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.

Longitudinal association of epicardial and thoracic adipose tissues with coronary and cardiac characteristics in psoriasis

Background

s: Psoriasis is a disease of systemic inflammation associated with increased cardiometabolic risk. Epicardial adipose tissue (EAT) and thoracic adipose tissue (TAT) are contributing factors for atherosclerosis and cardiac dysfunction. We strove to assess the longitudinal impact of the EAT and TAT on coronary and cardiac characteristics in psoriasis.

Methods

The study consisted of 301 patients with baseline coronary computed tomography angiography (CTA), of which 139 had four-year follow up scans. EAT and TAT volumes from non-contrast computed tomography scans were quantified by an automated segmentation framework. Coronary plaque characteristics and left ventricular (LV) mass were quantified by CTA.

Results

When stratified by baseline EAT and TAT volume quartiles, a stepwise significant increase in cardiometabolic parameters was observed. EAT and TAT volumes associated with fibro-fatty burden (FFB) (TAT: ρ = 0.394, P < 0.001; EAT: ρ = 0.459, P < 0.001) in adjusted models. Only EAT had a significant four-year time-dependent association with FFB in fully adjusted models (β = 0.307 P = 0.003), whereas only TAT volume associated with myocardial injury in fully adjusted models (TAT: OR = 1.57 95 % CI = (1.00-2.60); EAT: OR = 1.46 95 % CI = (0.91-2.45). Higher quartiles of EAT and TAT had increased LV mass and developed strong correlation (TAT: ρ = 0.370, P < 0.001; EAT: ρ = 0.512, P < 0.001).

Conclusions

Our study is the first to explore how both EAT and TAT volumes associate with increased cardiometabolic risk profile in an inflamed psoriasis cohorts and highlight the need for further studies on its use as a potential prognostic tool for high-risk coronary plaques and cardiac dysfunction.

Comparison of CT and Dixon MR Abdominal Adipose Tissue Quantification Using a Unified Computer-Assisted Software Framework

PURPOSE

Reliable and objective measures of abdominal fat distribution across imaging modalities are essential for various clinical and research scenarios, such as assessing cardiometabolic disease risk due to obesity. We aimed to compare quantitative measures of subcutaneous (SAT) and visceral (VAT) adipose tissues in the abdomen between computed tomography (CT) and Dixon-based magnetic resonance (MR) images using a unified computer-assisted software framework.

MATERIALS AND METHODS

This study included 21 subjects who underwent abdominal CT and Dixon MR imaging on the same day. For each subject, two matched axial CT and fat-only MR images at the L2-L3 and the L4-L5 intervertebral levels were selected for fat quantification. For each image, an outer and an inner abdominal wall regions as well as SAT and VAT pixel masks were automatically generated by our software. The computer-generated results were then inspected and corrected by an expert reader.

RESULTS

There were excellent agreements for both abdominal wall segmentation and adipose tissue quantification between matched CT and MR images. Pearson coefficients were 0.97 for both outer and inner region segmentation, 0.99 for SAT, and 0.97 for VAT quantification. Bland-Altman analyses indicated minimum biases in all comparisons.

CONCLUSION

We showed that abdominal adipose tissue can be reliably quantified from both CT and Dixon MR images using a unified computer-assisted software framework. This flexible framework has a simple-to-use workflow to measure SAT and VAT from both modalities to support various clinical research applications.

DeepHeartCT: A fully automatic artificial intelligence hybrid framework based on convolutional neural network and multi-atlas segmentation for multi-structure cardiac computed tomography angiography image segmentation

Cardiac computed tomography angiography (CTA) is an emerging imaging modality for assessing coronary artery as well as various cardiovascular structures. Recently, deep learning (DL) methods have been successfully applied to many applications of medical image analysis including cardiac CTA structure segmentation. However, DL requires a large amounts of data and high-quality labels for training which can be burdensome to obtain due to its labor-intensive nature. In this study, we aim to develop a fully automatic artificial intelligence (AI) system, named DeepHeartCT, for accurate and rapid cardiac CTA segmentation based on DL. The proposed system was trained using a large clinical dataset with computer-generated labels to segment various cardiovascular structures including left and right ventricles (LV, RV), left and right atria (LA, RA), and LV myocardium (LVM). This new system was trained directly using high-quality computer labels generated from our previously developed multi-atlas based AI system. In addition, a reverse ranking strategy was proposed to assess the segmentation quality in the absence of manual reference labels. This strategy allowed the new framework to assemble optimal computer-generated labels from a large dataset for effective training of a deep convolutional neural network (CNN). A large clinical cardiac CTA studies (n = 1,064) were used to train and validate our framework. The trained model was then tested on another independent dataset with manual labels (n = 60). The Dice score, Hausdorff distance and mean surface distance were used to quantify the segmentation accuracy. The proposed DeepHeartCT framework yields a high median Dice score of 0.90 [interquartile range (IQR), 0.90-0.91], a low median Hausdorff distance of 7 mm (IQR, 4-15 mm) and a low mean surface distance of 0.80 mm (IQR, 0.57-1.29 mm) across all segmented structures. An additional experiment was conducted to evaluate the proposed DL-based AI framework trained with a small vs. large dataset. The results show our framework also performed well when trained on a small optimal training dataset (n = 110) with a significantly reduced training time. These results demonstrated that the proposed DeepHeartCT framework provides accurate and rapid cardiac CTA segmentation that can be readily generalized for handling large-scale medical imaging applications.

