Volumetric assessment and longitudinal changes of subcortical structures in formalinized Beagle brains.
Francesca Del SignoreGermain ArribaratLeonardo Della SaldaGiovanni MogicatoAlexandra DeviersBenjamin CartiauxMassimo VignoliPatrice PeranFrancesco de PasqualePublished in: PloS one (2022)
High field MRI is an advanced technique for diagnostic and research purposes on animal models, such as the Beagle dog. In this context, studies on neuroscience applications, e.g. aging and neuro-pathologies, are currently increasing. This led to a need for reference values, in terms of volumetric assessment, for the structures typically involved. Nowadays, several canine brain MRI atlases have been provided. However, no reports are available regarding the measurements' reproducibility and little is known about the effect of formalin on MRI segmentation. Here, we assessed the segmentation variability of selected structures among operators (two operators segmented the same data) in a sample of 11 Beagle dogs. Then, we analyzed, for one Beagle dog, the longitudinal volumetric changes of these structures. We considered four conditions: in vivo, post mortem (after euthanasia), ex vivo (brain extracted and studied after 1 month in formalin, and after 12 months). The MRI data were collected with a 3 T scanner. Our findings suggest that the segmentation procedure was overall reproducible since only slight statistical differences were detected. In the post mortem/ ex vivo comparison, most structures showed a higher contrast, thereby leading to greater reproducibility between operators. We observed a net increase in the volume of the studied structures. This could be justified by the intrinsic relaxation time changes observed because of the formalin fixation. This led to an improvement in brain structure visualization and segmentation. To conclude, MRI-based segmentation seems to be a useful and accurate tool that allows longitudinal studies on formalin-fixed brains.
Keyphrases
- contrast enhanced
- deep learning
- high resolution
- convolutional neural network
- magnetic resonance imaging
- diffusion weighted imaging
- white matter
- resting state
- magnetic resonance
- computed tomography
- cross sectional
- electronic health record
- machine learning
- functional connectivity
- big data
- artificial intelligence
- mass spectrometry
- single molecule
- blood brain barrier
- subarachnoid hemorrhage
- clinical evaluation
- dual energy