Optimized Three-Dimensional Cardiovascular Magnetic Resonance Whole Heart Imaging Utilizing Non-Selective Excitation and Compressed Sensing in Children and Adults with Congenital Heart Disease

Background:In congenital heart disease(CHD)patients,detailed three-dimensional anatomy depiction plays a pivotal role for diagnosis and therapeutical decision making.Hence,the present study investigated the applicability of an advanced cardiovascular magnetic resonance(CMR)whole heart imaging approach utilizing nonselective excitation and compressed sensing for anatomical assessment and interventional guidance of CHD patients in comparison to conventional dynamic CMR angiography.Methods:86 consecutive pediatric patients and adults with congenital heart disease(age,1 to 74 years;mean,35 years)underwent CMR imaging including a freebreathing,ECG-triggered 3D nonselective SSFP whole heart acquisition using compressed SENSE(nsWHcs).Anatomical assessability and signal intensity ratio(SIR)measurements were compared with conventional dynamic 3D-/4D-MR angiography.Results:The most frequent diagnoses were partial anomalous pulmonary venous drainage(17/86,20%),transposition of the great arteries(15/86,17%),tetralogy of Fallot(12/86,14%),and a single ventricle(7/86,8%).Image quality of nsWHcs was rated as excellent/good in 98%of patients.nsWHcs resulted in a reliable depiction of all large thoracic vessels(anatomic assessability,99%–100%)and the proximal segments of coronary arteries and coronary sinus(>90%).nsWHcs achieved a homogenously distributed SIR in all cardiac cavities and thoracic vessels without a significant difference between pulmonary and systemic circulation(10.9±3.5 and 10.6±3.4;p=0.15),while 3D angiography showed significantly increased SIR for targeted vs.non-targeted circulation(PA-angiography,15.2±8.1 vs.5.8±3.6,p<0.001;PV-angiography,7.0±3.9 vs.17.3±6.8,p<0.001).Conclusions:The proposed nsWHcs imaging approach provided a consistently high image quality and a homogeneous signal intensity distribution within the pulmonary and systemic circulation in pediatric patients and adults with a wide spectrum of congenital heart diseases.nsWHcs enabled detailed anatomical assessment and three-dimensional reconstruction of all cardiac cavities and large thoracic vessels and can be regarded particularly useful for preprocedural planning and interventional guidance in CHD patients.

Diagnosis and management of ischemic cardiomyopathy: Role of cardiovascular magnetic resonance imaging

Coronary artery disease(CAD) represents an important cause of mortality. Cardiovascular magnetic resonance(CMR) imaging evolved as an imaging modality that allows the assessment of myocardial function, perfusion, contractile reserve and extent of fibrosis in a single comprehensive exam. This review highlights the role of CMR in the differential diagnosis of acute chest pain by detecting the location of obstructive CAD or necrosis and identifying other conditions like stress cardiomyopathy or myocarditis that can present with acute chest pain. Besides, it underlines the prognostic implication of perfusion abnormalities in the setting of acute chest pain. Furthermore, the review addresses the role of CMR to detect significant CAD in patients with stable CAD. It elucidates the accuracy and clinical utility of CMR with respect to other imaging modalitieslike single-photon emission computed tomography and positron emission tomography. Besides, the prognostic value of CMR stress testing is discussed. Additionally, it summarizes the available CMR techniques to assess myocardial viability and describes algorithm to identify those patient who might profit from revascularization those who should be treated medically. Finally, future promising imaging techniques that will provide further insights into the fundamental disease processes in ischemic cardiomyopathy are discussed.

Artificial intelligence and machine learning in cardiovascular computed tomography

Computed tomography(CT)is emerging as a prominent diagnostic modality in the field of cardiovascular imaging.Artificial intelligence(AI)is making significant strides in the field of information technology,the commercial industry,and health care.Machine learning(ML),a branch of AI,can optimize the performance of CT and augment the assessment of coronary artery disease.These ML platforms can automate multiple tasks,perform calculations,and integrate information from a variety of data sources.In this review article,we explore the ML in CT imaging.

Role of nuclear cardiology for guiding device therapy in patients with heart failure

Heart failure is a dynamic condition with high morbidity and mortality and its prognosis should be reassessed frequently, particularly in patients for whom critical treatment decisions may depend on the results of prognostication. In patients with heart failure, nuclear cardiology techniques are useful to establish the etiol-ogy and the severity of the disease, while fewer studies have explored the potential capability of nuclear cardi-ology to guide cardiac resynchronization therapy （CRT） and to select patients for implantable cardioverter defbrillators （ICD）. Left ventricular synchrony may be assessed by radionuclide angiography or gated single-photon emission computed tomography myocardial perfusion scintigraphy. These modalities have shown promise as predictors of CRT outcome using phase analysis. Combined assessment of myocardial viability and left ventricular dyssynchrony is feasible using posi-tron emission tomography and could improve conven-tional response prediction criteria for CRT. Preliminary data also exists on integrated positron emission tomog-raphy/computed tomography approach for assessing myocardial viability, identifying the location of biven-tricular pacemaker leads, and obtaining left ventricular functional data, including contractile phase analysis. Fi-nally, cardiac imaging with autonomic radiotracers may be useful in predicting CRT response and for identifying patients at risk for sudden cardiac death, therefore po-tentially offering a way to select patients for both CRT and ICD therapy. Prospective trials where imaging is combined with image-test driven therapy are needed to better defne the role of nuclear cardiology for guiding device therapy in patients with heart failure.