Compared to other types of imaging, in MRI it is possible to acquire images with different contrasts (T1, T2 and proton density weighted contrasts). By playing with the acquisition parameters, it is possible to minimize or accentuate the signal of certain tissues. The weighted images contain additional information, which can be summarized by the clinician to make a diagnosis. Nevertheless, to further improve the analysis, it would be interesting to obtain quantitative parametric images that provide information that is more reliable, unbiased and reproducible.
This is not a trivial technological leap, especially at ultra-high magnetic fields. Researchers at the CEA-Joliot (NeuroSpin), in collaboration with the CRMBM (Marseille) and the ICM (Paris), have developed a unique sequence to acquire in parallel all the parameters needed to reconstruct different parametric (and superimposable) maps for the entire brain, and in a time frame suitable for clinical examination.
Eleven contrasts were acquired from six healthy volunteers at 7 teslas, using an optimized sequence. These preliminary results show a robust retrieval of the principal maps used by clinicians (proton density, flip angle, T1 and T2). With this method, reproducible quantification could make personalized diagnosis possible.
“Somewhat like a biological analysis of a blood sample, we would be able to tell a patient which parameter in a specific area (voxel) of the brain is not within normal range,” explains Alexandre Vignaud, coordinator of this study. “On the longer term, all the data could be interpreted by artificial intelligence algorithms to assist diagnosis,” he concludes.
Frédéric Joliot Institute for Life Sciences - CEA Paris-Saclay
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Paris brain institute, Paris
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Center for Magnetic Resonance in Biology and Medicine, Marseille
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