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

MRI of cardiac involvement in COVID-19

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to a diverse pattern of myocardial injuries, including myocarditis, which is linked to adverse outcomes in patients. Research indicates that myocardial injury is associated with higher mortality in hospitalized severe COVID-19 patients (75.8% vs 9.7%). Cardiovascular Magnetic Resonance (CMR) has emerged as a crucial tool in diagnosing both ischaemic and non-ischaemic myocardial injuries, providing detailed insights into the impact of COVID-19 on myocardial tissue and function. This review synthesizes existing studies on the histopathological findings and CMR imaging patterns of myocardial injuries in COVID-19 patients. CMR imaging has revealed a complex pattern of cardiac damage in these patients, including myocardial inflammation, oedema, fibrosis, and ischaemic injury, due to coronary microthrombi. This review also highlights the role of LLC criteria in diagnosis of COVID-related myocarditis and the importance of CMR in detecting cardiac complications of COVID-19 in specific groups, such as children, manifesting multisystem inflammatory syndrome in children (MIS-C) and athletes, as well as myocardial injuries post-COVID-19 infection or following COVID-19 vaccination. By summarizing existing studies on CMR in COVID-19 patients and highlighting ongoing research, this review contributes to a deeper understanding of the cardiac impacts of COVID-19. It emphasizes the effectiveness of CMR in assessing a broad spectrum of myocardial injuries, thereby enhancing the management and prognosis of patients with COVID-19 related cardiac complications.

High-resolution free-breathing automated quantitative myocardial perfusion by cardiovascular magnetic resonance for the detection of functionally significant coronary artery disease

AIMS

Current assessment of myocardial ischaemia from stress perfusion cardiovascular magnetic resonance (SP-CMR) largely relies on visual interpretation. This study investigated the use of high-resolution free-breathing SP-CMR with automated quantitative mapping in the diagnosis of coronary artery disease (CAD). Diagnostic performance was evaluated against invasive coronary angiography (ICA) with fractional flow reserve (FFR) measurement.

METHODS AND RESULTS

Seven hundred and three patients were recruited for SP-CMR using the research sequence at 3 Tesla. Of those receiving ICA within 6 months, 80 patients had either FFR measurement or identification of a chronic total occlusion (CTO) with inducible perfusion defects seen on SP-CMR. Myocardial blood flow (MBF) maps were automatically generated in-line on the scanner following image acquisition at hyperaemic stress and rest, allowing myocardial perfusion reserve (MPR) calculation. Seventy-five coronary vessels assessed by FFR and 28 vessels with CTO were evaluated at both segmental and coronary territory level. Coronary territory stress MBF and MPR were reduced in FFR-positive (≤0.80) regions [median stress MBF: 1.74 (0.90-2.17) mL/min/g; MPR: 1.67 (1.10-1.89)] compared with FFR-negative regions [stress MBF: 2.50 (2.15-2.95) mL/min/g; MPR 2.35 (2.06-2.54) P < 0.001 for both]. Stress MBF ≤ 1.94 mL/min/g and MPR ≤ 1.97 accurately detected FFR-positive CAD on a per-vessel basis (area under the curve: 0.85 and 0.96, respectively; P < 0.001 for both).

CONCLUSION

A novel scanner-integrated high-resolution free-breathing SP-CMR sequence with automated in-line perfusion mapping is presented which accurately detects functionally significant CAD.

Prognostic Value of Stress Perfusion Cardiac MRI in Cardiovascular Disease: A Systematic Review and Meta-Analysis of the Effects of the Scanner, Stress Agent, and Analysis Technique

Purpose To perform a systematic review and meta-analysis to assess the prognostic value of stress perfusion cardiac MRI in predicting cardiovascular outcomes. Materials and Methods A systematic literature search from the inception of PubMed, Embase, Web of Science, and China National Knowledge Infrastructure until January 2023 was performed for articles that reported the prognosis of stress perfusion cardiac MRI in predicting cardiovascular outcomes. The quality of included studies was assessed using the Quality in Prognosis Studies tool. Reported hazard ratios (HRs) of univariable regression analyses with 95% CIs were pooled. Comparisons were performed across different analysis techniques (qualitative, semiquantitative, and fully quantitative), magnetic field strengths (1.5 T vs 3 T), and stress agents (dobutamine, adenosine, and dipyridamole). Results Thirty-eight studies with 58 774 patients with a mean follow-up time of 53 months were included. There were 1.9 all-cause deaths and 3.5 major adverse cardiovascular events (MACE) per 100 patient-years. Stress-inducible ischemia was associated with a higher risk of all-cause mortality (HR: 2.55 [95% CI: 1.89, 3.43]) and MACE (HR: 3.90 [95% CI: 2.69, 5.66]). For MACE, pooled HRs of qualitative, semiquantitative, and fully quantitative methods were 4.56 (95% CI: 2.88, 7.22), 3.22 (95% CI: 1.60, 6.48), and 1.78 (95% CI: 1.39, 2.28), respectively. For all-cause mortality, there was no evidence of a difference between qualitative and fully quantitative methods (P = .79). Abnormal stress perfusion cardiac MRI findings remained prognostic when subgrouped based on underlying disease, stress agent, and field strength, with HRs of 3.54, 2.20, and 3.38, respectively, for all-cause mortality and 3.98, 3.56, and 4.21, respectively, for MACE. There was no evidence of subgroup differences in prognosis between field strengths or stress agents. There was significant heterogeneity in effect size for MACE outcomes in the subgroups assessing qualitative versus quantitative stress perfusion analysis, underlying disease, and field strength. Conclusion Stress perfusion cardiac MRI is valuable for predicting cardiovascular outcomes, regardless of the analysis method, stress agent, or magnetic field strength used. Keywords: MR-Perfusion, MRI, Cardiac, Meta-Analysis, Stress Perfusion, Cardiac MR, Cardiovascular Disease, Prognosis, Quantitative © RSNA, 2024 Supplemental material is available for this article.

Clinical implementation of a fully automated quantitative perfusion cardiovascular magnetic resonance imaging workflow with a simplified dual-bolus contrast administration scheme

This study clinically implemented a ready-to-use quantitative perfusion (QP) cardiovascular magnetic resonance (QP CMR) workflow, encompassing a simplified dual-bolus gadolinium-based contrast agent (GBCA) administration scheme and fully automated QP image post-processing. Twenty-five patients with suspected obstructive coronary artery disease (CAD) underwent both adenosine stress perfusion CMR and an invasive coronary angiography or coronary computed tomography angiography. The dual-bolus protocol consisted of a pre-bolus (0.0075 mmol/kg GBCA at 0.5 mmol/ml concentration + 20 ml saline) and a main bolus (0.075 mmol/kg GBCA at 0.5 mmol/ml concentration + 20 ml saline) at an infusion rate of 3 ml/s. The arterial input function curves showed excellent quality. Stress MBF ≤ 1.84 ml/g/min accurately detected obstructive CAD (area under the curve 0.79; 95% Confidence Interval: 0.66 to 0.89). Combined visual assessment of color pixel QP maps and conventional perfusion images yielded a diagnostic accuracy of 84%, sensitivity of 70% and specificity of 93%. The proposed easy-to-use dual-bolus QP CMR workflow provides good image quality and holds promise for high accuracy in diagnosis of obstructive CAD. Implementation of this approach has the potential to serve as an alternative to current methods thus increasing the accessibility to offer high-quality QP CMR imaging by a wide range of CMR laboratories.

A history of cardiovascular magnetic resonance imaging in clinical practice and population science

Cardiovascular magnetic resonance (CMR) imaging has become an invaluable clinical and research tool. Starting from the discovery of nuclear magnetic resonance, this article provides a brief overview of the key developments that have led to CMR as it is today, and how it became the modality of choice for large-scale population studies.

Cardiometabolic biomarker patterns associated with cardiac MRI defined fibrosis and microvascular dysfunction in patients with heart failure with preserved ejection fraction

Introduction

Heart failure with preserved ejection fraction (HFpEF) is a complex disease process influenced by metabolic disorders, systemic inflammation, myocardial fibrosis, and microvascular dysfunction. The goal of our study is to identify potential relationships between plasma biomarkers and cardiac magnetic resonance (CMR) imaging markers in patients with HFpEF.

