Memory Performance and Quantitative Neuroimaging Software in Mild Cognitive Impairment: A Concurrent Validity Study

• Published in: Journal of the International Neuropsychological Society Vol. 26; no. 10; pp. 954 - 962
• Main Authors: Umfleet, Laura Glass, Butts, Alissa M., Janecek, Julie K., Reiter, Katherine, Agarwal, Mohit, Brett, Benjamin L., Ryan, Joseph J., Reuss, James, Klein, Andrew, Correro, Anthony N., Franczak, Malgorzata
• Format: Journal Article
• Language: English
• Published: New York, USA Cambridge University Press 01.11.2020
• Subjects: Age; Atrophy; Automation; Biomarkers; Brain research; Cognitive ability; Dementia; Disease; Hippocampus; Magnetic resonance imaging; Medical imaging; Memory; Neurodegeneration; Neuroimaging; Neuropsychology; Patients; Phenotypes; Prediction models; Regular Research; Software; Standard scores; Statistical analysis; Validity; Volumetric analysis; Logical Memory; Visual Reproduction; Alzheimer’s disease; MRI; HVLT-R; Hippocampal volumes
• ISSN: 1355-6177; 1469-7661
• DOI: 10.1017/S1355617720000454

This study examined the relationship between patient performance on multiple memory measures and regional brain volumes using an FDA-cleared quantitative volumetric analysis program - Neuroreader™. Ninety-two patients diagnosed with mild cognitive impairment (MCI) by a clinical neuropsychologist completed cognitive evaluations and underwent MR Neuroreader™ within 1 year of testing. Select brain regions were correlated with three widely used memory tests. Regression analyses were conducted to determine if using more than one memory measures would better predict hippocampal z-scores and to explore the added value of recognition memory to prediction models. Memory performances were most strongly correlated with hippocampal volumes than other brain regions. After controlling for encoding/Immediate Recall standard scores, statistically significant correlations emerged between Delayed Recall and hippocampal volumes (rs ranging from .348 to .490). Regression analysis revealed that evaluating memory performance across multiple memory measures is a better predictor of hippocampal volume than individual memory performances. Recognition memory did not add further predictive utility to regression analyses. This study provides support for use of MR Neuroreader™ hippocampal volumes as a clinically informative biomarker associated with memory performance, which is a critical diagnostic feature of MCI phenotype.