Comparison of the Diagnostic Performance of Four Quantitative Myocardial Perfusion Estimation Methods Used in Cardiac MR Imaging: CE-MARC Substudy

Automatic detection of myocardial ischaemia using generalisable spatio-temporal hierarchical Bayesian modelling of DCE-MRI

Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) can be used as a non-invasive method for the assessment of myocardial perfusion. The acquired images can be utilised to analyse the spatial extent and severity of myocardial ischaemia (regions with impaired microvascular blood flow). In the present paper, we propose a novel generalisable spatio-temporal hierarchical Bayesian model (GST-HBM) to automate the detection of ischaemic lesions and improve the in silico prediction accuracy by systematically integrating spatio-temporal context information. We present a computational inference procedure with an adequate trade-off between accuracy and computational efficiency, whereby model parameters are sampled from the posterior distribution with Gibbs sampling, while lower-level hyperparameters are selected using model selection strategies based on the Watanabe Akaike information criterion (WAIC). We have assessed our method on both synthetic (in silico) data with known gold-standard and 12 sets of clinical first-pass myocardial perfusion DCE-MRI datasets. We have also carried out a comparative performance evaluation with four established alternative methods: Gaussian mixture model (GMM), opening and closing operations based on Gaussian mixture model (GMMC&Omax), Markov random field constrained Gaussian mixture model (GMM-MRF) and model-based hierarchical Bayesian model (M-HBM). Our results show that the proposed GST-HBM method achieves much higher in silico prediction accuracy than the established alternative methods. Furthermore, this method appears to provide a more robust delineation of ischaemic lesions in datasets affected by spatially variant noise.

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.

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.

Sex- and age-specific normal values for automated quantitative pixel-wise myocardial perfusion cardiovascular magnetic resonance

AIMS

Recently developed in-line automated cardiovascular magnetic resonance (CMR) myocardial perfusion mapping has been shown to be reproducible and comparable with positron emission tomography (PET), and can be easily integrated into clinical workflows. Bringing quantitative myocardial perfusion CMR into routine clinical care requires knowledge of sex- and age-specific normal values in order to define thresholds for disease detection. This study aimed to establish sex- and age-specific normal values for stress and rest CMR myocardial blood flow (MBF) in healthy volunteers.

METHODS AND RESULTS

A total of 151 healthy volunteers recruited from two centres underwent adenosine stress and rest myocardial perfusion CMR. In-line automatic reconstruction and post processing of perfusion data were implemented within the Gadgetron software framework, creating pixel-wise perfusion maps. Rest and stress MBF were measured, deriving myocardial perfusion reserve (MPR) and were subdivided by sex and age. Mean MBF in all subjects was 0.62 ± 0.13 mL/g/min at rest and 2.24 ± 0.53 mL/g/min during stress. Mean MPR was 3.74 ± 1.00. Compared with males, females had higher rest (0.69 ± 0.13 vs. 0.58 ± 0.12 mL/g/min, P < 0.01) and stress MBF (2.41 ± 0.47 vs. 2.13 ± 0.54 mL/g/min, P = 0.001). Stress MBF and MPR showed significant negative correlations with increasing age (r = -0.43, P < 0.001 and r = -0.34, P < 0.001, respectively).

CONCLUSION

Fully automated in-line CMR myocardial perfusion mapping produces similar normal values to the published CMR and PET literature. There is a significant increase in rest and stress MBF, but not MPR, in females and a reduction of stress MBF and MPR with advancing age, advocating the use of sex- and age-specific reference ranges for diagnostic use.

Subclinical Systemic Sclerosis Primary Heart Involvement by Cardiovascular Magnetic Resonance Shows No Significant Interval Change

OBJECTIVE

Subclinical systemic sclerosis (SSc) primary heart involvement is commonly described. Whether these findings progress over time is not clear. The study aimed to investigate cardiovascular magnetic resonance (CMR) interval change of subclinical SSc primary heart involvement.

METHODS

Patients with SSc with no cardiovascular disease underwent two CMR scans that included T1 mapping and quantitative stress perfusion. The CMR change (mean difference) and association between CMR measures and clinical phenotype were assessed. The study had a prospective design.

RESULTS

Thirty-one patients with SSc participated, with a median (interquartile range) follow-up of 33 (17-37) months (10 [32%] in the diffuse subset, 16 [52%] with interstitial lung disease [ILD], and 11 [29%] who were Scl-70+). Four of thirty-one patients had focal late gadolinium enhancement (LGE) at visit 1; one of four had an increase in LGE scar mass between visits. Two patients showed new focal LGE at visit 2. No change in other CMR indices was noted. The three patients with SSc with increased or new LGE at visit 2 had diffuse cutaneous SSc with ILD, and two were Scl-70+. A reduction in forced vital capacity and total lung capacity was associated with a reduction in left ventricular ejection fraction (ρ = 0.413, P = 0.021; ρ = 0.335, P = 0.07) and myocardial perfusion reserve (MPR) (ρ = 0.543, P = 0.007; ρ = 0.627, P = 0.002). An increase in the N-terminal pro-brain natriuretic peptide level was associated with a reduction in MPR (ρ = -0.448, P = 0.042). Patients on disease-modifying antirheumatic drugs (DMARDs) had an increase in native T1 (mean [SD] 1208 [65] vs. 1265 [56] milliseconds, P = 0.008). No other clinically meaningful CMR change in patients receiving DMARDs or vasodilators was noted.

CONCLUSION

Serial CMR detects interval subclinical SSc primary heart involvement progression; however, this study suggests abnormalities remain largely stable with follow-up.

Revisiting sample size planning for receiver operating characteristic studies: A confidence interval approach with precision and assurance

Estimation of areas under receiver operating characteristic curves and their differences is a key task in diagnostic studies. Here we develop closed-form sample size formulas for such studies with a focus on estimation rather than hypothesis testing, by explicitly incorporating pre-specified precision and assurance, with precision denoted by the lower limit of confidence interval and assurance denoted by the probability of achieving that lower limit. For sample size estimation purposes, we introduce a normality-based variance function for valid estimation allowing for unequal variances of observations in the disease and non-disease groups. Simulation results demonstrate that the proposed formulas produce empirical assurance probability close to the pre-specified assurance probability and empirical coverage probability close to the nominal level. Compared with a frequently used existing variance function, the proposed function provides more accurate and efficient sample size estimates. For an illustration of the proposed formulas, we present real-world worked examples. To facilitate implementation, we have developed an online calculator openly available at https://dishu.page/calculator/.

