The effect of and correction for through-slice dephasing on 2D gradient-echo double angle B 1 + mapping.

PURPOSE: To show that B 0 $$ {\mathrm{B}}_0 $$ variations through slice and slice profile effects are two major confounders affecting 2D dual angle B 1 + $$ {\mathrm{B}}_1^{+} $$ maps using gradient-echo signals and thus need to be corrected to obtain accurate B 1 + $$ {\mathrm{B}}_1^{+} $$ maps. METHODS: The 2D gradient-echo transverse complex signal was Bloch-simulated and integrated across the slice dimension including nonlinear variations in B 0 $$ {\mathrm{B}}_0 $$ inhomogeneities through slice. A nonlinear least squares fit was used to find the B 1 + $$ {\mathrm{B}}_1^{+} $$ factor corresponding to the best match between the two gradient-echo signals experimental ratio and the Bloch-simulated ratio. The correction was validated in phantom and in vivo at 3T. RESULTS: For our RF excitation pulse, the error in the B 1 + $$ {\mathrm{B}}_1^{+} $$ factor scales by approximately 3.8% for every 10 Hz/cm variation in B 0 $$ {\mathrm{B}}_0 $$ along the slice direction. Higher accuracy phantom B 1 + $$ {\mathrm{B}}_1^{+} $$ maps were obtained after applying the proposed correction; the root mean square B 1 + $$ {\mathrm{B}}_1^{+} $$ error relative to the gold standard B 1 + $$ {\mathrm{B}}_1^{+} $$ decreased from 6.4% to 2.6%. In vivo whole-liver T 1 $$ {\mathrm{T}}_1 $$ maps using the corrected B 1 + $$ {\mathrm{B}}_1^{+} $$ map registered a significant decrease in T 1 $$ {\mathrm{T}}_1 $$ gradient through slice. CONCLUSION: B 0 $$ {\mathrm{B}}_0 $$ inhomogeneities varying through slice were seen to have an impact on the accuracy of 2D double angle B 1 + $$ {\mathrm{B}}_1^{+} $$ maps using gradient-echo sequences. Consideration of this confounder is crucial for research relying on accurate knowledge of the true excitation flip angles, as is the case of T 1 $$ {\mathrm{T}}_1 $$ mapping using a spoiled gradient recalled echo sequence.

10-channel phased-array coil for carotid wall MRI at 3T.

BACKGROUND: Accurate assessment of plaque accumulation near the carotid bifurcation is important for the effective prevention and treatment of stroke. However, vessel and plaque delineation using MRI can be limited by low contrast-to-noise ratio (CNR) and long acquisition times. In this work, a 10-channel phased-array receive coil design for bilateral imaging of the carotid bifurcation using 3T MRI is proposed. METHODS: The proposed 10-channel receive coil was compared to a commercial 4-channel receive coil configuration using data acquired from phantoms and healthy volunteers (N = 9). The relative performance of the coils was assessed, by comparing signal-to-noise ratio (SNR), noise correlation, g-factor noise amplification, and the CNR between vessel wall and lumen using black-blood sequences. Patient data were acquired from 12 atherosclerotic carotid artery disease patients. RESULTS: The 10-channel coil consistently provided substantially increased SNR in phantoms (+77 ± 27%) and improved CNR in healthy carotid arteries (+62 ± 11%), or reduced g-factor noise amplification. Patient data showed excellent delineation of atherosclerotic plaque along the length of the carotid bifurcation using the 10-channel coil. CONCLUSIONS: The proposed 10-channel coil design allows for improved visualization of the carotid arteries and the carotid bifurcation and increased parallel imaging acceleration factors relative to a commercial 4-channel coil design.

Optimal flip angles for in vivo liver 3D T1 mapping and B1+ mapping at 3T.

