Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Oct 28, 2021
Date Accepted: Mar 13, 2022
Date Submitted to PubMed: Apr 18, 2022
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Associations Between the Digital Clock Drawing Test and Brain Volume: Large Community-Based Prospective Cohort (Framingham Heart Study)
ABSTRACT
Background:
Digitizing Clock Drawing Test (dCDT) has been recently used as a more objective tool to assess cognition. However, the association between digitally obtained clock drawing features and structural neuroimaging measures has not been assessed in large population-based studies.
Objective:
We aimed to investigate the association between dCDT features and brain volume.
Methods:
This study included participants from the Framingham Heart Study who had both a dCDT and MRI scan who were free of dementia or stroke. Linear regression models were used to assess the association between 18 dCDT composite scores (derived from 105 dCDT raw features) and brain MRI measures, including total cerebral brain volume (TCBV), cerebral white matter volume, cerebral gray matter volume, hippocampal volume, and white matter hyperintensity (WMH) volume. Classification models were also built from clinical risk factors, dCDT composite scores, and MRI measures to distinguish people with mild cognitive impairment (MCI) from those who were cognitively intact.
Results:
A total of 1,656 participants were included in the current study (mean age 61±13 years, 50.9% women) with 23 participants diagnosed with MCI. All dCDT composite scores were associated with TCBV after adjusting for multiple testing (P value<0.05/18). Eleven dCDT composite scores were associated with cerebral white matter volume, but only one dCDT composite score was associated with cerebral gray matter volume. None of the dCDT composite scores was associated with hippocampal volume or WMH volume. The classification model for MCI versus NC participants incorporating age, sex, education, MRI measures, and dCDT composite scores reached the area under the curve (AUC) of 0.897.
Conclusions:
dCDT composite scores were significantly associated with multiple brain MRI measures in a large community-based cohort. The scores also showed potential application in the clinical diagnosis of MCI.
Citation
