Keywords: Myocardium, Myocardium, Late Gadolinium Enhancement , infarction

Motivation: Low-field wide-bore MRI scanners are cost-effective but suffer from lower SNR, impacting myocardial LGE image quality.

Goal(s): To introduce and evaluate a novel imaging strategy that offers full heart coverage and reduces image count by 50%.

Approach: Developed a sequence acquiring 45-55 overlapped short-axis 2-D slices with patch-based motion compensated filtering to enhance SNR.

Results: The new technique improved SNR in whole heart coverage LGE imaging at 0.55T, though further studies with scarred myocardium are needed.

Impact: This study advances cardiac MRI by demonstrating that a novel LGE imaging technique coupled with MC-KW patch filtering substantially enhances SNR in low-field wide-bore scanners, promising improved myocardial scar detection at reduced costs.

Keywords: Myocardium, Cardiovascular

Motivation: The 3D fusion of coronary structure and myocardial blood flow data helps to reduce the misallocation of affected vessels to their associated myocardial territories.

Goal(s): An AI-based pipeline has been developed that uses advanced machine learning algorithms to automatically fuse images from cardiac CTCA and perfusion MRI.

Approach: The pipeline includes an automatic reorientation of 3D CT coronary angiography and fusion with stress cardiovascular magnetic resonance images.

Results: we achieved 3D fusion of CTCA and CMR establishing a correlation between coronary artery stenosis and stress-induced myocardial hypoperfusion.

Impact: the pipeline can assist in clinical assessments of coronary artery disease.

Keywords: Myocardium, Machine Learning/Artificial Intelligence

Motivation: Although late Gadolinium Enhancement (LGE) imaging is widely used for diagnosing myocardial infarction (MI), contrast-free approaches are in need for patients with gadolinium contraindications.

Goal(s): To develop Cine Generated Enhancement (CGE), a novel technique that uses contrast-free cine images to predict images resembling LGE.

Approach: A deep generative model was trained to translate cine images into LGE images of acute MI exploiting the different motion dynamics between heathy and infarcted myocardium.

Results: Realistic enhancement images can be generated for acute MI patients using cine images unseen during training. The scar size and transmurality estimated with CGE agreed well with LGE.

Impact: This study presents an effective, non-invasive, and contrast-free method for predicting LGE in acute MI, potentially reducing the use of gadolinium-based contrast agents and shortening cardiac MR examinations.

Keywords: Atherosclerosis, Low-Field MRI, Late gadolinium enhanced

Motivation: 3D whole-heart late gadolinium enhancement imaging has previously been demonstrated at 1.5T, but not at low-field (0.55T).

Goal(s): To develop a novel free breathing, whole-heart, late gadolinium enhancement imaging framework at low field.

Approach: Patients with known ischaemic heart disease were scanned and results of the proposed 3D sequence were compared with 2D LGE images.

Results: There is excellent agreement between the 3D and 2D datasets in the detection of myocardial scar.

Impact: Preliminary results demonstrate the feasibility of the proposed framework for comprehensive 3D whole-heart late gadolinium enhancement imaging for the detection of myocardial scar at 0.55T. 

Keywords: Myocardium, Cardiovascular

Motivation: Coronary Arterial Disease (CAD) evaluations often require myocardium perfusion exams. Many CAD patients also have stents which makes difficult to evaluate images due to susceptibility artifacts. A reliable non-contrast MR perfusion technique in CAD patients with stents is needed. 

Goal(s): To introduce Time-SLIP technique with Stack-of-Stars (SoS) sequence for more inclusive myocardial assessments without the need for contrast mediums.

Approach: Implemented diaphragm navigator echoes and T2-prep with the SoS sequence, refined through phantom trials, for tagging the proximal aortic root blood flow to visualize myocardial perfusion.

Results: Preliminary in-vivo scans indicate reduced stent-related artifacts and the feasibility of non-contrast perfusion quantification.

Impact: Our non-contrast myocardial perfusion approach offers a safer CAD evaluation, reducing risks from contrast agents. This method opens doors for inclusive patient assessments and encourages further refinement in non-invasive cardiac diagnostics.

Keywords: Myocardium, Cardiomyopathy

Motivation: CMR first-pass-perfusion imaging (FPI) had revealed coronary microvascular dysfunction (CMD) in dilated cardiomyopathy (DCM). However, it’s unknown if FPI could predict left ventricular reverse remodeling (LVRR) in DCM.

Goal(s): Investigating the value of FPI parameters for predicting LVRR.

Approach: 94 DCM patients and 35 healthy controls were enrolled. FPI as well as the left ventricular structure, function and late gadolinium enhancement (LGE) parameters were analyzed. 

Results:  FPI showed more serious CMD in non-LVRR than LVRR. Time_max of FPI as well as left ventricular remodeling index and LGE extent were independent predictors.

