Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI.

PURPOSE: The purpose of this study was to determine an optimal saturation-recovery time (TS) for minimizing the underestimation of arterial input function (AIF) in quantitative cardiac perfusion MRI without multiple gadolinium injections per subject. METHODS: We scanned 18 subjects (mean age = 59 ± 14 years, 9/9 males/females) to acquire resting perfusion data and 1 additional subject (age = 38 years, male) to obtain stress-rest perfusion data using a 5-fold accelerated pulse sequence with radial k-space sampling and applied k-space weighted image contrast (KWIC) filters on the same k-space data to retrospectively reconstruct five AIF images with effective TS ranging from 10 to 21.2 ms (2.8 ms steps). Undersampled images were reconstructed using a compressed sensing framework with temporal-total-variation and temporal-principal-component as 2 orthogonal sparsifying transforms. The image processing steps included, same motion correction across five different AIF images, signal normalization by the proton-density-weighted-image, signal-to-T1 conversion using a Bloch equation, T1 -to-gadolinium-concentration conversion assuming fast water exchange, T2 * correction to the AIF, and gadolinium-concentration to myocardial blood flow (MBF) conversion based on a Fermi model. RESULTS: Among five TS values, the shortest TS (10 ms) produced significantly (P < 0.05) higher peak AIF and lower resting MBF (13.73 mM, 0.73 mL g-1 min-1 ) than 12.8 ms (11.24 mM, 0.89 mL g-1 min-1 ), 15.6 ms (9.56 mM, 1.05 mL g-1 min-1 ), 18.4 ms (8.55 mM, 1.17 mL g-1 min-1 ), and 21.2 ms (7.95 mM, 1.27 mL g-1 min-1 ). Similarly, shorter TS reduced underestimation of AIF (or overestimation of MBF) for both during stress and at rest, but this effect was canceled in myocardial-perfusion-reserve (MPR). CONCLUSION: This study demonstrates that TS of 10 ms reduces the underestimation of AIF and, hence, the overestimation of MBF compared with longer TS values (12.8-21.2 ms).

A theoretical framework for retrospective T2∗ correction to the arterial input function in quantitative myocardial perfusion MRI.

PURPOSE: To develop and evaluate a flexible, Bloch-equation based framework for retrospective T2∗ correction to the arterial input function (AIF) obtained with quantitative cardiac perfusion pulse sequences. METHODS: Our framework initially calculates the gadolinium concentration [Gd] based on T1 measurements alone. Next, T2∗ is estimated from this initial calculation of [Gd] while assuming fast water exchange and using the literature native T2 and static magnetic field variation (ΔB0 ) values. Finally, the [Gd] is recalculated after performing T2∗ correction to the Bloch equation signal model. Using this approach, we performed T2∗ correction to historical phantom and in vivo, dual-imaging perfusion data sets from 3 different patient groups obtained using different pulse sequences and imaging parameters. Images were processed to quantify both the AIF and resting myocardial blood flow (MBF). We also performed a sensitivity analysis of our T2∗ correction to ±20% variations in native T2 and ΔB0 . RESULTS: Compared with the ground truth [Gd] of phantom, the normalized root-means-square-error (NRMSE) in measured [Gd] was 5.1%, 1.3%, and 0.6% for uncorrected, our corrected, and Kellman's corrected, respectively. For in vivo data, both the peak AIF (7.0 ± 3.0 mM vs. 8.6 ± 7.1 mM, 7.2 ± 0.9 mM vs. 8.6 ± 1.7 mM, 7.7 ± 1.8 mM vs. 10.3 ± 5.1 mM, P < .001) and resting MBF (1.3 ± 0.1 mL/g/min vs. 1.1 ± 0.1 mL/g/min, 1.3 ± 0.1 mL/g/min vs. 1.1 ± 0.1 mL/g/min, 1.2 ± 0.1 mL/g/min vs. 0.9 ± 0.1 mL/g/min, P < .001) values were significantly different between uncorrected and corrected for all 3 patient groups. Both the peak AIF and resting MBF values varied by <5% over the said variations in native T2 and ΔB0 . CONCLUSION: Our theoretical framework enables retrospective T2∗ correction to the AIF obtained with dual-imaging, cardiac perfusion pulse sequences.

Reliable segmentation of 2D cardiac magnetic resonance perfusion image sequences using time as the 3rd dimension.