Real-time echocardiography image analysis and quantification of cardiac indices

Deep learning has a huge potential to transform echocardiography in clinical practice and point of care ultrasound testing by providing real-time analysis of cardiac structure and function. Automated echocardiography analysis is benefited through use of machine learning for tasks such as image quality assessment, view classification, cardiac region segmentation, and quantification of diagnostic indices. By taking advantage of high-performing deep neural networks, we propose a novel and eicient real-time system for echocardiography analysis and quantification. Our system uses a self-supervised modality-specific representation trained using a publicly available large-scale dataset. The trained representation is used to enhance the learning of target echo tasks with relatively small datasets. We also present a novel Trilateral Attention Network (TaNet) for real-time cardiac region segmentation. The proposed network uses a module for region localization and three lightweight pathways for encoding rich low-level, textural, and high-level features. Feature embeddings from these individual pathways are then aggregated for cardiac region segmentation. This network is fine-tuned using a joint loss function and training strategy. We extensively evaluate the proposed system and its components, which are echo view retrieval, cardiac segmentation, and quantification, using four echocardiography datasets. Our experimental results show a consistent improvement in the performance of echocardiography analysis tasks with enhanced computational eiciency that charts a path toward its adoption in clinical practice. Specifically, our results show superior real-time performance in retrieving good quality echo from individual cardiac view, segmenting cardiac chambers with complex overlaps, and extracting cardiac indices that highly agree with the experts’ values. The source code of our implementation can be found in the project ‘ s GitHub page.

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).

The relationship between systemic inflammation and increased left ventricular mass is partly mediated by noncalcified coronary artery disease burden in psoriasis

Objective

Increased left ventricular (LV) mass is an important precursor to heart failure. Inflammation plays an important role in increasing LV mass. However, the contribution of subclinical coronary artery disease (CAD) to the inflammation-LV mass relationship is unknown. In subjects with psoriasis, a chronic inflammatory skin disease, we evaluated if systemic inflammation assessed by plasma glycoprotein A (GlycA) associated with LV mass measured on coronary CT angiography (CCTA). Additionally, we analyzed whether this relationship was mediated by early CAD assessed as noncalcified coronary burden (NCB).

Methods

We performed an observational longitudinal study of 213 subjects with psoriasis free of known cardiovascular disease, 189 of whom were followed over one year. All participants had GlycA measurements by nuclear magnetic resonance spectroscopy and LV mass and NCB quantified by CCTA.

Results

The cohort had a mean age of 50.3 (±12.9) years and 59% were male. There was moderate psoriasis severity and low cardiovascular risk. LV mass increased by GlycA tertiles [1st tertile:24.6 g/m^2.7(3.8), 2nd tertile:25.5 g/m^2.7(3.8), 3rd tertile:27.7 g/m^2.7(5.5), p<0.001]. Both GlycA (β=0.24, p = 0.001) and NCB (β=0.50, p<0.001) associated with LV mass in models adjusted for age, sex, hypertension, hypertension therapy, lipid therapy, biologic therapy for psoriasis, waist:hip ratio, psoriasis disease duration and severity. In multivariable-adjusted mediation analyses, NCB accounted for 32% of the GlycA-LV mass relationship. Finally, over one year, change in NCB independently associated with change in LV mass (β=0.25, p = 0.002).

Conclusions

Both systemic inflammation and coronary artery NCB were associated with LV mass beyond cardiovascular risk factors in psoriasis. Furthermore, a substantial proportion of the inflammatory-LV mass relationship was mediated by NCB. These findings underscore the possible contribution of early coronary artery disease to the relationship between systemic inflammation and LV mass.

A theoretical framework for retrospective T 2 ∗ correction to the arterial input function in quantitative myocardial perfusion MRI

PURPOSE

To develop and evaluate a flexible, Bloch-equation based framework for retrospective T 2 ∗ 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, T 2 ∗ 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 T 2 ∗ correction to the Bloch equation signal model. Using this approach, we performed T 2 ∗ 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 T 2 ∗ 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 T 2 ∗ correction to the AIF obtained with dual-imaging, cardiac perfusion pulse sequences.

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.

