Detection of Recent Myocardial Infarction Using Native T1 Mapping in a Swine Model: A Validation Study

Developing and evaluating a chronic ischemic cardiomyopathy in swine model by rest and stress CMR

A large animal model of chronic coronary artery disease (CAD) is crucial for the understanding the underlying pathophysiological processes of chronic CAD and consequences for cardiac structure and function. The goal of this study was to develop a chronic model of CAD in a swine model and to evaluate the changes of myocardial structure, myocardial motility, and myocardial viability during coronary stenosis. A total of 30 swine (including 24 experimental animals and 6 controls) were enrolled. The chronic ischemia model was constructed by using Ameroid constrictor in experimental group. The 24 experimental animals were further divided into 4 groups (6 animals in each group) and were sacrificed at 1, 2, 3 and 4 weeks after operation for pathological examination, respectively. Cardiac magnetic resonance (CMR) was performed preoperatively and weekly postoperatively until sacrificed both in experimental and control group. CMR cine images, rest/adenosine triphosphate (ATP) stress myocardial contrast perfusion and LGE were performed and analyzed. The rest wall thickening (WT) score was calculated from rest cine images. The MPRI (myocardial perfusion reserve index) and MPR (myocardial perfusion reserve) were calculated based on rest and stress perfusion images. Pathology staining including triphenyltetrazolium chloride, HE and picrosirus red staining were performed after swine were sacrificed and collagen volume fraction (CVF) was calculated. The time to formation of ischemic, hibernating, and infarcted myocardium was recorded. In experimental group, from 1w to 4w after surgery, the rest WT score decreased gradually from 35.2 ± 2.0%, 32.0 ± 2.9% to 30.5 ± 3.0% and finally 29.06 ± 1.78%, p < 0.001. Left ventricular ejection fraction was gradually impaired after modeling (58.9 ± 12.6%, 56.3 ± 10.1%, 55.3 ± 9.0%, 53.8 ± 9.9%, respectively). And the MPR and MPRI also decreased stepwise with extent of surgery time (MPRI dropped from 2.1 ± 0.4, 2.0 ± 0.2 to 1.8 ± 0.3 and finally 1.7 ± 0.1, p = 0.004; MPR dropped from 2.3 ± 0.4, 2.1 ± 0.2 to 1.9 ± 0.4 and finally 1.8 ± 0.1, p < 0.001). Stronger associations between MPR, MPRI and CVF were paralleled lower wall thickening scores in fibrosis-affected areas. The ischemic myocardium was first appeared in the first week after surgery (involving ten segments), hibernated myocardium was first appeared in the second week after surgery (involving seventeen segments). LGE was first appeared in eight swine in the third weeks after surgery (16 segments). At 4w after surgery, average 9.6 g scar tissue was found among 6 swine. At the same time, histological analysis established the presence of fibrosis and ongoing apoptosis in the infarcted area. In conclusion, our study provided valuable insights into the pathophysiological processes of chronic CAD and its consequences for cardiac structure and function in a large animal model through combining myocardial motion and stress perfusion.

Adenosine Triphosphate Stress Myocardial Strain in Ischemic Heart Disease: An Animal Study with Histological Validation

RATIONALE AND OBJECTIVES

It is still challenging for cardiac magnetic resonance (CMR) to detect ischemic heart disease (IHD) without the use of gadolinium contrast. We aimed to evaluate the potential value of adenosine triphosphate (ATP) stress myocardial strain derived from feature tracking (FT) as a novel method for detecting IHD in a swine model.

MATERIALS AND METHODS

CMR cines, myocardial perfusion imaging at rest and during ATP stress, and late gadolinium enhancement were obtained in both control and IHD swine. Normal, remote, ischemic, and infarcted myocardium were analyzed. The diagnostic accuracy of myocardial strain for infarction and ischemia was assessed using coronary angiography and pathology as reference.

