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2012 Proceedings - International Tissue Elasticity Conference

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030 SENSITIVITY OF MAGNETIC RESONANCE ELASTOGRAPHY TO DETECT BRAIN<br />

DEVELOPMENT AND MATURATION.<br />

Katharina Schregel 1,2 , Julie Le Faouder 2,3 , Eva Würfel 4 , Simon Chatelin 2 , Pierre Bedossa 2,5 ,<br />

Jens Wüerfel 1 , Ralph Sinkus 2 .<br />

1 Institute of Neuroradiology, University Luebeck, Luebeck, GERMANY; 2 Université Paris Diderot,<br />

Sorbonne Paris Cité, INSERM, CRB3 U773, Paris, FRANCE; 3 Institut Fédératif de Recherche<br />

Claude Bernard, Université Paris-Diderot, Paris, FRANCE; 4 Neuropediatrics Department,<br />

University Goettingen, Goettingen, GERMANY; 5 Pathology Department, Beaujon Hospital,<br />

Assistance Publique–Hôpitaux de Paris and Université Paris-Diderot, Paris, FRANCE.<br />

Background: Cerebral tissue structure is altered in many neurodegenerative diseases but also during<br />

physiological processes like maturation or aging. It is reasonable to assume that structural changes<br />

directly affect the mechanical tissue properties. Magnetic Resonance Elastography (MRE) is an imaging<br />

technique capable of assessing biomechanical brain parenchymal properties non–invasively [1].<br />

Viscoelasticity can be quantified by analyzing the propagation of mechanically elicited shear waves in the<br />

investigated tissue. Thus, MRE could be a helpful tool to detect physiological or pathological processes<br />

influencing the cerebral tissue integrity.<br />

Aims: As previously demonstrated, cerebral viscoelastic properties change during ongoing brain<br />

maturation in adolescent mice [2]. However, the underlying cellular or molecular mechanisms responsible<br />

for the observed changes have not been elucidated so far. In the present study, we combine full 3D–MRE<br />

with MALDI–IMS (Matrix Assisted Laser Desorption Ionization Imaging Mass Spectrometry) in order to (1)<br />

prove an age–dependent behavior of cerebral biomechanics and (2) identify the underlying process.<br />

Methods: 20 healthy 4–week-old female C57/BL6 mice were investigated 3–weekly. They were studied for<br />

12 weeks, corresponding to a final age of 16 weeks. High resolution T2–weighted scans in addition to full<br />

3D–MRE were performed on a 7 Tesla rodent scanner. The value of the complex–valued shear modulus<br />

|G*| was calculated in a region of interest (ROI) covering the corpus callosum, rendering information on<br />

its viscoelasticity. After each scanning period, 5 mice were sacrificed and brains were harvested for<br />

further analyses. One part was investigated by MALDI–IMS, the remaining part by<br />

immunohistochemistry.<br />

Results: Viscoelasticity shows a triphasic course, matching the time course already observed in former<br />

experiments [2]: it decreases from week 0 to 3, then increases up to week 9 and stabilizes afterwards.<br />

MALDI–IMS renders matching spectra for all time points. Protein distribution correlates well with<br />

anatomical features and peak intensity differs age–dependently.<br />

Conclusions: Viscoelasticity developed during adolescence and reached a plateau at a mean age of 16<br />

weeks, corresponding to the adulthood of the animals. Protein expression assessed with MALDI–IMS<br />

seems to be age related as well. As volume fraction of the extra–cellular matrix (ECM) is described to<br />

decrease during maturation [3], yet to perform protein identification and immunohistochemistry may help<br />

to identify the exact mechanism responsible for the alterations of brain biomechanics during maturation.<br />

Figure: (A) Quantitative analysis of viscoelasticity |G*| in the<br />

corpus callosum (cc). Triphasic timecourse with<br />

decrease, then increase and plateau of viscoelasticity.<br />

(B) Optical image of the mouse brain with superposed<br />

MALDI–MS image (pink). ROI covers the cc. Protein<br />

distribution correlates with anatomy. (C) Superposed<br />

spectra from different time points. Inlet shows<br />

exemplary that peak intensity changes with age.<br />

References:<br />

[1] Green MA et al.: NMR Biomed, 21, pp, 755–764, 2008.<br />

[2] Schregel K et al.: PNAS, 109, pp. 6650–6655, <strong>2012</strong>.<br />

[3] Sykova E, Mazel T, Simonova Z: Exp Gerontol., 33, pp. 837–851 1998.<br />

114<br />

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