Qualitative and Quantitative Stress Perfusion Cardiac Magnetic Resonance in Clinical Practice: A Comprehensive Review

Stress cardiovascular magnetic resonance (CMR) imaging is a well-validated non-invasive stress test to diagnose significant coronary artery disease (CAD), with higher diagnostic accuracy than other common functional imaging modalities. One-stop assessment of myocardial ischemia, cardiac function, and myocardial viability qualitatively and quantitatively has been proven to be a cost-effective method in clinical practice for CAD evaluation. Beyond diagnosis, stress CMR also provides prognostic information and guides coronary revascularisation. In addition to CAD, there is a large body of literature demonstrating CMR's diagnostic performance and prognostic value in other common cardiovascular diseases (CVDs), especially coronary microvascular dysfunction (CMD). This review focuses on the clinical applications of stress CMR, including stress CMR scanning methods, practical interpretation of stress CMR images, and clinical utility of stress CMR in a setting of CVDs with possible myocardial ischemia.

AI-AIF: artificial intelligence-based arterial input function for quantitative stress perfusion cardiac magnetic resonance

Aims

One of the major challenges in the quantification of myocardial blood flow (MBF) from stress perfusion cardiac magnetic resonance (CMR) is the estimation of the arterial input function (AIF). This is due to the non-linear relationship between the concentration of gadolinium and the MR signal, which leads to signal saturation. In this work, we show that a deep learning model can be trained to predict the unsaturated AIF from standard images, using the reference dual-sequence acquisition AIFs (DS-AIFs) for training.

Methods and results

A 1D U-Net was trained, to take the saturated AIF from the standard images as input and predict the unsaturated AIF, using the data from 201 patients from centre 1 and a test set comprised of both an independent cohort of consecutive patients from centre 1 and an external cohort of patients from centre 2 (n = 44). Fully-automated MBF was compared between the DS-AIF and AI-AIF methods using the Mann-Whitney U test and Bland-Altman analysis. There was no statistical difference between the MBF quantified with the DS-AIF [2.77 mL/min/g (1.08)] and predicted with the AI-AIF (2.79 mL/min/g (1.08), P = 0.33. Bland-Altman analysis shows minimal bias between the DS-AIF and AI-AIF methods for quantitative MBF (bias of -0.11 mL/min/g). Additionally, the MBF diagnosis classification of the AI-AIF matched the DS-AIF in 669/704 (95%) of myocardial segments.

Conclusion

Quantification of stress perfusion CMR is feasible with a single-sequence acquisition and a single contrast injection using an AI-based correction of the AIF.

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.

Inflammation in Coronary Microvascular Dysfunction

Chronic low-grade inflammation is involved in coronary atherosclerosis, presenting multiple clinical manifestations ranging from asymptomatic to stable angina, acute coronary syndrome, heart failure and sudden cardiac death. Coronary microvasculature consists of vessels with a diameter less than 500 μm, whose potential structural and functional abnormalities can lead to inappropriate dilatation and an inability to meet the required myocardium oxygen demands. This review focuses on the pathogenesis of coronary microvascular dysfunction and the capability of non-invasive screening methods to detect the phenomenon. Anti-inflammatory agents, such as statins and immunomodulators, including anakinra, tocilizumab, and tumor necrosis factor-alpha inhibitors, have been assessed recently and may constitute additional or alternative treatment approaches to reduce cardiovascular events in atherosclerotic heart disease characterized by coronary microvascular dysfunction.

Vasomotor Dysfunction in Patients with Ischemia and Non-Obstructive Coronary Artery Disease: Current Diagnostic and Therapeutic Strategies

Many patients who present with symptoms or objective evidence of ischemia have no or non-physiologically-significant disease on invasive coronary angiography. The diagnosis of ischemic heart disease is thus often dismissed, and patients receive false reassurance or other diagnoses are pursued. We now know that a significant proportion of these patients have coronary microvascular dysfunction and/or vasospastic disease as the underlying pathophysiology of their clinical presentation. Making the correct diagnosis of such abnormalities is important not only because they impact the quality of life, with recurring symptoms and unnecessary repeated testing, but also because they increase the risk for adverse cardiovascular events. The mainstay of diagnosis remains an invasive comprehensive physiologic assessment, which further allows stratifying these patients into appropriate “endotypes”. It has been shown that tailoring treatment to the patient’s assigned endotype improves symptoms and quality of life. In addition to the conventional drugs used in chronic stable angina, multiple newer agents are being investigated. Moreover, innovative non-pharmacologic and interventional therapies are emerging to provide a bail-out in refractory cases. Many of these novel therapies fail to show consistent benefits, but others show quite promising results.

Cardiovascular outcomes in systemic sclerosis with abnormal cardiovascular MRI and serum cardiac biomarkers

Objectives

To explore the prognostic value of subclinical cardiovascular (CV) imaging measures and serum cardiac biomarkers in systemic sclerosis (SSc) for the development of CV outcomes of primary heart involvement (pHI).

Methods

Patients with SSc with no clinical SSc-pHI and no history of heart disease underwent cardiovascular magnetic resonance (CMR) imaging, and measurement of serum high-sensitivity-troponin I (hs-TnI) and N-terminal-pro-brain natriuretic peptide (NT-proBNP). Follow-up clinical and CV outcome data were recorded. CV outcomes were defined as myocarditis, arrhythmia and/or echocardiographic functional impairment including systolic dysfunction and/or diastolic dysfunction.

Results

Seventy-four patients with a median (IQR) age of 57 (49, 63) years, 32% diffuse cutaneous SSc, 39% interstitial lung disease, 30% Scl70+ were followed up for median (IQR) 22 (15, 54) months. Ten patients developed CV outcomes, comprising one patient with myocarditis and systolic dysfunction and nine arrhythmias: three non-sustained ventricular tachycardia and six supraventricular arrhythmias. The probability of CV outcomes was considerably higher in those with NT-proBNP >125 pg/mL versus normal NT-proBNP (X²=4.47, p=0.035). Trend for poorer time-to-event was noted in those with higher extracellular volume (ECV; indicating diffuse fibrosis) and hs-TnI levels versus those with normal values (X²=2.659, p=0.103; X²=2.530, p=0.112, respectively). In a predictive model, NT-proBNP >125 pg/mL associated with CV outcomes (OR=5.335, p=0.040), with a trend observed for ECV >29% (OR=4.347, p=0.073).

Conclusion

These data indicate standard serum cardiac biomarkers (notably NT-proBNP) and CMR indices of myocardial fibrosis associate with adverse CV outcomes in SSc. This forms the basis to develop a prognostic model in larger, longitudinal studies.

