New thesis on methods for the analysis and characterization of brain morphology from MRI images
Hi Irene Brusini, PhD student at the Division of Clinical Geriatrics, NVS. On March 25 you will defend your thesis ”Methods for the analysis and characterization of brain morphology from MRI images”, what's the main focus of the thesis?
My thesis aims to advance the knowledge on how brain MRI image analysis can be used to analyze and characterize brain structure. From an MRI scan, it is possible to extract multiple properties of different brain regions, such as their volume and shape. These measures can allow a better understanding of the brain and contribute to the identification of important biomarkers of neurological and psychiatric diseases.
Which are the most important results?
First, the effect of domestication was studied in rabbits, and it was found that this evolutionary process significantly reshaped their brain structure compared to their wild counterparts. Second, lifestyle-induced brain changes were investigated on rats: a healthy lifestyle intervention was found to significantly slow their brain aging. Finally, the three human studies of my thesis show that deep learning-based methods can be successfully used to segment brain structures that can be severely affected by neurodegeneration: in particular, the hippocampus in Alzheimer's patients and the corpus callosum in multiple sclerosis patients. Morphological measures extracted from these brain regions were also shown to be significantly associated with disease state.
How can this new knowledge contribute to the improvement of people’s health?
The results on the positive effects of a healthy lifestyle on brain aging can support the use of lifestyle-related prevention approaches to slow down brain aging. Moreover, my research on brain segmentation in neurodegeneration is valuable to expand the current knowledge on imaging biomarkers, and on how we could improve the clinical routines by making use of advanced deep learning-based tools that can aid diagnosis and disease monitoring.
What's in the future for you? Will you keep on conducting research?
I would love to continue working in this field in the future, and in general to continue to devote my work to improving people's health by promoting and implementing new technologies.