RESULTS

Eleven IHD swine and five healthy control swine were enrolled in this study. Strain parameters, even at rest, were associated with myocardial ischemia and infarction(all p < 0.05). The area under receiver operating characteristic curve (AUC) values of all strain parameters for detecting infarcted myocardium exceeded 0.900 (all p < 0.05). The AUC values for detecting ischemic myocardium were as follows: 0.906 and 0.847 for stress and rest radial strain, 0.763 and 0.716 for stress and rest circumferential strain, 0.758 and 0.663 for stress and rest longitudinal strain (all p < 0.001). Heat maps demonstrated that all strain parameters showed mild to moderate correlations with the stress myocardial blood flow and myocardial perfusion reserve (all p < 0.05).

CONCLUSION

CMR-FT-derived ATP stress myocardial strain shows promise as a noninvasive method for detecting myocardial ischemia and infarction in an IHD swine model, with rest strain parameters offering potential as a needle-free diagnostic option.

Cardiac magnetic resonance assessment of cardiac involvement in autoimmune diseases

Cardiac magnetic resonance (CMR) is emerging as the modality of choice to assess early cardiovascular involvement in patients with autoimmune rheumatic diseases (ARDs) that often has a silent presentation and may lead to changes in management. Besides being reproducible and accurate for functional and volumetric assessment, the strength of CMR is its unique ability to perform myocardial tissue characterization that allows the identification of inflammation, edema, and fibrosis. Several CMR biomarkers may provide prognostic information on the severity and progression of cardiovascular involvement in patients with ARDs. In addition, CMR may add value in assessing treatment response and identification of cardiotoxicity related to therapy with immunomodulators that are commonly used to treat these conditions. In this review, we aim to discuss the following objectives: •Illustrate imaging findings of multi-parametric CMR approach in the diagnosis of cardiovascular involvement in various ARDs;•Review the CMR signatures for risk stratification, prognostication, and guiding treatment strategies in ARDs;•Describe the utility of routine and advanced CMR sequences in identifying cardiotoxicity related to immunomodulators and disease-modifying agents in ARDs;•Discuss the limitations of CMR, recent advances, current research gaps, and potential future developments in the field.

Endogenous assessment of late gadolinium enhancement grey zone in patients with non-ischaemic cardiomyopathy with T1ρ and native T1 mapping

AIMS

This study aims to validate and compare the feasibility of T1ρ and native longitudinal relaxation time (T1) mapping in detection of myocardial fibrosis in patients with non-ischaemic cardiomyopathy, focusing on the performance of both methods in identifying late gadolinium enhancement (LGE) grey zone.

METHODS AND RESULTS

Twenty-seven hypertrophic cardiomyopathy (HCM) patients, 16 idiopathic dilated cardiomyopathy (DCM) patients, and 18 healthy controls were prospectively enrolled for native T1 and T1ρ mapping imaging and then all the patients underwent enhancement scan for LGE extent and extracellular volume (ECV) values. In LGE positive patients, the LGE areas were divided into LGE core (6 SDs above remote myocardium) and grey zone (2-6 SDs above remote myocardium) according to the signal intensity of LGE. Both HCM and DCM patients showed significantly higher native T1 values and T1ρ values than controls no matter the presence of LGE (all P < 0.01). There were significant differences in native T1 and T1ρ values among four different types of myocardia (LGE core, grey zone, remote area and control, P < 0.0001). However, the T1ρ values of grey zone were significantly higher than control (P < 0.01), while the native T1 values were not (P = 0.089). T1ρ values were significantly associated with both native T1 values (r = 0.54, P < 0.001) and ECV values (r = 0.54, P < 0.001).

CONCLUSION

T1ρ mapping is a feasible method to detect myocardial fibrosis in patients with non-ischaemic cardiomyopathy no matter the presence of LGE. Compared with native T1, T1ρ may serve as a better discriminator in the identification of LGE grey zone.