Cardiac Magnetic Resonance Tissue Characterization in Ischemic Cardiomyopathy

Ischemic cardiomyopathy (ICM) is one of the most common causes of congestive heart failure. In patients with ICM, tissue characterization with cardiac magnetic resonance imaging (CMR) allows for evaluation of myocardial abnormalities in acute and chronic settings. Myocardial edema, microvascular obstruction (MVO), intracardiac thrombus, intramyocardial hemorrhage, and late gadolinium enhancement of the myocardium are easily depicted using standard CMR sequences. In the acute setting, tissue characterization is mainly focused on assessment of ventricular thrombus and MVO, which are associated with poor prognosis. Conversely, in chronic ICM, it is important to depict late gadolinium enhancement and myocardial ischemia using stress perfusion sequences. Overall, with CMR's ability to accurately characterize myocardial tissue in acute and chronic ICM, it represents a valuable diagnostic and prognostic imaging method for treatment planning. In particular, tissue characterization abnormalities in the acute setting can provide information regarding the patients that may develop major adverse cardiac event and show the presence of ventricular thrombus; in the chronic setting, evaluation of viable myocardium can be fundamental for planning myocardial revascularization. In this review, the main findings on tissue characterization are illustrated in acute and chronic settings using qualitative and quantitative tissue characterization.

Noninvasive rapid cardiac magnetic resonance for the assessment of cardiomyopathies in low-middle income countries

Introduction: Cardiac Magnetic Resonance (CMR) is a crucial diagnostic imaging test that redefines diagnosis and enables targeted therapies, but the access to CMR is limited in low-middle Income Countries (LMICs) even though cardiovascular disease is an emergent primary cause of mortality in LMICs. New abbreviated CMR protocols can be less expensive, faster, whilst maintaining accuracy, potentially leading to a higher utilization in LMICs.Areas covered: This article will review cardiovascular disease in LMICs and the current role of CMR in cardiac diagnosis and enable targeted therapy, discussing the main obstacles to prevent the adoption of CMR in LMICs. We will then review the potential utility of abbreviated, cost-effective CMR protocols to improve cardiac diagnosis and care, the clinical indications of the exam, current evidence and future directions.Expert opinion: Rapid CMR protocols, provided that they are utilized in potentially high yield cases, could reduce cost and increase effectiveness. The adoption of these protocols, their integration into care pathways, and prioritizing key treatable diagnoses can potentially improve patient care. Several LMIC countries are now pioneering these approaches and the application of rapid CMR protocols appears to have a bright future if delivered effectively.

Diagnostic Accuracy of Spiral Whole-Heart Quantitative Adenosine Stress Cardiovascular Magnetic Resonance With Motion Compensated L1-SPIRIT

BACKGROUND

Variable density spiral (VDS) pulse sequences with motion compensated compressed sensing (MCCS) reconstruction allow for whole-heart quantitative assessment of myocardial perfusion but are not clinically validated.

PURPOSE

Assess performance of whole-heart VDS quantitative stress perfusion with MCCS to detect obstructive coronary artery disease (CAD).

STUDY TYPE

Prospective cross sectional.

POPULATION

Twenty-five patients with chest pain and known or suspected CAD and nine normal subjects.

FIELD STRENGTH/SEQUENCE

Segmented steady-state free precession (SSFP) sequence, segmented phase sensitive inversion recovery sequence for late gadolinium enhancement (LGE) imaging and VDS sequence at 1.5 T for rest and stress quantitative perfusion at eight short-axis locations.

ASSESSMENT

Stenosis was defined as ≥50% by quantitative coronary angiography (QCA). Visual and quantitative analysis of MRI data was compared to QCA. Quantitative analysis assessed average myocardial perfusion reserve (MPR), average stress myocardial blood flow (MBF), and lowest stress MBF of two contiguous myocardial segments. Ischemic burden was measured visually and quantitatively.

STATISTICAL TESTS

Student's t-test, McNemar's test, chi-square statistic, linear mixed-effects model, and area under receiver-operating characteristic curve (ROC).

RESULTS

Per-patient visual analysis demonstrated a sensitivity of 84% (95% confidence interval [CI], 60%-97%) and specificity of 83% [95% CI, 36%-100%]. There was no significant difference between per-vessel visual and quantitative analysis for sensitivity (69% [95% CI, 51%-84%] vs. 77% [95% CI, 60%-90%], P = 0.39) and specificity (88% [95% CI, 73%-96%] vs. 80% [95% CI, 64%-91%], P = 0.75). Per-vessel quantitative analysis ROC showed no significant difference (P = 0.06) between average MPR (0.68 [95% CI, 0.56-0.81]), average stress MBF (0.74 [95% CI, 0.63-0.86]), and lowest stress MBF (0.79 [95% CI, 0.69-0.90]). Visual and quantitative ischemic burden measurements were comparable (P = 0.85).

DATA CONCLUSION

Whole-heart VDS stress perfusion demonstrated good diagnostic accuracy and ischemic burden evaluation. No significant difference was seen between visual and quantitative diagnostic performance and ischemic burden measurements.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Influence of the arterial input sampling location on the diagnostic accuracy of cardiovascular magnetic resonance stress myocardial perfusion quantification

BACKGROUND

Quantification of myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) by cardiovascular magnetic resonance (CMR) perfusion requires sampling of the arterial input function (AIF). While variation in the AIF sampling location is known to impact quantification by CMR and positron emission tomography (PET) perfusion, there is no evidence to support the use of a specific location based on their diagnostic accuracy in the detection of coronary artery disease (CAD). This study aimed to evaluate the accuracy of stress MBF and MPR for different AIF sampling locations for the detection of abnormal myocardial perfusion with expert visual assessment as the reference.

METHODS

Twenty-five patients with suspected or known CAD underwent vasodilator stress-rest perfusion with a dual-sequence technique at 3T. A low-resolution slice was acquired in 3-chamber view to allow AIF sampling at five different locations: left atrium (LA), basal left ventricle (bLV), mid left ventricle (mLV), apical left ventricle (aLV) and aortic root (AoR). MBF and MPR were estimated at the segmental level using Fermi function-constrained deconvolution. Segments were scored as having normal or abnormal perfusion by visual assessment and the diagnostic accuracy of stress MBF and MPR for each location was evaluated using receiver operating characteristic curve analysis.