OBJECTIVES: Cardiac magnetic resonance (CMR) first-pass perfusion is an established noninvasive diagnostic imaging modality for detecting myocardial ischemia. A CMR perfusion sequence provides a time series of 2D images for dynamic contrast enhancement of the heart. Accurate myocardial segmentation of the perfusion images is essential for quantitative analysis and it can facilitate automated pixel-wise myocardial perfusion quantification. METHODS: In this study, we compared different deep learning methodologies for CMR perfusion image segmentation. We evaluated the performance of several image segmentation methods using convolutional neural networks, such as the U-Net in 2D and 3D (2D plus time) implementations, with and without additional motion correction image processing step. We also present a modified U-Net architecture with a novel type of temporal pooling layer which results in improved performance. RESULTS: The best DICE scores were 0.86 and 0.90 for LV myocardium and LV cavity, while the best Hausdorff distances were 2.3 and 2.1 pixels for LV myocardium and LV cavity using 5-fold cross-validation. The methods were corroborated in a second independent test set of 20 patients with similar performance (best DICE scores 0.84 for LV myocardium). CONCLUSIONS: Our results showed that the LV myocardial segmentation of CMR perfusion images is best performed using a combination of motion correction and 3D convolutional networks which significantly outperformed all tested 2D approaches. Reliable frame-by-frame segmentation will facilitate new and improved quantification methods for CMR perfusion imaging. KEY POINTS: • Reliable segmentation of the myocardium offers the potential to perform pixel level perfusion assessment. • A deep learning approach in combination with motion correction, 3D (2D + time) methods, and a deep temporal connection module produced reliable segmentation results.

Cardiovascular magnetic resonance predictors of heart failure in hypertrophic cardiomyopathy: the role of myocardial replacement fibrosis and the microcirculation.

INTRODUCTION: Heart failure (HF) in hypertrophic cardiomyopathy (HCM) is associated with high morbidity and mortality. Predictors of HF, in particular the role of myocardial fibrosis and microvascular ischemia remain unclear. We assessed the predictive value of cardiovascular magnetic resonance (CMR) for development of HF in HCM in an observational cohort study. METHODS: Serial patients with HCM underwent CMR, including adenosine first-pass perfusion, left atrial (LA) and left ventricular (LV) volumes indexed to body surface area (i) and late gadolinium enhancement (%LGE- as a % of total myocardial mass). We used a composite endpoint of HF death, cardiac transplantation, and progression to NYHA class III/IV. RESULTS: A total of 543 patients with HCM underwent CMR, of whom 94 met the composite endpoint at baseline. The remaining 449 patients were followed for a median of 5.6 years. Thirty nine patients (8.7%) reached the composite endpoint of HF death (n = 7), cardiac transplantation (n = 2) and progression to NYHA class III/IV (n = 20). The annual incidence of HF was 2.0 per 100 person-years, 95% CI (1.6-2.6). Age, previous non-sustained ventricular tachycardia, LV end-systolic volume indexed to body surface area (LVESVI), LA volume index ; LV ejection fraction, %LGE and presence of mitral regurgitation were significant univariable predictors of HF, with LVESVI (Hazard ratio (HR) 1.44, 95% confidence interval (95% CI) 1.16-1.78, p = 0.001), %LGE per 10% (HR 1.44, 95%CI 1.14-1.82, p = 0.002) age (HR 1.37, 95% CI 1.06-1.77, p = 0.02) and mitral regurgitation (HR 2.6, p = 0.02) remaining independently predictive on multivariable analysis. The presence or extent of inducible perfusion defect assessed using a visual score did not predict outcome (p = 0.16, p = 0.27 respectively). DISCUSSION: The annual incidence of HF in a contemporary ambulatory HCM population undergoing CMR is low. Myocardial fibrosis and LVESVI are strongly predictive of future HF, however CMR visual assessment of myocardial perfusion was not.

Genetic dysregulation of endothelin-1 is implicated in coronary microvascular dysfunction.

AIMS: Endothelin-1 (ET-1) is a potent vasoconstrictor peptide linked to vascular diseases through a common intronic gene enhancer [(rs9349379-G allele), chromosome 6 (PHACTR1/EDN1)]. We performed a multimodality investigation into the role of ET-1 and this gene variant in the pathogenesis of coronary microvascular dysfunction (CMD) in patients with symptoms and/or signs of ischaemia but no obstructive coronary artery disease (CAD). METHODS AND RESULTS: Three hundred and ninety-one patients with angina were enrolled. Of these, 206 (53%) with obstructive CAD were excluded leaving 185 (47%) eligible. One hundred and nine (72%) of 151 subjects who underwent invasive testing had objective evidence of CMD (COVADIS criteria). rs9349379-G allele frequency was greater than in contemporary reference genome bank control subjects [allele frequency 46% (129/280 alleles) vs. 39% (5551/14380); P = 0.013]. The G allele was associated with higher plasma serum ET-1 [least squares mean 1.59 pg/mL vs. 1.28 pg/mL; 95% confidence interval (CI) 0.10-0.53; P = 0.005]. Patients with rs9349379-G allele had over double the odds of CMD [odds ratio (OR) 2.33, 95% CI 1.10-4.96; P = 0.027]. Multimodality non-invasive testing confirmed the G allele was associated with linked impairments in myocardial perfusion on stress cardiac magnetic resonance imaging at 1.5 T (N = 107; GG 56%, AG 43%, AA 31%, P = 0.042) and exercise testing (N = 87; -3.0 units in Duke Exercise Treadmill Score; -5.8 to -0.1; P = 0.045). Endothelin-1 related vascular mechanisms were assessed ex vivo using wire myography with endothelin A receptor (ETA) antagonists including zibotentan. Subjects with rs9349379-G allele had preserved peripheral small vessel reactivity to ET-1 with high affinity of ETA antagonists. Zibotentan reversed ET-1-induced vasoconstriction independently of G allele status. CONCLUSION: We identify a novel genetic risk locus for CMD. These findings implicate ET-1 dysregulation and support the possibility of precision medicine using genetics to target oral ETA antagonist therapy in patients with microvascular angina. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03193294.

