Assessment of advanced coronary artery disease: advantages of quantitative cardiac magnetic resonance perfusion analysis

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.

Arterial Input Function (AIF) Correction Using AIF Plus Tissue Inputs with a Bi-LSTM Network

Background: The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time-concentration curve of a contrast agent. Inaccurate AIFs can significantly affect perfusion quantification. Purpose: When only saturated and biased AIFs are measured, this work investigates multiple ways of leveraging tissue curve information, including using AIF + tissue curves as inputs and optimizing the loss function for deep neural network training. Methods: Simulated data were generated using a 12-parameter AIF mathematical model for the AIF. Tissue curves were created from true AIFs combined with compartment-model parameters from a random distribution. Using Bloch simulations, a dictionary was constructed for a saturation-recovery 3D radial stack-of-stars sequence, accounting for deviations such as flip angle, T2* effects, and residual longitudinal magnetization after the saturation. A preliminary simulation study established the optimal tissue curve number using a bidirectional long short-term memory (Bi-LSTM) network with just AIF loss. Further optimization of the loss function involves comparing just AIF loss, AIF with compartment-model-based parameter loss, and AIF with compartment-model tissue loss. The optimized network was examined with both simulation and hybrid data, which included in vivo 3D stack-of-star datasets for testing. The AIF peak value accuracy and ktrans results were assessed. Results: Increasing the number of tissue curves can be beneficial when added tissue curves can provide extra information. Using just the AIF loss outperforms the other two proposed losses, including adding either a compartment-model-based tissue loss or a compartment-model parameter loss to the AIF loss. With the simulated data, the Bi-LSTM network reduced the AIF peak error from -23.6 ± 24.4% of the AIF using the dictionary method to 0.2 ± 7.2% (AIF input only) and 0.3 ± 2.5% (AIF + ten tissue curve inputs) of the network AIF. The corresponding ktrans error was reduced from -13.5 ± 8.8% to -0.6 ± 6.6% and 0.3 ± 2.1%. With the hybrid data (simulated data for training; in vivo data for testing), the AIF peak error was 15.0 ± 5.3% and the corresponding ktrans error was 20.7 ± 11.6% for the AIF using the dictionary method. The hybrid data revealed that using the AIF + tissue inputs reduced errors, with peak error (1.3 ± 11.1%) and ktrans error (-2.4 ± 6.7%). Conclusions: Integrating tissue curves with AIF curves into network inputs improves the precision of AI-driven AIF corrections. This result was seen both with simulated data and with applying the network trained only on simulated data to a limited in vivo test dataset.

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.

Assessment of Myocardial Viability and Risk Stratification in Coronary Chronic Total Occlusion: A Qualitative and Quantitative Stress Cardiac MRI Study

BACKGROUND

Indicators for assessing myocardial viability and risk stratification in patients with coronary chronic total occlusion (CTO) are still in the research stage.

PURPOSE

To use stress-MRI to assess myocardial function, blood perfusion, and viability and to explore their relationship with collateral circulation.

STUDY TYPE

Prospective.

SUBJECTS

Fifty-one patients with CTO in at least one major artery confirmed by X-ray coronary angiography (male: 46; age 55.2 ± 10.8 years).

FIELD STRENGTH/SEQUENCE

3.0T; TurboFlash, balanced steady-state free precession cine, and phase-sensitive inversion recovery sequences.

ASSESSMENT

Stress-MRI was used to obtain qualitative and quantitative parameters of segmental myocardium. Myocardial segments supplied by CTO target vessels were grouped according to the degree of collateral circulation assessed by radiographic coronary angiography (no/mild, moderate, or good). Depending on qualitative stress perfusion assessment and late gadolinium enhancement (LGE) extent, segments were also categorized as negative, viable, or trans-infarcted.

STATISTICAL TESTS

Independent sample Student's t-test, one-way analysis of variance (ANOVA) test, Mann-Whitney U test, Kruskal-Wallis test, Spearman correlation coefficient (r). P < 0.05 was considered statistically significant.