Automatic uncertainty-based quality controlled T1 mapping and ECV analysis from native and post-contrast cardiac T1 mapping images using Bayesian vision transformer

Deep learning-based methods for cardiac MR segmentation have achieved state-of-the-art results. However, these methods can generate incorrect segmentation results which can lead to wrong clinical decisions in the downstream tasks. Automatic and accurate analysis of downstream tasks, such as myocardial tissue characterization, is highly dependent on the quality of the segmentation results. Therefore, it is of paramount importance to use quality control methods to detect the failed segmentations before further analysis. In this work, we propose a fully automatic uncertainty-based quality control framework for T1 mapping and extracellular volume (ECV) analysis. The framework consists of three parts. The first one focuses on segmentation of cardiac structures from a native and post-contrast T1 mapping dataset (n=295) using a Bayesian Swin transformer-based U-Net. In the second part, we propose a novel uncertainty-based quality control (QC) to detect inaccurate segmentation results. The QC method utilizes image-level uncertainty features as input to a random forest-based classifier/regressor to determine the quality of the segmentation outputs. The experimental results from four different types of segmentation results show that the proposed QC method achieves a mean area under the ROC curve (AUC) of 0.927 on binary classification and a mean absolute error (MAE) of 0.021 on Dice score regression, significantly outperforming other state-of-the-art uncertainty based QC methods. The performance gap is notably higher in predicting the segmentation quality from poor-performing models which shows the robustness of our method in detecting failed segmentations. After the inaccurate segmentation results are detected and rejected by the QC method, in the third part, T1 mapping and ECV values are computed automatically to characterize the myocardial tissues of healthy and cardiac pathological cases. The native myocardial T1 and ECV values computed from automatic and manual segmentations show an excellent agreement yielding Pearson coefficients of 0.990 and 0.975 (on the combined validation and test sets), respectively. From the results, we observe that the automatically computed myocardial T1 and ECV values have the ability to characterize myocardial tissues of healthy and cardiac diseases like myocardial infarction, amyloidosis, Tako-Tsubo syndrome, dilated cardiomyopathy, and hypertrophic cardiomyopathy.

Artificial Intelligence for Contrast-Free MRI: Scar Assessment in Myocardial Infarction Using Deep Learning-Based Virtual Native Enhancement

BACKGROUND

Myocardial scars are assessed noninvasively using cardiovascular magnetic resonance late gadolinium enhancement (LGE) as an imaging gold standard. A contrast-free approach would provide many advantages, including a faster and cheaper scan without contrast-associated problems.

METHODS

Virtual native enhancement (VNE) is a novel technology that can produce virtual LGE-like images without the need for contrast. VNE combines cine imaging and native T1 maps to produce LGE-like images using artificial intelligence. VNE was developed for patients with previous myocardial infarction from 4271 data sets (912 patients); each data set comprises slice position-matched cine, T1 maps, and LGE images. After quality control, 3002 data sets (775 patients) were used for development and 291 data sets (68 patients) for testing. The VNE generator was trained using generative adversarial networks, using 2 adversarial discriminators to improve the image quality. The left ventricle was contoured semiautomatically. Myocardial scar volume was quantified using the full width at half maximum method. Scar transmurality was measured using the centerline chord method and visualized on bull's-eye plots. Lesion quantification by VNE and LGE was compared using linear regression, Pearson correlation (R), and intraclass correlation coefficients. Proof-of-principle histopathologic comparison of VNE in a porcine model of myocardial infarction also was performed.

RESULTS

VNE provided significantly better image quality than LGE on blinded analysis by 5 independent operators on 291 data sets (all P<0.001). VNE correlated strongly with LGE in quantifying scar size (R, 0.89; intraclass correlation coefficient, 0.94) and transmurality (R, 0.84; intraclass correlation coefficient, 0.90) in 66 patients (277 test data sets). Two cardiovascular magnetic resonance experts reviewed all test image slices and reported an overall accuracy of 84% for VNE in detecting scars when compared with LGE, with specificity of 100% and sensitivity of 77%. VNE also showed excellent visuospatial agreement with histopathology in 2 cases of a porcine model of myocardial infarction.

