Accelerated high-resolution free-breathing 3D whole-heart T2-prepared black-blood and bright-blood cardiovascular magnetic resonance

Abstract

Background The free-breathing 3D whole-heart T2-prepared Bright-blood and black-blOOd phase SensiTive inversion recovery (BOOST) cardiovascular magnetic resonance (CMR) sequence was recently proposed for simultaneous bright-blood coronary CMR angiography and black-blood late gadolinium enhancement (LGE) imaging. This sequence enables simultaneous visualization of cardiac anatomy, coronary arteries and fibrosis. However, high-resolution (< 1.4 × 1.4 × 1.4 mm3) fully-sampled BOOST requires long acquisition times of ~ 20 min. Methods In this work, we propose to extend a highly efficient respiratory-resolved motion-corrected reconstruction framework (XD-ORCCA) to T2-prepared BOOST to enable high-resolution 3D whole-heart coronary CMR angiography and black-blood LGE in a clinically feasible scan time. Twelve healthy subjects were imaged without contrast injection (pre-contrast BOOST) and 10 patients with suspected cardiovascular disease were imaged after contrast injection (post-contrast BOOST). A quantitative analysis software was used to compare accelerated pre-contrast BOOST against the fully-sampled counterpart (vessel sharpness and length of the left and right coronary arteries). Moreover, three cardiologists performed diagnostic image quality scoring for clinical 2D LGE and both bright- and black-blood 3D BOOST imaging using a 4-point scale (1–4, non-diagnostic–fully diagnostic). A two one-sided test of equivalence (TOST) was performed to compare the pre-contrast BOOST images. Nonparametric TOST was performed to compare post-contrast BOOST image quality scores. Results The proposed method produces images from 3.8 × accelerated non-contrast-enhanced BOOST acquisitions with comparable vessel length and sharpness to those obtained from fully- sampled scans in healthy subjects. Moreover, in terms of visual grading, the 3D BOOST LGE datasets (median 4) and the clinical 2D counterpart (median 3.5) were found to be statistically equivalent (p < 0.05). In addition, bright-blood BOOST images allowed for visualization of the proximal and middle left anterior descending and right coronary sections with high diagnostic quality (mean score > 3.5). Conclusions The proposed framework provides high‐resolution 3D whole-heart BOOST images from a single free-breathing acquisition in ~ 7 min.

Three-dimensional static-fluid MR urography with gradient- and spin-echo (GRASE) at 3.0T: comparison of image quality and diagnostic performance with respiratory-triggered fast spin-echo (FSE)

“…A Wilcoxon signed-rank test was used to evaluate the differences in the qualitative scores of overall imaging quality, artifacts, and structure visualization between the two MRU techniques. A two one-sided test of equivalence (TOST) based on the Wilcoxon signed-rank test was performed to assess the equivalence of qualitative scores of the two MRU images, using a ± 0.5 equivalence region [21,22]. Kappa statistics or intraclass correlation coefficient (ICC) were calculated (1) to measure the interobserver agreement between two readers; and (2) to evaluate the inter-sequence consistency for performance ability between BH-GRASE and RT-FSE.…”

Cardiac MR: From Theory to Practice

“…CMR also has the added advantage of enabling visualization of the aorta and great vessels which can often need intervention in patients with aortic valve disease, particularly if this is associated with aortopathy such as patients with bicuspid aortic valves. This can be achieved using time-resolved angiographic approaches (110), as well as with 3D-sequences acquired in freebreathing that can increasingly be combined with multiple tissue contrasts (111)(112)(113). The former can enable the visualization of multiple vascular beds and structures (systemic venous, pulmonary arterial and venous, and systemic arterial) with a single dose of contrast (Figure 7) (110).…”

Dark-blood late gadolinium-enhancement cardiac magnetic resonance imaging for myocardial scar detection based on simplified timing scheme: single-center experience in patients with suspected coronary artery disease

“…This could be done via patient-specific, data-driven or even machine learning-aided optimization (20), in which case full automation may be expected to address challenge in routine clinical workflow and to minimize additional examination times. Given these limitations, larger studies in patients are warranted to further assess the diagnostic value and clinical impact of DB-LGE for scar detection, particularly in comparison to other existing methods either without additional magnetization preparation (16,17) or in free-breathing (29) or 3D imaging (30).…”