Fully quantitative pixel-wise analysis of cardiovascular magnetic resonance perfusion improves discrimination of dark rim artifact from perfusion defects associated with epicardial coronary stenosis.

BACKGROUND: Dark rim artifacts in first-pass cardiovascular magnetic resonance (CMR) perfusion images can mimic perfusion defects and affect diagnostic accuracy for coronary artery disease (CAD). We evaluated whether quantitative myocardial blood flow (MBF) can differentiate dark rim artifacts from true perfusion defects in CMR perfusion. METHODS: Regadenoson perfusion CMR was performed at 1.5 T in 76 patients. Significant CAD was defined by quantitative invasive coronary angiography (QCA) ≥ 50% diameter stenosis. Non-significant CAD (NonCAD) was defined as stenosis by QCA < 50% diameter stenosis or computed tomographic coronary angiography (CTA) < 30% in all major epicardial arteries. Dark rim artifacts had study specific and guideline-based definitions for comparison purposes. MBF was quantified at the pixel-level and sector-level. RESULTS: In a NonCAD subgroup with dark rim artifacts, stress MBF was lower in the subendocardial than midmyocardial and epicardial layers (2.17 ± 0.61 vs. 3.06 ± 0.75 vs. 3.24 ± 0.80 mL/min/g, both p < 0.001) and was also 30% lower than in remote regions (2.17 ± 0.61 vs. 2.83 ± 0.67 mL/min/g, p < 0.001). However, subendocardial stress MBF in dark rim artifacts was 37-56% higher than in true perfusion defects (2.17 ± 0.61 vs. 0.95 ± 0.43 mL/min/g, p < 0.001). Absolute stress MBF differentiated CAD from NonCAD with an accuracy ranging from 86 to 89% (all p < 0.001) using pixel-level analyses. Similar results were seen at a sector level. CONCLUSION: Quantitative stress MBF is lower in dark rim artifacts than remote myocardium but significantly higher than in true perfusion defects. If confirmed in larger series, this approach may aid the interpretation of clinical stress perfusion exams. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00027170 ; first posted 11/28/2001; updated 11/27/2017.

Apheresis as novel treatment for refractory angina with raised lipoprotein(a): a randomized controlled cross-over trial.

AIMS: To determine the clinical impact of lipoprotein apheresis in patients with refractory angina and raised lipoprotein(a) > 500 mg/L on the primary end point of quantitative myocardial perfusion, as well as secondary end points including atheroma burden, exercise capacity, symptoms, and quality of life. METHODS: We conducted a single-blinded randomized controlled trial in 20 patients with refractory angina and raised lipoprotein(a) > 500 mg/L, with 3 months of blinded weekly lipoprotein apheresis or sham, followed by crossover. The primary endpoint was change in quantitative myocardial perfusion reserve (MPR) assessed by cardiovascular magnetic resonance. Secondary endpoints included measures of atheroma burden, exercise capacity, symptoms and quality of life. RESULTS: The primary endpoint, namely MPR, increased following apheresis (0.47; 95% CI 0.31-0.63) compared with sham (-0.16; 95% CI - 0.33-0.02) yielding a net treatment increase of 0.63 (95% CI 0.37-0.89; P < 0.001 between groups). Improvements with apheresis compared with sham also occurred in atherosclerotic burden as assessed by total carotid wall volume (P < 0.001), exercise capacity by the 6 min walk test (P = 0.001), 4 of 5 domains of the Seattle angina questionnaire (all P < 0.02) and quality of life physical component summary by the short form 36 survey (P = 0.001). CONCLUSION: Lipoprotein apheresis may represent an effective novel treatment for patients with refractory angina and raised lipoprotein(a) improving myocardial perfusion, atheroma burden, exercise capacity and symptoms.