Harnessing Machine Intelligence in Automatic Echocardiogram Analysis: Current Status, Limitations, and Future Directions

Echocardiography (echo) is a critical tool in diagnosing various cardiovascular diseases. Despite its diagnostic and prognostic value, interpretation and analysis of echo images are still widely performed manually by echocardiographers. A plethora of algorithms has been proposed to analyze medical ultrasound data using signal processing and machine learning techniques. These algorithms provided opportunities for developing automated echo analysis and interpretation systems. The automated approach can significantly assist in decreasing the variability and burden associated with manual image measurements. In this paper, we review the state-of-the-art automatic methods for analyzing echocardiography data. Particularly, we comprehensively and systematically review existing methods of four major tasks: echo quality assessment, view classification, boundary segmentation, and disease diagnosis. Our review covers three echo imaging modes, which are B-mode, M-mode, and Doppler. We also discuss the challenges and limitations of current methods and outline the most pressing directions for future research. In summary, this review presents the current status of automatic echo analysis and discusses the challenges that need to be addressed to obtain robust systems suitable for efficient use in clinical settings or point-of-care testing.

Automated Segmental Analysis of Fully Quantitative Myocardial Blood Flow Maps by First-Pass Perfusion Cardiovascular Magnetic Resonance

First pass gadolinium-enhanced cardiovascular magnetic resonance (CMR) perfusion imaging allows fully quantitative pixel-wise myocardial blood flow (MBF) assessment, with proven diagnostic value for coronary artery disease. Segmental analysis requires manual segmentation of the myocardium. This work presents a fully automatic method of segmenting the left ventricular myocardium from MBF pixel maps, validated on a retrospective dataset of 247 clinical CMR perfusion studies, each including rest and stress images of three slice locations, performed on a 1.5T scanner. Pixel-wise MBF maps were segmented using an automated pipeline including region growing, edge detection, principal component analysis, and active contours to segment the myocardium, detect key landmarks, and divide the myocardium into sectors appropriate for analysis. Automated segmentation results were compared against a manually defined reference standard using three quantitative metrics: Dice coefficient, Cohen Kappa and myocardial border distance. Sector-wise average MBF and myocardial perfusion reserve (MPR) were compared using Pearson's correlation coefficient and Bland-Altman Plots. The proposed method segmented stress and rest MBF maps of 243 studies automatically. Automated and manual myocardial segmentation had an average (± standard deviation) Dice coefficient of 0.86 ± 0.06, Cohen Kappa of 0.86 ± 0.06, and Euclidian distances of 1.47 ± 0.73 mm and 1.02 ± 0.51 mm for the epicardial and endocardial border, respectively. Automated and manual sector-wise MBF and MPR values correlated with Pearson's coefficient of 0.97 and 0.92, respectively, while Bland-Altman analysis showed bias of 0.01 and 0.07 ml/g/min. The validated method has been integrated with our fully automated MBF pixel mapping pipeline to aid quantitative assessment of myocardial perfusion CMR.

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.

Improving multi-atlas cardiac structure segmentation of computed tomography angiography: A performance evaluation based on a heterogeneous dataset

Multi-atlas based segmentation is an effective technique that transforms a representative set of atlas images and labels into a target image for structural segmentation. However, a significant limitation of this approach relates to the fact that the atlas and the target images need to be similar in volume orientation, coverage, or acquisition protocols in order to prevent image misregistration and avoid segmentation fault. In this study, we aim to evaluate the impact of using a heterogeneous Computed Tomography Angiography (CTA) dataset on the performance of a multi-atlas cardiac structure segmentation framework. We propose a generalized technique based upon using the Simple Linear Iterative Clustering (SLIC) supervoxel method to detect a bounding box region enclosing the heart before subsequent cardiac structure segmentation. This technique facilitates our framework to process CTA datasets acquired from distinct imaging protocols and to improve its segmentation accuracy and speed. In a four-way cross comparison based on 60 CTA studies from our institution and 60 CTA datasets from the Multi-Modality Whole Heart Segmentation MICCAI challenge, we show that the proposed framework performs well in segmenting seven different cardiac structures based upon interchangeable atlas and target datasets acquired from different imaging settings. For the overall results, our automated segmentation framework attains a median Dice, mean distance, and Hausdorff distance of 0.88, 1.5 mm, and 9.69 mm over the entire datasets. The average processing time was 1.55 min for both datasets. Furthermore, this study shows that it is feasible to exploit heterogenous datasets from different imaging protocols and institutions for accurate multi-atlas cardiac structure segmentation.

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.

Accelerated Wideband Myocardial Perfusion Pulse Sequence with Compressed Sensing Reconstruction for Myocardial Blood Flow Quantification in Patients with a Cardiac Implantable Electronic Device

Purpose

To develop an accelerated wideband cardiac perfusion pulse sequence and test whether it can produce diagnostically acceptable image quality and whether it can be used to reliably quantify myocardial blood flow (MBF) in patients with a cardiac implantable electronic device (CIED).

Materials and Methods

A fivefold-accelerated wideband perfusion pulse sequence was developed using compressed sensing to sample one arterial input function plane and three myocardial perfusion (MP) planes per heartbeat in patients with a CIED with heart rates as high as 102 beats per minute. Resting perfusion scans were performed in 10 patients with a CIED and in 10 patients with no device as a control group. Two clinical readers compared the resulting images and retrospective images of the 10 patients with a CIED, which were obtained by using a previously described twofold-accelerated wideband perfusion pulse sequence with temporal generalized autocalibrating partially parallel acquisition. Summed visual score (SVS) was defined as the sum of conspicuity, artifact, and noise scores individually ranging from 1 (worst) to 5 (best). Resting MBF in the remote zones was quantified using Fermi deconvolution.