RESULTS

In both normal (300 out of 400, 75 %) and abnormal segments, rest MBF, stress MBF and MPR were significantly different across AIF sampling locations (p < 0.001). Stress MBF for the AoR (normal: 2.42 (2.15-2.84) mL/g/min; abnormal: 1.71 (1.28-1.98) mL/g/min) had the highest diagnostic accuracy (sensitivity 80 %, specificity 85 %, area under the curve 0.90; p < 0.001 versus stress MBF for all other locations including bLV: normal: 2.78 (2.39-3.14) mL/g/min; abnormal: 2.22 (1.83-2.48) mL/g/min; sensitivity 91 %, specificity 63 %, area under the curve 0.81) and performed better than MPR for the LV locations (p < 0.01). MPR for the AoR (normal: 2.43 (1.95-3.14); abnormal: 1.58 (1.34-1.90)) was not superior to MPR for the bLV (normal: 2.59 (2.04-3.20); abnormal: 1.69 (1.36-2.14); p = 0.717).

CONCLUSIONS

The AIF sampling location has a significant impact on MBF and MPR estimates by CMR perfusion, with AoR-based stress MBF comparing favorably to that for the current clinical reference bLV.

Stress CMR in Known or Suspected CAD: Diagnostic and Prognostic Role

The recently published 2019 guidelines on chronic coronary syndromes (CCS) focus on the need for noninvasive imaging modalities to accurately establish the diagnosis of coronary artery disease (CAD) and assess the risk of clinical scenario occurrence. Appropriate patient management should rely on controlling symptoms, improving prognosis, and guiding each therapeutic strategy as well as monitoring disease progress. Among the noninvasive imaging modalities, cardiovascular magnetic resonance (CMR) has gained broad acceptance in past years due to its unique features in providing a complete assessment of CAD through data on cardiac anatomy and function and myocardial viability, with high spatial and temporal resolution and without ionizing radiation. In detail, evaluation of the presence and extent of myocardial ischemia through stress CMR (S-CMR) has shown a high rule-in power in detecting functionally significant coronary artery stenosis in patients suspected of CCS. Moreover, S-CMR technique may add significant prognostic value, as demonstrated by different studies which have progressively evidenced the valuable power of this multiparametric imaging modality in predicting adverse cardiac events. The latest scientific progress supports a greater expansion of S-CMR with improvement of quantitative myocardial perfusion analysis, myocardial strain, and native mapping within the same examination. Although further study is warranted, these techniques, which are currently mostly restricted to the research field, are likely to become increasingly prevalent in the clinical setting with the scope of increasing accuracy in the selection of patients to be sent to invasive revascularization. This review investigates the diagnostic and prognostic role of S-CMR in the context of CAD, by analysing a strong, long-standing, scientific evidence together with an appraisal of new advanced techniques which may potentially enrich CAD management in the next future.

Clinical associations with stage B heart failure in adults with type 2 diabetes

BACKGROUND

There is a high prevalence of asymptomatic (American Heart Association Stage B) heart failure (SBHF) in people with type 2 diabetes (T2D). We aimed to identify associations between clinical characteristics and markers of SBHF in adults with T2D, which may allow therapeutic interventions prior to symptom onset.

METHODS

Adults with T2D from a multi-ethnic population with no prevalent cardiovascular disease [n = 247, age 52 ± 12 years, glycated haemoglobin A1c (HbA1c) 7.4 ± 1.1% (57 ± 12 mmol/mol), duration of diabetes 61 (32, 120) months] underwent echocardiography and adenosine stress perfusion cardiovascular magnetic resonance imaging. Multivariable linear regression analyses were performed to identify independent associations between clinical characteristics and markers of SBHF.

RESULTS

In a series of multivariable linear regression models containing age, sex, ethnicity, smoking history, number of glucose-lowering agents, systolic blood pressure (BP) duration of diabetes, body mass index (BMI), HbA1c, serum creatinine, and low-density lipoprotein (LDL)-cholesterol, independent associations with: left ventricular mass:volume were age (β = 0.024), number of glucose-lowering agents (β = 0.022) and systolic BP (β = 0.027); global longitudinal strain were never smoking (β = -1.196), systolic BP (β = 0.328), and BMI (β = -0.348); myocardial perfusion reserve were age (β = -0.364) and male sex (β = 0.458); and aortic distensibility were age (β = -0.629) and systolic BP (β = -0.348). HbA1c was not independently associated with any marker of SBHF.

CONCLUSIONS

In asymptomatic adults with T2D, age, systolic BP, BMI, and smoking history, but not glycaemic control, are the major determinants of SBHF. Given BP and BMI are modifiable, these may be important targets to reduce the development of symptomatic heart failure.

Vascular effects of serelaxin in patients with stable coronary artery disease: a randomized placebo-controlled trial

AIMS

The effects of serelaxin, a recombinant form of human relaxin-2 peptide, on vascular function in the coronary microvascular and systemic macrovascular circulation remain largely unknown. This mechanistic, clinical study assessed the effects of serelaxin on myocardial perfusion, aortic stiffness, and safety in patients with stable coronary artery disease (CAD).

METHODS AND RESULTS

In this multicentre, double-blind, parallel-group, placebo-controlled study, 58 patients were randomized 1:1 to 48 h intravenous infusion of serelaxin (30 µg/kg/day) or matching placebo. The primary endpoints were change from baseline to 47 h post-initiation of the infusion in global myocardial perfusion reserve (MPR) assessed using adenosine stress perfusion cardiac magnetic resonance imaging, and applanation tonometry-derived augmentation index (AIx). Secondary endpoints were: change from baseline in AIx and pulse wave velocity, assessed at 47 h, Day 30, and Day 180; aortic distensibility at 47 h; pharmacokinetics and safety. Exploratory endpoints were the effect on cardiorenal biomarkers [N-terminal pro-brain natriuretic peptide (NT-proBNP), high-sensitivity troponin T (hsTnT), endothelin-1, and cystatin C]. Of 58 patients, 51 were included in the primary analysis (serelaxin, n = 25; placebo, n = 26). After 2 and 6 h of serelaxin infusion, mean placebo-corrected blood pressure reductions of -9.6 mmHg (P = 0.01) and -13.5 mmHg (P = 0.0003) for systolic blood pressure and -5.2 mmHg (P = 0.02) and -8.4 mmHg (P = 0.001) for diastolic blood pressure occurred. There were no between-group differences from baseline to 47 h in global MPR (-0.24 vs. -0.13, P = 0.44) or AIx (3.49% vs. 0.04%, P = 0.21) with serelaxin compared with placebo. Endothelin-1 and cystatin C levels decreased from baseline in the serelaxin group, and there were no clinically relevant changes observed with serelaxin for NT-proBNP or hsTnT. Similar numbers of serious adverse events were observed in both groups (serelaxin, n = 5; placebo, n = 7) to 180-day follow-up.

CONCLUSION

In patients with stable CAD, 48 h intravenous serelaxin reduced blood pressure but did not alter myocardial perfusion.

