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Abstract #1670

Towards clinic-ready relaxometry with MR-STAT: multi-site repeatability, motion detection and integration in the clinical data workflow

Edwin Versteeg1, Oscar van der Heide1, Francesco Ghielmetti2, Marta Lancione3, Michela Tosetti3, Laura Biagi3, Matteo Cencini4, Anna Nigri2, Domenico Aquino2, Cornelis van den Berg1, and Alessandro Sbrizzi1
1Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, Netherlands, 2IRCCS Istituto Neurologico Carlo Besta, Milan, Italy, 3IRCCS Fondazione Stella Maris, Pisa, Italy, 4INFN Sezione di Pisa, Pisa, Italy

Synopsis

Keywords: Quantitative Imaging, Quantitative Imaging

Motivation: Clinical adoption of transient-state based relaxometry methods necessitates the assessment of repeatability and robustness of the quantitative MRI method.

Goal(s): Present a multi-site repeatability, automatic motion detection and DICOM-based reconstruction for the MR-STAT framework

Approach: MR-STAT is a quantitative imaging framework that reconstruction T1/T2 directly from time-domain data. Repeatability was investigated in healthy volunteers at two different medical centers. A histogram-based automatic motion framework was developed and a DICOM-based reconstruction pipeline was validated.

Results: Repeatability experiments demonstrated intra-subject of less than 1.2% for T1/T2. Motion was detected automatically in a subject with motion and DICOM-based reconstruction were equivalent to a raw-data pipeline.

Impact: This work shows that quantitative MRI (MR-STAT) yields repeatable results and can be incorporated in a clinical data workflow by using a DICOM-based reconstruction and automatic motion detection.

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