PURPOSE: The spoiled gradient recalled echo (SPGR) sequence with variable flip angles (FAs) enables whole liver T 1 $$ {T}_1 $$ mapping at high spatial resolutions but is strongly affected by B 1 + $$ {B}_1^{+} $$ inhomogeneities. The aim of this work was to study how the precision of acquired T 1 $$ {T}_1 $$ maps is affected by the T 1 $$ {T}_1 $$ and B 1 + $$ {B}_1^{+} $$ ranges observed in the liver at 3T, as well as how noise propagates from the acquired signals into the resulting T 1 $$ {T}_1 $$ map. THEORY: The T 1 $$ {T}_1 $$ variance was estimated through the Fisher information matrix with a total noise variance including, for the first time, the B 1 + $$ {B}_1^{+} $$ map noise as well as contributions from the SPGR noise. METHODS: Simulations were used to find the optimal FAs for both the B 1 + $$ {B}_1^{+} $$ mapping and T 1 $$ {T}_1 $$ mapping. The simulations results were validated in 10 volunteers. RESULTS: Four optimized SPGR FAs of 2°, 2°, 15°, and 15° (TR = 4.1 ms) and B 1 + $$ {B}_1^{+} $$ map FAs of 65° and 130° achieved a T 1 $$ {T}_1 $$ coefficient of variation of 6.2 ± 1.7% across 10 volunteers and validated our theoretical model. Four optimal FAs outperformed five uniformly spaced FAs, saving the patient one breath-hold. For the liver B 1 + $$ {B}_1^{+} $$ and T 1 $$ {T}_1 $$ parameter space at 3T, a higher return in T 1 $$ {T}_1 $$ precision was obtained by investing FAs in the SPGR acquisition rather than in the B 1 + $$ {B}_1^{+} $$ map. CONCLUSION: A novel framework was developed and validated to calculate the SPGR T 1 $$ {T}_1 $$ variance. This framework efficiently identifies optimal FA values and determines the total number of SPGR and B 1 + $$ {B}_1^{+} $$ measurements needed to achieve a desired T 1 $$ {T}_1 $$ precision.

Estimation of field inhomogeneity map following magnitude-based ambiguity-resolved water-fat separation.

Magnitude-based PDFF (Proton Density Fat Fraction) and R2∗ mapping with resolved water-fat ambiguity is extended to calculate field inhomogeneity (field map) using the phase images. The estimation is formulated in matrix form, resolving the field map in a least-squares sense. PDFF and R2∗ from magnitude fitting may be updated using the estimated field maps. The limits of quantification of our voxel-independent implementation were assessed. Bland-Altman was used to compare PDFF and field maps from our method against a reference complex-based method on 152 UK Biobank subjects (1.5 T Siemens). A separate acquisition (3 T Siemens) presenting field inhomogeneities was also used. The proposed field mapping was accurate beyond double the complex-based limit range. High agreement was obtained between the proposed method and the reference in UK. Robust field mapping was observed at 3 T, for inhomogeneities over 400 Hz including rapid variation across edges. Field mapping following unambiguous magnitude-based water-fat separation was demonstrated in-vivo and showed potential at 3 T.

The Additive Value of Cardiovascular Magnetic Resonance in Convalescent COVID-19 Patients.

In COVID-19 the development of severe viral pneumonia that is coupled with systemic inflammatory response triggers multi-organ failure and is of major concern. Cardiac involvement occurs in nearly 60% of patients with pre-existing cardiovascular conditions and heralds worse clinical outcome. Diagnoses carried out in the acute phase of COVID-19 rely upon increased levels of circulating cardiac injury biomarkers and transthoracic echocardiography. These diagnostics, however, were unable to pinpoint the mechanisms of cardiac injury in COVID-19 patients. Identifying the main features of cardiac injury remains an urgent yet unmet need in cardiology, given the potential clinical consequences. Cardiovascular magnetic resonance (CMR) provides an unparalleled opportunity to gain a deeper insight into myocardial injury given its unique ability to interrogate the properties of myocardial tissue. This endeavor is particularly important in convalescent COVID-19 patients as many continue to experience chest pain, palpitations, dyspnea and exertional fatigue, six or more months after the acute illness. This review will provide a critical appraisal of research on cardiovascular damage in convalescent adult COVID-19 patients with an emphasis on the use of CMR and its value to our understanding of organ damage.

Emerging artificial intelligence applications in liver magnetic resonance imaging.