Cardiovascular Determinants of Aerobic Exercise Capacity in Adults With Type 2 Diabetes

OBJECTIVE

To assess the relationship between subclinical cardiac dysfunction and aerobic exercise capacity (peak VO₂) in adults with type 2 diabetes (T2D), a group at high risk of developing heart failure.

RESEARCH DESIGN AND METHODS

Cross-sectional study. We prospectively enrolled a multiethnic cohort of asymptomatic adults with T2D and no history, signs, or symptoms of cardiovascular disease. Age-, sex-, and ethnicity-matched control subjects were recruited for comparison. Participants underwent bioanthropometric profiling, cardiopulmonary exercise testing, and cardiovascular magnetic resonance with adenosine stress perfusion imaging. Multivariable linear regression analysis was undertaken to identify independent associations between measures of cardiovascular structure and function and peak VO₂.

RESULTS

A total of 247 adults with T2D (aged 51.8 ± 11.9 years, 55% males, 37% black or south Asian ethnicity, HbA_1c 7.4 ± 1.1% [57 ± 12 mmol/mol], and duration of diabetes 61 [32-120] months) and 78 control subjects were included. Subjects with T2D had increased concentric left ventricular remodeling, reduced myocardial perfusion reserve (MPR), and markedly lower aerobic exercise capacity (peak VO₂ 18.0 ± 6.6 vs. 27.8 ± 9.0 mL/kg/min; P < 0.001) compared with control subjects. In a multivariable linear regression model containing age, sex, ethnicity, smoking status, and systolic blood pressure, only MPR (β = 0.822; P = 0.006) and left ventricular diastolic filling pressure (E/e') (β = -0.388; P = 0.001) were independently associated with peak VO₂ in subjects with T2D.

CONCLUSIONS

In a multiethnic cohort of asymptomatic people with T2D, MPR and diastolic function are key determinants of aerobic exercise capacity, independent of age, sex, ethnicity, smoking status, or blood pressure.

Cardiovascular Imaging Techniques to Assess Microvascular Dysfunction

The understanding of microvascular dysfunction without evidence of epicardial coronary artery disease pales in comparison with that of obstructive epicardial coronary artery disease. A primary limitation in the past had been the lack of development of noninvasive methods of detecting and quantifying microvascular dysfunction. This limitation has particularly affected the ability to study the pathophysiology, morbidity, and treatment of this disease. More recently, almost all of the noninvasive cardiac imaging modalities have been used to quantify blood flow and advance understanding of microvascular dysfunction.

A randomized, open-label, active comparator trial assessing the effects of 26 weeks of liraglutide or sitagliptin on cardiovascular function in young obese adults with type 2 diabetes

AIM

To compare the effects of a glucagon-like peptide-1 receptor agonist and a dipeptidyl peptidase-4 inhibitor on magnetic resonance imaging-derived measures of cardiovascular function.

MATERIALS AND METHODS

In a prospective, randomized, open-label, blinded endpoint trial liraglutide (1.8 mg) and sitagliptin (100 mg) were compared in asymptomatic, non-insulin treated young (aged 18-50 years) adults with obesity and type 2 diabetes. The primary outcome was difference in circumferential peak early diastolic strain rate change (PEDSR), a biomarker of cardiac diastolic dysfunction 26 weeks after randomization. Secondary outcomes included other indices of cardiac structure and function, HbA1c and body weight.

RESULTS

Seventy-six participants were randomized (54% female, mean ± SD age 44 ± 6 years, diabetes duration 4.4 years, body mass index 35.3 ± 6.1 kg m^-2 ), of whom 65% had ≥1 cardiovascular risk factor. Sixty-one participants had primary outcome data available. There were no statistically significant between-group differences (intention-to-treat; mean [95% confidence interval]) in PEDSR change (-0.01 [-0.07, +0.06] s^-1 ), left ventricular ejection fraction (-1.98 [-4.90, +0.94]%), left ventricular mass (+1.14 [-5.23, +7.50] g) or aortic distensibility (-0.35 [-0.98, +0.28] mmHg^-1  × 10^-3 ) after 26 weeks. Reductions in HbA1c (-4.57 [-9.10, -0.37] mmol mol^-1 ) and body weight (-3.88 [-5.74, -2.01] kg) were greater with liraglutide.

CONCLUSION

There were no differences in cardiovascular structure or function after short-term use of liraglutide and sitagliptin in younger adults with obesity and type 2 diabetes. Longer studies in patients with more severe cardiac dysfunction may be necessary before definitive conclusions can be made about putative pleiotropic properties of incretin-based therapies.

Pixel-wise assessment of cardiovascular magnetic resonance first-pass perfusion using a cardiac phantom mimicking transmural myocardial perfusion gradients

PURPOSE

Cardiovascular magnetic resonance first-pass perfusion for the pixel-wise detection of coronary artery disease is rapidly becoming the clinical standard, yet no widely available method exists for its assessment and validation. This study introduces a novel phantom capable of generating spatially dependent flow values to enable assessment of new perfusion imaging methods at the pixel level.

METHODS

A synthetic multicapillary myocardial phantom mimicking transmural myocardial perfusion gradients was designed and manufactured with high-precision 3D printing. The phantom was used in a stationary flow setup providing reference myocardial perfusion rates and was scanned on a 3T system. Repeated first-pass perfusion MRI for physiological perfusion rates between 1 and 4 mL/g/min was performed using a clinical dual-sequence technique. Fermi function-constrained deconvolution was used to estimate pixel-wise perfusion rate maps. Phase contrast (PC)-MRI was used to obtain velocity measurements that were converted to perfusion rates for validation of reference values and cross-method comparison. The accuracy of pixel-wise maps was assessed against simulated reference maps.

RESULTS

PC-MRI indicated excellent reproducibility in perfusion rate (coefficient of variation [CoV] 2.4-3.5%) and correlation with reference values (R² = 0.985) across the full physiological range. Similar results were found for first-pass perfusion MRI (CoV 3.7-6.2%, R² = 0.987). Pixel-wise maps indicated a transmural perfusion difference of 28.8-33.7% for PC-MRI and 23.8-37.7% for first-pass perfusion, matching the reference values (30.2-31.4%).

CONCLUSION

The unique transmural perfusion pattern in the phantom allows effective pixel-wise assessment of first-pass perfusion acquisition protocols and quantification algorithms before their introduction into routine clinical use.