CONCLUSIONS

VNE demonstrated high agreement with LGE cardiovascular magnetic resonance for myocardial scar assessment in patients with previous myocardial infarction in visuospatial distribution and lesion quantification with superior image quality. VNE is a potentially transformative artificial intelligence-based technology with promise in reducing scan times and costs, increasing clinical throughput, and improving the accessibility of cardiovascular magnetic resonance in the near future.

Prognostic significance of myocardial salvage assessed by cardiac magnetic resonance in reperfused ST-segment elevation myocardial infarction

Aims

Myocardial salvage index (MSI) is attracting increasing attention for predicting prognosis in acute myocardial infarction (AMI); however, the evaluation of MSI is mainly based on contrast agent-dependent cardiac magnetic resonance (CMR) scanning sequences. This study aims to investigate the prognostic value of MSI in reperfused ST-segment elevation myocardial infarction (STEMI) through the contrast agent-free CMR technique.

Methods and results

Nighty-two patients with acute STEMI, who underwent CMR after primary percutaneous coronary intervention (PPCI), were finally enrolled. Patients were subcategorized into two groups according to median MSI. T1 and T2 mapping were conducted for measuring infarct size (IS) and area at risk (AAR). IS was significantly larger in < median MSI group than ≥ median MSI group (P < 0.001). AAR between the two groups showed no obvious differences (P = 0.108). Left ventricular ejection fraction (LVEF) was lower in < median MSI group than ≥ median MSI group (P = 0.014). There was an obvious inverse correlation between MSI and reperfusion time (R = –0.440, P < 0.001) and a strong inverse correlation between MSI and IS (R = –0.716, P = 0.011). As for the relationship LVEF, MSI showed positive but weak correlation (R = 0.2265, P < 0.001). Over a median follow-up period of 263 (227–238) days, prevalence of MACEs was significantly higher in the < median MSI group [HR: 0.15 (0.04–0.62); Log-rank P = 0.008]. The univariate Cox regression analysis revealed that LVEF, IS, and MSI were significant predictors for major adverse cardiovascular events (MACEs) (all P < 0.05). In the stepwise multivariate Cox regression analysis, LVEF and MSI were identified as independent parameters for predicting MACEs (both P < 0.05). In the receiver-operating characteristic analysis, LVEF, IS, and MSI showed prognostic value in predicting MACEs with AUCs of 0.809, 0.779, and 0.896, respectively, all (P < 0.05). A combination of MSI with LVEF showed the strongest prognostic value of MACEs (AUC: 0.901, sensitivity: 77.78%, specificity: 98.80%, P < 0.001). Delong’s test showed that the combination of LVEF with MSI had an incremental value than LVEF itself in predicting MACEs (P = 0.026).

Conclusion

Contrast agent-free CMR technique provides a reliable evaluation of MSI, which contributes to assessing the efficacy of reperfusion therapy and predicting the occurrence of MACEs.

Free-breathing gradient recalled echo-based CMR in a swine heart failure model

In swine models, there are well-established protocols for creating a closed-chest myocardial infarction (MI) as well as protocols for characterization of cardiac function with cardiac magnetic resonance (CMR). This methods manuscript outlines a novel technique in CMR data acquisition utilizing smart-signal gradient recalled echo (GRE)-based array sequences in a free-breathing swine heart failure model allowing for both high spatial and temporal resolution imaging. Nine male Yucatan mini swine weighing 48.7 ± 1.6 kg at 58.2 ± 3.1 weeks old underwent the outlined imaging protocol before and 1-month after undergoing closed chest left anterior descending coronary artery (LAD) occlusion/reperfusion. The left ventricular ejection fraction (LVEF) at baseline was 59.3 ± 2.4% and decreased to 48.1 ± 3.7% 1-month post MI (P = 0.029). The average end-diastolic volume (EDV) at baseline was 55.2 ± 1.7 ml and increased to 74.2 ± 4.2 ml at 1-month post MI (P = 0.001). The resulting images from this novel technique and post-imaging analysis are presented and discussed. In a Yucatan swine model of heart failure via closed chest left anterior descending coronary artery (LAD) occlusion/reperfusion, we found that CMR with GRE-based array sequences produced clinical-grade images with high spatial and temporal resolution in the free-breathing setting.