Methods

Nineteen subjects with HFpEF and 15 age-matched healthy controls were enrolled and underwent multiparametric CMR and plasma biomarker analysis using the Olink® Cardiometabolic Panel (Olink Proteomics, Uppsala, Sweden). Partial least squares discriminant analysis (PLS-DA) was used to characterize CMR and biomarker variables that differentiate the subject groups into two principal components. Orthogonal projection to latent structures by partial least squares (OPLS) analysis was used to identify biomarker patterns that correlate with myocardial perfusion reserve (MPR) and extracellular volume (ECV) mapping.

Results

A PLS-DA could differentiate between HFpEF and normal controls with two significant components explaining 79% (Q2 = 0.47) of the differences. For OPLS, there were 7 biomarkers that significantly correlated with ECV (R2 = 0.85, Q = 0.53) and 6 biomarkers that significantly correlated with MPR (R2 = 0.92, Q2 = 0.32). Only 1 biomarker significantly correlated with both ECV and MPR.

Discussion

Patients with HFpEF have unique imaging and biomarker patterns that suggest mechanisms associated with metabolic disease, inflammation, fibrosis and microvascular dysfunction.

Myocardial Blood Flow Quantified Using Stress Cardiac Magnetic Resonance After Mild COVID-19 Infection

BACKGROUND

Severe COVID-19 infection is known to alter myocardial perfusion through its effects on the endothelium and microvasculature. However, the majority of patients with COVID-19 infection experience only mild symptoms, and it is unknown if their myocardial perfusion is altered after infection.

OBJECTIVES

The authors aimed to determine if there are abnormalities in myocardial blood flow (MBF), as measured by stress cardiac magnetic resonance (CMR), in individuals after a mild COVID-19 infection.

METHODS

We conducted a prospective, comparative study of individuals who had a prior mild COVID-19 infection (n = 30) and matched controls (n = 26) using stress CMR. Stress and rest myocardial blood flow (sMBF, rMBF) were quantified using the dual sequence technique. Myocardial perfusion reserve was calculated as sMBF/rMBF. Unpaired t-tests were used to test differences between the groups.

RESULTS

The median time interval between COVID-19 infection and CMR was 5.6 (IQR: 4-8) months. No patients with the COVID-19 infection required hospitalization. Symptoms including chest pain, shortness of breath, syncope, and palpitations were more commonly present in the group with prior COVID-19 infection than in the control group (57% vs 7%, P < 0.001). No significant differences in rMBF (1.08 ± 0.27 mL/g/min vs 0.97 ± 0.29 mL/g/min, P = 0.16), sMBF (3.08 ± 0.79 mL/g/min vs 3.06 ± 0.89 mL/g/min, P = 0.91), or myocardial perfusion reserve (2.95 ± 0.90 vs 3.39 ± 1.25, P = 0.13) were observed between the groups.

CONCLUSIONS

This study suggests that there are no significant abnormalities in rest or stress myocardial perfusion, and thus microvascular function, in individuals after mild COVID-19 infection.

Comparison of machine learning-based CT fractional flow reserve with cardiac MR perfusion mapping for ischemia diagnosis in stable coronary artery disease

OBJECTIVES

To compare the diagnostic performance of machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.

METHODS

Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference.

RESULTS

The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01).

CONCLUSION

ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis.

CLINICAL RELEVANCE STATEMENT

ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other.

KEY POINTS

• Both machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis. • Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis. • ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.

Coronary Microvascular Dysfunction and Diffuse Myocardial Fibrosis in Patients With Type 2 Diabetes Using Quantitative Perfusion MRI

BACKGROUND

Imaging techniques that quantitatively and automatically measure changes in the myocardial microcirculation in patients with diabetes are lacking.

PURPOSE

To detect diabetic myocardial microvascular complications using a novel automatic quantitative perfusion MRI technique, and to explore the relationship between myocardial microcirculation dysfunction and fibrosis.

STUDY TYPE

Prospective.

SUBJECTS

101 patients with type 2 diabetes mellitus (T2DM) (53 without and 48 with complications), 20 healthy volunteers.

FIELD STRENGTH/SEQUENCE

3.0T; modified Look-Locker inversion-recovery sequence; saturation recovery sequence and dual-bolus technique; segmented fast low-angle shot sequence.

ASSESSMENT

All participants underwent MRI to determine the rest myocardial blood flow (MBF), stress MBF, myocardial perfusion reserve (MPR), and extracellular volume (ECV), which represents the extent of myocardial fibrosis.

STATISTICAL TESTS

Kolmogorov-Smirnov test, Shapiro-Wilk test, Kruskal-Wallis H test, Mann-Whitney U test, chi-square test, Spearman correlation coefficient, multivariable linear regression analysis. P < 0.05 was considered statistically significant.

RESULTS

The rest MBF was not significantly different between the T2DM without complications group (1.1, IQR: 0.9-1.3) and the control group (1.1, 1.0-1.3) (P = 1.000), but it was significantly lower in the T2DM with complications group (0.8, 0.6-1.0) than in both other groups. The stress MBF and MPR were significantly lower in the T2DM without complications group (1.9, 1.5-2.3, and 1.7, 1.4-2.1, respectively) than in the control group (3.0, 2.6-3.5, and 2.7, 2.4-3.1, respectively), and were also significantly lower in the T2DM with complications group (1.1, 0.9-1.4, and 1.4, 1.2-1.8, respectively) than in the T2DM without complications group. A decrease in MBF and MPR were significantly associated with an increase in the ECV.

DATA CONCLUSION

Quantitative perfusion MRI can evaluate myocardial microcirculation dysfunction. In T2DM, there was a significant decrease in both MBF and MPR compared to healthy controls, with the decrease being significantly different between T2DM with and without complications groups. The decrease of MBF was significantly associated with the development of myocardial fibrosis, as determined by ECV.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 3.

Perfusion Imaging for the Heart

The use of myocardial perfusion imaging during a stress cardiac magnetic resonance (CMR) examination for the evaluation of coronary artery disease is now recommended by both US and European guidelines. Several studies have demonstrated high diagnostic accuracy for the detection of hemodynamically significant coronary artery disease. Stress perfusion CMR has been shown to be a noninvasive and cost-effective alternative to guide coronary revascularization.

High-resolution quantification of stress perfusion defects by cardiac magnetic resonance

Aims

Quantitative stress perfusion cardiac magnetic resonance (CMR) is becoming more widely available, but it is still unclear how to integrate this information into clinical decision-making. Typically, pixel-wise perfusion maps are generated, but diagnostic and prognostic studies have summarized perfusion as just one value per patient or in 16 myocardial segments. In this study, the reporting of quantitative perfusion maps is extended from the standard 16 segments to a high-resolution bullseye. Cut-off thresholds are established for the high-resolution bullseye, and the identified perfusion defects are compared with visual assessment.

Methods and results

Thirty-four patients with known or suspected coronary artery disease were retrospectively analysed. Visual perfusion defects were contoured on the CMR images and pixel-wise quantitative perfusion maps were generated. Cut-off values were established on the high-resolution bullseye consisting of 1800 points and compared with the per-segment, per-coronary, and per-patient resolution thresholds. Quantitative stress perfusion was significantly lower in visually abnormal pixels, 1.11 (0.75-1.57) vs. 2.35 (1.82-2.9) mL/min/g (Mann-Whitney U test P < 0.001), with an optimal cut-off of 1.72 mL/min/g. This was lower than the segment-wise optimal threshold of 1.92 mL/min/g. The Bland-Altman analysis showed that visual assessment underestimated large perfusion defects compared with the quantification with good agreement for smaller defect burdens. A Dice overlap of 0.68 (0.57-0.78) was found.

Conclusion

This study introduces a high-resolution bullseye consisting of 1800 points, rather than 16, per patient for reporting quantitative stress perfusion, which may improve sensitivity. Using this representation, the threshold required to identify areas of reduced perfusion is lower than for segmental analysis.

The diagnostic performance of quantitative flow ratio and perfusion imaging in patients with prior coronary artery disease

AIMS

In chronic coronary syndrome (CCS) patients with documented coronary artery disease (CAD), ischaemia detection by myocardial perfusion imaging (MPI) and an invasive approach are viable diagnostic strategies. We compared the diagnostic performance of quantitative flow ratio (QFR) with single-photon emission computed tomography (SPECT), positron emission tomography (PET), and cardiac magnetic resonance imaging (CMR) in patients with prior CAD [previous percutaneous coronary intervention (PCI) and/or myocardial infarction (MI)].