Hierarchical Bayesian myocardial perfusion quantification

Myocardial blood flow can be quantified from dynamic contrast-enhanced magnetic resonance (MR) images through the fitting of tracer-kinetic models to the observed imaging data. The use of multi-compartment exchange models is desirable as they are physiologically motivated and resolve directly for both blood flow and microvascular function. However, the parameter estimates obtained with such models can be unreliable. This is due to the complexity of the models relative to the observed data which is limited by the low signal-to-noise ratio, the temporal resolution, the length of the acquisitions and other complex imaging artefacts. In this work, a Bayesian inference scheme is proposed which allows the reliable estimation of the parameters of the two-compartment exchange model from myocardial perfusion MR data. The Bayesian scheme allows the incorporation of prior knowledge on the physiological ranges of the model parameters and facilitates the use of the additional information that neighbouring voxels are likely to have similar kinetic parameter values. Hierarchical priors are used to avoid making a priori assumptions on the health of the patients. We provide both a theoretical introduction to Bayesian inference for tracer-kinetic modelling and specific implementation details for this application. This approach is validated in both in silico and in vivo settings. In silico, there was a significant reduction in mean-squared error with the ground-truth parameters using Bayesian inference as compared to using the standard non-linear least squares fitting. When applied to patient data the Bayesian inference scheme returns parameter values that are in-line with those previously reported in the literature, as well as giving parameter maps that match the independant clinical diagnosis of those patients.

State-of-the-Art Quantitative Assessment of Myocardial Ischemia by Stress Perfusion Cardiac Magnetic Resonance

Ischemic heart disease remains the foremost determinant of death and disability across the world. Quantification of the ischemia burden is currently the preferred approach to predict event risk and to trigger adequate treatment. Cardiac magnetic resonance (CMR) can be a prime protagonist in this scenario due to its synergistic features. It allows assessment of wall motility, myocardial perfusion, and tissue scar by means of late gadolinium enhancement imaging. We discuss the clinical and preclinical aspects of gadolinium-based, perfusion CMR imaging, including the relevance of high spatial resolution and 3-dimensional whole-heart coverage, among important features of this auspicious method.

Automated Quantitative Stress Perfusion in a Clinical Routine

Cardiovascular magnetic resonance (CMR) perfusion imaging is a robust noninvasive technique to evaluate ischemia in patients with coronary artery disease (CAD). Although qualitative and semiquantitative methods have shown that CMR has high accuracy in diagnosing flow-obstructing lesions in CAD, quantitative ischemic burden is an important variable used in clinical practice for treatment decisions. Quantitative CMR perfusion techniques have evolved significantly, with accuracy comparable with both PET and microsphere evaluation. Routine clinical use of these quantitative techniques has been facilitated by the introduction of automated methods that accelerate the work flow and rapidly generate pixel-based myocardial blood flow maps.

Cardiovascular imaging in cardio-oncology

Cancer therapy may lead to cardiovascular complications and can promote each aspect of cardiac disease manifestation, such as vascular disease including coronary heart disease, myocardial diseases including heart failure, structural heart diseases including valvular heart diseases, and rhythm disorders. All potential complications of cancer therapy onto the cardiovascular system require imaging for diagnostic workup as well as monitoring of therapy. Transthoracic echocardiography (TTE) is the most frequently used tool for assessment of cardiac function during or after cancer therapy in daily clinical routine. With modern techniques like strain analysis, echocardiography allows to detect a variety of cardiac diseases as caused by cancer therapy even at subclinical stages. For further workup, specific imaging techniques including nuclear imaging are needed in a multimodality imaging approach to in detail characterize the underlying pathophysiology and to improve the management of the patients. Therefore, the field of imaging in cardio-oncology is rapidly growing. This review article will give an overview about existing literature regarding the role of imaging in the diagnostic evaluation and management of therapy in patient with prior or ongoing cancer therapy.

Importance of operator training and rest perfusion on the diagnostic accuracy of stress perfusion cardiovascular magnetic resonance

BACKGROUND

Clinical evaluation of stress perfusion cardiovascular magnetic resonance (CMR) is currently based on visual assessment and has shown high diagnostic accuracy in previous clinical trials, when performed by expert readers or core laboratories. However, these results may not be generalizable to clinical practice, particularly when less experienced readers are concerned. Other factors, such as the level of training, the extent of ischemia, and image quality could affect the diagnostic accuracy. Moreover, the role of rest images has not been clarified. The aim of this study was to assess the diagnostic accuracy of visual assessment for operators with different levels of training and the additional value of rest perfusion imaging, and to compare visual assessment and automated quantitative analysis in the assessment of coronary artery disease (CAD).

METHODS

We evaluated 53 patients with known or suspected CAD referred for stress-perfusion CMR. Nine operators (equally divided in 3 levels of competency) blindly reviewed each case twice with a 2-week interval, in a randomised order, with and without rest images. Semi-automated Fermi deconvolution was used for quantitative analysis and estimation of myocardial perfusion reserve as the ratio of stress to rest perfusion estimates.

RESULTS

Level-3 operators correctly identified significant CAD in 83.6% of the cases. This percentage dropped to 65.7% for Level-2 operators and to 55.7% for Level-1 operators (p < 0.001). Quantitative analysis correctly identified CAD in 86.3% of the cases and was non-inferior to expert readers (p = 0.56). When rest images were available, a significantly higher level of confidence was reported (p = 0.022), but no significant differences in diagnostic accuracy were measured (p = 0.34).

CONCLUSIONS

Our study demonstrates that the level of training is the main determinant of the diagnostic accuracy in the identification of CAD. Level-3 operators performed at levels comparable with the results from clinical trials. Rest images did not significantly improve diagnostic accuracy, but contributed to higher confidence in the results. Automated quantitative analysis performed similarly to level-3 operators. This is of increasing relevance as recent technical advances in image reconstruction and analysis techniques are likely to permit the clinical translation of robust and fully automated quantitative analysis into routine clinical practice.

Pixel-wise quantification of myocardial perfusion using spatial Tikhonov regularization

Quantification of myocardial perfusion by contrast-enhanced cardiovascular magnetic resonance imaging (CMR) aims for an observer independent and reproducible risk assessment of cardiovascular disease. Currently, the data used for the pixel-wise analysis of cardiac perfusion are either filtered prior to a fitting procedure, which inherently reduces the spatial resolution of data; or all pixels are considered without any regularization or prior filtering, which yields an unstable fit in the presence of low signal-to-noise ratio. Here, we propose a new pixel-wise analysis based on spatial Tikhonov regularization which exploits the spatial smoothness of the data and ensures accurate quantification even for images with low signal-to-noise ratio. The regularization parameter is determined automatically by an L-curve criterion. We study the performance of our method on a numerical phantom and demonstrate that the method reduces significantly the root-mean square error in the perfusion estimate compared to a non-regularized fit. In patient data our method allows us to recover the myocardial perfusion and to distinguish between healthy and ischemic regions.

