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The ultimate signal-to-noise ratio in realistic body models.

ABSTRACT: PURPOSE:We compute the ultimate signal-to-noise ratio (uSNR) and G-factor (uGF) in a realistic head model from 0.5 to 21 Tesla. METHODS:We excite the head model and a uniform sphere with a large number of electric and magnetic dipoles placed at 3?cm from the object. The resulting electromagnetic fields are computed using an ultrafast volume integral solver, which are used as basis functions for the uSNR and uGF computations. RESULTS:Our generalized uSNR calculation shows good convergence in the sphere and the head and is in close agreement with the dyadic Green's function approach in the uniform sphere. In both models, the uSNR versus B0 trend was linear at shallow depths and supralinear at deeper locations. At equivalent positions, the rate of increase of the uSNR with B0 was greater in the sphere than in the head model. The uGFs were lower in the realistic head than in the sphere for acceleration in the anterior-posterior direction, but similar for the left-right direction. CONCLUSION:The uSNR and uGFs are computable in nonuniform body models and provide fundamental performance limits for human imaging with close-fitting MRI array coils. Magn Reson Med 78:1969-1980, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

SUBMITTER: Guerin B

PROVIDER: S-EPMC5532082 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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The ultimate signal-to-noise ratio in realistic body models.

Guérin Bastien B Villena Jorge F JF Polimeridis Athanasios G AG Adalsteinsson Elfar E Daniel Luca L White Jacob K JK Wald Lawrence L LL

Magnetic resonance in medicine 20161204 5

<h4>Purpose</h4>We compute the ultimate signal-to-noise ratio (uSNR) and G-factor (uGF) in a realistic head model from 0.5 to 21 Tesla.<h4>Methods</h4>We excite the head model and a uniform sphere with a large number of electric and magnetic dipoles placed at 3 cm from the object. The resulting electromagnetic fields are computed using an ultrafast volume integral solver, which are used as basis functions for the uSNR and uGF computations.<h4>Results</h4>Our generalized uSNR calculation shows go ...[more]

PMID: 27917528

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Project description:MotivationTarget-specific hybridization depends on oligo-probe characteristics that improve hybridization specificity and minimize genome-wide cross-hybridization. Interplay between specific hybridization and genome-wide cross-hybridization has been insufficiently studied, despite its crucial role in efficient probe design and in data analysis.ResultsIn this study, we defined hybridization specificity as a ratio between oligo target-specific hybridization and oligo genome-wide cross-hybridization. A microarray database, derived from the Genomic Comparison Hybridization (GCH) experiment and performed using the Affymetrix platform, contains two different types of probes. The first type of oligo-probes does not have a specific target on the genome and their hybridization signals are derived from genome-wide cross-hybridization alone. The second type includes oligonucleotides that have a specific target on the genomic DNA and their signals are derived from specific and cross-hybridization components combined together in a total signal. A comparative analysis of hybridization specificity of oligo-probes, as well as their nucleotide sequences and thermodynamic features was performed on the database. The comparison has revealed that hybridization specificity was negatively affected by low stability of the fully-paired oligo-target duplex, stable probe self-folding, G-rich content, including GGG motifs, low sequence complexity and nucleotide composition symmetry.ConclusionFiltering out the probes with defined 'negative' characteristics significantly increases specific hybridization and dramatically decreasing genome-wide cross-hybridization. Selected oligo-probes have two times higher hybridization specificity on average, compared to the probes that were filtered from the analysis by applying suggested cutoff thresholds to the described parameters. A new approach for efficient oligo-probe design is described in our study.Contactshabalin@ncbi.nlm.nih.gov or olga.matveeva@gmail.comSupplementary informationSupplementary data are available at Bioinformatics online.

Project description:BackgroundIn MRI, the signal-to-noise ratio (SNR) theoretically increases with B0 field strength. However, because of attenuation of the radiofrequency (RF) fields at 7T, it is not certain if this SNR gain can be realized for prostate imaging.Purpose/hypothesisTo investigate the SNR gain in prostate imaging at 7T as compared with 3T. It is expected that SNR will improve for prostate imaging at 7T compared with 3T.Study typeProspective.SubjectsFour healthy volunteers and one prostate cancer patient.Field strength/sequenceAll subjects were scanned at 3T and at 7T using optimal coil setups for both field strengths. For all volunteers, proton density-weighted images were acquired for SNR analysis and actual flip angle imaging (AFI) B 1 + | maps were acquired for correction of measured SNR values. In the patient, a T2 -weighted (T2 w) image was acquired at 3T and at 7T.AssessmentSNR was calculated in the prostate region for all volunteers. SNR was normalized for flip angle, receiver bandwidth, and voxel volume. SNR was also calculated for different sensitivity encoding (SENSE) acceleration factors.Statistical testingSNR values are represented as the arithmetic mean of SNR values in the prostate. Estimated SNR in the T2 w image is calculated as the arithmetic mean of the signal intensity (SI) divided by the standard deviation of the SI in a specified zone. Tumor-to-tissue contrast is calculated as (SItumor +SIzone )/( SItumor -SIzone ).ResultsAn increase in SNR ranging from 1.7-fold to 2.8-fold was measured in the prostate at 7T in comparison to 3T for four volunteers. At 7T, it is possible to achieve a 4-fold SENSE acceleration in the left-right direction with similar SNR to a nonaccelerated 3T image. T2 w imaging was done at 3T and 7T in one patient, where improved tumor-to-tissue contrast was demonstrated at 7T.Data conclusionSNR improves for prostate imaging at 7T as compared with 3T.Level of evidence2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1446-1455.

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The ultimate signal-to-noise ratio in realistic body models.

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The ultimate signal-to-noise ratio in realistic body models.

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