Impact: This study firstly showed the role of FPI in predicting LVRR in DCM.

Keywords: Myocardium, Cardiovascular

Motivation: 2D high-resolution late gadolinium enhancement (LGE) imaging can benefit from shorter scan times. Current acceleration techniques lead large signal-to-noise (SNR) penalties, reducing diagnostic quality while longer breath-holds increases scan time and makes the imaging susceptible to artifacts. 

Goal(s): To assess the feasibility of a rapid 2D LGE imaging using Resolution Enhancement Generative Adversarial Inline Neural Network (REGAIN).

Approach: Images were acquired with 3.3 and 5.7-fold accelerations, reconstructed using REGAIN, and compared with 1.8-fold GRAPPA acceleration. 

Results: REGAIN successfully improved visual image sharpness in LGE images acquired with 3.3-fold (~6-second) and 5.7-fold (~10-second) accelerations. Image quality was comparable to 1.8-fold (~16-second) GRAPPA acceleration.   

Impact: REGAIN enables accelerated LGE imaging with significantly reduced breath-hold duration. 

Keywords: Heart Failure, Cardiomyopathy, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)

Motivation: Late gadolinium enhancement (LGE) CMR‘s wider clinical adoption is hindered by its prolonged wait time and imaging protocol dependence.

Goal(s): Develop a delayed dynamic contrast enhancement (dDCE) model to shorten the LGE wait time and provide a quantitative characterization of the myocardium contrast washout process.

Approach: Dynamic T1 maps were acquired in the contrast washout period in dogs with myocardial infarctions. dDCE maps and synthesized LGE images were derived from data collected within 5-minute post-contrast injection.

Results: The 5-minute dDCE maps provide physiologically reasonable measurements and comparable myocardial viability assessment ability to standard LGE images.

Impact: The shortened LGE wait time from the quantitative dDCE maps may benefit patients unable to tolerate long CMR examination time and open new dimensions for quantitative myocardium viability assessment.

Keywords: Myocardium, Cardiovascular

Motivation: To overcome the limitations of LGE imaging, including respiratory motion artifacts and lengthy scan times, while enhancing myocardial scar imaging.

Goal(s): To develop a deep learning-based free-breathing single-beat LGE. 

Approach: Free-breathing single-beat low-resolution 2D LGE images are acquired and followed by resolution enhancement generative adversarial inline neural network (REGAIN) to enhance the spatial resolution. Each slice was acquired in a single beat, followed by one beat for signal recovery. The entire left ventricular dataset was acquired in 20 heartbeats.

Results: REGAIN improved image sharpness and quality of single-beat 2D LGE acquired with 4.7-fold acceleration with spatial resolution of 1.5 × 5 mm².  

Impact: A rapid single-beat 2D LGE imaging can reduce CMR scan time, increase patient comfort, and reduce sensitivity to breathing motion. 

Keywords: Atherosclerosis, Cardiovascular, Myocardial Perfusion

Motivation: Model-based quantitative myocardial perfusion MRI is feasible. However, few studies have investigated its diagnostic accuracy in detecting significant coronary artery disease (CAD).

Goal(s): To evaluate the diagnostic accuracy of quantitative stress myocardial perfusion MRI using Patlak plot method for the detection of significant CAD.

Approach: Myocardial blood flow (MBF) and myocardial flow reserve (MFR) determined by Patlak analysis of stress perfusion MRI with LV blood saturation correction were compared with fractional flow reserve.

Results: Model-based quantitative stress perfusion MRI has a high diagnostic accuracy for detecting significant CAD with the AUC of 0.739 and 0.745 for stress MBF and MFR, respectively.

Impact: Absolute quantification of myocardial blood flow and myocardial flow reserve by stress-rest myocardial perfusion MRI with model-based approach permits accurate and objective assessment of myocardial ischemia due to flow-limiting obstructive coronary artery disease, which can aid daily routine clinical practice.

Keywords: Myocardium, Myocardium, hemorrhage, intramyocardial hemorrhage, myocardial infarction, ischemia-reperfusion injury, ischemia , animals, blood, blood vessels, cardiovascular, contrast agents, contrast mechanisms, heart, novel contrast mechanism, preclinical

Motivation: Intramyocardial hemorrhage (IMH) frequently occurs in acute myocardial infarction (AMI) and is associated with adverse outcomes.  While T₂* cardiac magnetic resonance (CMR) imaging has emerged as the reference standard for noninvasive IMH detection, it relies on the paramagnetic properties of hemoglobin breakdown products, usually detectable between 1 and 3 days following IMH.  

Goal(s): We demonstrate an alternative approach that can more promptly detect active myocardial bleeding.

Approach: We leveraged the T₁ shortening effects of intravascular ferumoxytol to identify IMH following acute ischemia-reperfusion injury.  

Results: Ferumoxytol-enhanced CMR depiction of IMH were in agreement with gross and histologic evaluations.