Chronic liver diseases (CLDs) are becoming increasingly more prevalent in modern society. The use of imaging techniques for early detection, such as magnetic resonance imaging (MRI), is crucial in reducing the impact of these diseases on healthcare systems. Artificial intelligence (AI) algorithms have been shown over the past decade to excel at image-based analysis tasks such as detection and segmentation. When applied to liver MRI, they have the potential to improve clinical decision making, and increase throughput by automating analyses. With Liver diseases becoming more prevalent in society, the need to implement these techniques to utilize liver MRI to its full potential, is paramount. In this review, we report on the current methods and applications of AI methods in liver MRI, with a focus on machine learning and deep learning methods. We assess four main themes of segmentation, classification, image synthesis and artefact detection, and their respective potential in liver MRI and the wider clinic. We provide a brief explanation of some of the algorithms used and explore the current challenges affecting the field. Though there are many hurdles to overcome in implementing AI methods in the clinic, we conclude that AI methods have the potential to positively aid healthcare professionals for years to come.

Hydration and glycogen affect T1 relaxation times of liver tissue.

T1 mapping is a useful tool for the assessment of patients with nonalcoholic fatty liver disease but still suffers from a large unexplained variance in healthy subjects. This study aims to characterize the potential effects of liver glycogen concentration and body hydration status on liver shortened modified Look-Locker inversion recovery (shMOLLI) T1 measurements. Eleven glycogen phantoms and 12 healthy volunteers (mean age: 31 years, three females) were scanned at 3 T using inversion recovery spin echo, multiple contrast spin echo (in phantoms), shMOLLI T1 mapping, multiple-echo spoiled gradient recalled echo and 13 C spectroscopy (in healthy volunteers). Phantom r1 and r2 relaxivities were determined from measured T1 and T2 values. Participants underwent a series of five metabolic experiments to vary their glycogen concentration and hydration levels: feeding, food fasting, exercising, underhydration, and rehydration. Descriptive statistics were calculated for shMOLLI T1 , inferior vena cava to aorta cross-sectional area ratio (IVC/Ao) as a marker of body hydration status, glycogen concentration, T2 * and proton density fat fraction values. A linear mixed model for shMOLLI R1 was constructed to determine the effects of glycogen concentration and IVC/Ao ratio. The mean shMOLLI T1 after fasting was 737 ± 67 ms. The mean within-subject change was 80 ± 45 ms. The linear mixed model revealed a glycogen r1 relaxivity in volunteers (0.18 M-1 s-1 , p = 0.03) close to that determined in phantoms (0.28 M-1 s-1 ). A unit change in IVC/Ao ratio was associated with a drop of -0.113 s-1 in R1 (p < 0.001). This study demonstrated a dependence of liver shMOLLI T1 values on liver glycogen concentration and overall body hydration status. Interparticipant variation of hydration status should be minimized in future liver MRI studies. Additionally, caution is advised when interpreting liver T1 measurements in participants with excess liver glycogen.

Magnetic resonance phase contrast velocity mapping for flow quantification in irregular heart rhythms using radial k-space ultrashort echo time imaging.

BACKGROUND: Phase contrast velocity mapping sequences utilising ultrashort echo time (UTE) radial k-space sequences have been used to reduce intravoxel dephasing at high velocities. We evaluated the accuracy of the UTE flow sequence for mitral regurgitation (MR) quantification, including patients with atrial fibrillation. METHODS: Forty patients underwent cardiac MRI for indirect MR quantification by assessment of aortic flow using a UTE phase contrast sequence (TE 0.65 ms) combined with left ventricular stroke volume. Retrospective ECG-gating was used in sinus rhythm (30 patients), prospective ECG-triggering in atrial fibrillation (10). MR was also quantified by a standard phase contrast sequence (TE 2.85 ms, standard flow method) and by comparing stroke volumes (volumetric method). RESULTS: UTE flow-derived MR measurement showed modest agreement in sinus rhythm (95% limits of agreement: ±38.2 ml; ±29.8%) and atrial fibrillation (±33.7 ml; ±30.3%) compared to standard flow assessment. There was little systematic bias in sinus rhythm (mean offset -4.4 ml /-3.5% compared to standard flow assessment), but a slight bias towards greater regurgitation in atrial fibrillation (+15.2 ml /+14.0%). There were wider limits of agreement between the UTE flow method and volumetric method than between the regular flow method and the volumetric method in sinus rhythm (±48.4 ml; ±36.4%; mean offset: -12.2 ml /-9.0%) and similar limits of agreement in atrial fibrillation (±29.6 ml; 25.8%; +12.0 ml /+10.3%). CONCLUSIONS: UTE flow imaging is inferior to conventional flow techniques for MR assessment in patients with sinus rhythm as well as atrial fibrillation. However, the number of atrial fibrillation patients in this initial study is small.

