Sub-1-min relaxation-enhanced non-contrast non-triggered cervical MRA using compressed SENSE with deep learning reconstruction in healthy volunteers.

Abstract

Background: We evaluated the acceleration of a three-dimensional isotropic flow-independent magnetic resonance angiography (MRA) (relaxation-enhanced angiography without contrast and triggering, REACT) of neck arteries using compressed SENSE (CS) combined with deep learning (adaptive intelligence, AI)-based reconstruction (CS-AI).

Methods: Thirty-four volunteers received 3-T REACT MRA, acquired threefold: (i) CS acceleration factor 7 (CS7), scan time 1:20 min:s; (ii) CS acceleration factor 10 (CS10), scan time 0:55 min:s; and (iii) CS-AI acceleration factor 10 (CS10-AI), scan time 0:55 min:s. Two radiologists rated the image quality of seven arterial segments and overall image noise. Additionally, a pairwise forced-choice comparison was conducted. Apparent signal-to-noise ratio (aSNR) and contrast-to-noise ratio (aCNR) were measured, and image sharpness was assessed using the edge-rise distance (ERD). Multiple t-tests and nonparametric tests with Bonferroni correction were performed for comparison to CS7 as the reference standard.

Results: Compared to CS7, CS10 showed lower image quality (p < 0.001) while CS10-AI obtained higher scores (p = 0.010). Image noise was similar between CS7 and CS10 (p = 0.138) while CS10-AI yielded a lower noise (p = 0.008). Forced choice revealed preferences for CS7 over CS10 (p < 0.001), but no preference between CS7 and CS10-AI (p > 0.999). Compared to CS7, aSNR and aCNR were lower in CS10 (p < 0.001) and the ERD was longer (p = 0.004), while CS10-AI provided better aSNR and aCNR (p = 0.001) and showed no difference in ERD (p = 0.776).

Conclusion: Sub-1-min CS-AI cervical REACT MRA was acquired without compromising image quality.

Relevance statement: The implementation of a fast and reliable non-contrast MRA has the potential to reduce costs and time while increasing patient comfort and safety. Clinical studies evaluating the diagnostic performance for stenosis or dissection are needed.

Trial registration: DRKS00030210 (German Clinical Trials Register; https://drks.de/ ) KEY POINTS: Deep learning reconstruction enables sub-1-min non-contrast-enhanced MRA of extracranial arteries. Acceleration without deep learning reconstruction causes inferior image quality. Acceleration with deep learning reconstruction exceeds, in part, the clinical standard.