RESULTS

A total of 334 segments were supplied by CTO target vessels. The radial strain (RS), circumferential strain (CS), longitudinal strain (LS) of the negative, viable, and trans-infarcted regions showed a significant and stepwise impairment. Myocardial blood flow at rest was positively correlated with RS, CS, and LS (r = 0.42, 0.43, 0.38, respectively). Among the different collateral circulation, there were no significant differences in RS, CS, LS, and LGE volume (P = 0.788, 0.562, 0.122, 0.170, respectively), and there were also no statistically significant differences in the proportions of negative, viable, and trans-infarcted regions (P = 0.372).

DATA CONCLUSION

Myocardial perfusion obtained by stress-MRI combined with strain and LGE may comprehensively evaluate myocardial function and viability, and has potential to facilitate risk stratification of CTO.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

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.

Clinical and Translational Imaging and Sensing of Diabetic Microangiopathy: A Narrative Review

Microvascular changes in diabetes affect the function of several critical organs, such as the kidneys, heart, brain, eye, and skin, among others. The possibility of detecting such changes early enough in order to take appropriate actions renders the development of appropriate tools and techniques an imperative need. To this end, several sensing and imaging techniques have been developed or employed in the assessment of microangiopathy in patients with diabetes. Herein, we present such techniques; we provide insights into their principles of operation while discussing the characteristics that make them appropriate for such use. Finally, apart from already established techniques, we present novel ones with great translational potential, such as optoacoustic technologies, which are expected to enter clinical practice in the foreseeable future.

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.

The Non-Invasive Diagnosis of Chronic Coronary Syndrome: A Focus on Stress Computed Tomography Perfusion and Stress Cardiac Magnetic Resonance

Coronary artery disease is still a major cause of death and morbidity worldwide. In the setting of chronic coronary disease, demonstration of inducible ischemia is mandatory to address treatment. Consequently, scientific and technological efforts were made in response to the request for non-invasive diagnostic tools with better sensitivity and specificity. To date, clinicians have at their disposal a wide range of stress-imaging techniques. Among others, stress cardiac magnetic resonance (S-CMR) and computed tomography perfusion (CTP) techniques both demonstrated their diagnostic efficacy and prognostic value in clinical trials when compared to other non-invasive ischemia-assessing techniques and invasive fractional flow reserve measurement techniques. Standardized protocols for both S-CMR and CTP usually imply the administration of vasodilator agents to induce hyperemia and contrast agents to depict perfusion defects. However, both methods have their own limitations, meaning that optimizing their performance still requires a patient-tailored approach. This review focuses on the characteristics, drawbacks, and future perspectives of these two techniques.

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.

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.

Quantifying Myocardial Blood Flow and Resistance Using 4D-Flow Cardiac Magnetic Resonance Imaging

Background

Ischaemia with nonobstructive coronary arteries is most commonly caused by coronary microvascular dysfunction but remains difficult to diagnose without invasive testing. Myocardial blood flow (MBF) can be quantified noninvasively on stress perfusion cardiac magnetic resonance (CMR) or positron emission tomography but neither is routinely used in clinical practice due to practical and technical constraints. Quantification of coronary sinus (CS) flow may represent a simpler method for CMR MBF quantification. 4D flow CMR offers comprehensive intracardiac and transvalvular flow quantification. However, it is feasibility to quantify MBF remains unknown.

Methods

Patients with acute myocardial infarction (MI) and healthy volunteers underwent CMR. The CS contours were traced from the 2-chamber view. A reformatted phase contrast plane was generated through the CS, and flow was quantified using 4D flow CMR over the cardiac cycle and normalised for myocardial mass. MBF and resistance (MyoR) was determined in ten healthy volunteers, ten patients with myocardial infarction (MI) without microvascular obstruction (MVO), and ten with known MVO.

Results

MBF was quantified in all 30 subjects. MBF was highest in healthy controls (123.8 ± 48.4 mL/min), significantly lower in those with MI (85.7 ± 30.5 mL/min), and even lower in those with MI and MVO (67.9 ± 29.2 mL/min/) (P < 0.01 for both differences). Compared with healthy controls, MyoR was higher in those with MI and even higher in those with MI and MVO (0.79 (±0.35) versus 1.10 (±0.50) versus 1.50 (±0.69), P=0.02).