Results

Median SVS was significantly different (P < .05) between the prospective and retrospective CIED groups (13 vs nine) and between the nondevice group and the retrospective CIED group (13.5 vs nine); all median SVSs were nine or greater (clinically acceptable cut point). The median resting MBF in remote zones was not significantly different (P = .27) between patients with a CIED (1.1 mL/min/g; median left ventricular ejection fraction [LVEF], 52.5%) and patients with no device (1.3 mL/min/g; median LVEF, 64.0%). Mean MBF values were consistent with those (mean resting MBF range, 1.0-1.2 mL/min/g) reported by two prior state-of-the-art cardiac perfusion MRI studies.

Conclusion

The proposed scan yielded diagnostically acceptable image quality and enabled reliable quantification of MBF with three MP planes per heartbeat in patients with a CIED with heart rates as high as 102 beats per minute. Supplemental material is available for this article. © RSNA, 2020.

Simultaneous Multi-Structure Segmentation of the Heart and Peripheral Tissues in Contrast Enhanced Cardiac Computed Tomography Angiography

Contrast enhanced cardiac computed tomography angiography (CTA) is a prominent imaging modality for diagnosing cardiovascular diseases non-invasively. It assists the evaluation of the coronary artery patency and provides a comprehensive assessment of structural features of the heart and great vessels. However, physicians are often required to evaluate different cardiac structures and measure their size manually. Such task is very time-consuming and tedious due to the large number of image slices in 3D data. We present a fully automatic method based on a combined multi-atlas and corrective segmentation approach to label the heart and its associated cardiovascular structures. This method also automatically separates other surrounding intrathoracic structures from CTA images. Quantitative assessment of the proposed method is performed on 36 studies with a reference standard obtained from expert manual segmentation of various cardiac structures. Qualitative evaluation is also performed by expert readers to score 120 studies of the automatic segmentation. The quantitative results showed an overall Dice of 0.93, Hausdorff distance of 7.94 mm, and mean surface distance of 1.03 mm between automatically and manually segmented cardiac structures. The visual assessment also attained an excellent score for the automatic segmentation. The average processing time was 2.79 minutes. Our results indicate the proposed automatic framework significantly improves accuracy and computational speed in conventional multi-atlas based approach, and it provides comprehensive and reliable multi-structural segmentation of CTA images that is valuable for clinical application.

Microvascular Dysfunction in Dilated Cardiomyopathy: A Quantitative Stress Perfusion Cardiovascular Magnetic Resonance Study

OBJECTIVES

This study sought to quantify myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) in dilated cardiomyopathy (DCM) and examine the relationship between myocardial perfusion and adverse left ventricular (LV) remodeling.

BACKGROUND

Although regarded as a nonischemic condition, DCM has been associated with microvascular dysfunction, which is postulated to play a role in its pathogenesis. However, the relationship of the resulting perfusion abnormalities to myocardial fibrosis and the degree of LV remodeling is unclear.

METHODS

A total of 65 patients and 35 healthy control subjects underwent adenosine (140 μg/kg/min) stress perfusion cardiovascular magnetic resonance with late gadolinium enhancement imaging. Stress and rest MBF and MPR were derived using a modified Fermi-constrained deconvolution algorithm.

RESULTS

Patients had significantly higher global rest MBF compared with control subjects (1.73 ± 0.42 ml/g/min vs. 1.14 ± 0.42 ml/g/min; p < 0.001). In contrast, global stress MBF was significantly lower versus control subjects (3.07 ± 1.02 ml/g/min vs. 3.53 ± 0.79 ml/g/min; p = 0.02), resulting in impaired MPR in the DCM group (1.83 ± 0.58 vs. 3.50 ± 1.45; p < 0.001). Global stress MBF (2.70 ± 0.89 ml/g/min vs. 3.44 ± 1.03 ml/g/min; p = 0.017) and global MPR (1.67 ± 0.61 vs. 1.99 ± 0.50; p = 0.047) were significantly reduced in patients with DCM with LV ejection fraction ≤35% compared with those with LV ejection fraction >35%. Segments with fibrosis had lower rest MBF (mean difference: -0.12 ml/g/min; 95% confidence interval: -0.23 to -0.01 ml/g/min; p = 0.035) and lower stress MBF (mean difference: -0.15 ml/g/min; 95% confidence interval: -0.28 to -0.03 ml/g/min; p = 0.013).

CONCLUSIONS

Patients with DCM exhibit microvascular dysfunction, the severity of which is associated with the degree of LV impairment. However, rest MBF is elevated rather than reduced in DCM. If microvascular dysfunction contributes to the pathogenesis of DCM, then the underlying mechanism is more likely to involve stress-induced repetitive stunning rather than chronic myocardial hypoperfusion.

