The mechanisms of arterial signal intensity profile in non-contrast coronary MRA (NC-MRCA): a 3D printed phantom investigation and clinical translations

The international journal of cardiovascular imaging(2022)

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摘要
Signal intensity (SI) drop has been proposed as an indirect stenosis assessment in non-contrast coronary MRA (NC-MRCA) but it uses unproven assumptions . We aimed to clarify the mechanisms that govern the SI in vitro and develop a stenosis detection method in vivo. Flow phantom tubes with/without stenosis were scanned under two spatial resolutions (0.5/1.0 mm 3 ) on a 3.0 T MRI. Thirty-two coronary arteries from 11 volunteers were prospectively scanned with an EKG- and respiratory-gated 3D NC-MRCA with a resolution of 1.0 mm 3 , with coronary computed tomography angiography (CTA) as reference. The normalized SI along the centerline of the tubes or the coronary arteries was assessed against the distance from the orifice using a linear regression model. Its coefficient (SI decay slope) and goodness-of-fit (R2) were extracted to assess the effect of flow velocity and stenosis on the SI profile curve. The R2 was utilized for the stenosis detection. Phantom study: A slow flow velocity caused a steep SI decay slope. The SI drop revealed only at the inlet and outlet of stenosis due to the flow turbulence/vortex and yielded low R2, in which shape changed by the resolution. Clinical study: The R2 cutoff to detect ≥ 50% stenosis for the left and right coronary arteries were 0.64 and 0.20 with a sensitivity/specificity of 71.5/71.5 and 66.7/100 (%), respectively. The SI drop did not reflect the actual stenosis position and not suitable for the stenosis localization. The R2 cutoff represents an alternative method to detect stenoses on NC-MRCA at vessel level. Trial registration: ClinicalTrials.gov; NCT03768999, registered on December 7, 2018.
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关键词
3D-printed phantom,Coronary stenosis detection,Deep learning-based denoising,Non-contrast coronary MRA,SI profile curve,Transluminal attenuation gradient (TAG)
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