The neurogeometry project: how autistic spectrum disorder is reflected in the fractal dimensionality of multiparametric MRI
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Background Blood biomarkers levels are useful tools for the diagnosis and follow-up of some
diseases – e.g., glycated haemoglobin in diabetes control – so, some organs have a defined rate
of molecular synthesis. The brain is not less than other organs, so psychiatric entities must surely
leave their footprint in some way. For this reason, if fractal study perspective allows measuring the
complexity that characterizes both disease and wellness, clinical differences can be quantified with
multiparametric MRI and analysed with fractal geometry – in order to validate new imaging
biomarkers.
Objective To determine imaging biomarkers based on the structural and functional brain
connectivity in a first stage – as fractal imaging biomarkers related to the severity of the clinical
presentation – and to validate these new imaging biomarkers in a second stage.
Methodology The more convenient study design is a multicentre analytical transversal study –
addressed to young adults. Participants of the project will be divided into people of the spectrum
and neurotypical people as equal as possible.
The study setting in the first stage is to realise a standardized assessment protocol in order to
collect the data of the independent variable and covariates. Then, in a maximum period of two
weeks after completing the clinical evaluation, it will be performed an MRI to collect the data of
dependent variables. At this moment, there will not be more follow-up and all this data will be
available in a database. Thus, in the second stage, this data will be used to discuss the validation
of new imaging biomarkers.
Discussion Among other strengths, this protocol structure serves as an example to expand image
biomarkers in other psychiatric or neurological entities – e.g., in drug addiction, depression, eating
disorders, sleep disorders, schizophrenia, dementia, and other neurodevelopmental entities. Until
the full description of the brain areas – differentiated by age, sex, and the entity – and controlling
according to relevant covariates. Therefore, it could be defined a typical neurodevelopment that
allows programming models for research and adjusting them to the specific entity – this last in
order to help in the differential diagnosis, prognosis, or follow-up