Rationale and design of the Coronary Microvascular Angina Cardiac Magnetic Resonance Imaging (CorCMR) diagnostic study: the CorMicA CMR sub-study

Introduction

Angina with no obstructive coronary artery disease (ANOCA) is a common syndrome with unmet clinical needs. Microvascular and vasospastic angina are relevant but may not be diagnosed without measuring coronary vascular function. The relationship between cardiovascular magnetic resonance (CMR)-derived myocardial blood flow (MBF) and reference invasive coronary function tests is uncertain. We hypothesise that multiparametric CMR assessment will be clinically useful in the ANOCA diagnostic pathway.

Methods/analysis

The Stratified Medical Therapy Using Invasive Coronary Function Testing In Angina (CorMicA) trial is a prospective, blinded, randomised, sham-controlled study comparing two management approaches in patients with ANOCA. We aim to recruit consecutive patients with stable angina undergoing elective invasive coronary angiography. Eligible patients with ANOCA (n=150) will be randomised to invasive coronary artery function-guided diagnosis and treatment (intervention group) or not (control group). Based on these test results, patients will be stratified into disease endotypes: microvascular angina, vasospastic angina, mixed microvascular/vasospastic angina, obstructive epicardial coronary artery disease and non-cardiac chest pain. After randomisation in CorMicA, subjects will be invited to participate in the Coronary Microvascular Angina Cardiac Magnetic Resonance Imaging (CorCMR) substudy. Patients will undergo multiparametric CMR and have assessments of MBF (using a novel pixel-wise fully quantitative method), left ventricular function and mass, and tissue characterisation (T1 mapping and late gadolinium enhancement imaging). Abnormalities of myocardial perfusion and associations between MBF and invasive coronary artery function tests will be assessed. The CorCMR substudy represents the largest cohort of ANOCA patients with paired multiparametric CMR and comprehensive invasive coronary vascular function tests.

Ethics/dissemination

The CorMicA trial and CorCMR substudy have UK REC approval (ref.16/WS/0192).

Trial registration number

NCT03193294.

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.

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.

Diagnostic Performance of Fully Automated Pixel-Wise Quantitative Myocardial Perfusion Imaging by Cardiovascular Magnetic Resonance

OBJECTIVES

The authors developed a fully automated framework to quantify myocardial blood flow (MBF) from contrast-enhanced cardiac magnetic resonance (CMR) perfusion imaging and evaluated its diagnostic performance in patients.

BACKGROUND

Fully quantitative CMR perfusion pixel maps were previously validated with microsphere MBF measurements and showed potential in clinical applications, but the methods required laborious manual processes and were excessively time-consuming.

METHODS

CMR perfusion imaging was performed on 80 patients with known or suspected coronary artery disease (CAD) and 17 healthy volunteers. Significant CAD was defined by quantitative coronary angiography (QCA) as ≥70% stenosis. Nonsignificant CAD was defined by: 1) QCA as <70% stenosis; or 2) coronary computed tomography angiography as <30% stenosis and a calcium score of 0 in all vessels. Automatically generated MBF maps were compared with manual quantification on healthy volunteers. Diagnostic performance of the automated MBF pixel maps was analyzed on patients using absolute MBF, myocardial perfusion reserve (MPR), and relative measurements of MBF and MPR.

RESULTS

The correlation between automated and manual quantification was excellent (r = 0.96). Stress MBF and MPR in the ischemic zone were lower than those in the remote myocardium in patients with significant CAD (both p < 0.001). Stress MBF and MPR in the remote zone of the patients were lower than those in the normal volunteers (both p < 0.001). All quantitative metrics had good area under the curve (0.864 to 0.926), sensitivity (82.9% to 91.4%), and specificity (75.6% to 91.1%) on per-patient analysis. On a per-vessel analysis of the quantitative metrics, area under the curve (0.837 to 0.864), sensitivity (75.0% to 82.7%), and specificity (71.8% to 80.9%) were good.

CONCLUSIONS

Fully quantitative CMR MBF pixel maps can be generated automatically, and the results agree well with manual quantification. These methods can discriminate regional perfusion variations and have high diagnostic performance for detecting significant CAD. (Technical Development of Cardiovascular Magnetic Resonance Imaging; NCT00027170)

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.

Early Gadolinium Enhancement for Determination of Area at Risk: A Preclinical Validation Study

OBJECTIVES

The aim of this study was to determine whether early gadolinium enhancement (EGE) by cardiac magnetic resonance (CMR) in a canine model of reperfused myocardial infarction depicts the area at risk (AAR) as determined by microsphere blood flow analysis.

BACKGROUND

It remains controversial whether only the irreversibly injured myocardium enhances when CMR is performed in the setting of acute myocardial infarction. Recently, EGE has been proposed as a measure of the AAR in acute myocardial infarction because it correlates well with T2-weighted imaging of the AAR, but this still requires pathological validation.