Impact: We demonstrate the effectiveness of ferumoxytol-enhanced cardiovascular magnetic resonance (FE-CMR) in detecting active intramyocardial hemorrhage after ischemia-reperfusion injury.  This may facilitate the development, testing, and clinical adoption of strategies to mitigate IMH-associated complications.

Keywords: Myocardium, Cardiovascular

Motivation: Traditional bright-blood late gadolinium enhancement (BB-LGE) technique often obscures the visualization of endocardial LGE. In contrast, black blood technique overcomes this limitation but sacrifices contrast between the myocardium and blood pool.

Goal(s): By selecting specific TI (inversion time) values, gray blood images can be generated to achieve the desired contrast among the blood pool, myocardium, and scar tissue.

Approach: We conducted a comparative analysis of image quality, diagnostic confidence score, detection of delayed enhancement lesions, and the contrast-to-noise ratio (CNR) between BB-LGE and GB-LGE.

Results: The implementation of GB-LGE  enhances diagnostic confidence and improves CNR between the blood pool and myocardial scar tissue.

Impact: The proposed GB-LGE sequence in this study enhances scar detection rates and diagnostic confidence, addressing limitations associated with equipment and technology. It optimizes clinical workflow efficiency while offering a universal approach with potential for widespread adoption.

Keywords: Myocardium, Myocardium, noncontrast, perfusion, deep learning

Motivation: Cardiac arterial spin labeling (ASL) method is sensitive to noise (system and physiology), which may lead to inaccurate MBF measurement.

Goal(s): A cardiac MRI arterial spin labeling method was developed with assistance of a deep learning networks (DeepCASL) to improve image quality and measurement accuracy.

Approach: The performance of the DeepCASL method was evaluated in a canine model of coronary arterial disease by comparing and correlating with MBF determined by microsphere measurements.

Results: The validation study revealed moderate to strong correlations in absolute myocardial blood flow values between MRI and microsphere reference methods.

Impact: This new DeepCASL technique opens a door for clinical applications of noncontrast cardiac perfusion as a screen tool for reliable diagnosis of perfusion deficit in a variety of cardiomyopathy disorders.

Keywords: Myocardium, Perfusion, Simultaneous multi-slice, myocardial blood flow

Motivation: While simultaneous multi-slice (SMS) excitation has been proposed to increase the myocardial coverage for cardiac perfusion MRI, its influence on the quantification of myocardial blood flow (MBF) has not been evaluated. 

Goal(s): To determine whether SMS with multiband factor of two preserves accuracy in the quantification of MBF compared with the corresponding perfusion MRI with single-slice excitation. 

Approach: We prospectively enrolled six patients and performed standard and SMS perfusion MRI back-to-back and calculated the arterial input function (AIF) and resting MBF.

Results: Both the AIF and MBF values calculated from the datasets acquired with the two perfusion sequences were comparable.

Impact: This study demonstrates feasibility of utilizing a 2D simultaneous multi-slice (SMS) (multiband factor = 2) perfusion sequence to increase the myocardial coverage and quantify the myocardial blood flow to help coronary artery disease diagnosis.

Keywords: Myocardium, Heart, Myocardial infarction，Patch，Cardiac magnetic resonance

Motivation: Evaluation of therapeutic effect of myocardial infarction（MI） patch using cardiac magnetic resonance （CMR） imaging

Goal(s): Cooperation between medicine and polymer science

Approach: We made a pig model of MI. The MI pigs in the patch group attached the patch to the epicardial side, while the MI pigs in the control group were not treated. We performed CMR imaging before operation, 2 weeks and 8 weeks after modeling. Finally, the heart was taken for pathological verification.

Results: Compared with the control group, the patch group pig had thicker ventricular wall, better cardiac function and smaller LGE%. Histology and imaging correspond well.

Impact: By non-invasively analyzing the heart's structure and function, CMR helps us evaluate the potential of using patches to treat MI and offers valuable insights for preventing ventricular aneurysms after heart attacks in clinical practice.

Keywords: Myocardium, Perfusion

Motivation: While extensive research has explored robust pixel-wise quantification of myocardial blood flow, there is also a need for further investigation into accurate myocardial signal delay estimation, given its diagnostic value, for enhancing conventional clinical myocardial perfusion protocols.

Goal(s): We seek to address the primary challenges in calculating delay and improve its estimation accuracy.

Approach: We introduce a deep learning approach designed to recognize motion artifacts as outliers along the temporal signal curve of each voxel, subsequently eliminating them from the perfusion quantification process. 

Results: Our findings suggest that eliminating outliers enhances the accuracy of perfusion delay parameter estimation in scenarios with residual motion.

Impact: Enhancing the precision of delay estimation will increase its diagnostic value as a biomarker, offering crucial insights into the identification of perfusion defects in ischemic hearts.