Myocardial blood flow is the dominant factor influencing cardiac magnetic resonance adenosine stress T2

Stress imaging identifies ischemic myocardium by comparing hemodynamics during rest and hyperemic stress. Hyperemia affects multiple hemodynamic parameters in myocardium, including myocardial blood flow (MBF), myocardial blood volume (MBV), and venous blood oxygen levels (PvO2 ). Cardiac T2 is sensitive to these changes and therefore is a promising non-contrast option for stress imaging; however, the impact of individual hemodynamic factors on T2 is poorly understood, making the connection from altered T2 to changes within the tissue difficult. To better understand this interplay, we performed T2 mapping and measured various hemodynamic factors independently in healthy pigs at multiple levels of hyperemic stress, induced by different doses of adenosine (0.14-0.56 mg/kg/min). T1 mapping quantified changes in MBV. MBF was assessed with microspheres, and oxygen consumption was determined by the rate pressure product (RPP). Simulations were also run to better characterize individual contributions to T2. Myocardial T2, MBF, oxygen consumption, and MBV all changed to varying extents between each level of adenosine stress (T2 = 37.6-41.8 ms; MBF = 0.48-1.32 mL/min/g; RPP = 6507-4001 bmp*mmHg; maximum percent change in MBV = 1.31%). Multivariable analyses revealed MBF as the dominant influence on T2 during hyperemia (significant β-values >7). Myocardial oxygen consumption had almost no effect on T2 (β-values <0.002); since PvO2 is influenced by both oxygen consumption and MBF, PvO2 changes detected by T2 during adenosine stress can be attributed to MBF. Simulations varying PvO2 and MBV confirmed that PvO2 had the strongest influence on T2, but MBV became important at high PvO2 . Together, these data suggest a model where, during adenosine stress, myocardial T2 responds predominantly to changes in MBF, but at high hyperemia MBV is also influential. Thus, changes in adenosine stress T2 can now be interpreted in terms of the physiological changes that led to it, enabling T2 mapping to become a viable non-contrast option to detect ischemic myocardial tissue.

Cardiac MRI to Visualize Myocardial Damage after ST-Segment Elevation Myocardial Infarction: A Review of Its Histologic Validation

Cardiac MRI is a noninvasive diagnostic tool using nonionizing radiation that is widely used in patients with ST-segment elevation myocardial infarction (STEMI). Cardiac MRI depicts different prognosticating components of myocardial damage such as edema, intramyocardial hemorrhage (IMH), microvascular obstruction (MVO), and fibrosis. But how do cardiac MRI findings correlate to histologic findings? Shortly after STEMI, T2-weighted imaging and T2* mapping cardiac MRI depict, respectively, edema and IMH. The acute infarct size can be determined with late gadolinium enhancement (LGE) cardiac MRI. T2-weighted MRI should not be used for area-at-risk delineation because T2 values change dynamically over the first few days after STEMI and the severity of T2 abnormalities can be modulated with treatment. Furthermore, LGE cardiac MRI is the most accurate method to visualize MVO, which is characterized by hemorrhage, microvascular injury, and necrosis in histologic samples. In the chronic setting post-STEMI, LGE cardiac MRI is best used to detect replacement fibrosis (ie, final infarct size after injury healing). Finally, native T1 mapping has recently emerged as a contrast material-free method to measure infarct size that, however, remains inferior to LGE cardiac MRI. Especially LGE cardiac MRI-defined infarct size and the presence and extent of MVO may be used to monitor the effect of new therapeutic interventions in the treatment of reperfusion injury and infarct size reduction. © RSNA, 2021 Online supplemental material is available for this article.