Constraints in estimating the proton density fat fraction.

The study evaluates four physically motivated constraints in the estimation of the proton density fat fraction (PDFF). Least squares approaches were developed for constraining the parameters in PDFF quantification based on the physics of magnetic resonance imaging. These were smooth fieldmap, smooth initial phase, nonnegative proton density and moderate R2∗ values. The constraints were evaluated in terms of their influence on the bias and standard deviation of the estimated parameters using numerical simulations and in vivo data acquired at 0.35 T. Results show that unconstrained least squares estimation is noisy and biased and that constraints can be effective at reducing both the standard deviation and bias.

Navigator-based reacquisition and estimation of motion-corrupted data: Application to multi-echo spin echo for carotid wall MRI.

PURPOSE: To assess whether artifacts in multi-slice multi-echo spin echo neck imaging, thought to be caused by brief motion events such as swallowing, can be corrected by reacquiring corrupted central k-space data and estimating the remainder with parallel imaging. METHODS: A single phase-encode line (ky = 0, phase-encode direction anteroposterior) navigator echo was used to identify motion-corrupted data and guide the online reacquisition. If motion corruption was detected in the 7 central k-space lines, they were replaced with reacquired data. Subsequently, GRAPPA reconstruction was trained on the updated central portion of k-space and then used to estimate the remaining motion-corrupted k-space data from surrounding uncorrupted data. Similar compressed sensing-based approaches have been used previously to compensate for respiration in cardiac imaging. The g-factor noise amplification was calculated for the parallel imaging reconstruction of data acquired with a 10-channel neck coil. The method was assessed in scans with 9 volunteers and 12 patients. RESULTS: The g-factor analysis showed that GRAPPA reconstruction of 2 adjacent motion-corrupted lines causes high noise amplification; therefore, the number of 2-line estimations should be limited. In volunteer scans, median ghosting reduction of 24% was achieved with 2 adjacent motion-corrupted lines correction, and image quality was improved in 2 patient scans that had motion corruption close to the center of k-space. CONCLUSION: Motion-corrupted echo-trains can be identified with a navigator echo. Combined reacquisition and parallel imaging estimation reduced motion artifacts in multi-slice MESE when there were brief motion events, especially when motion corruption was close to the center of k-space.

Non-invasive assessment of portal hypertension by multi-parametric magnetic resonance imaging of the spleen: A proof of concept study.

BACKGROUND AND AIMS: Non-invasive assessment of portal hypertension is an area of unmet need. This proof of concept study aimed to evaluate the diagnostic accuracy of a multi-parametric magnetic resonance technique in the assessment of portal hypertension. Comparison to other non-invasive technologies was a secondary aim. METHODS: T1 and T2* maps through the liver and spleen were acquired prior to trans-jugular liver biopsy and hepatic vein pressure gradient (HVPG) measurement. T1 measurements reflect changes in tissue water content, but this relationship is confounded by the presence of iron, which in turn can be quantified accurately from T2* maps. Data were analysed using LiverMultiScan (Perspectum Diagnostics, Oxford, UK) which applies an algorithm to remove the confounding effect of iron, yielding the "iron corrected T1" (cT1). Sensitivity, specificity, diagnostic values and area under the curve were derived for spleen cT1, liver cT1, transient elastography, and serum fibrosis scores. HVPG was the reference standard. RESULTS: Nineteen patients (15 men) with median age 57 years were included. Liver disease aetiologies included non-alcoholic fatty liver disease (n = 9; 47%) and viral hepatitis (n = 4; 21%). There was strong correlation between spleen cT1 and HVPG (r = 0.69; p = 0.001). Other non-invasive biomarkers did not correlate with HVPG. Spleen cT1 had excellent diagnostic accuracy for portal hypertension (HVPG >5 mmHg) and clinically significant portal hypertension (HVPG ≥10 mmHg) with an area under the receiver operating characteristic curve of 0.92 for both. CONCLUSION: Spleen cT1 is a promising biomarker of portal pressure that outperforms other non-invasive scores and should be explored further.