Robust universal nonrigid motion correction framework for first-pass cardiac MR perfusion imaging.

PURPOSE: To present and assess an automatic nonrigid image registration framework that compensates motion in cardiac magnetic resonance imaging (MRI) perfusion series and auxiliary images acquired under a wide range of conditions to facilitate myocardial perfusion quantification. MATERIALS AND METHODS: Our framework combines discrete feature matching for large displacement estimation with a dense variational optical flow formulation in a multithreaded architecture. This framework was evaluated on 291 clinical subjects to register 1.5T and 3.0T steady-state free-precession (FISP) and fast low-angle shot (FLASH) dynamic contrast myocardial perfusion images, arterial input function (AIF) images, and proton density (PD)-weighted images acquired under breath-hold (BH) and free-breath (FB) settings. RESULTS: Our method significantly improved frame-to-frame appearance consistency compared to raw series, expressed in correlation coefficient (R2 = 0.996 ± 3.735E-3 vs. 0.978 ± 2.024E-2, P < 0.0001) and mutual information (3.823 ± 4.098E-1 vs. 2.967 ± 4.697E-1, P < 0.0001). It is applicable to both BH (R2 = 0.998 ± 3.217E-3 vs. 0.990 ± 7.527E-3) and FB (R2 = 0.995 ± 3.410E-3 vs. 0.968 ± 2.257E-3) paradigms as well as FISP and FLASH sequences. The method registers PD images to perfusion T1 series (9.70% max increase in R2 vs. no registration, P < 0.001) and also corrects motion in low-resolution AIF series (R2 = 0.987 ± 1.180E-2 vs. 0.964 ± 3.860E-2, P < 0.001). Finally, we showed the myocardial perfusion contrast dynamic was preserved in the motion-corrected images compared to the raw series (R2 = 0.995 ± 6.420E-3). CONCLUSION: The critical step of motion correction prior to pixel-wise cardiac MR perfusion quantification can be performed with the proposed universal system. It is applicable to a wide range of perfusion series and auxiliary images with different acquisition settings. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1060-1072.

Evaluation of an automated method for arterial input function detection for first-pass myocardial perfusion cardiovascular magnetic resonance.

BACKGROUND: Quantitative assessment of myocardial blood flow (MBF) with first-pass perfusion cardiovascular magnetic resonance (CMR) requires a measurement of the arterial input function (AIF). This study presents an automated method to improve the objectivity and reduce processing time for measuring the AIF from first-pass perfusion CMR images. This automated method is used to compare the impact of different AIF measurements on MBF quantification. METHODS: Gadolinium-enhanced perfusion CMR was performed on a 1.5 T scanner using a saturation recovery dual-sequence technique. Rest and stress perfusion series from 270 clinical studies were analyzed. Automated image processing steps included motion correction, intensity correction, detection of the left ventricle (LV), independent component analysis, and LV pixel thresholding to calculate the AIF signal. The results were compared with manual reference measurements using several quality metrics based on the contrast enhancement and timing characteristics of the AIF. The median and 95% confidence interval (CI) of the median were reported. Finally, MBF was calculated and compared in a subset of 21 clinical studies using the automated and manual AIF measurements. RESULTS: Two clinical studies were excluded from the comparison due to a congenital heart defect present in one and a contrast administration issue in the other. The proposed method successfully processed 99.63% of the remaining image series. Manual and automatic AIF time-signal intensity curves were strongly correlated with median correlation coefficient of 0.999 (95% CI [0.999, 0.999]). The automated method effectively selected bright LV pixels, excluded papillary muscles, and required less processing time than the manual approach. There was no significant difference in MBF estimates between manually and automatically measured AIFs (p = NS). However, different sizes of regions of interest selection in the LV cavity could change the AIF measurement and affect MBF calculation (p = NS to p = 0.03). CONCLUSION: The proposed automatic method produced AIFs similar to the reference manual method but required less processing time and was more objective. The automated algorithm may improve AIF measurement from the first-pass perfusion CMR images and make quantitative myocardial perfusion analysis more robust and readily available.

A Model-based approach for microvasculature structure distortion correction in two-photon fluorescence microscopy images.