Cardiovascular Magnetic Resonance in the Oncology Patient

Patients with or receiving potentially cardiotoxic treatment for cancer are susceptible to developing decrements in left ventricular mass, diastolic function, or systolic function. They may also experience valvular heart disease, pericardial disease, or intracardiac masses. Cardiovascular magnetic resonance may be used to assess cardiac anatomy, structure, and function and to characterize myocardial tissue. This combination of features facilitates the diagnosis and management of disease processes in patients with or those who have survived cancer. This report outlines and describes prior research involving cardiovascular magnetic resonance for assessing cardiovascular disease in patients with or previously having received treatment for cancer.

Absolute quantification of myocardial blood flow

With the increasing availability of positron emission tomography (PET) myocardial perfusion imaging, the absolute quantification of myocardial blood flow (MBF) has become popular in clinical settings. Quantitative MBF provides an important additional diagnostic or prognostic information over conventional visual assessment. The success of MBF quantification using PET/computed tomography (CT) has increased the demand for this quantitative diagnostic approach to be more accessible. In this regard, MBF quantification approaches have been developed using several other diagnostic imaging modalities including single-photon emission computed tomography, CT, and cardiac magnetic resonance. This review will address the clinical aspects of PET MBF quantification and the new approaches to MBF quantification.

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)

Multimodality quantitative assessments of myocardial perfusion using dynamic contrast enhanced magnetic resonance and 15O-labelled water positron emission tomography imaging

Kinetic modelling of myocardial perfusion imaging data allows the absolute quantification of myocardial blood flow (MBF) and can improve the diagnosis and clinical assessment of coronary artery disease (CAD). Positron emission tomography (PET) imaging is considered the reference standard technique for absolute quantification, whilst oxygen-15 (¹⁵O)-water has been extensively implemented for MBF quantification. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has also been used for MBF quantification and showed comparable diagnostic performance against (¹⁵O)-water PET studies. We investigated for the first time the diagnostic performance of two different PET MBF analysis softwares PMOD and Carimas, for obstructive CAD detection against invasive clinical standard methods in 20 patients with known or suspected CAD. Fermi and distributed parameter modelling-derived MBF quantification from DCE-MRI was also compared against (¹⁵O)-water PET, in a subgroup of 6 patients. The sensitivity and specificity for PMOD was significantly superior for obstructive CAD detection in both per vessel (0.83, 0.90) and per patient (0.86, 0.75) analysis, against Carimas (0.75, 0.65), (0.81, 0.70), respectively. We showed strong, significant correlations between MR and PET MBF quantifications (r=0.83-0.92). However, DP and PMOD analysis demonstrated comparable and higher haemodynamic differences between obstructive versus (no, minor or non)-obstructive CAD, against Fermi and Carimas analysis. Our MR method assessments against the optimum PET reference standard technique for perfusion analysis showed promising results in per segment level and can support further multi-modality assessments in larger patient cohorts. Further MR against PET assessments may help to determine their comparative diagnostic performance for obstructive CAD detection.

A comparison of cardiovascular magnetic resonance and single photon emission computed tomography (SPECT) perfusion imaging in left main stem or equivalent coronary artery disease: a CE-MARC substudy

BACKGROUND

Assessment of left main stem (LMS) stenosis has prognostic and therapeutic implications. Data on assessment of LMS disease by cardiovascular magnetic resonance (CMR) and single photon emission computed tomography (SPECT) are limited. CE-MARC is the largest prospective comparison of CMR and SPECT against quantitative invasive coronary angiography (QCA) for detection of coronary artery disease (CAD), and provided the framework for this evaluation. The aims of this study were to compare diagnostic accuracy of visual and quantitative perfusion CMR to SPECT in patients with LMS stable CAD.

METHODS

Fifty-four patients from the CE-MARC study were included: 27 (4%) with significant LMS or LMS-equivalent disease on QCA, and 27 age/sex-matched patients with no flow-limiting CAD. All patients underwent multi-parametric CMR, SPECT and QCA. Performance of visual and quantitative perfusion CMR by Fermi-constrained deconvolution to detect LMS disease was compared with SPECT.

RESULTS

Of 27 patients in the LMS group, 22 (81%) had abnormal CMR and 16 (59%) had abnormal SPECT. All patients with abnormal CMR had abnormal perfusion by visual analysis. CMR demonstrated significantly higher area under the curve (AUC) for detection of disease (0.95; 0.85-0.99) over SPECT (0.63; 0.49-0.76) (p = 0.0001). Global mean stress myocardial blood flow (MBF) by CMR in LMS patients was significantly lower than controls (1.77 ± 0.72 ml/g/min vs. 3.28 ± 1.20 ml/g/min, p < 0.001). MBF of <2.08 ml/g/min had sensitivity of 78% and specificity of 85% for diagnosis of LMS disease, with an AUC (0.87; 0.75-0.94) not significantly different to visual CMR analysis (p = 0.18), and more accurate than SPECT (p = 0.003).

CONCLUSION

Visual stress perfusion CMR had higher diagnostic accuracy than SPECT to detect LMS disease. Quantitative perfusion CMR had similar performance to visual CMR perfusion analysis.

Quantitative Assessment of Coronary Microvascular Function: Dynamic Single-Photon Emission Computed Tomography, Positron Emission Tomography, Ultrasound, Computed Tomography, and Magnetic Resonance Imaging

A healthy, functional microcirculation in combination with nonobstructed epicardial coronary arteries is the prerequisite of normal myocardial perfusion. Quantitative assessment in myocardial perfusion and determination of absolute myocardial blood flow can be achieved noninvasively using dynamic imaging with multiple imaging modalities. Extensive evidence supports the clinical value of noninvasively assessing indices of coronary flow for diagnosing coronary microvascular dysfunction; in certain diseases, the degree of coronary microvascular impairment carries important prognostic relevance. Although, currently positron emission tomography is the most commonly used tool for the quantification of myocardial blood flow, other modalities, including single-photon emission computed tomography, computed tomography, magnetic resonance imaging, and myocardial contrast echocardiography, have emerged as techniques with great promise for determination of coronary microvascular dysfunction. The following review will describe basic concepts of coronary and microvascular physiology, review available modalities for dynamic imaging for quantitative assessment of coronary perfusion and myocardial blood flow, and discuss their application in distinct forms of coronary microvascular dysfunction.