Scattering matrix imaging pulse design for real-time respiration and cardiac motion monitoring.

PURPOSE: The scattering matrix (S-matrix) of a parallel transmit (pTx) coil is sensitive to physiological motion but requires additional monitoring RF pulses to be measured. In this work, we present and evaluate pTx RF pulse designs that simultaneously excite for imaging and measure the S-matrix to generate real-time motion signals without prolonging the image sequence. THEORY AND METHODS: Three pTx waveforms for measuring the S-matrix were identified and superimposed onto the imaging excitation RF pulses: (1) time division multiplexing, (2) frequency division multiplexing, and (3) code division multiplexing. These 3 methods were evaluated in healthy volunteers for scattering sensitivity and image artefacts. The S-matrix and real-time motion signals were calculated on the image calculation environment of the MR scanner. Prospective cardiac triggers were identified in early systole as a high rate of change of the cardiac motion signal. Monitoring accuracy was compared against electrocardiogram or the imaged diaphragm position. RESULTS: All 3 monitoring approaches measure the S-matrix during image excitation with quality correlated to input power. No image artefacts were observed for frequency multiplexing, and low energy artefacts were observed in the other methods. The accuracy of the achieved prospective cardiac gating was 15 ± 16 ms for breath hold and 24 ± 17 ms during free breathing. The diaphragm position prediction accuracy was 1.3 ± 0.9 mm. In all volunteers, good quality cine images were acquired for breath hold scans and dual gated CINEs were demonstrated. CONCLUSION: The S-matrix can be measured during image excitation to generate real-time cardiac and respiratory motion signals for prospective gating. No artefacts are introduced when frequency division multiplexing is used.

Identification of Myocardial Disarray in Patients With Hypertrophic Cardiomyopathy and Ventricular Arrhythmias.

BACKGROUND: Myocardial disarray is a likely focus for fatal arrhythmia in hypertrophic cardiomyopathy (HCM). This microstructural abnormality can be inferred by mapping the preferential diffusion of water along cardiac muscle fibers using diffusion tensor cardiac magnetic resonance (DT-CMR) imaging. Fractional anisotropy (FA) quantifies directionality of diffusion in 3 dimensions. The authors hypothesized that FA would be reduced in HCM due to disarray and fibrosis that may represent the anatomic substrate for ventricular arrhythmia. OBJECTIVES: This study sought to assess FA as a noninvasive in vivo biomarker of HCM myoarchitecture and its association with ventricular arrhythmia. METHODS: A total of 50 HCM patients (47 ± 15 years of age, 77% male) and 30 healthy control subjects (46 ± 16 years of age, 70% male) underwent DT-CMR in diastole, cine, late gadolinium enhancement (LGE), and extracellular volume (ECV) imaging at 3-T. RESULTS: Diastolic FA was reduced in HCM compared with control subjects (0.49 ± 0.05 vs. 0.52 ± 0.03; p = 0.0005). Control subjects had a mid-wall ring of high FA. In HCM, this ring was disrupted by reduced FA, consistent with published histology demonstrating that disarray and fibrosis invade circumferentially aligned mid-wall myocytes. LGE and ECV were significant predictors of FA, in line with fibrosis contributing to low FA. Yet FA adjusted for LGE and ECV remained reduced in HCM (p = 0.028). FA in the hypertrophied segment was reduced in HCM patients with ventricular arrhythmia compared to patients without (n = 15; 0.41 ± 0.03 vs. 0.46 ± 0.06; p = 0.007). A decrease in FA of 0.05 increased odds of ventricular arrhythmia by 2.5 (95% confidence interval: 1.2 to 5.3; p = 0.015) in HCM and remained significant even after correcting for LGE, ECV, and wall thickness (p = 0.036). CONCLUSIONS: DT-CMR assessment of left ventricular myoarchitecture matched patterns reported previously on histology. Low diastolic FA in HCM was associated with ventricular arrhythmia and is likely to represent disarray after accounting for fibrosis. The authors propose that diastolic FA could be the first in vivo marker of disarray in HCM and a potential independent risk factor.