This paper investigates a postprocessing approach to correct spatial distortion in two-photon fluorescence microscopy images for vascular network reconstruction. It is aimed at in vivo imaging of large field-of-view, deep-tissue studies of vascular structures. Based on simple geometric modelling of the object-of-interest, a distortion function is directly estimated from the image volume by deconvolution analysis. Such distortion function is then applied to subvolumes of the image stack to adaptively adjust for spatially varying distortion and reduce the image blurring through blind deconvolution. The proposed technique was first evaluated in phantom imaging of fluorescent microspheres that are comparable in size to the underlying capillary vascular structures. The effectiveness of restoring three-dimensional (3D) spherical geometry of the microspheres using the estimated distortion function was compared with empirically measured point-spread function. Next, the proposed approach was applied to in vivo vascular imaging of mouse skeletal muscle to reduce the image distortion of the capillary structures. We show that the proposed method effectively improve the image quality and reduce spatially varying distortion that occurs in large field-of-view deep-tissue vascular dataset. The proposed method will help in qualitative interpretation and quantitative analysis of vascular structures from fluorescence microscopy images.

FLASH proton density imaging for improved surface coil intensity correction in quantitative and semi-quantitative SSFP perfusion cardiovascular magnetic resonance.

BACKGROUND: A low excitation flip angle (α < 10°) steady-state free precession (SSFP) proton-density (PD) reference scan is often used to estimate the B1-field inhomogeneity for surface coil intensity correction (SCIC) of the saturation-recovery (SR) prepared high flip angle (α = 40-50°) SSFP myocardial perfusion images. The different SSFP off-resonance response for these two flip angles might lead to suboptimal SCIC when there is a spatial variation in the background B0-field. The low flip angle SSFP-PD frames are more prone to parallel imaging banding artifacts in the presence of off-resonance. The use of FLASH-PD frames would eliminate both the banding artifacts and the uneven frequency response in the presence of off-resonance in the surface coil inhomogeneity estimate and improve homogeneity of semi-quantitative and quantitative perfusion measurements. METHODS: B0-field maps, SSFP and FLASH-PD frames were acquired in 10 healthy volunteers to analyze the SSFP off-resonance response. Furthermore, perfusion scans preceded by both FLASH and SSFP-PD frames from 10 patients with no myocardial infarction were analyzed semi-quantitatively and quantitatively (rest n = 10 and stress n = 1). Intra-subject myocardial blood flow (MBF) coefficient of variation (CoV) over the whole left ventricle (LV), as well as intra-subject peak contrast (CE) and upslope (SLP) standard deviation (SD) over 6 LV sectors were investigated. RESULTS: In the 6 out of 10 cases where artifacts were apparent in the LV ROI of the SSFP-PD images, all three variability metrics were statistically significantly lower when using the FLASH-PD frames as input for the SCIC (CoVMBF-FLASH = 0.3 ± 0.1, CoVMBF-SSFP = 0.4 ± 0.1, p = 0.03; SDCE-FLASH = 10 ± 2, SDCE-SSFP = 32 ± 7, p = 0.01; SDSLP-FLASH = 0.02 ± 0.01, SDSLP-SSFP = 0.06 ± 0.02, p = 0.03). Example rest and stress data sets from the patient pool demonstrate that the low flip angle SSFP protocol can exhibit severe ghosting artifacts originating from off-resonance banding artifacts at the edges of the field of view that parallel imaging is not able to unfold. These artifacts lead to errors in the quantitative perfusion maps and the semi-quantitative perfusion indexes, such as false positives. It is shown that this can be avoided by using FLASH-PD frames as input for the SCIC. CONCLUSIONS: FLASH-PD images are recommended as input for SCIC of SSFP perfusion images instead of low flip angle SSFP-PD images.

Quantitative pixel-wise measurement of myocardial blood flow: the impact of surface coil-related field inhomogeneity and a comparison of methods for its correction.

BACKGROUND: Surface coil-related field inhomogeneity potentially confounds pixel-wise quantitative analysis of perfusion CMR images. This study assessed the effect of surface coil-related field inhomogeneity on the spatial variation of pixel-wise myocardial blood flow (MBF), and assessed its impact on the ability of MBF quantification to differentiate ischaemic from remote coronary territories. Two surface coil intensity correction (SCIC) techniques were evaluated: 1) a proton density-based technique (PD-SCIC) and; 2) a saturation recovery steady-state free precession-based technique (SSFP-SCIC). METHODS: 26 subjects (18 with significant CAD and 8 healthy volunteers) underwent stress perfusion CMR using a motion-corrected, saturation recovery SSFP dual-sequence protocol. A proton density (PD)-weighted image was acquired at the beginning of the sequence. Surface coil-related field inhomogeneity was approximated using a third-order surface fit to the PD image or a pre-contrast saturation prepared SSFP image. The estimated intensity bias field was subsequently applied to the image series. Pixel-wise MBF was measured from mid-ventricular stress images using the two SCIC approaches and compared to measurements made without SCIC. RESULTS: MBF heterogeneity in healthy volunteers was higher using SSFP-SCIC (24.8 ± 4.1%) compared to PD-SCIC (20.8 ± 3.0%; p = 0.009), however heterogeneity was significantly lower using either SCIC technique compared to analysis performed without SCIC (36.2 ± 6.3%). In CAD patients, the difference in MBF between remote and ischaemic territories was minimal when analysis was performed without SCIC (0.06 ± 0.91 mL/min/kg), and was substantially lower than with either PD-SCIC (0.50 ± 0.63 mL/min/kg; p = 0.013) or with SSFP-SCIC (0.63 ± 0.89 mL/min/kg; p = 0.005). In 6 patients, MBF quantified without SCIC was artifactually higher in the stenosed coronary territory compared to the remote territory. PD-SCIC and SSFP-SCIC had similar differences in MBF between remote and ischaemic territories (p = 0.145). CONCLUSIONS: This study demonstrates that surface coil-related field inhomogeneity can confound pixel-wise MBF quantification. Whilst a PD-based SCIC led to a more homogenous correction than a saturation recovery SSFP-based technique, this did not result in an appreciable difference in the differentiation of ischaemic from remote coronary territories and thus either method could be applied.

