Multi-voxel algorithm for quantitative bi-exponential MRI T1 estimation

P. Bladt; G. Van Steenkiste; G. Ramos-Llordén; A. J. den Dekker; J. Sijbers

doi:10.1117/12.2216831

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21 March 2016 Multi-voxel algorithm for quantitative bi-exponential MRI T₁ estimation

P. Bladt, G. Van Steenkiste, G. Ramos-Llordén, A. J. den Dekker, J. Sijbers

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Proceedings Volume 9784, Medical Imaging 2016: Image Processing; 978402 (2016) https://doi.org/10.1117/12.2216831
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Quantification of the spin-lattice relaxation time, T₁, of tissues is important for characterization of tissues in clinical magnetic resonance imaging (MRI). In T₁ mapping, T₁ values are estimated from a set of T₁-weighted MRI images. Due to the limited spatial resolution of the T₁-weighted images, one voxel might consist of two tissues, causing partial volume effects (PVE). In conventional mono-exponential T₁ estimation, these PVE result in systematic errors in the T₁ map. To account for PVE, single-voxel bi-exponential estimators have been suggested. Unfortunately, in general, they suffer from low accuracy and precision. In this work, we propose a joint multi-voxel bi-exponential T₁ estimator (JMBE) and compare its performance to a single-voxel bi-exponential T₁ estimator (SBE). Results show that, in contrast to the SBE, and for clinically achievable single-voxel SNRs, the JMBE is accurate and efficient if four or more neighboring voxels are used in the joint estimation framework. This illustrates that, for clinically realistic SNRs, accurate results for quantitative biexponential T₁ estimation are only achievable if information of neighboring voxels is incorporated.

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P. Bladt, G. Van Steenkiste, G. Ramos-Llordén, A. J. den Dekker, and J. Sijbers "Multi-voxel algorithm for quantitative bi-exponential MRI T₁ estimation", Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 978402 (21 March 2016); https://doi.org/10.1117/12.2216831

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