Magnitude-intrinsic water-fat ambiguity can be resolved with multipeak fat modeling and a multipoint search method.

PURPOSE: To develop a postprocessing algorithm for multiecho chemical-shift encoded water-fat separation that estimates proton density fat fraction (PDFF) maps over the full dynamic range (0-100%) using multipeak fat modeling and multipoint search optimization. To assess its accuracy, reproducibility, and agreement with state-of-the-art complex-based methods, and to evaluate its robustness to artefacts in abdominal PDFF maps. METHODS: We introduce MAGO (MAGnitude-Only), a magnitude-based reconstruction that embodies multipeak liver fat spectral modeling and multipoint optimization, and which is compatible with asymmetric echo acquisitions. MAGO is assessed first for accuracy and reproducibility on publicly available phantom data. Then, MAGO is applied to N = 178 UK Biobank cases, in which its liver PDFF measures are compared using Bland-Altman analysis with those from a version of the hybrid iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) algorithm, LiverMultiScan IDEAL (LMS IDEAL, Perspectum Diagnostics Ltd, Oxford, UK). Finally, MAGO is tested on a succession of high field challenging cases for which LMS IDEAL generated artefacts in the PDFF maps. RESULTS: Phantom data showed accurate, reproducible MAGO PDFF values across manufacturers, field strengths, and acquisition protocols. Moreover, we report excellent agreement between MAGO and LMS IDEAL for 6-echo, 1.5 tesla human acquisitions (bias = -0.02% PDFF, 95% confidence interval = ±0.13% PDFF). When tested on 12-echo, 3 tesla cases from different manufacturers, MAGO was shown to be more robust to artefacts compared to LMS IDEAL. CONCLUSION: MAGO resolves the water-fat ambiguity over the entire fat fraction dynamic range without compromising accuracy, therefore enabling robust PDFF estimation where phase data is inaccessible or unreliable and complex-based and hybrid methods fail.

Measuring inorganic phosphate and intracellular pH in the healthy and hypertrophic cardiomyopathy hearts by in vivo 7T 31P-cardiovascular magnetic resonance spectroscopy.

BACKGROUND: Cardiovascular phosphorus MR spectroscopy (31P-CMRS) is a powerful tool for probing energetics in the human heart, through quantification of phosphocreatine (PCr) to adenosine triphosphate (ATP) ratio. In principle, 31P-CMRS can also measure cardiac intracellular pH (pHi) and the free energy of ATP hydrolysis (ΔGATP). However, these require determination of the inorganic phosphate (Pi) signal frequency and amplitude that are currently not robustly accessible because blood signals often obscure the Pi resonance. Typical cardiac 31P-CMRS protocols use low (e.g. 30°) flip-angles and short repetition time (TR) to maximise signal-to-noise ratio (SNR) within hardware limits. Unfortunately, this causes saturation of Pi with negligible saturation of the flowing blood pool. We aimed to show that an adiabatic 90° excitation, long-TR, 7T 31P-CMRS protocol will reverse this balance, allowing robust cardiac pHi measurements in healthy subjects and patients with hypertrophic cardiomyopathy (HCM). METHODS: The cardiac Pi T1 was first measured by the dual TR technique in seven healthy subjects. Next, ten healthy subjects and three HCM patients were scanned with 7T 31P-MRS using long (6 s) TR protocol and adiabatic excitation. Spectra were fitted for cardiac metabolites including Pi. RESULTS: The measured Pi T1 was 5.0 ± 0.3 s in myocardium and 6.4 ± 0.6 s in skeletal muscle. Myocardial pH was 7.12 ± 0.04 and Pi/PCr ratio was 0.11 ± 0.02. The coefficients of repeatability were 0.052 for pH and 0.027 for Pi/PCr quantification. The pH in HCM patients did not differ (p = 0.508) from volunteers. However, Pi/PCr was higher (0.24 ± 0.09 vs. 0.11 ± 0.02; p = 0.001); Pi/ATP was higher (0.44 ± 0.14 vs. 0.24 ± 0.05; p = 0.002); and PCr/ATP was lower (1.78 ± 0.07 vs. 2.10 ± 0.20; p = 0.020), in HCM patients, which is in agreement with previous reports. CONCLUSION: A 7T 31P-CMRS protocol with adiabatic 90° excitation and long (6 s) TR gives sufficient SNR for Pi and low enough blood signal to permit robust quantification of cardiac Pi and hence pHi. Pi was detectable in every subject scanned for this study, both in healthy subjects and HCM patients. Cardiac pHi was unchanged in HCM patients, but both Pi/PCr and Pi/ATP increased that indicate an energetic impairment in HCM. This work provides a robust technique to quantify cardiac Pi and pHi.