In vivo microscopy reveals extensive embedding of capillaries within the sarcolemma of skeletal muscle fibers.

OBJECTIVE: To provide insight into mitochondrial function in vivo, we evaluated the 3D spatial relationship between capillaries, mitochondria, and muscle fibers in live mice. METHODS: 3D volumes of in vivo murine TA muscles were imaged by MPM. Muscle fiber type, mitochondrial distribution, number of capillaries, and capillary-to-fiber contact were assessed. The role of Mb-facilitated diffusion was examined in Mb KO mice. Distribution of GLUT4 was also evaluated in the context of the capillary and mitochondrial network. RESULTS: MPM revealed that 43.6 ± 3.3% of oxidative fiber capillaries had ≥50% of their circumference embedded in a groove in the sarcolemma, in vivo. Embedded capillaries were tightly associated with dense mitochondrial populations lateral to capillary grooves and nearly absent below the groove. Mitochondrial distribution, number of embedded capillaries, and capillary-to-fiber contact were proportional to fiber oxidative capacity and unaffected by Mb KO. GLUT4 did not preferentially localize to embedded capillaries. CONCLUSIONS: Embedding capillaries in the sarcolemma may provide a regulatory mechanism to optimize delivery of oxygen to heterogeneous groups of muscle fibers. We hypothesize that mitochondria locate to PV regions due to myofibril voids created by embedded capillaries, not to enhance the delivery of oxygen to the mitochondria.

Coronary microvascular ischemia in hypertrophic cardiomyopathy - a pixel-wise quantitative cardiovascular magnetic resonance perfusion study.

BACKGROUND: Microvascular dysfunction in HCM has been associated with adverse clinical outcomes. Advances in quantitative cardiovascular magnetic resonance (CMR) perfusion imaging now allow myocardial blood flow to be quantified at the pixel level. We applied these techniques to investigate the spectrum of microvascular dysfunction in hypertrophic cardiomyopathy (HCM) and to explore its relationship with fibrosis and wall thickness. METHODS: CMR perfusion imaging was undertaken during adenosine-induced hyperemia and again at rest in 35 patients together with late gadolinium enhancement (LGE) imaging. Myocardial blood flow (MBF) was quantified on a pixel-by-pixel basis from CMR perfusion images using a Fermi-constrained deconvolution algorithm. Regions-of-interest (ROI) in hypoperfused and hyperemic myocardium were identified from the MBF pixel maps. The myocardium was also divided into 16 AHA segments. RESULTS: Resting MBF was significantly higher in the endocardium than in the epicardium (mean ± SD: 1.25 ± 0.35 ml/g/min versus 1.20 ± 0.35 ml/g/min, P<0.001), a pattern that reversed with stress (2.00 ± 0.76 ml/g/min versus 2.36 ± 0.83 ml/g/min, P<0.001). ROI analysis revealed 11 (31%) patients with stress MBF lower than resting values (1.05 ± 0.39 ml/g/min versus 1.22 ± 0.36 ml/g/min, P=0.021). There was a significant negative association between hyperemic MBF and wall thickness (ß=-0.047 ml/g/min per mm, 95% CI: -0.057 to -0.038, P<0.001) and a significantly lower probability of fibrosis in a segment with increasing hyperemic MBF (odds ratio per ml/g/min: 0.086, 95% CI: 0.078 to 0.095, P=0.003). CONCLUSIONS: Pixel-wise quantitative CMR perfusion imaging identifies a subgroup of patients with HCM that have localised severe microvascular dysfunction which may give rise to myocardial ischemia.

CMR provides comparable measurements of diastolic function as echocardiography.