METHODS AND RESULTS

This PACIFIC-2 sub-study evaluated 189 CCS patients with prior CAD for inclusion. Patients underwent SPECT, PET, and CMR followed by invasive coronary angiography with fractional flow reserve (FFR) measurements of all major coronary arteries (N = 567), except for vessels with a sub-total or chronic total occlusion. Quantitative flow ratio computation was attempted in 488 (86%) vessels with measured FFR available (FFR ≤0.80 defined haemodynamically significant CAD). Quantitative flow ratio analysis was successful in 334 (68%) vessels among 166 patients and demonstrated a higher accuracy (84%) and sensitivity (72%) compared with SPECT (66%, P < 0.001 and 46%, P = 0.001), PET (65%, P < 0.001 and 58%, P = 0.032), and CMR (72%, P < 0.001 and 33%, P < 0.001). The specificity of QFR (87%) was similar to that of CMR (83%, P = 0.123) but higher than that of SPECT (71%, P < 0.001) and PET (67%, P < 0.001). Lastly, QFR exhibited a higher area under the receiver operating characteristic curve (0.89) than SPECT (0.57, P < 0.001), PET (0.66, P < 0.001), and CMR (0.60, P < 0.001).

CONCLUSION

QFR correlated better with FFR in patients with prior CAD than MPI, as reflected in the higher diagnostic performance measures for detecting FFR-defined, vessel-specific, significant CAD.

Reduced stress perfusion in myocardial infarction with nonobstructive coronary arteries

Myocardial infarction with nonobstructive coronary arteries (MINOCA) has several possible underlying causes, including coronary microvascular dysfunction (CMD). Early cardiovascular magnetic resonance imaging (CMR) is recommended, however cannot provide a diagnosis in 25% of cases. Quantitative stress CMR perfusion mapping can identify CMD, however it is unknown if CMD is present during long-term follow-up of MINOCA patients. Therefore, this study aimed to evaluate presence of CMD during long-term follow-up in MINOCA patients with an initial normal CMR scan. MINOCA patients from the second Stockholm myocardial infarction with normal coronaries study (SMINC-2), with a normal CMR scan at median 3 days after hospitalization were investigated with comprehensive CMR including stress perfusion mapping a median of 5 years after the index event, together with age- and sex-matched volunteers without symptomatic ischemic heart disease. Cardiovascular risk factors, medication and symptoms of myocardial ischemia measured by the Seattle Angina Questionnaire 7 (SAQ-7), were registered. In total, 15 patients with MINOCA and an initial normal CMR scan (59 ± 7 years old, 60% female), and 15 age- and sex-matched volunteers, underwent CMR. Patients with MINOCA and an initial normal CMR scan had lower global stress perfusion compared to volunteers (2.83 ± 1.8 vs 3.53 ± 0.7 ml/min/g, p = 0.02). There were no differences in other CMR parameters, hemodynamic parameters, or cardiovascular risk factors, except for more frequent use of statins in the MINOCA patient group compared to volunteers. In conclusion, global stress perfusion is lower in MINOCA patients during follow-up, compared to age- and sex-matched volunteers, suggesting that CMD may be a possible pathophysiological mechanism in MINOCA.Clinical Trial Registration: Clinicaltrials.gov identifier NCT02318498. Registered 2014-12-17.

Automatic calculation of myocardial perfusion reserve using deep learning with uncertainty quantification

Background

Myocardial perfusion reserve index (MPRI) in magnetic resonance imaging (MRI) is an important indicator of ischemia, and its measurement typically involves manual procedures. The purposes of this study were to develop a fully automatic method for estimating the MPRI and to evaluate its performance.

Methods

The method consisted of segmenting the myocardium in dynamic contrast-enhanced (DCE) myocardial perfusion MRI data using Monte Carlo dropout U-Net, dividing the myocardium into segments based on landmark localization with machine learning, and estimating the MPRI after the calculation of the left ventricular and myocardial contrast upslopes. The proposed method was compared with a reference method, which involved manual adjustments of the myocardial contours and upslope ranges.

Results

In test subjects, MPRIs measured by the proposed technique correlated with those by the manual reference in segmental assessment [intraclass correlation coefficient (ICC) =0.75, 95% CI: 0.70-0.79, P<0.001]. The automatic and reference MPRI values showed a mean difference of -0.02 and 95% limits of agreement of (-0.86, 0.82).

Conclusions

The proposed automatic method is based on deep learning segmentation and machine learning landmark detection for MPRI measurements in DCE perfusion MRI. It holds the potential to efficiently and quantitatively assess myocardial ischemia without any user's interaction.

The coronary microvascular angina cardiovascular magnetic resonance imaging trial: Rationale and design

BACKGROUND

Coronary microvascular dysfunction may cause myocardial ischemia with no obstructive coronary artery disease (INOCA). If functional testing is not performed INOCA may pass undetected. Stress perfusion cardiovascular MRI (CMR) quantifies myocardial blood flow (MBF) but the clinical utility of stress CMR in the management of patients with suspected angina with no obstructive coronary arteries (ANOCA) is uncertain.

OBJECTIVES

First, to undertake a diagnostic study using stress CMR in patients with ANOCA following invasive coronary angiography and, second, in a nested, double-blind, randomized, controlled trial to assess the effect of disclosure on the final diagnosis and health status in the longer term.

DESIGN

All-comers referred for clinically indicated coronary angiography for the investigation of suspected coronary artery disease will be screened in 3 regional centers in the United Kingdom. Following invasive coronary angiography, patients with ANOCA who provide informed consent will undergo noninvasive endotyping using stress CMR within 3 months of the angiogram.

DIAGNOSTIC STUDY

Stress perfusion CMR imaging to assess the prevalence of coronary microvascular dysfunction and clinically significant incidental findings in patients with ANOCA. The primary outcome is the between-group difference in the reclassification rate of the initial diagnosis based on invasive angiography versus the final diagnosis after CMR imaging.

RANDOMIZED, CONTROLLED TRIAL

Participants will be randomized to inclusion (intervention group) or exclusion (control group) of myocardial blood flow to inform the final diagnosis. The primary outcome of the clinical trial is the mean within-subject change in the Seattle Angina Questionnaire summary score (SAQSS) at 6 months. Secondary outcome assessments include the EUROQOL EQ-5D-5L questionnaire, the Brief Illness Perception Questionnaire (Brief-IPQ), the Treatment Satisfaction Questionnaire (TSQM-9), the Patient Health Questionnaire-4 (PHQ-4), the Duke Activity Status Index (DASI), the International Physical Activity Questionnaire- Short Form (IPAQ-SF), the Montreal Cognitive Assessment (MOCA) and the 8-item Productivity Cost Questionnaire (iPCQ). Health and economic outcomes will be assessed using electronic healthcare records.

VALUE

To clarify if routine stress perfusion CMR imaging reclassifies the final diagnosis in patients with ANOCA and whether this strategy improves symptoms, health-related quality of life and health economic outcomes.

CLINICALTRIALS

GOV: NCT04805814.

Sex differences in diagnostic modalities of coronary artery disease: Evidence from coronary microcirculation

Although atherosclerosis is usually considered a disease of the large arteries, risk factors for atherosclerosis also trigger structural and functional abnormalities at a microvascular level. In cardiac disease, microvascular dysfunction is especially relevant in women, among whom the manifestation of ischemic disease due to impaired coronary microcirculation is more common than in men. This sex-specific clinical phenotype has important clinical implications and, given the higher pre-test probability of coronary microvascular dysfunction in females, different diagnostic modalities should be used in women compared to men. In this review, we summarize invasive and non-invasive diagnostic modalities to assess coronary microvascular function, ranging from catheter-based evaluation of endothelial function to Doppler echocardiography and positron emission tomography. Moreover, we discuss different clinical settings in which microvascular disease plays an important role, underlining the importance of choosing the right diagnostic modality depending on the sex of the patients.

