Alzheimer resemblance atrophy index, BrainAGE, and normal pressure hydrocephalus score in the prediction of subtle cognitive decline: added value compared to existing MR imaging markers

Abstract

Objectives Established visual brain MRI markers for dementia include hippocampal atrophy (mesio-temporal atrophy MTA), white matter lesions (Fazekas score), and number of cerebral microbleeds (CMBs). We assessed whether novel quantitative, artificial intelligence (AI)–based volumetric scores provide additional value in predicting subsequent cognitive decline in elderly controls. Methods A prospective study including 80 individuals (46 females, mean age 73.4 ± 3.5 years). 3T MR imaging was performed at baseline. Extensive neuropsychological assessment was performed at baseline and at 4.5-year follow-up. AI-based volumetric scores were derived from 3DT1: Alzheimer Disease Resemblance Atrophy Index (AD-RAI), Brain Age Gap Estimate (BrainAGE), and normal pressure hydrocephalus (NPH) index. Analyses included regression models between cognitive scores and imaging markers. Results AD-RAI score at baseline was associated with Corsi (visuospatial memory) decline (10.6% of cognitive variability in multiple regression models). After inclusion of MTA, CMB, and Fazekas scores simultaneously, the AD-RAI score remained as the sole valid predictor of the cognitive outcome explaining 16.7% of its variability. Its percentage reached 21.4% when amyloid positivity was considered an additional explanatory factor. BrainAGE score was associated with Trail Making B (executive functions) decrease (8.5% of cognitive variability). Among the conventional MRI markers, only the Fazekas score at baseline was positively related to the cognitive outcome (8.7% of cognitive variability). The addition of the BrainAGE score as an independent variable significantly increased the percentage of cognitive variability explained by the regression model (from 8.7 to 14%). The addition of amyloid positivity led to a further increase in this percentage reaching 21.8%. Conclusions The AI-based AD-RAI index and BrainAGE scores have limited but significant added value in predicting the subsequent cognitive decline in elderly controls when compared to the established visual MRI markers of brain aging, notably MTA, Fazekas score, and number of CMBs. Key Points • AD-RAI score at baseline was associated with Corsi score (visuospatial memory) decline. • BrainAGE score was associated with Trail Making B (executive functions) decrease. • AD-RAI index and BrainAGE scores have limited but significant added value in predicting the subsequent cognitive decline in elderly controls when compared to the established visual MRI markers of brain aging, notably MTA, Fazekas score, and number of CMBs.

Automatic MRI volumetry in asymptomatic cases at risk for normal pressure hydrocephalus

“…BrainAGE was estimated according to the approach described previously by Franke et al (2010) and Giannakopoulos et al (2022a). Briefly, the BrainAGE framework utilized relevance vector regression (RVR) using a linear kernel and a linear combination of pre-processed GM and WM images (Tipping, 2000(Tipping, , 2001.…”

“…The AD-RAI was determined as the probability score of the SVM output as a value between zero and one. The trained algorithm was applied to the current dataset without any further adjustments as in our previous work (Giannakopoulos et al, 2022a).…”

A Case for Estradiol: Younger Brains in Women with Earlier Menarche and Later Menopause

“…The BrainAGE algorithm has been shown to be robust and reliable across datasets, age-ranges, and scanner types 24,26 ; it has been successfully applied in a wide range of studies 24,25,[27][28][29] including those capturing hormonal changes in women 30,31 . Moreover, the BrainAGE index has been demonstrated to work as a predictor of dementia as well as agerelated cognitive decline 27,32 .…”