Conclusions

MBF and MyoR can be quantified from 4D flow CMR. Resting MBF was reduced in patients with MI and MVO.

Relation of Myocardial Perfusion Reserve and Left Ventricular Ejection Fraction in Ischemic and Nonischemic Cardiomyopathy

Quantification of myocardial perfusion reserve (MPR) using vasodilator stress cardiac magnetic resonance is increasingly used to detect coronary artery disease. However, MPR can also be altered because of changes in microvascular function. We aimed to determine whether MPR can distinguish between ischemic cardiomyopathy (IC) secondary to coronary artery disease and non-IC (NIC) with microvascular dysfunction and no underlying epicardial coronary disease. A total of 60 patients (mean age 65 ± 14 years, 30% women), including 31 with IC and 29 with NIC, were identified from a pre-existing vasodilator stress cardiac magnetic resonance registry. Short-axis cine slices were used to measure left ventricular ejection fraction (LVEF) using the Simpson method of disks. MPR index (MPRi) was determined from first-pass myocardial perfusion images during stress and rest using the upslope ratio, normalized for the arterial input and corrected for rate pressure product. Patients in both groups were divided into subgroups of LVEF ≤35% and LVEF >35%. Differences in MPRi between the subgroups were examined. MPRi was moderately correlated with LVEF in patients with NIC (r = 0.53, p = 0.03), whereas the correlation in patients with IC was lower (r = 0.32, p = 0.22). Average LVEF in NIC and IC was 34% ± 8% and 35% ± 8%, respectively (p = 0.63). MPRi was not significantly different in IC compared with NIC (1.17 [0.88 to 1.61] vs 1.23 [1.07 to 1.66], p = 0.41), including the subgroups of LVEF (IC: 1.20 ± 0.56 vs NIC: 1.15 ± 0.24, p = 0.75 for LVEF ≤35% and IC: 1.35 ± 0.44 vs NIC: 1.58 ± 0.50, p = 0.19 for LVEF >35%). However, MPRi was significantly lower in patients with LVEF ≤35% compared with those with LVEF>35% (1.17 ± 0.40 vs 1.47 ± 0.47, p = 0.01). Similar difference between LVEF groups was noted in the patients with NIC (1.15 ± 0.24 vs 1.58 ± 0.50, p = 0.006) but not in the patients with IC (1.20 ± 0.56 vs 1.35 ± 0.44, p = 0.42). MPRi can be abnormal in the presence of left ventricular dysfunction with nonischemic etiology. This is a potential pitfall to consider when using this approach to detect ischemia because of epicardial coronary disease using myocardial perfusion imaging.

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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2D high resolution vs. 3D whole heart myocardial perfusion cardiovascular magnetic resonance

AIMS

Developments in myocardial perfusion cardiovascular magnetic resonance (CMR) allow improvements in spatial resolution and/or myocardial coverage. Whole heart coverage may provide the most accurate assessment of myocardial ischaemic burden, while high spatial resolution is expected to improve detection of subendocardial ischaemia. The objective of this study was to compare myocardial ischaemic burden as depicted by 2D high resolution and 3D whole heart stress myocardial perfusion in patients with coronary artery disease.

METHODS AND RESULTS

Thirty-eight patients [age 61 ± 8 (21% female)] underwent 2D high resolution (spatial resolution 1.2 mm2) and 3D whole heart (in-plane spatial resolution 2.3 mm2) stress CMR at 3-T in randomized order. Myocardial ischaemic burden (%) was visually quantified as perfusion defect at peak stress perfusion subtracted from subendocardial myocardial scar and expressed as a percentage of the myocardium. Median myocardial ischaemic burden was significantly higher with 2D high resolution compared with 3D whole heart [16.1 (2.0-30.6) vs. 13.4 (5.2-23.2), P = 0.004]. There was excellent agreement between myocardial ischaemic burden (intraclass correlation coefficient 0.81; P < 0.0001), with mean ratio difference between 2D high resolution vs. 3D whole heart 1.28 ± 0.67 (95% limits of agreement -0.03 to 2.59). When using a 10% threshold for a dichotomous result for presence or absence of significant ischaemia, there was moderate agreement between the methods (κ = 0.58, P < 0.0001).