What Matters in Radiological Image Segmentation? Effect of Segmentation Errors on the Diagnostic Related Features

Segmentation is a crucial step in extracting the medical image features for clinical diagnosis. Though multiple metrics have been proposed to evaluate the segmentation performance, there is no clear study on how or to what extent the segmentation errors will affect the diagnostic related features used in clinical practice. Therefore, we proposed a segmentation robustness plot (SRP) to build the link between segmentation errors and clinical acceptance, where relative area under the curve (R-AUC) was designed to help clinicians to identify the robust diagnostic related image features. In experiments, we first selected representative radiological series from time series (cardiac first-pass perfusion) and spatial series (T2 weighted images on brain tumors) of magnetic resonance images, respectively. Then, dice similarity coefficient (DSC) and Hausdorff distance (HD), as the widely used evaluation metrics, were used to systematically control the degree of the segmentation errors. Finally, the differences between diagnostic related image features extracted from the ground truth and the derived segmentation were analyzed, using the statistical method large sample size T-test to calculate the corresponding p values. The results are denoted in the SRP, where the x-axis indicates the segmentation performance using the aforementioned evaluation metric, and the y-axis shows the severity of the corresponding feature changes, which are expressed in either the p values for a single case or the proportion of patients without significant change. The experimental results in SRP show that when DSC is above 0.95 and HD is below 3 mm, the segmentation errors will not change the features significantly in most cases. However, when segmentation gets worse, additional metrics are required for further analysis. In this way, the proposed SRP indicates the impact of the segmentation errors on the severity of the corresponding feature changes. By using SRP, one could easily define the acceptable segmentation errors in a challenge. Additionally, the R-AUC calculated from SRP provides an objective reference to help the selection of reliable features in image analysis.

Fully automated pixel-wise quantitative CMR-myocardial perfusion with CMR-coronary angiography to detect hemodynamically significant coronary artery disease

OBJECTIVES

We applied a fully automated pixel-wise post-processing framework to evaluate fully quantitative cardiovascular magnetic resonance myocardial perfusion imaging (CMR-MPI). In addition, we aimed to evaluate the additive value of coronary magnetic resonance angiography (CMRA) to the diagnostic performance of fully automated pixel-wise quantitative CMR-MPI for detecting hemodynamically significant coronary artery disease (CAD).

METHODS

A total of 109 patients with suspected CAD were prospectively enrolled and underwent stress and rest CMR-MPI, CMRA, invasive coronary angiography (ICA), and fractional flow reserve (FFR). CMRA was acquired between stress and rest CMR-MPI acquisition, without any additional contrast agent. Finally, CMR-MPI quantification was analyzed by a fully automated pixel-wise post-processing framework.

RESULTS

Of the 109 patients, 42 patients had hemodynamically significant CAD (FFR ≤ 0.80 or luminal stenosis ≥ 90% on ICA) and 67 patients had hemodynamically non-significant CAD (FFR ˃ 0.80 or luminal stenosis < 30% on ICA) were enrolled. On the per-territory analysis, patients with hemodynamically significant CAD had higher myocardial blood flow (MBF) at rest, lower MBF under stress, and lower myocardial perfusion reserve (MPR) than patients with hemodynamically non-significant CAD (p < 0.001). The area under the receiver operating characteristic curve of MPR (0.93) was significantly larger than those of stress and rest MBF, visual assessment of CMR-MPI, and CMRA (p < 0.05), but similar to that of the integration of CMR-MPI with CMRA (0.90).

CONCLUSIONS

Fully automated pixel-wise quantitative CMR-MPI can accurately detect hemodynamically significant CAD, but the integration of CMRA obtained between stress and rest CMR-MPI acquisition did not provide significantly additive value.

KEY POINTS

• Full quantification of stress and rest cardiovascular magnetic resonance myocardial perfusion imaging can be postprocessed fully automatically, generating pixel-wise myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) maps. • Fully quantitative MPR provided higher diagnostic performance for detecting hemodynamically significant coronary artery disease, compared with stress and rest MBF, qualitative assessment, and coronary magnetic resonance angiography (CMRA). • The integration of CMRA and MPR did not significantly improve the diagnostic performance of MPR alone.

Focal and diffuse myocardial fibrosis both contribute to regional hypoperfusion assessed by post-processing quantitative-perfusion MRI techniques

Introduction

Indications for stress-cardiovascular magnetic resonance imaging (CMR) to assess myocardial ischemia and viability are growing. First pass perfusion and late gadolinium enhancement (LGE) have limited value in balanced ischemia and diffuse fibrosis. Quantitative perfusion (QP) to assess absolute pixelwise myocardial blood flow (MBF) and extracellular volume (ECV) as a measure of diffuse fibrosis can overcome these limitations. We investigated the use of post-processing techniques for quantifying both pixelwise MBF and diffuse fibrosis in patients with clinically indicated CMR stress exams. We then assessed if focal and diffuse myocardial fibrosis and other features quantified during the CMR exam explain individual MBF findings.

Methods

This prospective observational study enrolled 125 patients undergoing a clinically indicated stress-CMR scan. In addition to the clinical report, MBF during regadenoson-stress was quantified using a post-processing QP method and T1 maps were used to calculate ECV. Factors that were associated with poor MBF were investigated.

Results

Of the 109 patients included (66 ± 11 years, 32% female), global and regional perfusion was quantified by QP analysis in both the presence and absence of visual first pass perfusion deficits. Similarly, ECV analysis identified diffuse fibrosis in myocardium beyond segments with LGE. Multivariable analysis showed both LGE (β = -0.191, p = 0.001) and ECV (β = -0.011, p < 0.001) were independent predictors of reduced MBF. In patients without clinically defined first pass perfusion deficits, the microvascular risk-factors of age and wall thickness further contributed to poor MBF (p < 0.001).

Discussion

Quantitative analysis of MBF and diffuse fibrosis detected regional tissue abnormalities not identified by traditional visual assessment. Multi-parametric quantitative analysis may refine the work-up of the etiology of myocardial ischemia in patients referred for clinical CMR stress testing in the future and provide a deeper insight into ischemic heart disease.

Comparison of CT-derived Plaque Characteristic Index With CMR Perfusion for Ischemia Diagnosis in Stable CAD

BACKGROUND

Coronary computed tomography angiography (CCTA) and cardiac magnetic resonance (CMR) have been used to diagnose lesion-specific ischemia in patients with coronary artery disease. The aim of this study was to investigate the diagnostic performance of CCTA-derived plaque characteristic index compared with myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) derived from CMR perfusion in the assessment of lesion-specific ischemia.

METHODS

Between October 2020 and March 2022, consecutive patients with suspected or known coronary artery disease, who were clinically referred for invasive coronary angiography were prospectively enrolled. All participants sequentially underwent CCTA and CMR and invasive fractional flow reserve within 2 weeks. The diagnostic performance of CCTA-derived plaque characteristics, CMR perfusion-derived stress MBF, and MPR were compared. Lesions with fractional flow reserve ≤0.80 were considered to be hemodynamically significant stenosis.

RESULTS

Nighty-two patients with 141 vessels were included in this study. Plaque length, minimum luminal area, plaque area, percent area stenosis, total atheroma volume, vessel volume, lipid-rich volume, spotty calcium, napkin-ring signs, stress MBF, and MPR in flow-limiting stenosis group were significantly different from nonflow-limiting group. The overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of lesion-specific ischemia diagnosis were 61.0%, 55.3%, 63.1%, 35.6%, and 79.3% for stress MBF, and 89.4%, 89.5%, 89.3%, 75.6%, 95.8% for MPR; meanwhile, 82.3%, 79.0%, 84.5%, 65.2%, and 91.6% for CCTA-derived plaque characteristic index.

CONCLUSIONS

In our prospective study, CCTA-derived plaque characteristics and MPR derived from CMR performed well in diagnosing lesion-specific myocardial ischemia and were significantly better than stress MBF in stable coronary artery disease.