Feasibility of absolute quantification for 31 P MRS at 7 T.

PURPOSE: Phosphorus spectroscopy can differentiate among liver disease stages and types. To quantify absolute concentrations of phosphorus metabolites, sensitivity calibration and transmit field ( B1+ ) correction are required. The trend toward ultrahigh fields (7 T) and the use of multichannel RF coils makes this ever more challenging. We investigated the constraints on reference phantoms, and implemented techniques for the absolute quantification of human liver phosphorus spectra acquired using a 10-cm loop and a 16-channel array at 7 T. METHODS: The effect of phantom conductivity was assessed at 25.8 MHz (1.5 T), 49.9 MHz (3 T), and 120.3 MHz (7 T) by electromagnetic modeling. Radiofrequency field maps ( B1± ) were measured in phosphate phantoms (18 mM and 40 mM) at 7 T. These maps were used to assess the correction of 4 phantom 3D-CSI data sets using 3 techniques: phantom replacement, explicit normalization, and simplified normalization. In vivo liver spectra acquired with a 10-cm loop were corrected with all 3 methods. Simplified normalization was applied to in vivo 16-channel array data sets. RESULTS: Simulations show that quantification errors of less than 3% are achievable using a uniform electrolyte phantom with a conductivity of 0.23-0.86 S.m-1 at 1.5 T, 0.39-0.58 S.m-1 at 3 T, and 0.34-0.42 S.m-1 (16-19 mM KH2 PO4(aq) ) at 7 T. The mean γ-ATP concentration quantified in vivo at 7 T was 1.39 ± 0.30 mmol.L-1 to 1.71 ± 0.35 mmol.L-1 wet tissue for the 10-cm loop and 1.88 ± 0.25 mmol.L-1 wet tissue for the array. CONCLUSION: It is essential to select a calibration phantom with appropriate conductivity for quantitative phosphorus spectroscopy at 7 T. Using an 18-mM phosphate phantom and simplified normalization, human liver phosphate metabolite concentrations were successfully quantified at 7 T.

Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data.

INTRODUCTION: Aortic distensibility can be calculated using semi-automated methods to segment the aortic lumen on cine CMR (Cardiovascular Magnetic Resonance) images. However, these methods require visual quality control and manual localization of the region of interest (ROI) of ascending (AA) and proximal descending (PDA) aorta, which limit the analysis in large-scale population-based studies. Using 5100 scans from UK Biobank, this study sought to develop and validate a fully automated method to 1) detect and locate the ROIs of AA and PDA, and 2) provide a quality control mechanism. METHODS: The automated AA and PDA detection-localization algorithm followed these steps: 1) foreground segmentation; 2) detection of candidate ROIs by Circular Hough Transform (CHT); 3) spatial, histogram and shape feature extraction for candidate ROIs; 4) AA and PDA detection using Random Forest (RF); 5) quality control based on RF detection probability. To provide the ground truth, overall image quality (IQ = 0-3 from poor to good) and aortic locations were visually assessed by 13 observers. The automated algorithm was trained on 1200 scans and Dice Similarity Coefficient (DSC) was used to calculate the agreement between ground truth and automatically detected ROIs. RESULTS: The automated algorithm was tested on 3900 scans. Detection accuracy was 99.4% for AA and 99.8% for PDA. Aorta localization showed excellent agreement with the ground truth, with DSC ≥ 0.9 in 94.8% of AA (DSC = 0.97 ± 0.04) and 99.5% of PDA cases (DSC = 0.98 ± 0.03). AA×PDA detection probabilities could discriminate scans with IQ ≥ 1 from those severely corrupted by artefacts (AUC = 90.6%). If scans with detection probability < 0.75 were excluded (350 scans), the algorithm was able to correctly detect and localize AA and PDA in all the remaining 3550 scans (100% accuracy). CONCLUSION: The proposed method for automated AA and PDA localization was extremely accurate and the automatically derived detection probabilities provided a robust mechanism to detect low quality scans for further human review. Applying the proposed localization and quality control techniques promises at least a ten-fold reduction in human involvement without sacrificing any accuracy.

