Dmitriy Yablonskiy, United States of America

Washington University in Saint Louis Radiology

Author Of 1 Presentation

BRAIN DARK MATTER – A NEW BIOMARKER FOR EARLY DETECTION OF ALZHEIMER DISEASE

Session Type
SYMPOSIUM
Date
12.03.2021, Friday
Session Time
08:00 - 10:00
Room
On Demand Symposia B
Lecture Time
09:15 - 09:30
Session Icon
On-Demand

Abstract

Aims

Brain tissue atrophy serves as an in vivo MRI biomarker of neurodegeneration in Alzheimer Disease (AD). However, postmortem studies show that loss of memory is related to loss of neurons that in AD exceeds volumetric loss of tissue. Thus, in vivo detection of neuronal loss prior to detectable atrophy is essential for early AD diagnosis.

Methods

We used quantitative Gradient Recalled Echo (qGRE) MRI for in vivo evaluation of neuronal loss in human hippocampus. Seventy participants were recruited from the Knight Alzheimer Disease Research Center, representing three groups: Healthy Controls (HC, Clinical Dementia Rating® [CDR®]=0, amyloidβ [Aβ]-negative, n=34); Preclinical (PC, CDR=0, Aβ-positive, n=19); and mild AD (CDR=0.5 or 1, Aβ-positive, n=17).

Results

qGRE identified two types of regions: one, practically devoid of neurons, we designate as “Dark Matter”, the other, with relatively preserved neurons, “Viable Tissue”. Hippocampal Dark Matter (Figure1) showed: (i) significant group differences among all groups - HC, PC and mild AD, while Total tissue volume did not differentiate PC from HC; (ii) greater neuronal loss (~37%) than volume loss (~15%) in the mild AD group compared with the healthy control group. Direct neuronal count from histopathological study of a participant who underwent in vivo qGRE 14 months prior to expiration showed a significant association with the hypointense R2t* signal (Figure2) that defines Dark Matter.

Conclusions

qGRE method identifies neuronal loss that is associated with impaired AD-related cognition but is not recognized by morphological measurements of tissue atrophy, therefore providing new biomarkers for early AD detection.

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