Imaging Early Life Cardiovascular Phenotype

The growing epidemics of obesity, hypertension, and diabetes, in addition to worsening environmental factors such as air pollution, water scarcity, and climate change, have fueled the continuously increasing prevalence of cardiovascular diseases (CVDs). This has caused a markedly increasing burden of CVDs that includes mortality and morbidity worldwide. Identification of subclinical CVD before overt symptoms can lead to earlier deployment of preventative pharmacological and nonpharmacologic strategies. In this regard, noninvasive imaging techniques play a significant role in identifying early CVD phenotypes. An armamentarium of imaging techniques including vascular ultrasound, echocardiography, magnetic resonance imaging, computed tomography, noninvasive computed tomography angiography, positron emission tomography, and nuclear imaging, with intrinsic strengths and limitations can be utilized to delineate incipient CVD for both clinical and research purposes. In this article, we review the various imaging modalities used for the evaluation, characterization, and quantification of early subclinical cardiovascular diseases.

Imaging of pediatric cardiac tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee White Paper

Cardiac tumors in children are rare and the majority are benign. The most common cardiac tumor in children is rhabdomyoma, usually associated with tuberous sclerosis complex. Other benign cardiac masses include fibromas, myxomas, hemangiomas, and teratomas. Primary malignant cardiac tumors are exceedingly rare, with the most common pathology being soft tissue sarcomas. This paper provides consensus-based imaging recommendations for the evaluation of patients with cardiac tumors at diagnosis and follow-up, including during and after therapy.

Quantitative myocardial perfusion with a hybrid 2D simultaneous multi-slice sequence

PURPOSE

To evaluate a novel 2D simultaneous multi-slice (SMS) myocardial perfusion acquisition and compare directly to a published quantitative 3D stack-of-stars (SoS) acquisition.

METHODS

A hybrid saturation recovery radial 2D SMS sequence following a single saturation was created for the quantification of myocardial blood flow (MBF). This sequence acquired three slices simultaneously and generated an arterial input function (AIF) using the first 24 rays. Validation was done in a novel way by alternating heartbeats between the hybrid 2D SMS and the 3D SoS acquisitions. Initial studies were done to study the effects of using only every other beat for the 2D SMS in two subjects, and for the 3D SoS in four subjects. The proposed alternating acquisitions were then performed in ten dog studies at rest, four dog studies at adenosine stress, and two human resting studies. Quantitative MBF analysis was performed for 2D SMS and 3D SoS separately, using a compartment model.

RESULTS

Acquiring every-other-beat data resulted in 6 ± 5% ("ideal") and 11 ± 8% ("practical") perfusion changes for both 2D SMS and 3D SoS methods. For alternating acquisitions, 2D SMS and 3D SoS quantitative perfusion values were comparable for both the twelve rest studies (2D SMS: 0.69 ± 0.16 vs 3D: 0.69 ± 0.15 ml/g/min, p = 0.55) and the four stress studies (2D SMS: 1.28 ± 0.22 vs 3D: 1.30 ± 0.24 ml/g/min, p = 0.61).

CONCLUSION

Every-other-beat acquisition changed estimated perfusion values relatively little for both sequences. The quantitative hybrid radial 2D SMS myocardial first-pass perfusion imaging sequence gave results similar to 3D perfusion when compared directly with an alternating beat acquisition.

Myocardial Perfusion Imaging by Cardiovascular Magnetic Resonance: Research Progress and Current Implementation

Cardiovascular diseases pose a significant health and economic burden worldwide, with coronary artery disease still recognized as a major problem. It is closely associated with hypertension, diabetes, obesity, smoking, lack of exercise, poor diet, and excessive alcohol consumption, which may lead to macro- and microvascular abnormalities in the heart. Coronary artery stenosis reduces the local supply of oxygen and nutrients to the myocardium and results in reduced levels of myocardial perfusion, which can lead to more severe conditions and irreversible damage to myocardial tissues. Therefore, accurate evaluation of myocardial perfusion abnormalities in patients with these risk factors is critical. As technology advances, magnetic resonance myocardial perfusion imaging has become more accurate at evaluating the myocardial microcirculation and has shown a powerful ability to detect myocardial ischemia. The purpose of this review is to summarize the principle, research progress of acquisition and analysis, and clinical implementation of cardiovascular magnetic resonance (CMR) myocardial perfusion imaging.

Strengths and weaknesses of alternative noninvasive imaging approaches for microvascular ischemia

Structural and functional abnormalities of coronary microvasculature are highly prevalent in several clinical settings and often associated with worse clinical outcomes. Therefore, there is a growing interest in the detection and treatment of this, often overlooked, disease. Coronary angiography allows the assessment of the Coronary flow reserve (CFR) and the index of microcirculatory resistance (IMR). However, the measurement of these parameters is not always feasible because of limited technical availability and the need for a cardiac catheterization with a small but real risk of potential complications. Recent advances in non-invasive imaging techniques allow the assessment of coronary microvascular function with good accuracy and reproducibility. The objective of this review is to discuss the strengths and weaknesses of alternative non-invasive approaches used in the diagnosis of coronary microvascular dysfunction (CMD), highlighting the most recent advances for each imaging modality.

The Role of Imaging in Preventive Cardiology in Women

PURPOSE OF REVIEW

The prevalence of CVD in women is increasing and is due to the increased prevalence of CV risk factors. Traditional CV risk assessment tools for prevention have failed to accurately determine CVD risk in women. CAC has shown to more precisely determine CV risk and is a better predictor of CV outcomes. Coronary CTA provides an opportunity to determine the presence of CAD and initiate prevention in women presenting with angina. Identifying women with INOCA due to CMD with use of cPET or cMRI with MBFR is vital in managing these patients. This review article outlines the role of imaging in preventive cardiology for women and will include the latest evidence supporting the use of these imaging tests for this purpose.

RECENT FINDINGS

CV mortality is higher in women who have more extensive CAC burden. Women have a greater prevalence of INOCA which is associated with higher MACE. INOCA is due to CMD in most cases which is associated with traditional CVD risk factors. Over half of these women are untreated or undertreated. Recent study showed that stratified medical therapy, tailored to the specific INOCA endotype, is feasible and improves angina in women. Coronary CTA is useful in the setting of women presenting with acute chest pain to identify CAD and initiate preventive therapy. CAC confers greater relative risk for CV mortality in women versus (vs.) men. cMRI or cPET is useful to assess MBFR to diagnose CMD and is another useful imaging tool in women for CV prevention.

Signal intensity informed multi-coil encoding operator for physics-guided deep learning reconstruction of highly accelerated myocardial perfusion CMR

PURPOSE

To develop a physics-guided deep learning (PG-DL) reconstruction strategy based on a signal intensity informed multi-coil (SIIM) encoding operator for highly-accelerated simultaneous multislice (SMS) myocardial perfusion cardiac MRI (CMR).

METHODS

First-pass perfusion CMR acquires highly-accelerated images with dynamically varying signal intensity/SNR following the administration of a gadolinium-based contrast agent. Thus, using PG-DL reconstruction with a conventional multi-coil encoding operator leads to analogous signal intensity variations across different time-frames at the network output, creating difficulties in generalization for varying SNR levels. We propose to use a SIIM encoding operator to capture the signal intensity/SNR variations across time-frames in a reformulated encoding operator. This leads to a more uniform/flat contrast at the output of the PG-DL network, facilitating generalizability across time-frames. PG-DL reconstruction with the proposed SIIM encoding operator is compared to PG-DL with conventional encoding operator, split slice-GRAPPA, locally low-rank (LLR) regularized reconstruction, low-rank plus sparse (L + S) reconstruction, and regularized ROCK-SPIRiT.

RESULTS

Results on highly accelerated free-breathing first pass myocardial perfusion CMR at three-fold SMS and four-fold in-plane acceleration show that the proposed method improves upon the reconstruction methods use for comparison. Substantial noise reduction is achieved compared to split slice-GRAPPA, and aliasing artifacts reduction compared to LLR regularized reconstruction, L + S reconstruction and PG-DL with conventional encoding. Furthermore, a qualitative reader study indicated that proposed method outperformed all methods.

CONCLUSION

PG-DL reconstruction with the proposed SIIM encoding operator improves generalization across different time-frames /SNRs in highly accelerated perfusion CMR.

