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Despite in-depth research on new dementia biomarkers from blood and positron emission tomography (PET) imaging, biomarkers from structural magnetic resonance imaging (MRI) are still an area of concern
.
MRI can capture the cumulative damage caused by the pathological process over time, and has the following advantages:
The development of MRI-based dementia risk biomarkers is still an active research area, and new innovations are constantly being produced
.
Some MRI biomarkers are guided by expert knowledge
For example, Racine and colleagues proposed a personalized AD cortical thickness index
.
They used a comprehensive measure, estimated as the average cortical thickness of nine regions, which is considered an early target for AD to predict the progression from mild cognitive impairment (MCI) to dementia
Brickman and colleagues proposed a degenerative brain and vascular index pathology, which (Aβ) PET imaging and CSF total tau, phosphorylated tau and Aβ1-42 levels associated with amyloid beta], and the prediction of cognitive Obstacles
.
Wu et al.
explored the value of different MRI indicators as risk factors for MCI and AD in the community atherosclerosis risk (or ARIC) cohort, and reported that brain tissue atrophy and vascular disease both contribute to ARIC's dementia and cognition Obstacles
Someone proposed MRI data-driven biomarkers based on machine learning methods
.
Few people have deployed systems in the context of AD and related dementias
So far, there are relatively few comparisons between data-driven and hypothesis-driven MRI indexes, especially in different cohorts, as indicators for predicting event-related cognitive impairment
.
There are several important purposes of this work:Especially in different cohorts, there are relatively few comparisons as indicators for predicting event-related cognitive impairment.
Especially in different cohorts, there are relatively few comparisons as indicators for predicting event-related cognitive impairment.
(1) Extend the AD-PS score to the ARIC cohort, and evaluate its relationship with cognitive impairment in different cohorts of cognitively non-impaired persons
.
(2) Compared with the hypothesis-driven composite volume measurement of several brain regions susceptible to AD in ARIC, assess the relative advantage of AD-PS score; (3) For gender, race, and lipoprotein E gene (APOE) ɛ4 Carrier status was analyzed by exploratory stratification to evaluate the influence of these factors on AD-PS score and composite volume measurement in predicting cognitive impairment of the event
.
They applied AD-PS scores to 839 people without cognitive impairment, and the average follow-up time was 4.
86 years
Logistic regression analysis shows that data-driven AD-PS scores can more effectively predict new cognitive impairment
.
Among white, female, and lipoprotein E gene (APOE) epsilon 4 carriers, the two biomarkers were more predictive of cognitive impairment
.
In random forest analysis that incorporates predictors from different fields, AD-PS score is the most relevant MRI predictor for cognitive impairment
.
.
AD-PS score is the most relevant MRI predictor of cognitive impairment
AD-PS score is a strong MRI predictor of cognitive impairment in non-cognitively impaired persons
.
AD-PS score is a strong MRI predictor of cognitive impairment in non-cognitively impaired persons
.
Original source:
Casanova R, Hsu F, Barnard RT, et al.
Comparing data-driven and hypothesis-driven MRI-based predictors of cognitive impairment in individuals from the Atherosclerosis Risk in Communities (ARIC) study.
Alzheimer's & Dementia.
Published online July 26, 2021:alz.
12427.
doi:10.
1002/alz.
12427