METHODS

Eleven dogs underwent 2 h of coronary artery occlusion and 48 h of reperfusion before imaging at 1.5-T. EGE imaging was performed 3 min after contrast administration with coverage of the entire left ventricle. Late gadolinium enhancement imaging was performed between 10 and 15 min after contrast injection. AAR was defined as myocardium with blood flow <2 SD from remote myocardium determined by microspheres during occlusion. The size of infarction was determined with triphenyltetrazolium chloride.

RESULTS

There was no significant difference in the size of enhancement by EGE compared with the size of AAR by microspheres (44.1 ± 15.8% vs. 42.7 ± 9.2%; p = 0.61), with good correlation (r = 0.88; p < 0.001) and good agreement by Bland-Altman analysis (mean bias 1.4 ± 17.4%). There was no difference in the size of enhancement by EGE compared with enhancement on native T1 and T2 maps. The size of EGE was significantly greater than the infarct by triphenyltetrazolium chloride (44.1 ± 15.8% vs. 20.7 ± 14.4%; p < 0.001) and late gadolinium enhancement (44.1 ± 15.8% vs. 23.5 ± 12.7%; p < 0.001).

CONCLUSIONS

At 3 min post-contrast, EGE correlated well with the AAR by microspheres and CMR and was greater than infarct size. Thus, EGE enhances both reversibly and irreversibly injured myocardium.

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.

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.

Quantitative assessment of myocardial fibrosis in an age-related rat model by ex vivo late gadolinium enhancement magnetic resonance imaging with histopathological correlation

Late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR) imaging can detect the presence of myocardial infarction from ischemic cardiomyopathies (ICM). However, it is more challenging to detect diffuse myocardial fibrosis from non-ischemic cardiomyopathy (NICM) with this technique due to more subtle and heterogeneous enhancement of the myocardium. This study investigates whether high-resolution LGE CMR can detect age-related myocardial fibrosis using quantitative texture analysis with histological validation. LGE CMR of twenty-four rat hearts (twelve 6-week-old and twelve 2-year-old) was performed using a 7T MRI scanner. Picrosirius red was used as the histopathology reference for collagen staining. Fibrosis in the myocardium was quantified with standard deviation (SD) threshold methods from the LGE CMR images and 3D contrast texture maps that were computed from gray level co-occurrence matrix of the CMR images. There was a significant increase of collagen fibers in the aged compared to the young rat histology slices (2.60±0.27 %LV vs. 1.24±0.29 %LV, p<0.01). Both LGE CMR and texture images showed a significant increase of myocardial fibrosis in the elderly compared to the young rats. Fibrosis in the LGE CMR images correlated strongly with histology with the 3 SD threshold (r=0.84, y=0.99x+0.00). Similarly, fibrosis in the contrast texture maps correlated with the histology using the 4 SD threshold (r=0.89, y=1.01x+0.00). High resolution ex-vivo LGE CMR can detect the presence of diffuse fibrosis that naturally developed in elderly rat hearts. Our results suggest that texture analysis may improve the assessment of myocardial fibrosis in LGE CMR images.

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.

Mechanisms for overestimating acute myocardial infarct size with gadolinium-enhanced cardiovascular magnetic resonance imaging in humans: a quantitative and kinetic study

Aims

It remains controversial whether cardiovascular magnetic resonance imaging with gadolinium only enhances acutely infarcted or also salvaged myocardium. We hypothesized that enhancement of salvaged myocardium may be due to altered extracellular volume (ECV) and contrast kinetics compared with normal and infarcted myocardium. If so, these mechanisms could contribute to overestimation of acute myocardial infarction (AMI) size.

Methods and results

Imaging was performed at 1.5T ≤ 7 days after AMI with serial T₁ mapping and volumetric early (5 min post-contrast) and late (20 min post-contrast) gadolinium enhancement imaging. Infarcts were classified as transmural (>75% transmural extent) or non-transmural. Patients with non-transmural infarctions (n = 15) had shorter duration of symptoms before reperfusion (P = 0.02), lower peak troponin (P = 0.008), and less microvascular obstruction (P < 0.001) than patients with transmural infarcts (n = 22). The size of enhancement at 5 min was greater than at 20 min (18.7 ± 12.7 vs. 12.1 ± 7.0%, P = 0.003) in non-transmural infarctions, but similar in transmural infarctions (23.0 ± 10.0 vs. 21.9 ± 9.9%, P = 0.21). ECV of salvaged myocardium was greater than normal (39.5 ± 5.8 vs. 24.1 ± 3.1%) but less than infarcted myocardium (50.5 ± 6.0%, both P < 0.001). In kinetic studies of non-transmural infarctions, salvaged and infarcted myocardium had similar T₁ at 4 min but different T₁ at 8–20 min post-contrast.

Conclusion

The extent of gadolinium enhancement in AMI is modulated by ECV and contrast kinetics. Image acquisition too early after contrast administration resulted in overestimation of infarct size in non-transmural infarctions due to enhancement of salvaged myocardium.