Cardiac Magnetic Resonance in Hypertensive Heart Disease: Time for a New Chapter

Hypertension is one of the most important cardiovascular risk factors, associated with significant morbidity and mortality. Chronic high blood pressure leads to various structural and functional changes in the myocardium. Different sophisticated imaging methods are developed to properly estimate the severity of the disease and to prevent possible complications. Cardiac magnetic resonance can provide a comprehensive assessment of patients with hypertensive heart disease, including accurate and reproducible measurement of left and right ventricle volumes and function, tissue characterization, and scar quantification. It is important in the proper evaluation of different left ventricle hypertrophy patterns to estimate the presence and severity of myocardial fibrosis, as well as to give more information about the benefits of different therapeutic modalities. Hypertensive heart disease often manifests as a subclinical condition, giving exceptional value to cardiac magnetic resonance as an imaging modality capable to detect subtle changes. In this article, we are giving a comprehensive review of all the possibilities of cardiac magnetic resonance in patients with hypertensive heart disease.

Cardiovascular Magnetic Resonance Parametric Mapping Techniques for the Assessment of Chronic Coronary Syndromes

The term chronic coronary syndromes encompasses a variety of clinical presentations of coronary artery disease (CAD), ranging from stable angina due to epicardial coronary artery disease to microvascular coronary dysfunction. Cardiac magnetic resonance (CMR) imaging has an established role in the diagnosis, prognostication and treatment planning of patients with CAD. Recent advances in parametric mapping CMR techniques have added value in the assessment of patients with chronic coronary syndromes, even without the need for gadolinium contrast administration. Furthermore, quantitative perfusion CMR techniques have enabled the non-invasive assessment of myocardial blood flow and myocardial perfusion reserve and can reliably identify multivessel coronary artery disease and microvascular dysfunction. This review summarizes the clinical applications and the prognostic value of the novel CMR parametric mapping techniques in the setting of chronic coronary syndromes and discusses their strengths, pitfalls and future directions.

Impact of Temporal Resolution and Methods for Correction on Cardiac Magnetic Resonance Perfusion Quantification

BACKGROUND

Acquisition of magnetic resonance first-pass perfusion images is synchronized to the patient's heart rate (HR) and governs the temporal resolution. This is inherently linked to the process of myocardial blood flow (MBF) quantification and impacts MBF accuracy but to an unclear extent.

PURPOSE

To assess the impact of temporal resolution on quantitative perfusion and compare approaches for accounting for its variability.

STUDY TYPE

Prospective phantom and retrospective clinical study.

POPULATION AND PHANTOM

Simulations, a cardiac perfusion phantom, and 30 patients with (16, 53%) or without (14, 47%) coronary artery disease.

FIELD STRENGTH/SEQUENCE

3.0 T/2D saturation recovery spoiled gradient echo sequence.

ASSESSMENT

Dynamic perfusion data were simulated for a range of reference MBF (1 mL/g/min-5 mL/g/min) and HR (30 bpm-150 bpm). Perfusion imaging was performed in patients and a phantom for different temporal resolutions. MBF and myocardial perfusion reserve (MPR) were quantified without correction for temporal resolution or following correction by either MBF scaling based on the sampling interval or data interpolation prior to quantification. Simulated data were quantified using Fermi deconvolution, truncated singular value decomposition, and one-compartment modeling, whereas phantom and clinical data were quantified using Fermi deconvolution alone.

STATISTICAL TESTS

Shapiro-Wilk tests for normality, percentage error (PE) for measuring MBF accuracy in simulations, and one-way repeated measures analysis of variance with Bonferroni correction to compare clinical MBF and MPR. Statistical significance set at P < 0.05.

RESULTS

For Fermi deconvolution and an example simulated 1 mL/g/min, the MBF PE without correction for temporal resolution was between 55.4% and -62.7% across 30-150 bpm. PE was between -22.2% and -6.8% following MBF scaling and between -14.2% and -14.2% following data interpolation across the same HR. An interpolated HR of 240 bpm reduced PE to ≤10%. Clinical rest and stress MBF and MPR were significantly different between analyses.

DATA CONCLUSION

Accurate perfusion quantification needs to account for the variability of temporal resolution, with data interpolation prior to quantification reducing MBF variability across different resolutions.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 1.

Myocardial perfusion in excessively trabeculated hearts: Insights from imaging and histological studies

In gestation, the coronary circulation develops initially in the compact layer and it expands only in fetal development to the trabeculations. Conflicting data have been published as to whether the trabecular layer is hypoperfused relative to the compact wall after birth. If so, this could explain the poor pump function in patients with left ventricular excessive trabeculation, or so-called noncompaction. Here, we review direct and indirect assessments of myocardial perfusion in normal and excessively trabeculated hearts by in vivo imaging by magnetic resonance imaging (MRI), positron emission tomography (PET)/single photon emission computed tomography (SPECT), and echocardiography in addition to histology, injections of labelled microspheres in animals, and electrocardiography. In MRI, PET/SPECT, and echocardiography, flow of blood or myocardial uptake of blood-borne tracer molecules are measured. The imaged trabecular layer comprises trabeculations and blood-filled intertrabecular spaces whereas the compact layer comprises tissue only, and spatio-temporal resolution likely affects measurements of myocardial perfusion differently in the two layers. Overall, studies measuring myocardial uptake of tracers (PET/SPECT) suggest trabecular hypoperfusion. Studies measuring the quantity of blood (echocardiography and MRI) suggest trabecular hyperperfusion. These conflicting results are reconciled if the low uptake from intertrabecular spaces in PET/SPECT and the high signal from intertrabecular spaces in MRI and echocardiography are considered opposite biases. Histology on human hearts reveal a similar capillary density of trabecular and compact myocardium. Injections of labelled microspheres in animals reveal a similar perfusion of trabecular and compact myocardium. In conclusion, trabecular and compact muscle are likely equally perfused in normal hearts and most cases of excessive trabeculation.

State-of-the-Art of Myocardial Perfusion by CMR: A Practical View

Ischemic heart disease (IHD) outstands among diseases threatening public health. Essential for its management are the continuous advances in medical and interventional therapies, although a prompt and accurate diagnosis and prognostic stratification are equally important. Besides information on the anatomy of coronary arteries, well covered nowadays by invasive and non-invasive angiographic techniques, there are also other components of the disease with clinical impact, as the presence of myocardial necrosis, the extent of pump function impairment, and the presence and extent of inducible myocardial ischemia, that must be considered in every patient. Cardiovascular Magnetic Resonance (CMR) is a multiparametric diagnostic imaging technique that provides reliable information on these issues. Regarding the detection and grading of inducible ischemia in particular, the technique has been widely adopted in the form of myocardial perfusion sequences under vasodilator stress, which is the subject of this review. While the analysis of images is conventionally performed by visual inspection of dynamic first-pass studies, with the inherent dependency on the operator capability, the recent introduction of a reliable application of quantitative perfusion (QP) represents a significant advance in the field. QP is based on a dual-sequence strategy for conversion of signal intensities into contrast agent concentration units and includes a full automatization of processes such as myocardial blood flow (MBF) calculation (in mL/min/g), generation of a pixel-wise flow mapping, myocardial segmentation, based on machine learning, and allocation of MBF values to myocardial segments. The acquisition of this protocol during induced vasodilation and at rest gives values of stress/rest MBF (in mL/min/g) and myocardial perfusion reserve (MPR), both global and per segment. Dual-sequence QP has been successfully validated against different reference methods, and its prognostic value has been shown in large longitudinal studies. The fact of the whole process being automated, without operator interaction, permits to conceive new interesting scenarios of integration of CMR into systems of entirely automated diagnostic workflow in patients with IHD.

Definition and epidemiology of coronary microvascular disease

Ischemic heart disease remains one of the leading causes of death and disability worldwide. However, most patients referred for a noninvasive computed tomography coronary angiogram (CTA) or invasive coronary angiogram for the investigation of angina do not have obstructive coronary artery disease (CAD). Approximately two in five referred patients have coronary microvascular disease (CMD) as a primary diagnosis and, in addition, CMD also associates with CAD and myocardial disease (dual pathology). CMD underpins excess morbidity, impaired quality of life, significant health resource utilization, and adverse cardiovascular events. However, CMD often passes undiagnosed and the onward management of these patients is uncertain and heterogeneous. International standardized diagnostic criteria allow for the accurate diagnosis of CMD, ensuring an often overlooked patient population can be diagnosed and stratified for targeted medical therapy. Key to this is assessing coronary microvascular function-including coronary flow reserve, coronary microvascular resistance, and coronary microvascular spasm. This can be done by invasive methods (intracoronary temperature-pressure wire, intracoronary Doppler flow-pressure wire, intracoronary provocation testing) and non-invasive methods [positron emission tomography (PET), cardiac magnetic resonance imaging (CMR), transthoracic Doppler echocardiography (TTDE), cardiac computed tomography (CT)]. Coronary CTA is insensitive for CMD. Functional coronary angiography represents the combination of CAD imaging and invasive diagnostic procedures.