CONCLUSION

2D high resolution and 3D whole heart myocardial perfusion stress CMR are comparable for detection of ischaemia. 2D high resolution gives higher values for myocardial ischaemic burden compared with 3D whole heart, suggesting that 2D high resolution is more sensitive for detection of ischaemia.

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.

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

Purpose

The purpose of this study was to determine an optimal saturation‐recovery time (TS) for minimizing the underestimation of arterial input function (AIF) in quantitative cardiac perfusion MRI without multiple gadolinium injections per subject.

Methods

We scanned 18 subjects (mean age = 59 ± 14 years, 9/9 males/females) to acquire resting perfusion data and 1 additional subject (age = 38 years, male) to obtain stress‐rest perfusion data using a 5‐fold accelerated pulse sequence with radial k‐space sampling and applied k‐space weighted image contrast (KWIC) filters on the same k‐space data to retrospectively reconstruct five AIF images with effective TS ranging from 10 to 21.2 ms (2.8 ms steps). Undersampled images were reconstructed using a compressed sensing framework with temporal‐total‐variation and temporal‐principal‐component as 2 orthogonal sparsifying transforms. The image processing steps included, same motion correction across five different AIF images, signal normalization by the proton‐density‐weighted‐image, signal‐to‐T₁ conversion using a Bloch equation, T₁‐to‐gadolinium‐concentration conversion assuming fast water exchange, T₂* correction to the AIF, and gadolinium‐concentration to myocardial blood flow (MBF) conversion based on a Fermi model.

Results

Among five TS values, the shortest TS (10 ms) produced significantly (P < 0.05) higher peak AIF and lower resting MBF (13.73 mM, 0.73 mL g⁻¹ min⁻¹) than 12.8 ms (11.24 mM, 0.89 mL g⁻¹ min⁻¹), 15.6 ms (9.56 mM, 1.05 mL g⁻¹ min⁻¹), 18.4 ms (8.55 mM, 1.17 mL g⁻¹ min⁻¹), and 21.2 ms (7.95 mM, 1.27 mL g⁻¹ min⁻¹). Similarly, shorter TS reduced underestimation of AIF (or overestimation of MBF) for both during stress and at rest, but this effect was canceled in myocardial‐perfusion‐reserve (MPR).

Conclusion

This study demonstrates that TS of 10 ms reduces the underestimation of AIF and, hence, the overestimation of MBF compared with longer TS values (12.8‐21.2 ms).

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.

Quantification of balanced SSFP myocardial perfusion imaging at 1.5 T: Impact of the reference image

PURPOSE

To investigate the use of a high flip-angle (HFA) balanced SSFP (bSSFP) reference image (in comparison to conventional proton density [PD]-weighted reference images) for conversion of bSSFP myocardial perfusion images into dynamic T1 maps for improved myocardial blood flow (MBF) quantification at 1.5 T.

METHODS

The HFA-bSSFP (flip angle [FA] = 50°), PD gradient-echo (PD-GRE; FA = 5°), and PD-bSSFP (FA = 8°) reference images were acquired before a dual-sequence bSSFP perfusion acquisition. Simulations were used to study accuracy and precision of T1 and MBF quantification using the three techniques. The accuracy and precision of T1 , and the precision and intersegment variability of MBF were compared among the three techniques in 8 patients under rest conditions.