Clinical application of cardiac magnetic resonance (CMR) is expanding but CMR assessment of LV diastolic function is still being validated. The purpose of this study was to validate assessments of left ventricular (LV) diastolic dysfunction (DD) using CMR by comparing with transthoracic echocardiography (TTE) performed on the same day. Patients with suspected or diagnosed cardiomyopathy (n = 63) and healthy volunteers (n = 24) were prospectively recruited and included in the study. CMR diastolic parameters were measured on cine images and velocity-encoded phase contrast cine images and compared with corresponding parameters measured on TTE. A contextual correlation feature tracking method was developed to calculate the mitral annular velocity curve. LV DD was classified by CMR and TTE following 2016 guidelines. Overall DD classification was 78.1% concordant between CMR and TTE (p < 0.0001). The trans-mitral inflow parameters correlated well between the two modalities (E, r = 0.78; A, r = 0.90; E/A, r = 0.82; all p < 0.0001) while the remaining diastolic parameters showed moderate correlation (e', r = 0.64; E/e', r = 0.54; left atrial volume index (LAVi), r = 0.61; all p < 0.0001). Classification of LV diastolic function by CMR showed good concordance with standardized grades established for TTE. CMR-based LV diastolic function may be integrated in routine clinical practice.Name of the registry: Technical Development of Cardiovascular Magnetic Resonance Imaging. Trial registration number: NCT00027170. Date of registration: November 26, 2001. URL of trial registry record: https://clinicaltrials.gov/ct2/show/NCT00027170.

The gut-brain axis in individuals with alcohol use disorder: An exploratory study of associations among clinical symptoms, brain morphometry, and the gut microbiome.

BACKGROUND: Alcohol use disorder (AUD) is commonly associated with distressing psychological symptoms. Pathologic changes associated with AUD have been described in both the gut microbiome and brain, but the mechanisms underlying gut-brain signaling in individuals with AUD are unknown. This study examined associations among the gut microbiome, brain morphometry, and clinical symptoms in treatment-seeking individuals with AUD. METHODS: We performed a secondary analysis of data collected during inpatient treatment for AUD in subjects who provided gut microbiome samples and had structural brain magnetic resonance imaging (MRI; n = 16). Shotgun metagenomics sequencing was performed, and the morphometry of brain regions of interest was calculated. Clinical symptom severity was quantified using validated instruments. Gut-brain modules (GBMs) used to infer neuroactive signaling potential from the gut microbiome were generated in addition to microbiome features (e.g., alpha diversity and bacterial taxa abundance). Bivariate correlations were performed between MRI and clinical features, microbiome and clinical features, and MRI and microbiome features. RESULTS: Amygdala volume was significantly associated with alpha diversity and the abundance of several bacteria including taxa classified to Blautia, Ruminococcus, Bacteroides, and Phocaeicola. There were moderate associations between amygdala volume and GBMs, including butyrate synthesis I, glutamate synthesis I, and GABA synthesis I & II, but these relationships were not significant after false discovery rate (FDR) correction. Other bacterial taxa with shared associations to MRI features and clinical symptoms included Escherichia coli and Prevotella copri. CONCLUSIONS: We identified gut microbiome features associated with MRI morphometry and AUD-associated symptom severity. Given the small sample size and bivariate associations performed, these results require confirmation in larger samples and controls to provide meaningful clinical inferences. Nevertheless, these results will inform targeted future research on the role of the gut microbiome in gut-brain communication and how signaling may be altered in patients with AUD.

Regadenoson and adenosine are equivalent vasodilators and are superior than dipyridamole- a study of first pass quantitative perfusion cardiovascular magnetic resonance.

