Can MR imaging biomarkers readily available in rural and underserved areas aid in the accurate clinical diagnosis of Alzheimer's disease?. (31st December 2021)

• Record Type: Journal Article
• Authors: Gustavsen, Tanner; He, Yao; Duff, Kevin M.; Anzai, Yoshimi; Hoffman, John M.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 1
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• 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.052638
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Hippocampal volume (HV) measured with brain magnetic resonance imaging (MRI), a NIA‐AA biomarker of Alzheimer's disease (AD), could be widely available in rural and underserved areas in the United States. Amyloid positron imaging tomography (aPET) identifies the presence of amyloid AD pathology but is available only to cognitive specialty centers in predominantly large metropolitan areas. We wished to determine whether rural primary care providers could benefit from commercially available automated measurements of HV to improve the accuracy of their diagnosis of early AD Method: We used NeuroQuant ®□ (NQ) to derive operator‐independent volumetric measurements of HV relative to total intracranial volume (rHV) in 70 patients (27 men, 43 women; mean age 73 ± 8, range 45‐89) found to have cognitive impairment during a clinical evaluation. We compared the frequency of abnormal rHV using a recommended 5 th percentile cutoff value from NQ's extensive normative database in patients with visually interpreted positive (n=57) or negative (n=13) aPET with flutemetamol. We assessed the validity of rHV to measure underlying AD pathology with a 2x2 factorial analysis to calculate sensitivity, specificity, positive and negative predictive value (PPV, NPV). We measured the rHV in MCI (n=39) versus dementia (n=31). We contrasted the age and severity at time of referral of rural (n=16) and non‐rural (n=54) patients. Result: 12/14 (86%) patients with an abnormal rHV had a positive aPET, however most patients with a positive aPET did not have an abnormal rHV (45/57). The ability of small rHV to predict underlying AD pathology had a specificity=0.84, PPV=0.85, sensitivity=0.21, and NPV=0.19. rHV was smaller in dementia than MCI (0.37, 0.42; p=.003). Rural patients were younger (68 ± 11 vs. 75 ± 7; p=.02) and more likely to have dementia when referred (56% vs. 40%; p=.03). Conclusion: An abnormal rHV is highly predictive of cortical amyloid AD pathology in the right setting, but is insensitive at the time of initial cognitive evaluation. Commercially available automated rHV decreases as the severity of cognitive impairment increases. Imaging biomarkers could aid rural primary care providers to validate the clinical significance of a memory complaint and justify earlier evaluation, referral, and treatment.