Seeking a Widely Adoptable Practical Standard to Estimate Signal‐to‐Noise Ratio in Magnetic Resonance Imaging for Multiple‐Coil Reconstructions

• Published in: Journal of magnetic resonance imaging Vol. 54; no. 6; pp. 1952 - 1964
• Main Authors: Montin, Eros, Lattanzi, Riccardo
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.12.2021; Wiley Subscription Services, Inc
• Subjects: array combining; Background noise; Entropy; Field strength; Image processing; Image reconstruction; Magnetic resonance imaging; Neuroimaging; Noise; Noise standards; Performance evaluation; pseudo multiple replica; Resonance; signal‐to‐noise ratio; SNR; Stability analysis; Statistical analysis; Statistical methods; Statistical tests; Subtraction
• ISSN: 1053-1807; 1522-2586; 1522-2586
• DOI: 10.1002/jmri.27816

Background Signal‐to‐noise ratio (SNR) is used to evaluate the performance of magnetic resonance (MR) imaging systems. Accurate and consistent estimations are needed to routinely use SNR to assess coils and image reconstruction techniques. Purpose To identify a reliable and practical method for SNR estimation in multiple‐coil reconstructions. Study Type Technical evaluation and comparison. Subjects/Phantom A uniform phantom and four healthy volunteers: 35, 38, 39 y/o males, 25 y/o female. Field Strength/Sequence Two‐dimensional multislice gradient‐echo pulse sequence at 3 T and 7 T. Assessment Reference‐standard SNR was calculated from 100 multiple replicas. Six SNR methods were compared against it: difference image (DI), analytic array combination (AC), pseudo‐multiple‐replica (PMR), generalized pseudo‐replica (GPR), smoothed image subtraction (SIS), and DI with temporal instability correction (TIC). The assessment was repeated for different multiple‐coil reconstructions. Statistical Tests SNR methods were evaluated in terms of relative deviation (RD) and normalized mutual information (NMI) with respect to the reference‐standard, using a linear regression (0.05 significance level) to assess how different factors affect accuracy. Results Average RD (phantom) for DI, AC, PMR, GPR, SIS, and TIC was 7.9%, 6%, 6.7%, 10.1%, 40%, and 14.6%, respectively. RD increased with acceleration. SNR maps with AC were the most similar to the reference standard (NMI = 0.358). Considering all brain regions of interest, average RD for all SNR methods varied 96% among volunteers but remained approximately 10% for AC, PMR, and GPR, whereas it was more than 30% for DI, SIS, and TIC. RD was mainly affected by image reconstruction (beta = 12) for AC and SNR entropy for SIS (beta = 19). Data Conclusion AC provided accurate and robust SNR estimation. PMR and GPR are more generally applicable than AC. DI and TIC should be used only at low acceleration factors, when an additional noise‐only scan cannot be acquired. SIS is a single‐acquisition alternative to DI for generalized autocalibrating partial parallel acquisition (GRAPPA) reconstructions. Evidence Level 1 Technical Efficacy Stage 1