Temporal and spatial characteristics of the area at risk investigated using computed tomography and T1-weighted magnetic resonance imaging

Aims

Cardiovascular magnetic resonance (CMR) imaging can measure the myocardial area at risk (AAR), but the technique has received criticism for inadequate validation. CMR commonly depicts an AAR that is wider than the infarct, which in turn would require a lateral perfusion gradient within the AAR. We investigated the presence of a lateral perfusion gradient within the AAR and validated CMR measures of AAR against three independent reference standards of high quality.

Methods and results

Computed tomography (CT) perfusion imaging, microsphere blood flow analysis, T₁-weighted 3T CMR and fluorescent microparticle pathology were used to investigate the AAR in a canine model (n = 10) of ischaemia and reperfusion. AAR size by CMR correlated well with CT (R² = 0.80), microsphere blood flow (R² = 0.80), and pathology (R² = 0.74) with good limits of agreement [−0.79 ± 4.02% of the left ventricular mass (LVM) vs. CT; −1.49 ± 4.04% LVM vs. blood flow and −1.01 ± 4.18% LVM vs. pathology]. The lateral portion of the AAR had higher perfusion than the core of the AAR by CT perfusion imaging (40.7 ± 11.8 vs. 25.2 ± 17.7 Hounsfield units, P = 0.0008) and microsphere blood flow (0.11 ± 0.04 vs. 0.05 ± 0.02 mL/g/min, lateral vs. core, P = 0.001). The transmural extent of MI was lower in the lateral portion of the AAR than the core (28.2 ± 10.2 vs. 17.4 ± 8.4% of the wall, P = 0.001).

Conclusion

T₁-weighted CMR accurately quantifies size of the AAR with excellent agreement compared with three independent reference standards. A lateral perfusion gradient results in lower transmural extent of infarction at the edges of the AAR compared with the core.

Epidemiology of invasive fungal diseases among patients with haematological disorders in the Asia-Pacific: a prospective observational study

We conducted a 2-year multicentre prospective observational study to determine the epidemiology of and mortality associated with invasive fungal diseases (IFDs) among patients with haematological disorders in Asia. Eleven institutions from 8 countries/regions participated, with 412 subjects (28.2% possible, 38.3% probable and 33.5% proven IFDs) recruited. The epidemiology of IFDs in participating institutions was similar to Western centres, with Aspergillus spp. (65.9%) or Candida spp. (26.7%) causing the majority of probable and proven IFDs. The overall 30-day mortality was 22.1%. Progressive haematological disorder (odds ratio [OR] 5.192), invasive candidiasis (OR 3.679), and chronic renal disease (OR 6.677) were independently associated with mortality.

Treating pit-and-fissure caries: a systematic review and network meta-analysis

For shallow or moderately deep pit-and-fissure lesions, various treatment options are available: (1) noninvasive treatments (e.g., fluoride application, antibacterial treatments, oral hygiene advice) avoid any dental hard tissue removal; (2) microinvasive treatments (e.g., sealing) remove only a few micrometers of hard tissues by etching; and minimally invasive methods (e.g., "preventive" resin/sealant restoration) remove carious dentin but avoid sacrificing sound tissues. We aimed at systematically reviewing and comparing these strategies for treating pit-and-fissure lesions in permanent teeth using network meta-analysis. Randomized or nonrandomized clinical trials investigating shallow or moderately deep primary caries lesions in fissured or pitted surfaces were included. We compared the risk of requiring invasive treatments or any retreatments in noninvasive, microinvasive, and minimally invasive treated lesions; untreated lesions were used as controls. Five electronic databases were systematically screened up to September 2013 and cross-referencing performed. Pairwise and network meta-analyses were performed and odds ratios and 95% confidence intervals (CI) calculated. Certainty of estimates was evaluated via GRADE criteria. From a total of 2,214 identified records, 14 studies representing 1,440 patients with 3,551 treated lesions were included. Pairwise meta-analysis found microinvasive and minimally invasive treated lesions to require less invasive retreatments than control lesions (odds ratios [95% confidence intervals]: 0.13 [0.07 to 0.26], 0.13 [0.03 to 0.50], respectively), whereas the estimate for noninvasively treated lesions remained nonsignificant (0.64 [0.39 to 1.06]). These findings were reflected in the strategy ranking stemming from network meta-analysis (first, minimally invasive; second, microinvasive; third, noninvasive). However, microinvasive treatment required significantly more total retreatments (including resealing) than minimally or noninvasive treatments. Due to limited study quality, the evidence was graded as low or very low. Clinical treatment decisions should consider the long-term sequelae and costs stemming from different therapies as well as their subjective impact on the patient. Available treatment options seem suitable for treating shallow or moderately deep pit-and-fissure lesions in permanent teeth; further conclusions are not possible.

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.

