Characterization of neuro-endocrine tumors in an athymic nude mouse model using dedicated synchronization strategies for T2-weigted MR imaging at 7T.

Endocrine tumours, with digestive localization, are tumours with variable forecast which are independent of their invasive and metastatic extensions. The experimental model of endocrine tumors with liver dissemination is available for evaluation of new medical therapeutics such as antiangiogenic therapy. MRI is a non invasive modality allowing in vivo examinations and is suitable to follow liver lesion evolution during longitudinal study on animal models. The goal of this study was to assess the detection level and to characterize the liver lesions in an athymic nude mouse model, using a dedicated MRI protocol and an optimized synchronization strategy at high magnetic field strength. The experiments were performed at 7T. To detect liver lesions, respiratory-triggered T2-weighted MR images is the sequence of choice. With conventional acquisition strategies used on small animal MR systems, trigger signal is performed at each respiratory cycle and thus, the T2 contrast is not freely controlled. Additionally, the slice number is limited by the expiration delay. To overcome these drawbacks, we proposed an original strategy enabling true T2-weighted imaging with minimal movement artifacts, regardless of the respiratory period and the number of slices. This protocol was used to carry out a longitudinal follow-up of hepatic lesions in 8 nude mice at stages D7, D12, D17 and D24. The fraction of lesion over the total liver volume was quantified. Moreover, the characterization of cystic or non-cystic type of lesions was achieved using various TE leading to T2 maps. In conclusion, the level of lesion detection and characterization of liver lesions was performed using a devoted protocol with original synchronization strategy dedicated to high field MRI. MR imaging could be used with relevance in the evaluation of new therapeutics protocol for treatment of liver lesions in neuroendocrine tumors using small animal model.