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Section: New Results
Applications in Neuroradiology and Neurological Disorders
Brain perfusion gender differences using ASL in young adults
Participants : Léa Itmi, Pierre Maurel, Isabelle Corouge, Jean-Christophe Ferré, Christian Barillot.
The use of population models is becoming increasingly important in cerebral imaging, particularly using Arterial Spin Labeling perfusion imaging. Therefore, it is important to know the limits of the models before applying them, to guarantee the reliability of the results. It is now well-known that brain perfusion, in particular cerebral blood flow (CBF), changes with age, and this effect needs to be taken into account when evaluating brain perfusion images. But gender differences have not been well studied yet. It is known that female brain perfusion is, in average, higher than male brain perfusion, but only few studies have investigated whether some regional perfusion differences exist or not. This work aims to assess whether, as for the age, gender differences should be taken into account when analyzing brain perfusion images. We then focus on adult subjects and study the CBF gender differences. We compared the raw CBF means and the means after normalization, we also investigated perfusion asymetries. We used atlases for the region comparisons and the General Linear Model for the voxel level. Our results confirmed that women have a higher CBF than men, and showed that this difference can be suppressed with a normalization process, but no specific major regional difference or asymmetry was found.
Arterial Spin Labeling Motor Activation Presurgical Mapping for Brain Tumor Resection
Participants : Isabelle Corouge, Elise Bannier, Jean-Christophe Ferré.
Functional Arterial Spin Labeling (fASL) has demonstrated its greater specificity as a marker of neuronal activity than the reference BOLD fMRI for motor activation mapping in healthy volunteers. Motor fASL is yet to be investigated in the context of tumors, under the assumption that fASL would be less sensitive to venous contamination induced by the hemodynamics remodeling in the tumor vicinity than BOLD fMRI. As the arterial transit time may be shortened in activation areas, this preliminary study explores the ability of fASL to map the motor areas at different post-labeling delays (PLD) in healthy subjects and patient with brain tumor [21] .
Dynamic assessment of macrophages infiltration and tissue damage in MS lesions
Participants : Anne Kerbrat, Benoit Combès, Olivier Commowick, Jean-Christophe Ferré, Elise Bannier, Christian Barillot, Gilles Edan.
Inflammation is a dynamic and complex process that could be beneficial when it supports tissue repair but also detrimental when excessive, leading to worsen tissue injury. In multiple sclerosis, it is well known from pathological and MRI studies that the prognostic between white matter lesions differed at the lesion level. Thus, 10 to 30% of T2 hyperintense lesions are seen as area of persistent hypointensity on T1-w images. These T1 hypointensity are areas of pathologically confirmed severe axonal loss. Complementary, quantitative MRI such as Diffusion imaging, magnetization transfer imaging and relaxometry can quantify and characterize tissue changes on MRI before, during, and after the evolution of a new MRI-detected lesion. They are related to damage to myelin and axons. However, identifying in vivo the dynamic pathophysiological processes that leads to these various degree of demyelination and axonal loss in MS lesions remained challenging. In recent year, molecular and cellular imaging of the inflammatory process have been developed. Although some techniques remains at the pre-clinical level, MRI using non targeted USPIO as contrast agent can be used in MS patients. USPIO are phagocyted in periphery by macrophages and migrate to the central nervous system to characterize in vivo macrophages infiltrations within lesions. The association of cellular imaging and longitudinal quantitative MRI consist of a great opportunity to assess more specifically the overall process. In a recent study from our group, we demonstrated that infiltration of activated macrophages evidenced by USPIO enhancement, was present at the onset of MS and associated with higher local loss of tissue structure [17] . This year, we pursued this work by analyzing a longitudinal study with USPIO infusion every 3 months, associated with quantitative MRI assessment including MTI, diffusion imaging and relaxometry with the objectives of describing relationships between macrophages infiltration and quantitative MRI metrics reflecting tissue structure along time.
The effect of water suppression on the hepatic lipid quantification, as assessed by the LCModel, in a preclinical and clinical scenario
Participant : Elise Bannier.
This work investigates the effect of water suppression on the hepatic lipid quantification, using the LCModel. MR spectra with and without water suppression were acquired in the liver of mice at 4.7 T and patients at 3 T, and processed with the LCModel. The Cramer-Rao Lower Bound (CRLB) values of the seven lipid resonances were determined to assess the impact of water suppression on hepatic lipid quantification. A paired t test was used for comparison between the CRLBs obtained with and without water suppression. For the preclinical data, in the high (low) fat fraction subset an overall impairment in hepatic lipid quantification, i.e. an increase of CRLBs (no significant change of CRLBs) was observed in spectra acquired with water suppression. For the clinical data, there were no substantial changes in the CRLB with water suppression. Because (1) the water suppression does not overall improve the quantification of the lipid resonances and (2) the MR spectrum without water suppression is always acquired for fat fraction calculation, the optimal data-acquisition strategy for liver MRS is to acquire only the MR spectrum without water suppression. For quantification of hepatic lipid resonances, it is advantageous to perform MR spectroscopy without water suppression in a clinical and preclinical scenario (at moderate fields) [14] .