Role of cardiac MRI in the diagnosis of immune checkpoint inhibitor-associated myocarditis

Immune Checkpoint Inhibitor (ICI)-induced cardiotoxicity is a rare immune-related adverse event (irAE) characterized by a high mortality rate. From a pathological point of view, this condition can result from a series of causes, including binding of ICIs to target molecules on non-lymphocytic cells, cross-reaction of T lymphocytes against tumor antigens with off-target tissues, generation of autoantibodies, and production of pro-inflammatory cytokines. The diagnosis of ICI-induced cardiotoxicity can be challenging, and cardiac magnetic resonance (CMR) represents the diagnostic tool of choice in clinically stable patients with suspected myocarditis. CMR is gaining a central role in diagnosis and monitoring of cardiovascular damage in cancer patients, and it is entering international cardiology and oncology guidelines. In this narrative review, we summarized the clinical aspects of ICI-associated myocarditis, highlighting its radiological aspects and proposing a novel algorithm for the use of CMR.

Free-breathing motion-informed locally low-rank quantitative 3D myocardial perfusion imaging

Purpose

To propose respiratory motion‐informed locally low‐rank reconstruction (MI‐LLR) for robust free‐breathing single‐bolus quantitative 3D myocardial perfusion CMR imaging. Simulation and in‐vivo results are compared to locally low‐rank (LLR) and compressed sensing reconstructions (CS) for reference.

Methods

Data were acquired using a 3D Cartesian pseudo‐spiral in‐out k‐t undersampling scheme (R = 10) and reconstructed using MI‐LLR, which encompasses two stages. In the first stage, approximate displacement fields are derived from an initial LLR reconstruction to feed a motion‐compensated reference system to a second reconstruction stage, which reduces the rank of the inverse problem. For comparison, data were also reconstructed with LLR and frame‐by‐frame CS using wavelets as sparsifying transform (ℓ1‐wavelet).

Reconstruction accuracy relative to ground truth was assessed using synthetic data for realistic ranges of breathing motion, heart rates, and SNRs. In‐vivo experiments were conducted in healthy subjects at rest and during adenosine stress. Myocardial blood flow (MBF) maps were derived using a Fermi model.

Results

Improved uniformity of MBF maps with reduced local variations was achieved with MI‐LLR. For rest and stress, intra‐volunteer variation of absolute and relative MBF was lower in MI‐LLR (±0.17 mL/g/min [26%] and ±1.07 mL/g/min [33%]) versus LLR (±0.19 mL/g/min [28%] and ±1.22 mL/g/min [36%]) and versus ℓ1‐wavelet (±1.17 mL/g/min [113%] and ±6.87 mL/g/min [115%]). At rest, intra‐subject MBF variation was reduced significantly with MI‐LLR.

Conclusion

The combination of pseudo‐spiral Cartesian undersampling and dual‐stage MI‐LLR reconstruction improves free‐breathing quantitative 3D myocardial perfusion CMR imaging under rest and stress condition.

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Myocardial microvascular function assessed by CMR first-pass perfusion in patients treated with chemotherapy for gynecologic malignancies

OBJECTIVES

Cancer chemotherapy potentially increases the risk of myocardial ischemia. This study assessed myocardial microvascular function by cardiac magnetic resonance (CMR) first-pass perfusion in patients treated with chemotherapy for gynecologic malignancies.

METHODS

A total of 81 patients treated with chemotherapy for gynecologic malignancies and 39 healthy volunteers were prospectively enrolled and underwent CMR imaging. Among the patients, 32 completed CMR follow-up, with a median interval of 6 months. The CMR sequences comprised cardiac cine, rest first-pass perfusion, and late gadolinium enhancement.

RESULTS

There were no significant differences in the baseline characteristics between the patients and normal controls (all p > 0.05). Compared with the normal controls, the patients had a lower myocardial perfusion index (PI) (13.62 ± 2.01% vs. 12% (11 to 14%), p = 0.001) but demonstrated no significant variation with an increase in the number of chemotherapy cycles at follow-up (11.79 ± 2.36% vs. 11.19 ± 2.19%, p = 0.234). In multivariate analysis with adjustments for clinical confounders, a decrease in the PI was independently associated with chemotherapy treatment (β = - 0.362, p = 0.002) but had no correlation with the number of chemotherapy cycles (r = - 0.177, p = 0.053).

CONCLUSION

Myocardial microvascular dysfunction was associated with chemotherapy treatment in patients with gynecologic malignancies, and can be assessed and monitored by rest CMR first-pass perfusion.

KEY POINTS

• Chemotherapy was associated with but did not aggravate myocardial microvascular dysfunction in patients with gynecologic malignancies. • Rest CMR first-pass perfusion is an ideal modality for assessing and monitoring alterations in myocardial microcirculation during chemotherapy treatment.

Physics-informed neural networks for myocardial perfusion MRI quantification

Tracer-kinetic models allow for the quantification of kinetic parameters such as blood flow from dynamic contrast-enhanced magnetic resonance (MR) images. Fitting the observed data with multi-compartment exchange models is desirable, as they are physiologically plausible and resolve directly for blood flow and microvascular function. However, the reliability of model fitting is limited by the low signal-to-noise ratio, temporal resolution, and acquisition length. This may result in inaccurate parameter estimates. This study introduces physics-informed neural networks (PINNs) as a means to perform myocardial perfusion MR quantification, which provides a versatile scheme for the inference of kinetic parameters. These neural networks can be trained to fit the observed perfusion MR data while respecting the underlying physical conservation laws described by a multi-compartment exchange model. Here, we provide a framework for the implementation of PINNs in myocardial perfusion MR. The approach is validated both in silico and in vivo. In the in silico study, an overall decrease in mean-squared error with the ground-truth parameters was observed compared to a standard non-linear least squares fitting approach. The in vivo study demonstrates that the method produces parameter values comparable to those previously found in literature, as well as providing parameter maps which match the clinical diagnosis of patients.

High-Resolution Free-Breathing Quantitative First-Pass Perfusion Cardiac MR Using Dual-Echo Dixon With Spatio-Temporal Acceleration

Introduction

To develop and test the feasibility of free-breathing (FB), high-resolution quantitative first-pass perfusion cardiac MR (FPP-CMR) using dual-echo Dixon (FOSTERS; Fat-water separation for mOtion-corrected Spatio-TEmporally accelerated myocardial peRfuSion).

Materials and Methods

FOSTERS was performed in FB using a dual-saturation single-bolus acquisition with dual-echo Dixon and a dynamically variable Cartesian k-t undersampling (8-fold) approach, with low-rank and sparsity constrained reconstruction, to achieve high-resolution FPP-CMR images. FOSTERS also included automatic in-plane motion estimation and T2* correction to obtain quantitative myocardial blood flow (MBF) maps. High-resolution (1.6 x 1.6 mm²) FB FOSTERS was evaluated in eleven patients, during rest, against standard-resolution (2.6 x 2.6 mm²) 2-fold SENSE-accelerated breath-hold (BH) FPP-CMR. In addition, MBF was computed for FOSTERS and spatial wavelet-based compressed sensing (CS) reconstruction. Two cardiologists scored the image quality (IQ) of FOSTERS, CS, and standard BH FPP-CMR images using a 4-point scale (1–4, non-diagnostic – fully diagnostic).

Results

FOSTERS produced high-quality images without dark-rim and with reduced motion-related artifacts, using an 8x accelerated FB acquisition. FOSTERS and standard BH FPP-CMR exhibited excellent IQ with an average score of 3.5 ± 0.6 and 3.4 ± 0.6 (no statistical difference, p > 0.05), respectively. CS images exhibited severe artifacts and high levels of noise, resulting in an average IQ score of 2.9 ± 0.5. MBF values obtained with FOSTERS presented a lower variance than those obtained with CS.