Assessment of stable coronary artery disease by cardiovascular magnetic resonance imaging: Current and emerging techniques

Coronary artery disease (CAD) is a leading cause of death and disability worldwide. Cardiovascular magnetic resonance (CMR) is established in clinical practice guidelines with a growing evidence base supporting its use to aid the diagnosis and management of patients with suspected or established CAD. CMR is a multi-parametric imaging modality that yields high spatial resolution images that can be acquired in any plane for the assessment of global and regional cardiac function, myocardial perfusion and viability, tissue characterisation and coronary artery anatomy, all within a single study protocol and without exposure to ionising radiation. Advances in technology and acquisition techniques continue to progress the utility of CMR across a wide spectrum of cardiovascular disease, and the publication of large scale clinical trials continues to strengthen the role of CMR in daily cardiology practice. This article aims to review current practice and explore the future directions of multi-parametric CMR imaging in the investigation of stable CAD.

Cardiac Imaging in Heart Failure with Comorbidities

Imaging modalities stand at the frontiers for progress in congestive heart failure (CHF) screening, risk stratification and monitoring. Advancements in echocardiography (ECHO) and Magnetic Resonance Imaging (MRI) have allowed for improved tissue characterizations, cardiac motion analysis, and cardiac performance analysis under stress. Common cardiac comorbidities such as hypertension, metabolic syndromes and chronic renal failure contribute to cardiac remodeling, sharing similar pathophysiological mechanisms starting with interstitial changes, structural changes and finally clinical CHF. These imaging techniques can potentially detect changes earlier. Such information could have clinical benefits for screening, planning preventive therapies and risk stratifying patients. Imaging reports have often focused on traditional measures without factoring these novel parameters. This review is aimed at providing a synopsis on how we can use this information to assess and monitor improvements for CHF with comorbidities.

Quantitative assessment of myocardial blood flow in coronary artery disease by cardiovascular magnetic resonance: comparison of Fermi and distributed parameter modeling against invasive methods

BACKGROUND

Mathematical modeling of perfusion cardiovascular magnetic resonance (CMR) data allows absolute quantification of myocardial blood flow and can potentially improve the diagnosis and prognostication of obstructive coronary artery disease (CAD), against the current clinical standard of visual assessments. This study compares the diagnostic performance of distributed parameter modeling (DP) against the standard Fermi model, for the detection of obstructive CAD, in per vessel against per patient analysis.

METHODS

A pilot cohort of 28 subjects (24 included in the final analysis) with known or suspected CAD underwent adenosine stress-rest perfusion CMR at 3T. Data were analysed using Fermi and DP modeling against invasive coronary angiography and fractional flow reserve, acquired in all subjects. Obstructive CAD was defined as luminal stenosis of ≥70 % alone, or luminal stenosis ≥50 % and fractional flow reserve ≤0.80.

RESULTS

On ROC analysis, DP modeling outperformed the standard Fermi model, in per vessel and per patient analysis. In per patient analysis, DP modeling-derived myocardial blood flow at stress demonstrated the highest sensitivity and specificity (0.96, 0.92) in detecting obstructive CAD, against Fermi modeling (0.78, 0.88) and visual assessments (0.79, 0.88), respectively.

CONCLUSIONS

DP modeling demonstrated consistently increased diagnostic performance against Fermi modeling and showed that it may have merit for stratifying patients with at least one vessel with obstructive CAD.

TRIAL REGISTRATION

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov NCT01368237 Registered 6 of June 2011. URL: https://clinicaltrials.gov/ct2/show/NCT01368237.

Update on Computed Tomography Myocardial Perfusion Imaging

PURPOSE OF REVIEW

Computed tomography (CT) coronary angiography is a well-validated non-invasive technique for accurate and expedient diagnosis of coronary artery disease (CAD). However, a limitation of coronary CT angiography (CCTA) is its limited capability to identify physiologically significant stenoses, which may eventuate the need for further functional testing. Stress CT myocardial perfusion imaging (CT-MPI) is an emerging technique that has the ability to identify flow-limiting stenoses.

RECENT FINDINGS

The combination of CCTA coronary and CT-MPI has transformed the modality from a tool to assess anatomy and morphology to a modality capable of simultaneous assessment of coronary stenoses and their physiologic significance. A growing number of studies have demonstrated the feasibility and diagnostic accuracy of CT-MPI in comparison to a number of reference standard modalities for CAD diagnosis, including single-photon emission CT, cardiovascular magnetic resonance imaging, and invasive coronary angiography with and without fractional flow-reserve testing.

SUMMARY

While there is still a need for consensus regarding acquisition techniques as well as analysis and interpretation of CT-MPI, with further validation, it is likely to become a powerful adjunctive tool to CCTA in the management of patients with suspected coronary disease.

Investigation into diagnostic accuracy of common strategies for automated perfusion motion correction

Respiratory motion is a significant obstacle to the use of quantitative perfusion in clinical practice. Increasingly complex motion correction algorithms are being developed to correct for respiratory motion. However, the impact of these improvements on the final diagnosis of ischemic heart disease has not been evaluated. The aim of this study was to compare the performance of four automated correction methods in terms of their impact on diagnostic accuracy. Three strategies for motion correction were used: (1) independent translation correction for all slices, (2) translation correction for the basal slice with transform propagation to the remaining two slices assuming identical motion in the remaining slices, and (3) rigid correction (translation and rotation) for the basal slice. There were no significant differences in diagnostic accuracy between the manual and automatic motion-corrected datasets ([Formula: see text]). The area under the curve values for manual motion correction and automatic motion correction were 0.93 and 0.92, respectively. All of the automated motion correction methods achieved a comparable diagnostic accuracy to manual correction. This suggests that the simplest automated motion correction method (method 2 with translation transform for basal location and transform propagation to the remaining slices) is a sufficiently complex motion correction method for use in quantitative myocardial perfusion.

Cardiovascular Imaging: The Past and the Future, Perspectives in Computed Tomography and Magnetic Resonance Imaging

Today's noninvasive imaging of the cardiovascular system has revolutionized the approach to various diseases and has substantially affected prognostic information. Cardiovascular magnetic resonance (MR) and computed tomographic (CT) imaging are at center stage of these approaches, although 5 decades ago, these technologies were unheard of. Both modalities had their inception in the 1970s with a primary focus on noncardiovascular applications. The technical development of the various decades, however, substantially pushed the envelope for cardiovascular MR and CT applications. Within the past 10-15 years, MR and CT technologies have pushed each other in cardiac applications; and without the "rival" modality, neither one would likely not have reached its potential today. This view on the history of MR and CT in the field of cardiovascular applications provides insight into the story of success of applications that once have been ideas only but are at prime time today.