Literature DB >> 31755588

Multi-pathway multi-echo acquisition and neural contrast translation to generate a variety of quantitative and qualitative image contrasts.

Cheng-Chieh Cheng1, Frank Preiswerk1, Bruno Madore1.   

Abstract

PURPOSE: Clinical exams typically involve acquiring many different image contrasts to help discriminate healthy from diseased states. Ideally, 3D quantitative maps of all of the main MR parameters would be obtained for improved tissue characterization. Using data from a 7-min whole-brain multi-pathway multi-echo (MPME) scan, we aimed to synthesize several 3D quantitative maps (T1 and T2 ) and qualitative contrasts (MPRAGE, FLAIR, T1 -weighted, T2 -weighted, and proton density [PD]-weighted). The ability of MPME acquisitions to capture large amounts of information in a relatively short amount of time suggests it may help reduce the duration of neuro MR exams.
METHODS: Eight healthy volunteers were imaged at 3.0T using a 3D isotropic (1.2 mm) MPME sequence. Spin-echo, MPRAGE, and FLAIR scans were performed for training and validation. MPME signals were interpreted through neural networks for predictions of different quantitative and qualitative contrasts. Predictions were compared to reference values at voxel and region-of-interest levels.
RESULTS: Mean absolute errors (MAEs) for T1 and T2 maps were 216 ms and 11 ms, respectively. In ROIs containing white matter (WM) and thalamus tissues, the mean T1 /T2 predicted values were 899/62 ms and 1139/58 ms, consistent with reference values of 850/66 ms and 1126/58 ms, respectively. For qualitative contrasts, signals were normalized to those of WM, and MAEs for MPRAGE, FLAIR, T1 -weighted, T2 -weighted, and PD-weighted contrasts were 0.14, 0.15, 0.13, 0.16, and 0.05, respectively.
CONCLUSIONS: Using an MPME sequence and neural-network contrast translation, whole-brain results were obtained with a variety of quantitative and qualitative contrast in ~6.8 min.
© 2019 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  contrast translation; machine learning; multi-pathway multi-echo acquisition; quantitative imaging; synthetic imaging

Mesh:

Year:  2019        PMID: 31755588      PMCID: PMC7047605          DOI: 10.1002/mrm.28077

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


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