Caron, I and Micotti, E and Paladini, A and Merlino, G and Plebani, L and Forloni, G and Modo, M and Bendotti, C
(2015)
Comparative magnetic resonance imaging and histopathological correlates in two SOD1 transgenic mouse models of amyotrophic lateral sclerosis.
PLoS ONE, 10 (7).
Abstract
Amyotrophic Lateral Sclerosis (ALS) is a progressive and fatal disease due to motoneuron degeneration. Magnetic resonance imaging (MRI) is becoming a promising non-invasive approach to monitor the disease course but a direct correlation with neuropathology is not feasible in human. Therefore in this study we aimed to examine MRI changes in relation to histopathology in two mouse models of ALS (C57BL6/J and 129S2/SvHsd SOD1G93A mice) with different disease onset and progression. A longitudinal in vivo analysis of T2 maps, compared to ex vivo histological changes, was performed on cranial motor nuclei. An increased T2 value was associated with a significant tissue vacuolization that occurred prior to motoneuron loss in the cranial nuclei of C57 SOD1G93A mice. Conversely, in 129Sv SOD1G93A mice, which exhibit a more severe phenotype, MRI detected a milder increase of T2 value, associated with a milder vacuolization. This suggests that alteration within brainstem nuclei is not predictive of a more severe phenotype in the SOD1G93A mouse model. Using an ex vivo paradigm, Diffusion Tensor Imaging was also applied to study white matter spinal cord degeneration. In contrast to degeneration of cranial nuclei, alterations in white matter and axons loss reflected the different disease phenotype of SOD1G93A mice. The correspondence between MRI and histology further highlights the potential of MRI to monitor progressive motoneuron and axonal degeneration non-invasively in vivo. The identification of prognostic markers of the disease nevertheless requires validation in multiple models of ALS to ensure that these are not merely model-specific. Eventually this approach has the potential to lead to the development of robust and validated non-invasive imaging biomarkers in ALS patients, which may help to monitor the efficacy of therapies.
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