Diagnostic accuracy of stress perfusion CMR in comparison with quantitative coronary angiography: fully quantitative, semiquantitative, and qualitative assessment

OBJECTIVES

This study's primary objective was to determine the sensitivity, specificity, and accuracy of fully quantitative stress perfusion cardiac magnetic resonance (CMR) versus a reference standard of quantitative coronary angiography. We hypothesized that fully quantitative analysis of stress perfusion CMR would have high diagnostic accuracy for identifying significant coronary artery stenosis and exceed the accuracy of semiquantitative measures of perfusion and qualitative interpretation.

BACKGROUND

Relatively few studies apply fully quantitative CMR perfusion measures to patients with coronary disease and comparisons to semiquantitative and qualitative methods are limited.

METHODS

Dual bolus dipyridamole stress perfusion CMR exams were performed in 67 patients with clinical indications for assessment of myocardial ischemia. Stress perfusion images alone were analyzed with a fully quantitative perfusion (QP) method and 3 semiquantitative methods including contrast enhancement ratio, upslope index, and upslope integral. Comprehensive exams (cine imaging, stress/rest perfusion, late gadolinium enhancement) were analyzed qualitatively with 2 methods including the Duke algorithm and standard clinical interpretation. A 70% or greater stenosis by quantitative coronary angiography was considered abnormal.

RESULTS

The optimum diagnostic threshold for QP determined by receiver-operating characteristic curve occurred when endocardial flow decreased to <50% of mean epicardial flow, which yielded a sensitivity of 87% and specificity of 93%. The area under the curve for QP was 92%, which was superior to semiquantitative methods: contrast enhancement ratio: 78%; upslope index: 82%; and upslope integral: 75% (p = 0.011, p = 0.019, p = 0.004 vs. QP, respectively). Area under the curve for QP was also superior to qualitative methods: Duke algorithm: 70%; and clinical interpretation: 78% (p < 0.001 and p < 0.001 vs. QP, respectively).

CONCLUSIONS

Fully quantitative stress perfusion CMR has high diagnostic accuracy for detecting obstructive coronary artery disease. QP outperforms semiquantitative measures of perfusion and qualitative methods that incorporate a combination of cine, perfusion, and late gadolinium enhancement imaging. These findings suggest a potential clinical role for quantitative stress perfusion CMR.

Study of the development of the mouse thoracic aorta three-dimensional macromolecular structure using two-photon microscopy

Using the intrinsic optical properties of collagen and elastin, two-photon microscopy was applied to evaluate the three-dimensional (3D) macromolecular structural development of the mouse thoracic aorta from birth to 60 days old. Baseline development was established in the Scavenger Receptor Class B Type I-Deficient, Hypomorphic Apolipoprotein ER61 (SR-BI KO/ApoeR61(h/h)) mouse in preparation for modeling atherosclerosis. Precise dissection enabled direct observation of the artery wall in situ. En-face, optical sectioning of the aorta provided a novel assessment of the macromolecular structural development. During aortic development, the undulating lamellar elastin layers compressed consistent with the increases in mean aortic pressure with age. In parallel, a net increase in overall wall thickness (p<0.05, in day 60 compared with day 1 mice) occurred with age whereas the ratio of the tunicas adventitia and media to full aortic thickness remained nearly constant across age groups (~1:2.6, respectively). Histochemical analyses by brightfield microscopy and ultrastructure validated structural proteins and lipid deposition findings derived from two-photon microscopy. Development was associated with decreased decorin but not biglycan proteoglycan expression. This non-destructive 3D in situ approach revealed the aortic wall microstructure development. Coupling this approach with the intrinsic optical properties of the macromolecules may provide unique vascular wall 3D structure in many pathological conditions, including aortic atherosclerosis, dissections and aneurysms.

Rapidly growing mycobacteria in Singapore, 2006-2011

Nontuberculous mycobacteria infection is a growing global concern, but data from Asia are limited. This study aimed to describe the distribution and antibiotic susceptibility profiles of rapidly growing mycobacterium (RGM) isolates in Singapore. Clinical RGM isolates with antibiotic susceptibility tests performed between 2006 and 2011 were identified using microbiology laboratory databases and minimum inhibitory concentrations of amikacin, cefoxitin, clarithromycin, ciprofloxacin, doxycycline, imipenem, linezolid, moxifloxacin, sulfamethoxazole or trimethoprim-sulfamethoxazole, tigecycline and tobramycin were recorded. Regression analysis was performed to detect changes in antibiotic susceptibility patterns over time. A total of 427 isolates were included. Of these, 277 (65%) were from respiratory specimens, 42 (10%) were related to skin and soft tissue infections and 36 (8%) were recovered from blood specimens. The two most common species identified were Mycobacterium abscessus (73%) and Mycobacterium fortuitum group (22%), with amikacin and clarithromycin being most active against the former, and quinolones and trimethoprim-sulfamethoxazole against the latter. Decreases in susceptibility of M. abscessus to linezolid by 8.8% per year (p 0.001), M. fortuitum group to imipenem by 9.5% per year (p 0.023) and clarithromycin by 4.7% per year (p 0.033) were observed. M. abscessus in respiratory specimens is the most common RGM identified in Singapore. Antibiotic options for treatment of RGM infections are increasingly limited.

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 (β=-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.