Quantitative neuroimaging of volume loss in persons with Alzheimer's dementia: Neuroimaging / Optimal neuroimaging measures for early detection. (7th December 2020)

• Record Type: Journal Article
• Authors: Meysami, Somayeh; Raji, Cyrus A.; Merrill, David A.; Porter, Verna R.; Mendez, Mario F.
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.042321
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Automated brain volumetric software programs are FDA‐cleared for clinical use. However, these programs have not yet been tested in their diagnostic utility, specifically in the clinical setting of AD. Method: Clinically acquired volumetric MPRAGE brain MRI scans of 79 persons with a clinical diagnosis of AD (age 67.2 ± 11 years) were retrospectively reviewed and then analyzed using Neuroreader, an FDA‐cleared software program. In this sample, 54% were women. The volumes of 45 brain structures were calculated and statistically adjusted for head size, age, and gender. Regional volumes were then compared to a normative database to compute Z‐scores and percentiles for evaluating regionally specific atrophy. Result: Persons with clinically diagnosed AD demonstrated a pattern of diffuse, global atrophy with a temporal and mesial temporal predilection. Despite exhibiting the greatest magnitude of volume loss, regions such as the hippocampus, amygdala, putamen, ventral diencephalon, left parietal lobe, and temporal lobe were in the 30 th ‐40 th percentile compared to the normative database. These values are higher than the vendor recommended cutoff of 25 th percentile for determining abnormally low brain volume. Conclusion: Data driven quantitative thresholds for volumetrically evaluated brain atrophy on MRI scans do not currently exist in clinical practice. In our study, atrophy in patients with clinically diagnosed AD may be detected with automated brain volumetric software programs. In this study sample, regions demonstrating atrophy were in the 30 th ‐40 th percentile as compared to patients in a healthy normative database. As such, these regions would not have been considered "abnormal" in standard cut‐offs at the 25 th percentile. We suggest that regions in the 26 th ‐40 th percentile may therefore be atrophic and future studies with larger samples should further refine these thresholds.