RESULTS

In simulations, HFA-bSSFP demonstrated improved T1 /MBF precision (higher T1 /MBF SD of 30%-80%/50%-100% and 30%-90%/60%-115% for PD-GRE and PD-bSSFP, respectively). Proton density-GRE and PD-bSSFP were more sensitive to effective FA than HFA-bSSFP (maximum T1 /MBF errors of 13%/43%, 20%/43%, and 1%/3%, respectively). Sensitivity of all techniques (defined as T1 /MBF errors) to native T1 , native T2 , and effective saturation efficiency were negligible (<1%/<1%), moderate (<14%/<19%), and high (<63%/<94%), respectively. In vivo, no difference in T1 accuracy was observed among HFA-bSSFP, PD-GRE, and PD-bSSFP (-9 ± 44 ms vs -28 ± 55 ms vs -22 ± 71 ms, respectively; p > .08). The HFA-bSSFP led to improved T1 /MBF precision (T1 /MBF SD: 41 ± 19 ms/0.24 ± 0.08 mL/g/min vs PD-GRE: 48 ± 20 ms/0.29 ± 0.09 mL/g/min and PD-bSSFP: 59 ± 23 ms/0.33 ± 0.11 mL/g/min; p ≤ .02) and lower MBF intersegment variability (0.14 ± 0.09 mL/g/min vs PD-GRE: 0.21 ± 0.09 mL/g/min and PD-bSSFP: 0.20 ± 0.10 mL/g/min; p ≤ .046).

CONCLUSION

We have demonstrated the feasibility of using a HFA-bSSFP reference image for MBF quantification of bSSFP perfusion imaging at 1.5 T. Results from simulations demonstrate that the HFA-bSSFP reference image results in improved precision and reduced sensitivity to effective FA compared with conventional techniques using a PD reference image. Preliminary in vivo data acquired at rest also demonstrate improved precision and intersegment variability using the HFA-bSSFP technique compared with PD techniques; however, a clinical study in patients with coronary artery disease under stress conditions is required to determine the clinical significance of this finding.

Imaging techniques for the assessment of adverse cardiac remodeling in metabolic syndrome

Metabolic syndrome (MetS) includes different metabolic conditions (i.e. abdominal obesity, impaired glucose tolerance, hypertriglyceridemia, decreased HDL cholesterol, and/or hypertension) that concour in the development of cardiovascular disease and diabetes. MetS individuals often show adverse cardiac remodeling and myocardial dysfunction even in the absence of overt coronary artery disease or valvular affliction. Diastolic impairment and hypertrophy are hallmarks of MetS-related cardiac remodeling and represent the leading cause of heart failure with preserved ejection fraction (HFpEF). Altered cardiomyocyte function, increased neurohormonal tone, interstitial fibrosis, coronary microvascular dysfunction, and a myriad of metabolic abnormalities have all been implicated in the development and progression of adverse cardiac remodeling related to MetS. However, despite the enormous amount of literature produced on this argument, HF remains a leading cause of morbidity and mortality in such population. The early detection of initial adverse cardiac remodeling would enable the optimal implementation of effective therapies aiming at preventing the progression of the disease to the symptomatic phase. Beyond conventional imaging techniques, such as echocardiography, cardiac tomography, and magnetic resonance, novel post-processing tools and techniques provide information on the biological processes that underlie metabolic heart disease. In this review, we summarize the pathophysiology of MetS-related cardiac remodeling and illustrate the relevance of state-of-the-art multimodality cardiac imaging to identify and quantify the degree of myocardial involvement, prognosticate long-term clinical outcome, and potentially guide therapeutic strategies.

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.

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.

Spatio-temporal multi-task network cascade for accurate assessment of cardiac CT perfusion

The assessment of myocardial perfusion has become increasingly important in the early diagnosis of coronary artery disease. Currently, the process of perfusion assessment is time-consuming and subjective. Although automated methods by threshold processing have been proposed, they cannot obtain an accurate perfusion assessment. Thus, there is a great clinical demand to obtain a rapid and accurate assessment of myocardial perfusion through a standard procedure using an automated algorithm. In this work, we present a spatio-temporal multi-task network cascade (ST-MNC) to provide an accurate and robust assessment of myocardial perfusion. The proposed network captures patch-based spatio-temporal representations for each pixel through a spatio-temporal encoder-decoder network. Then the multi-task network cascade uses spatio-temporal representations as shared features to predict various perfusion parameters and myocardial ischemic regions. Extensive experiments on CT images of 232 subjects demonstrate ST-MNC could produce a good approximation for perfusion parameters and an accurate classification for ischemic regions. These results show that our proposed method can provide a fast and accurate assessment of myocardial perfusion.

