Five ways the brain can age: 50k scans reveal possible patterns of damage(nature.com)
nature.com
Five ways the brain can age: 50k scans reveal possible patterns of damage
https://www.nature.com/articles/d41586-024-02692-z
3 comments
I got curious and accessed the full paper. The five patterns (so called "R-indices") are:
R1. Subcortical atrophy • Stress-related gene set • Pregnancy
R2: MTL atrophy • Dementia • CN-MCI-dementia progression • Amyloid and tau • Cognitive dysfunction, mainly memory impairment • Birth weight
R3: Parieto-temporal atrophy • Dementia; schizophrenia;Parkinson’s; multiple sclerosis • MCI-dementia progression • Amyloid and tau • Cognitive dysfunction, mainlyin executive function • Pregnancy • Social/recreational activity
R4: Diffuse cortical atrophy • Multiple sclerosis • Smoking and alcohol consumption • Diet
R5: Perisylvian atrophy • Multi-organ chronic conditions • Psychological factors • Psychiatric diseases • Cardiovascular factors • WMH• Mortality risk • Smoking and alcohol consumption
These patterns were identified using a type of Deep Learning model, the paper then goes on studying the association between different factors (such as chronic diseases) and brain atrophy.
So in conclusion, this study have demonstrated how brain atrophy manifests itself in MRI brain scans and how we can "classify" them into one of five categories (or "patterns", if you like). The gain here is in diagnosis, imagine if a doctor could easily determine that a specific person exhibits " Type 2" atrophy? Much time, money and human suffering could be saved providing the patient with tailored treatment at the get-go.
R1. Subcortical atrophy • Stress-related gene set • Pregnancy
R2: MTL atrophy • Dementia • CN-MCI-dementia progression • Amyloid and tau • Cognitive dysfunction, mainly memory impairment • Birth weight
R3: Parieto-temporal atrophy • Dementia; schizophrenia;Parkinson’s; multiple sclerosis • MCI-dementia progression • Amyloid and tau • Cognitive dysfunction, mainlyin executive function • Pregnancy • Social/recreational activity
R4: Diffuse cortical atrophy • Multiple sclerosis • Smoking and alcohol consumption • Diet
R5: Perisylvian atrophy • Multi-organ chronic conditions • Psychological factors • Psychiatric diseases • Cardiovascular factors • WMH• Mortality risk • Smoking and alcohol consumption
These patterns were identified using a type of Deep Learning model, the paper then goes on studying the association between different factors (such as chronic diseases) and brain atrophy.
So in conclusion, this study have demonstrated how brain atrophy manifests itself in MRI brain scans and how we can "classify" them into one of five categories (or "patterns", if you like). The gain here is in diagnosis, imagine if a doctor could easily determine that a specific person exhibits " Type 2" atrophy? Much time, money and human suffering could be saved providing the patient with tailored treatment at the get-go.
Thank you! Exceptionally clarifying
Does anybody have a sense of what these five models are?
The research itself is not open access so I wasn’t able to actually read it.