Quantitative cardiovascular magnetic resonance perfusion imaging identifies reduced flow reserve in microvascular coronary artery disease

Zorach, Benjamin; Shaw, P.W.; Bourque, Jamieson M.; Kuruvilla, Sujith; Balfour, Pelbreton C.; Yang, Ya; Mathew, Roshin C.; Pan, Jingbo; González, Jorge A.; Taylor, Angela M.; Meyer, Craig H.; Epstein, Frederick H.; Kramer, Christopher M.; Salerno, Michael

doi:10.1186/s12968-018-0435-1

Cited by 80 publications

(69 citation statements)

References 31 publications

(33 reference statements)

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“…We utilized a quantitative spiral perfusion pulse sequence as we have previously described . Proton density (PD) images were acquired in the first two heartbeats (10° flip angle, FA) without a saturation pulse.…”

Section: Experimental Methodsmentioning

confidence: 99%

“…We utilized a quantitative spiral perfusion pulse sequence as we have previously described. 23,24 Proton density (PD) images were acquired in the first two heartbeats (10°flip angle, FA) without a saturation pulse. An arterial input function image was acquired during the first saturation recovery time (SRT) of each heartbeat with a single-shot spiral acquisition (6.95 mm in-plane resolution, 20 ms SRT, 90°FA).…”

Section: Cmr Imaging Protocolmentioning

confidence: 99%

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Adenosine stress CMR perfusion imaging of the temporal evolution of perfusion defects in a porcine model of progressive obstructive coronary artery occlusion

et al. 2019

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Adenosine stress CMR perfusion imaging can quantify absolute perfusion and myocardial perfusion reserve (MPR) in coronary artery disease (CAD) with higher spatial resolution than positron emission tomography, the only clinically available technique for quantitative myocardial perfusion imaging. While porcine models of CAD are excellent for studying perfusion abnormalities in chronic CAD, to date there are a limited number of studies that use quantitative perfusion for evaluation. Therefore, we developed an adenosine stress CMR protocol to evaluate the temporal evolution of perfusion defects in a porcine model of progressive obstructive CAD. 10 Yucatan minipigs underwent placement of an ameroid occluder around the left circumflex artery (LCX) to induce a progressive chronic coronary obstruction. Four animals underwent a hemodynamic dose range experiment to determine the adenosine dose inducing maximal hyperemia. Each animal had a CMR examination, including stress/rest spiral quantitative perfusion imaging at baseline and 1, 3, and 6 weeks. Late gadolinium enhancement images determined the presence of myocardial infarction, if any existed. Pixelwise quantitative perfusion maps were generated using Fermi deconvolution. The results were statistically analyzed with a repeated mixed measures model to block for physiological variation between the animals. Five animals developed myocardial infarction by 3 weeks, while three developed ischemia without an infarction. The perfusion defects were located in the inferolateral myocardium in the perfusion territory of the LCX. Stress perfusion values were higher in remote segments than both the infarcted and ischemic segments (p < 0.01). MPR values were significantly greater in the remote segments than infarcted and ischemic segments (p < 0.01). While the MPR decreased in all segments, the MPR recovered by the sixth week in the remote regions. We developed a model of progressive CAD and evaluated the temporal evolution of the development of quantitative perfusion defects. This model will serve as a platform for understanding the development of perfusion abnormalities in chronic occlusive CAD.

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Section: Experimental Methodsmentioning

confidence: 99%

Section: Cmr Imaging Protocolmentioning

confidence: 99%

Adenosine stress CMR perfusion imaging of the temporal evolution of perfusion defects in a porcine model of progressive obstructive coronary artery occlusion

et al. 2019

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“…Effects of diabetes on myocardial perfusion may be assessed both in absolute terms and as myocardial perfusion reserve. 16 Assessment of myocardial deformation by tagged imaging or feature tracking facilitates detection of altered myocardial strain or torsion which develop early in diabetic cardiomyopathy and are associated with abnormal myocardial perfusion reserve. 17 CMR can readily exclude regional myocardial changes, including infarction and inducible myocardial ischemia, which allows ischemic-myocardial dysfunction to be identified.…”

Section: Cardiovascular Magnetic Resonance Imagingmentioning

confidence: 99%

Diagnosing diabetic cardiomyopathy

2019

Heart Metab

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Diabetic cardiomyopathy reflects the presence of structural or functional abnormalities of the myocardium in an individual with diabetes which are not fully explained by other factors known to cause myocardial dysfunction. Diabetes promotes a range of molecular and cellular changes leading to left ventricular concentric hypertrophy, fibrosis, abnormal perfusion, lipid deposition, altered metabolism, diastolic dysfunction, and later progression to systolic dysfunction. Diagnosis of diabetic cardiomyopathy requires identification of such pathological features whilst at the same time excluding other causes of left ventricular dysfunction. In this article, avail- able modalities which can contribute to a diagnosis of diabetic cardiomyopathy are discussed. In most cases a diagnosis of diabetic cardiomyopathy can be reached by echocardiography or cardiac magnetic resonance imaging to detect structural and functional myocardial changes, with computed tomography coronary angiography being employed to exclude obstructive coronary artery disease which could account for left ventricular dysfunction.

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“…CMR research in valvular heart disease is focused on a number of areas such as free breathing sequences [69], fibrosis evaluation [70, 71], CMR-derived right ventricular strain evaluation [72], and microvascular disease assessment [73]. These advances in CMR technology will provide new information for assessing the heart in patients with valvular heart disease, which may yield new diagnostic and prognostic information.…”

Section: Future Directionsmentioning

confidence: 99%

Role of Cardiac Magnetic Resonance Imaging in Valvular Heart Disease: Diagnosis, Assessment, and Management

2018

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Purpose of Review This article will review the current techniques in cardiac magnetic resonance imaging (CMR) for diagnosing and assessing primary valvular heart disease. Recent Findings The recent advancements in CMR have led to an increased role of this modality for qualifying and quantifying various native valve diseases. Phase-contrast velocity encoded imaging is a well-established technique that can be used to quantify aortic and pulmonic flow. This technique, combined with the improved ability for CMR to obtain accurate left and right ventricular volumetrics, has allowed for increased accuracy and reproducibility in assessing valvular dysfunction. Advancements in CMR technology also allows for improved spatial and temporal resolution imaging of various valves and their regurgitant or stenotic jets. Therefore, CMR can be a powerful tool in evaluation of native valvular heart disease. Summary The role of CMR in assessing valvular heart disease is growing and being recognized in recent guidelines. CMR has the ability to assess valve morphology along with qualifying and quantifying valvular disease. In addition, the ability to obtain accurate volumetric measurements may improve more precise management strategies and may lead to improvements in mortality and morbidity.

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Quantitative cardiovascular magnetic resonance perfusion imaging identifies reduced flow reserve in microvascular coronary artery disease

Cited by 80 publications

References 31 publications

Adenosine stress CMR perfusion imaging of the temporal evolution of perfusion defects in a porcine model of progressive obstructive coronary artery occlusion

Adenosine stress CMR perfusion imaging of the temporal evolution of perfusion defects in a porcine model of progressive obstructive coronary artery occlusion

Diagnosing diabetic cardiomyopathy

Role of Cardiac Magnetic Resonance Imaging in Valvular Heart Disease: Diagnosis, Assessment, and Management

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