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.

What Is the Clinical Impact of Stress CMR After the ISCHEMIA Trial?

After progressively receding for decades, cardiovascular mortality due to coronary artery disease has recently increased, and the associated healthcare costs are projected to double by 2030. While the 2019 European Society of Cardiology guidelines for chronic coronary syndromes recommend non-invasive cardiac imaging for patients with suspected coronary artery disease, the impact of non-invasive imaging strategies to guide initial coronary revascularization and improve long-term outcomes is still under debate. Recently, the ISCHEMIA trial has highlighted the fundamental role of optimized medical therapy and the lack of overall benefit of early invasive strategies at a median follow-up of 3.2 years. However, sub-group analyses excluding procedural infarctions with longer follow-ups of up to 5 years have suggested that patients undergoing revascularization had better outcomes than those receiving medical therapy alone. A recent sub-study of ISCHEMIA in patients with heart failure or reduced left ventricular ejection fraction (LVEF <45%) indicated that revascularization improved clinical outcomes compared to medical therapy alone. Furthermore, other large observational studies have suggested a favorable prognostic impact of coronary revascularization in patients with severe inducible ischemia assessed by stress cardiovascular magnetic resonance (CMR). Indeed, some data suggest that stress CMR-guided revascularization assessing the extent of the ischemia could be useful in identifying patients who would most benefit from invasive procedures such as myocardial revascularization. Interestingly, the MR-INFORM trial has recently shown that a first-line stress CMR-based non-invasive assessment was non-inferior in terms of outcomes, with a lower incidence of coronary revascularization compared to an initial invasive approach guided by fractional flow reserve in patients with stable angina. In the present review, we will discuss the current state-of-the-art data on the prognostic value of stress CMR assessment of myocardial ischemia in light of the ISCHEMIA trial results, highlighting meaningful sub-analyses, and still unanswered opportunities of this pivotal study. We will also review the available evidence for the potential clinical application of quantifying the extent of ischemia to stratify cardiovascular risk and to best guide invasive and non-invasive treatment strategies.

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.

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

PURPOSE

To develop and evaluate a flexible, Bloch-equation based framework for retrospective T 2 ∗ correction to the arterial input function (AIF) obtained with quantitative cardiac perfusion pulse sequences.

METHODS

Our framework initially calculates the gadolinium concentration [Gd] based on T₁ measurements alone. Next, T 2 ∗ is estimated from this initial calculation of [Gd] while assuming fast water exchange and using the literature native T₂ and static magnetic field variation (ΔB₀ ) values. Finally, the [Gd] is recalculated after performing T 2 ∗ correction to the Bloch equation signal model. Using this approach, we performed T 2 ∗ correction to historical phantom and in vivo, dual-imaging perfusion data sets from 3 different patient groups obtained using different pulse sequences and imaging parameters. Images were processed to quantify both the AIF and resting myocardial blood flow (MBF). We also performed a sensitivity analysis of our T 2 ∗ correction to ±20% variations in native T₂ and ΔB₀ .

RESULTS

Compared with the ground truth [Gd] of phantom, the normalized root-means-square-error (NRMSE) in measured [Gd] was 5.1%, 1.3%, and 0.6% for uncorrected, our corrected, and Kellman's corrected, respectively. For in vivo data, both the peak AIF (7.0 ± 3.0 mM vs. 8.6 ± 7.1 mM, 7.2 ± 0.9 mM vs. 8.6 ± 1.7 mM, 7.7 ± 1.8 mM vs. 10.3 ± 5.1 mM, P < .001) and resting MBF (1.3 ± 0.1 mL/g/min vs. 1.1 ± 0.1 mL/g/min, 1.3 ± 0.1 mL/g/min vs. 1.1 ± 0.1 mL/g/min, 1.2 ± 0.1 mL/g/min vs. 0.9 ± 0.1 mL/g/min, P < .001) values were significantly different between uncorrected and corrected for all 3 patient groups. Both the peak AIF and resting MBF values varied by <5% over the said variations in native T₂ and ΔB₀ .