Discussion

FOSTERS enabled high-resolution FB FPP-CMR with MBF quantification. Combining motion correction with a low-rank and sparsity-constrained reconstruction results in excellent image quality.

Cardiac MR: From Theory to Practice

Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.

Clinical Application of Dynamic Contrast Enhanced Perfusion Imaging by Cardiovascular Magnetic Resonance

Functionally significant coronary artery disease impairs myocardial blood flow and can be detected non-invasively by myocardial perfusion imaging. While multiple myocardial perfusion imaging modalities exist, the high spatial and temporal resolution of cardiovascular magnetic resonance (CMR), combined with its freedom from ionising radiation make it an attractive option. Dynamic contrast enhanced CMR perfusion imaging has become a well-validated non-invasive tool for the assessment and risk stratification of patients with coronary artery disease and is recommended by international guidelines. This article presents an overview of CMR perfusion imaging and its clinical application, with a focus on chronic coronary syndromes, highlighting its strengths and challenges, and discusses recent advances, including the emerging role of quantitative perfusion analysis.

Stress Cardiac Magnetic Resonance Myocardial Perfusion Imaging: JACC Review Topic of the Week

Stress cardiovascular magnetic resonance imaging (CMR) is a cost-effective, noninvasive test that accurately assesses myocardial ischemia, myocardial viability, and cardiac function without the need for ionizing radiation. There is a large body of literature, including randomized controlled trials, validating its diagnostic performance, risk stratification capabilities, and ability to guide appropriate use of coronary intervention. Specifically, stress CMR has shown higher diagnostic sensitivity than single-photon emission computed tomography imaging in detecting angiographically significant coronary artery disease. Stress CMR is particularly valuable for the evaluation of patients with moderate to high pretest probability of having stable ischemic heart disease and for patients known to have challenging imaging characteristics, including women, individuals with prior revascularization, and those with left ventricular dysfunction. This paper reviews the basics principles of stress CMR, the data supporting its clinical use, the added-value of myocardial blood flow quantification, and the assessment of myocardial function and viability routinely obtained during a stress CMR study.

Artificial Intelligence Based Multimodality Imaging: A New Frontier in Coronary Artery Disease Management

Coronary artery disease (CAD) represents one of the most important causes of death around the world. Multimodality imaging plays a fundamental role in both diagnosis and risk stratification of acute and chronic CAD. For example, the role of Coronary Computed Tomography Angiography (CCTA) has become increasingly important to rule out CAD according to the latest guidelines. These changes and others will likely increase the request for appropriate imaging tests in the future. In this setting, artificial intelligence (AI) will play a pivotal role in echocardiography, CCTA, cardiac magnetic resonance and nuclear imaging, making multimodality imaging more efficient and reliable for clinicians, as well as more sustainable for healthcare systems. Furthermore, AI can assist clinicians in identifying early predictors of adverse outcome that human eyes cannot see in the fog of “big data.” AI algorithms applied to multimodality imaging will play a fundamental role in the management of patients with suspected or established CAD. This study aims to provide a comprehensive overview of current and future AI applications to the field of multimodality imaging of ischemic heart disease.

Influence of motion correction on the visual analysis of cardiac magnetic resonance stress perfusion imaging

OBJECTIVE

Image post-processing corrects for cardiac and respiratory motion (MoCo) during cardiovascular magnetic resonance (CMR) stress perfusion. The study analyzed its influence on visual image evaluation.

MATERIALS AND METHODS

Sixty-two patients with (suspected) coronary artery disease underwent a standard CMR stress perfusion exam during free-breathing. Image post-processing was performed without (non-MoCo) and with MoCo (image intensity normalization; motion extraction with iterative non-rigid registration; motion warping with the combined displacement field). Images were evaluated regarding the perfusion pattern (perfusion deficit, dark rim artifact, uncertain signal loss, and normal perfusion), the general image quality (non-diagnostic, imperfect, good, and excellent), and the reader's subjective confidence to assess the images (not confident, confident, very confident).

RESULTS

Fifty-three (non-MoCo) and 52 (MoCo) myocardial segments were rated as 'perfusion deficit', 113 vs. 109 as 'dark rim artifacts', 9 vs. 7 as 'uncertain signal loss', and 817 vs. 824 as 'normal'. Agreement between non-MoCo and MoCo was high with no diagnostic difference per-patient. The image quality of MoCo was rated more often as 'good' or 'excellent' (92 vs. 63%), and the diagnostic confidence more often as "very confident" (71 vs. 45%) compared to non-MoCo.

CONCLUSIONS

The comparison of perfusion images acquired during free-breathing and post-processed with and without motion correction demonstrated that both methods led to a consistent evaluation of the perfusion pattern, while the image quality and the reader's subjective confidence to assess the images were rated more favorably for MoCo.

Clinical Translation of Three-Dimensional Scar, Diffusion Tensor Imaging, Four-Dimensional Flow, and Quantitative Perfusion in Cardiac MRI: A Comprehensive Review

Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy—both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease.

Ischemic Heart Disease: Noninvasive Imaging Techniques and Findings

Ischemic heart disease is a leading cause of death worldwide and comprises a large proportion of annual health care expenditure. Management of ischemic heart disease is now best guided by the physiologic significance of coronary artery stenosis. Invasive coronary angiography is the standard for diagnosing coronary artery stenosis. However, it is expensive and has risks including vascular access site complications and contrast material–induced nephropathy. Invasive coronary angiography requires fractional flow reserve (FFR) measurement to determine the physiologic significance of a coronary artery stenosis. Multiple noninvasive cardiac imaging modalities can also anatomically delineate or functionally assess for significant coronary artery stenosis, as well as detect the presence of myocardial infarction (MI). While coronary CT angiography can help assess the degree of anatomic stenosis, its inability to assess the physiologic significance of lesions limits its specificity. Physiologic significance of coronary artery stenosis can be determined by cardiac MR vasodilator or dobutamine stress imaging, CT stress perfusion imaging, FFR CT, PET myocardial perfusion imaging (MPI), SPECT MPI, and stress echocardiography. Clinically unrecognized MI, another clear indicator of physiologically significant coronary artery disease, is relatively common and is best evaluated with cardiac MRI. The authors illustrate the spectrum of imaging findings of ischemic heart disease (coronary artery disease, myocardial ischemia, and MI); highlight the advantages and disadvantages of the various noninvasive imaging methods used to assess ischemic heart disease, as illustrated by recent clinical trials; and summarize current indications and contraindications for noninvasive imaging techniques for detection of ischemic heart disease.

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Direct Comparison of Bayesian and Fermi Deconvolution Approaches for Myocardial Blood Flow Quantification: In silico and Clinical Validations

Cardiac magnetic resonance myocardial perfusion imaging can detect coronary artery disease and is an alternative to single-photon emission computed tomography or positron emission tomography. However, the complex, non-linear MR signal and the lack of robust quantification of myocardial blood flow have hindered its widespread clinical application thus far. Recently, a new Bayesian approach was developed for brain imaging and evaluation of perfusion indexes (Kudo et al., 2014). In addition to providing accurate perfusion measurements, this probabilistic approach appears more robust than previous approaches, particularly due to its insensitivity to bolus arrival delays. We assessed the performance of this approach against a well-known and commonly deployed model-independent method based on the Fermi function for cardiac magnetic resonance myocardial perfusion imaging. The methods were first evaluated for accuracy and precision using a digital phantom to test them against the ground truth; next, they were applied in a group of coronary artery disease patients. The Bayesian method can be considered an appropriate model-independent method with which to estimate myocardial blood flow and delays. The digital phantom comprised a set of synthetic time-concentration curve combinations generated with a 2-compartment exchange model and a realistic combination of perfusion indexes, arterial input dynamics, noise and delays collected from the clinical dataset. The myocardial blood flow values estimated with the two methods showed an excellent correlation coefficient (r² > 0.9) under all noise and delay conditions. The Bayesian approach showed excellent robustness to bolus arrival delays, with a similar performance to Fermi modeling when delays were considered. Delays were better estimated with the Bayesian approach than with Fermi modeling. An in vivo analysis of coronary artery disease patients revealed that the Bayesian approach had an excellent ability to distinguish between abnormal and normal myocardium. The Bayesian approach was able to discriminate not only flows but also delays with increased sensitivity by offering a clearly enlarged range of distribution for the physiologic parameters.