Machine learning phenotyping of scarred myocardium from cine in hypertrophic cardiomyopathy

AIMS

Cardiovascular magnetic resonance (CMR) with late-gadolinium enhancement (LGE) is increasingly being used in hypertrophic cardiomyopathy (HCM) for diagnosis, risk stratification, and monitoring. However, recent data demonstrating brain gadolinium deposits have raised safety concerns. We developed and validated a machine-learning (ML) method that incorporates features extracted from cine to identify HCM patients without fibrosis in whom gadolinium can be avoided.

METHODS AND RESULTS

An XGBoost ML model was developed using regional wall thickness and thickening, and radiomic features of myocardial signal intensity, texture, size, and shape from cine. A CMR dataset containing 1099 HCM patients collected using 1.5T CMR scanners from different vendors and centres was used for model development (n=882) and validation (n=217). Among the 2613 radiomic features, we identified 7 features that provided best discrimination between +LGE and -LGE using 10-fold stratified cross-validation in the development cohort. Subsequently, an XGBoost model was developed using these radiomic features, regional wall thickness and thickening. In the independent validation cohort, the ML model yielded an area under the curve of 0.83 (95% CI: 0.77-0.89), sensitivity of 91%, specificity of 62%, F1-score of 77%, true negatives rate (TNR) of 34%, and negative predictive value (NPV) of 89%. Optimization for sensitivity provided sensitivity of 96%, F2-score of 83%, TNR of 19% and NPV of 91%; false negatives halved from 4% to 2%.

CONCLUSION

An ML model incorporating novel radiomic markers of myocardium from cine can rule-out myocardial fibrosis in one-third of HCM patients referred for CMR reducing unnecessary gadolinium administration.

Detection of Myocardial Fibrosis and Left Ventricular Dysfunction with Cardiac MRI in a Hypertensive Swine Model

Purpose

To quantitatively evaluate the dynamic changes of extracellular volume (ECV) and native T1 in hypertensive swine over time using histologic findings as standard of reference.

Materials and Methods

Eighteen hypertensive (hypertension group) and six healthy (control group) swine aged 6-12 months were studied. Both groups underwent cardiac MRI, including pre- and postcontrast T1 mapping and late gadolinium enhancement (LGE) imaging at three time points: baseline, 1 month, and 3 months after hypertensive model induction. The left ventricular function, strain, and strain rate were also calculated using the cine images. Animals were killed after the last MRI examination. Histopathologic examination of the heart was performed later. Analysis of the relationship between strain, ECV, and native T1 was carried out by Pearson correlation and linear regression models.

Results

The mean systolic and diastolic pressure increased from 111 mg Hg and 68 mm Hg to 160 mm Hg and 97 mm Hg, respectively, over 3 months during developing hypertension (P = .03, .02, respectively). There was no LGE detected at any of three imaging times. The ECV and native T1 value of myocardium in the hypertension group increased over 3 months (ECV, increased from 21.5% ± 4.4 to 27.3% ± 5.4; native T1, increased from a mean of 1056 msec ± 32 [standard deviation] to 1218 msec ± 66; all P < .001). The collagen volume fraction (CVF) was calculated and correlated with ECV (r = 0.63, P = .01) and native T1 (r = 0.80, P < .001). In addition, ECV was associated with longitudinal diastolic strain rate (r =-.34, P = .04). Native T1 was associated with radial strain (r = -0.62, P < .001) as well as circumferential strain (r = 0.57, P < .001).

Conclusion

Native T1 and ECV correlated significantly with the CVF, indicating that early myocardial interstitial fibrosis exists in hypertensive heart disease. As hypertension progresses, the values of ECV fraction and T1 native increase. Supplemental material is available for this article. © RSNA, 2020.