CONCLUSION

Our theoretical framework enables retrospective T 2 ∗ correction to the AIF obtained with dual-imaging, cardiac perfusion pulse sequences.

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

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

Stress myocardial perfusion with qualitative magnetic resonance and quantitative dynamic computed tomography: comparison of diagnostic performance and incremental value over coronary computed tomography angiography

AIMS

Assessment of haemodynamically significant coronary artery disease (CAD) using cardiovascular magnetic resonance (CMR) imaging perfusion or dynamic stress myocardial perfusion imaging by computed tomography (CT perfusion) may aid patient selection for invasive coronary angiography (ICA). We evaluated the diagnostic performance and incremental value of qualitative CMR perfusion and quantitative CT perfusion complementary to cardiac computed tomography angiography (CCTA) for the diagnosis of haemodynamically significant CAD using fractional flow reserve (FFR) and quantitative coronary angiography (QCA) as reference standard.

METHODS AND RESULTS

CCTA, qualitative visual CMR perfusion, visual CT perfusion, and quantitative relative myocardial blood flow (CT-MBF) were performed in patients with stable angina pectoris. FFR was measured in coronary vessels with stenosis visually estimated between 30% and 90% diameter reduction on ICA. Haemodynamically significant CAD was defined as FFR <0.80, or QCA ≥80% in those cases where FFR could not be performed. A total of 218 vessels from 93 patients were assessed. An optimal cut-off of 0.72 for relative CT-MBF was determined. The diagnostic performances (area under the receiver-operating characteristics curves, 95% CI) of visual CMR perfusion (0.84, 0.77-0.90) and relative CT-MBF (0.86, 0.81-0.92) were comparable and outperformed visual CT perfusion (0.64, 0.57-0.71). In combination with CCTA ≥50%, CCTA + visual CMR perfusion (0.91, 0.86-0.96), CCTA + relative CT-MBF (0.92, 0.88-0.96), and CCTA + visual CT perfusion (0.82, 0.75-0.90) improved discrimination compared with CCTA alone (all P < 0.05).

CONCLUSION

Visual CMR perfusion and relative CT-MBF outperformed visual CT perfusion and provided incremental discrimination compared with CCTA alone for the diagnosis of haemodynamically significant CAD.

Comparability of compressed sensing-based gradient echo perfusion sequence SPARSE and conventional gradient echo sequence in assessment of myocardial ischemia

PURPOSE

Stress perfusion imaging plays a major role in non-invasive detection of coronary artery disease. We compared a compressed sensing-based and a conventional gradient echo perfusion sequence with regard to image quality and diagnostic performance.

METHOD

Patients sent for coronary angiography due to pathologic stress perfusion CMR were recruited. All patients underwent two adenosine stress CMR using conventional TurboFLASH and prototype SPARSE sequence as well as quantitative coronary angiography with fractional flow reserve (FFR) within 6 weeks. Coronary angiography was considered gold standard with FFR < 0.75 or visual stenosis >90 % for identification of myocardial ischemia. Diagnostic performance of perfusion imaging was assessed in basal, mid-ventricular and apical slices by quantification of myocardial perfusion reserve (MPR) analysis utilizing the signal upslope method and a deconvolution technique using the fermi function model.

RESULTS

23 patients with mean age of 69.6 ± 8.9 years were enrolled. 46 % were female. Image quality was similar in conventional TurboFLASH sequence and SPARSE sequence (2.9 ± 0.5 vs 3.1 ± 0.7, p = 0,06). SPARSE sequence showed higher contrast-to-noise ratio (52.1 ± 27.4 vs 40.5 ± 17.6, p < 0.01) and signal-to-noise ratio (15.6 ± 6.2 vs 13.2 ± 4.2, p < 0.01) than TurboFLASH sequence. Dark-rim artifacts occurred less often with SPARSE (9 % of segments) than with TurboFLASH (23 %). In visual assessment of perfusion defects, SPARSE sequence detected less false-positive perfusion defects (n = 1) than TurboFLASH sequence (n = 3). Quantitative perfusion analysis on segment basis showed equal detection of perfusion defects for TurboFLASH and SPARSE with both upslope MPR analysis (TurboFLASH 0.88 ± 0.18; SPARSE 0.77 ± 0.26; p = 0.06) and fermi function model (TurboFLASH 0.85 ± 0.24; SPARSE 0.76 ± 0.30; p = 0.13).