Mapping tissue water T1 in the liver using the MOLLI T1 method in the presence of fat, iron and B0 inhomogeneity.

Modified Look-Locker inversion recovery (MOLLI) T1 mapping sequences can be useful in cardiac and liver tissue characterization, but determining underlying water T1 is confounded by iron, fat and frequency offsets. This article proposes an algorithm that provides an independent water MOLLI T1 (referred to as on-resonance water T1 ) that would have been measured if a subject had no fat and normal iron, and imaging had been done on resonance. Fifteen NiCl2 -doped agar phantoms with different peanut oil concentrations and 30 adults with various liver diseases, nineteen (63.3%) with liver steatosis, were scanned at 3 T using the shortened MOLLI (shMOLLI) T1 mapping, multiple-echo spoiled gradient-recalled echo and 1 H MR spectroscopy sequences. An algorithm based on Bloch equations was built in MATLAB, and water shMOLLI T1 values of both phantoms and human participants were determined. The quality of the algorithm's result was assessed by Pearson's correlation coefficient between shMOLLI T1 values and spectroscopically determined T1 values of the water, and by linear regression analysis. Correlation between shMOLLI and spectroscopy-based T1 values increased, from r = 0.910 (P < 0.001) to r = 0.998 (P < 0.001) in phantoms and from r = 0.493 (for iron-only correction; P = 0.005) to r = 0.771 (for iron, fat and off-resonance correction; P < 0.001) in patients. Linear regression analysis revealed that the determined water shMOLLI T1 values in patients were independent of fat and iron. It can be concluded that determination of on-resonance water (sh)MOLLI T1 independent of fat, iron and macroscopic field inhomogeneities was possible in phantoms and human subjects.

T2 mapping MRI technique quantifies carotid plaque lipid, and its depletion after statin initiation, following acute myocardial infarction.

BACKGROUND & AIMS: A recently-validated, highly-sensitive T2 mapping magnetic resonance (MRI) technique accurately quantifies carotid plaque lipid. The aims of this study were to determine: (i) the extent of carotid plaque lipid in patients with acute coronary syndromes (ACS); (ii) the effects of initiation of high-intensity statin on plaque lipid content and (iii) whether plaque lipid content is related to standard or 'functional' blood lipid measurements. METHODS: Statin naïve subjects presenting with ACS underwent carotid artery MRI at 3 T scanner to quantify plaque lipid. Patients were subsequently commenced on high dose statin as part of clinical care and underwent a second MRI after three months. Plaque composition was measured using objective semi-automated techniques. RESULTS: 23 out of 24 patients had measurable lipid. Three months after statin initiation there was a significant reduction in carotid lipid percentage [from 10.3% (7.2-14.2) to 7.4% (5.4-10.0), p = 0.002] and a significant increase in fibrous percentage [from 83.3% ±â€¯6.6-85.5% ±â€¯4.8, p = 0.039]. None of the studied functional blood biomarkers were related to either baseline carotid plaque lipid content or its propensity to change with statin treatment. CONCLUSIONS: T2-mapping demonstrated depleted carotid plaque lipid following the initiation of high-intensity statin treatment. Standard or 'functional' blood biomarkers were dissociated from plaque lipid content or changes with treatment. These findings further reinforce the importance of disease characterisation over risk factor assessment. Subject to clinical trial findings, quantification of plaque lipid may provide the basis for an approach to identify patients suitable for intensive lipid reduction regimes.