Estimation of total collagen volume: a T1 mapping versus histological comparison study in healthy Landrace pigs

Right ventricular biopsy represents the gold standard for the assessment of myocardial fibrosis and collagen content. This invasive technique, however, is accompanied by perioperative complications and poor reproducibility. Extracellular volume (ECV) measured through cardiovascular magnetic resonance (CMR) has emerged as a valid surrogate method to assess fibrosis non-invasively. Nonetheless, ECV provides an overestimation of collagen concentration since it also considers interstitial space. Our study aims to investigate the feasibility of estimating total collagen volume (TCV) through CMR by comparing it with the TCV measured at histology. Seven healthy Landrace pigs were acutely instrumented closed-chest and transported to the MRI facility for measurements. For each protocol, CMR imaging at 3T was acquired. MEDIS software was used to analyze T1 mapping and ECV for both the left ventricular myocardium (LV_myo) and left ventricular septum (LV_septum). ECV was then used to estimate TCV_CMR at LV_myo and LV_septum following previously published formulas. Tissues were prepared following an established protocol and stained with picrosirius red to analyze the TCV_histo in LV_myo and LV_septum. TCV measured at LV_myo and LV_septum with both histology (8 ± 5 ml and 7 ± 3 ml, respectively) and T1-Mapping (9 ± 5 ml and 8 ± 6 ml, respectively) did not show any regional differences. TCV_histo and TCV_CMR showed a good level of data agreement by Bland–Altman analysis. Estimation of TCV through CMR may be a promising way to non-invasively assess myocardial collagen content and may be useful to track disease progression or treatment response.

Role of Cardiac Magnetic Resonance to Improve Risk Prediction Following Acute ST-Elevation Myocardial Infarction

Cardiac magnetic resonance (CMR) imaging allows comprehensive assessment of myocardial function and tissue characterization in a single examination after acute ST-elevation myocardial infarction. Markers of myocardial infarct severity determined by CMR imaging, especially infarct size and microvascular obstruction, strongly predict recurrent cardiovascular events and mortality. The prognostic information provided by a comprehensive CMR analysis is incremental to conventional risk factors including left ventricular ejection fraction. As such, CMR parameters of myocardial tissue damage are increasingly recognized for optimized risk stratification to further ameliorate the burden of recurrent cardiovascular events in this population. In this review, we provide an overview of the current impact of CMR imaging on optimized risk assessment soon after acute ST-elevation myocardial infarction.

Non-contrast myocardial infarct scar assessment using a hybrid native T1 and magnetization transfer imaging sequence at 1.5T

PURPOSE

To develop a gadolinium-free cardiac MR technique that simultaneously exploits native T₁ and magnetization transfer (MT) contrast for the imaging of myocardial infarction.

METHODS

A novel hybrid T one and magnetization transfer (HYTOM) method was developed based on the modified look-locker inversion recovery (MOLLI) sequence, with a train of MT-prep pulses placed before the balanced SSFP (bSSFP) readout pulses. Numerical simulations, based on Bloch-McConnell equations, were performed to investigate the effects of MT induced by (1) the bSSFP readout pulses, and (2) the MT-prep pulses, on the measured, "apparent," native T₁ values. The HYTOM method was then tested on 8 healthy adult subjects, 6 patients, and a swine with prior myocardial infarction (MI). The resulting imaging contrast between normal myocardium and infarcted tissues was compared with that of MOLLI. Late gadolinium enhancement (LGE) images were also obtained for infarct assessment in patients and swine.

RESULTS

Numerical simulation and in vivo studies in healthy volunteers demonstrated that MT effects, resulting from on-resonance bSSFP excitation pulses and off-resonance MT-prep pulses, reduce the measured T₁ in both MOLLI and HTYOM. In vivo studies in patients and swine showed that the HYTOM sequence can identify locations of MI, as seen on LGE. Furthermore, the HYTOM method yields higher myocardium-to-scar contrast than MOLLI (contrast-to-noise ratio: 7.33 ± 1.67 vs. 3.77 ± 0.66, P < 0.01).

CONCLUSION

The proposed HYTOM method simultaneously exploits native T₁ and MT contrast and significantly boosts the imaging contrast for myocardial infarction.