CONCLUSIONS

Compressed sensing perfusion imaging using SPARSE sequence allows reliable detection of myocardial ischemia.

Stress cardiac MRI in stable coronary artery disease

PURPOSE OF REVIEW

Non-invasive testing is often the first step in the evaluation of stable coronary artery disease (CAD). Stress cardiac magnetic resonance imaging (CMR) is an established modality with high diagnostic accuracy and prognostic value. This review will focus on the recent advances in understanding how stress CMR can help guide patient care.

RECENT FINDINGS

Diagnostic accuracy of stress CMR has been validated against coronary angiography with fractional flow reserve (FFR) in patients with stable CAD. Large registry data have shown stress CMR to have important prognostic importance and that its cost-effectiveness compares favorably to alternatives. In patients with stable CAD, guidance using a CMR based strategy led to equivalent outcomes when compared to coronary angiography with FFR.

SUMMARY

In persons with stable CAD, Stress CMR is an accurate and cost-effective imaging modality that should be considered in patients at intermediate pre-test probability of CAD. Prognostic studies have shown it to have excellent negative predictive value and that it can safely serve as a "gatekeeper" for invasive angiography.

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.

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.

Frequency of Coronary Microvascular Dysfunction and Diffuse Myocardial Fibrosis (Measured by Cardiovascular Magnetic Resonance) in Patients With Heart Failure and Preserved Left Ventricular Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is frequently accompanied by co-morbidities and a systemic proinflammatory state, resulting in coronary microvascular dysfunction (CMD), as well as myocardial fibrosis. The purpose of this study is to examine the relation between myocardial perfusion reserve (MPR) and diffuse myocardial fibrosis in patients with HFpEF using cardiovascular magnetic resonance. A single center study was performed in 19 patients with clinical HFpEF and 15 healthy control subjects who underwent quantitative first-pass perfusion imaging to calculate global MPR. T1 mapping was used to assess fibrosis and to calculate extracellular volume. Spiral cine displacement encoded stimulated echo was used to calculate myocardial strain. Comprehensive 2D echocardiograms with speckle tracking, cardiopulmonary exercise testing, and brain natriuretic peptide levels were also obtained. In patients with HFpEF, mean left ventricular EF was 61% ± 9% and left ventricular mass index 45 ± 12 g/m². Compared with controls, HFpEF patients had reduced global MPR (2.29 ± 0.64 vs 3.38 ± 0.76, p = 0.002) and VO₂ max (16.5 ± 6.8 vs 30.9 ± 7.7 ml/kg min, p <0.001) whereas extracellular volume (0.29 ± 0.04 vs 0.25 ± 0.04, p = 0.02), pulmonary artery systolic pressure (35.4 ± 13.7 vs 22.3 ± 5.4 mm Hg, p = 0.004), and average E/e' (15.0 ± 7.6 vs 8.6 ± 2.0, p = 0.005) were increased. Displacement encoded stimulated echo peak systolic circumferential strain (p = 0.60) as well as echocardiographic derived global longitudinal strain (p = 0.07) were similar between both groups. The prevalence of CMD, defined as global MPR <2.5, in the HFpEF group was 69%. In conclusion, HFpEF patients have a high prevalence of CMD and diffuse fibrosis. These parameters may be useful clinical end points for future therapeutic trials.

Cardiovascular magnetic resonance: Stressing the future

Non-invasive cardiac stress imaging plays a central role in the assessment of patients with known or suspected coronary artery disease. The current guidelines suggest estimation of the myocardial ischaemic burden as a criterion for revascularisation on prognostic grounds despite the lack of standardised reporting of the magnitude of ischaemia on various non-invasive imaging methods. Future studies should aim to accurately describe the relationship between myocardial ischaemic burden as assessed by cardiovascular magnetic resonance imaging and mortality.

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.