Single-shot cine MRI reduced artifacts and matched conventional measurements in ventricular function assessment.
AI-enhanced single-shot cine MRI produces improved image quality and provides ventricular measurements comparable to conventional cine MRI, according to research published in Radiology: Cardiothoracic Imaging, a journal of the Radiological Society of North America.
Accurate assessment of left ventricular function is used to guide treatment decisions, monitor therapeutic response, and predict outcomes in patients with heart failure. Cardiac MRI is commonly used for this purpose and is typically performed using conventional cine sequences known as balanced steady-state free precession. These sequences require multiple breath-holds, which can be difficult for patients with arrhythmia.
“For patients with severe arrhythmias, breath-holding can be particularly challenging, often resulting in compromised image quality, exam failure or inaccurate assessments,” says Nan Zhang, MS, supervisor radiologic technologist in the Department of Radiology at Zhongshan Hospital of Fudan University in Shanghai, in a release.
Single-shot cine sequences capture the full cardiac cycle in two heartbeats, reducing breath-hold requirements and limiting the effects of arrhythmia on image quality.
In the study, Zhang and colleagues evaluated deep-learning–enhanced Compressed SENSE (AI-CS) for assessing left ventricular structure and function. The cohort included 25 healthy volunteers and 45 patients with suspected arrhythmias. Each participant underwent imaging with both conventional cine MRI and AI-CS single-shot cine sequences.
Researchers measured left ventricular parameters including end-diastolic and end-systolic volume, stroke volume, ejection fraction, and strain metrics. Three cardiovascular radiologists independently reviewed the images, assessing artifacts and visualization of cardiac structures.
The AI-CS single-shot cine approach showed improved image quality compared to conventional cine, particularly in patients with arrhythmia, with fewer mistrigger events and motion artifacts. It also demonstrated good-to-excellent agreement with conventional cine for measurements of biventricular volumes and left ventricular mass.
In cases where conventional cine imaging failed, AI-CS provided ejection fraction measurements comparable to echocardiography.
“The AI-CS sequence effectively avoided the cardiac motion artifacts commonly caused by mistriggering in conventional cine,” Zhang said. “It also demonstrated a shorter mean acquisition time while providing improved image quality, particularly in the visualization of the endocardial border, epicardial border, papillary muscles and cardiac motion.”
The success rate for AI-CS single-shot cine imaging was 100% in the study, compared to 88% for conventional cine imaging.
“The AI-CS framework offers a promising alternative for cardiac MRI examinations in the clinical setting, where long acquisition time remains a major challenge,” Zhang added. “Further optimization of the AI-CS framework, particularly regarding image contrast and artifact reduction, will enhance its applicability in routine clinical practice.”
Photo caption: Representative images of participants with difficulty with breath holding and arrhythmia. In the lower right corner of A–L, the position coordinates of the images are marked. Short-axis (SA) view images in the end-systole (A–F) and end-diastole (G–L) phases in participants with atrial fibrillation. (A–C, G–I) Balanced steady-state free precession (bSSFP) cardiac cine. (D–F, J–L) Deep learning–enhanced compressed sensing (AI-CS) single-shot cardiac cine. In contrast to AI-CS single-shot cardiac cine, endocardial contours were challenging to identify on conventional segmented cine in midventricular and apical sections. (M) Line graph of time curve during the whole cardiac cycle obtained from bSSFP cardiac cine. (N) Line graph of time curve during the whole cardiac cycle obtained from AI-CS single-shot cardiac cine. LV = left ventricle., 2D = two-dimensional.
Photo credit: RSNA
