomously identify areas of infarction. Magn Reson Med 58:34-40, 2007. © 2007 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Purpose: Guidelines recommend measuring myocardial extracellular volume (ECV) using T 1 -mapping before and 10-30 min after contrast agent administration. Data are then analyzed using a linear model (LM), which assumes fast water exchange (WX) between the ECV and cardiomyocytes. We investigated whether limited WX influences ECV measurements in patients with severe aortic stenosis (AS)., Methods: Twenty-five patients with severe AS and 5 healthy controls were recruited. T 1 measurements were made on a 3 T Siemens system using a multiparametric saturation-recovery single-shot acquisition (a) before contrast; (b) 4 min post 0.05 mmol/kg gadobutrol; and (c) 4 min, (d) 10 min, and (e) 30 min after an additional gadobutrol dose (0.1 mmol/kg). Three LM-based ECV estimates, made using paired T 1 measurements (a and b), (a and d), and (a and e), were compared to ECV estimates made using all 5 T 1 measurements and a two-site exchange model (2SXM) accounting for WX., Results: Median (range) ECV estimated using the 2SXM model was 25% (21%-39%) for patients and 26% (22%-29%) for controls. ECV estimated in patients using the LM at 10 min following a cumulative contrast dose of 0.15 mmol/kg was 21% (17%-32%) and increased significantly to 22% (19%-35%) at 30 min (p = 0.0001). ECV estimated using the LM was highest following low dose gadobutrol, 25% (19%-38%)., Conclusion: Current guidelines on contrast agent dose for ECV measurements may lead to underestimated ECV in patients with severe AS because of limited WX. Use of a lower contrast agent dose may mitigate this effect., (© 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)