BACKGROUND: Regadenoson, dipyridamole and adenosine are commonly used vasodilators in myocardial perfusion imaging for the detection of obstructive coronary artery disease. There are few comparative studies of the vasodilator properties of regadenoson, adenosine and dipyridamole in humans. The specific aim of this study was to determine the relative potency of these three vasodilators by quantifying stress and rest myocardial perfusion in humans using cardiovascular magnetic resonance (CMR). METHODS: Fifteen healthy normal volunteers, with Framingham score less than 1% underwent vasodilator stress testing with regadenoson (400 µg bolus), dipyridamole (0.56 mg/kg) and adenosine (140 µg /kg/min) on separate days. Rest perfusion imaging was performed initially. Twenty minutes later, stress imaging was performed at peak vasodilation, i.e. 70 seconds after regadenoson, 4 minutes after dipyridamole infusion and between 3-4 minutes of the adenosine infusion. Myocardial blood flow (MBF) in ml/min/g and myocardial perfusion reserve (MPR) were quantified using a fully quantitative model constrained deconvolution. RESULTS: Regadenoson produced higher stress MBF than dipyridamole and adenosine (3.58 ± 0.58 vs. 2.81 ± 0.67 vs. 2.78 ± 0.61 ml/min/g, p = 0.0009 and p = 0.0008 respectively). Regadenoson had a much higher heart rate response than adenosine and dipyridamole respectively (95 ± 11 vs. 76 ± 13 vs. 86 ± 12 beats/ minute) When stress MBF was adjusted for heart rate, there were no differences between regadenoson and adenosine (37.8 ± 6 vs. 36.6 ± 4 µl/sec/g, p = NS), but differences between regadenoson and dipyridamole persisted (37.8 ± 6 vs. 32.6 ± 5 µl/sec/g, p = 0.03). The unadjusted MPR was higher with regadenoson (3.11 ± 0.63) when compared with adenosine (2.7 ± 0.61, p = 0.02) and when compared with dipyridamole (2.61 ± 0.57, p = 0.04). Similar to stress MBF, these differences in MPR between regadenoson and adenosine were abolished when adjusted for heart rate (2.04 ± 0.34 vs. 2.12 ± 0.27, p = NS), but persisted between regadenoson and dipyridamole (2.04 ± 0.34 vs. 1.77 ± 0.33, p = 0.07) and between adenosine and dipyridamole (2.12 ± 0.27 vs. 1.77 ± 0.33, p = 0.01). CONCLUSIONS: Based on fully quantitative perfusion using CMR, regadenoson and adenosine have similar vasodilator efficacy and are superior to dipyridamole.

Extracellular volume imaging by magnetic resonance imaging provides insights into overt and sub-clinical myocardial pathology.

AIMS: Conventional late gadolinium enhancement (LGE) cardiac magnetic resonance can detect myocardial infarction and some forms of non-ischaemic myocardial fibrosis. However, quantitative imaging of extracellular volume fraction (ECV) may be able to detect subtle abnormalities such as diffuse fibrosis or post-infarct remodelling of remote myocardium. The aims were (1) to measure ECV in myocardial infarction and non-ischaemic myocardial fibrosis, (2) to determine whether ECV varies with age, and (3) to detect sub-clinical abnormalities in 'normal appearing' myocardium remote from regions of infarction. METHODS AND RESULTS: Cardiac magnetic resonance ECV imaging was performed in 126 patients with T1 mapping before and after injection of gadolinium contrast. Conventional LGE images were acquired for the left ventricle. In patients with a prior myocardial infarction, the infarct region had an ECV of 51 ± 8% which did not overlap with the remote 'normal appearing' myocardium that had an ECV of 27 ± 3% (P < 0.001, n = 36). In patients with non-ischaemic cardiomyopathy, the ECV of atypical LGE was 37 ± 6%, whereas the 'normal appearing' myocardium had an ECV of 26 ± 3% (P < 0.001, n = 30). The ECV of 'normal appearing' myocardium increased with age (r = 0.28, P = 0.01, n = 60). The ECV of 'normal appearing' myocardium remote from myocardial infarctions increased as left ventricular ejection fraction decreased (r = -0.50, P = 0.02). CONCLUSION: Extracellular volume fraction imaging can quantitatively characterize myocardial infarction, atypical diffuse fibrosis, and subtle myocardial abnormalities not clinically apparent on LGE images. Taken within the context of prior literature, these subtle ECV abnormalities are consistent with diffuse fibrosis related to age and changes remote from infarction.

Evaluation of an artificial intelligence-based system for echocardiographic estimation of right atrial pressure.

Current noninvasive estimation of right atrial pressure (RAP) by inferior vena cava (IVC) measurement during echocardiography may have significant inter-rater variability due to different levels of observers' experience. Therefore, there is a need to develop new approaches to decrease the variability of IVC analysis and RAP estimation. This study aims to develop a fully automated artificial intelligence (AI)-based system for automated IVC analysis and RAP estimation. We presented a multi-stage AI system to identify the IVC view, select good quality images, delineate the IVC region and quantify its thickness, enabling temporal tracking of its diameter and collapsibility changes. The automated system was trained and tested on expert manual IVC and RAP reference measurements obtained from 255 patients during routine clinical workflow. The performance was evaluated using Pearson correlation and Bland-Altman analysis for IVC values, as well as macro accuracy and chi-square test for RAP values. Our results show an excellent agreement (r=0.96) between automatically computed versus manually measured IVC values, and Bland-Altman analysis showed a small bias of [Formula: see text]0.33 mm. Further, there is an excellent agreement ([Formula: see text]) between automatically estimated versus manually derived RAP values with a macro accuracy of 0.85. The proposed AI-based system accurately quantified IVC diameter, collapsibility index, both are used for RAP estimation. This automated system could serve as a paradigm to perform IVC analysis in routine echocardiography and support various cardiac diagnostic applications.