Search

Objectives: This study aimed to evaluate the potential clinical value of a new brain age prediction model as a single interpretable variable representing the condition of our brain. Among many clinical use cases, brain age could be a novel outcome measure to assess the preventive effect of life-style interventions., Methods: The REMEMBER study population (N = 742) consisted of cognitively healthy (HC,N = 91), subjective cognitive decline (SCD,N = 65), mild cognitive impairment (MCI,N = 319) and AD dementia (ADD,N = 267) subjects. Automated brain volumetry of global, cortical, and subcortical brain structures computed by the CE-labeled and FDA-cleared software icobrain dm (dementia) was retrospectively extracted from T1-weighted MRI sequences that were acquired during clinical routine at participating memory clinics from the Belgian Dementia Council. The volumetric features, along with sex, were combined into a weighted sum using a linear model, and were used to predict 'brain age' and 'brain predicted age difference' (BPAD = brain age-chronological age) for every subject., Results: MCI and ADD patients showed an increased brain age compared to their chronological age. Overall, brain age outperformed BPAD and chronological age in terms of classification accuracy across the AD spectrum. There was a weak-to-moderate correlation between total MMSE score and both brain age (r = -0.38,p < .001) and BPAD (r = -0.26,p < .001). Noticeable trends, but no significant correlations, were found between BPAD and incidence of conversion from MCI to ADD, nor between BPAD and conversion time from MCI to ADD. BPAD was increased in heavy alcohol drinkers compared to non-/sporadic (p = .014) and moderate (p = .040) drinkers., Conclusions: Brain age and associated BPAD have the potential to serve as indicators for, and to evaluate the impact of lifestyle modifications or interventions on, brain health., (© 2024. The Author(s).)

Background and Purpose: The establishment of cognitive fluctuations is important when dementia with Lewy bodies (DLB) is suspected but can be especially difficult in the absence of a caregiver who lives with the patient. We examined the possibility of using fluctuating scores on a forward (FDS) and a backward digit span (BDS) test as a marker for cognitive fluctuation., Methods: Patients with DLB (21), other forms of dementia (14 with Alzheimer's disease, 8 with vascular dementia) and 20 controls were asked to perform an FDS and BDS twice, with an interval of 20 min., Results: Seventy percent of patients with DLB showed evidence of cognitive fluctuations for at least one test, while less than 10% of controls and patients with other dementias did. Evidence of cognitive fluctuations on at least one of both tests classified 83% of patients correctly (i.e. DLB or not), with a sensitivity of 70% and a specificity of 90%., Conclusions: Repeated forward and backward digit span tests seem a valid, short, easy and inexpensive bedside tool to detect cognitive fluctuations in the diagnostic work-up of DLB, even in the absence of a caregiver, which limits the use of questionnaires., (© 2023. The Author(s) under exclusive licence to Belgian Neurological Society.)

Background: Magnetic resonance imaging (MRI) has become important in the diagnostic work-up of neurodegenerative diseases. icobrain dm, a CE-labeled and FDA-cleared automated brain volumetry software, has shown potential in differentiating cognitively healthy controls (HC) from Alzheimer's disease (AD) dementia (ADD) patients in selected research cohorts., Objective: This study examines the diagnostic value of icobrain dm for AD in routine clinical practice, including a comparison to the widely used FreeSurfer software, and investigates if combined brain volumes contribute to establish an AD diagnosis., Methods: The study population included HC (n = 90), subjective cognitive decline (SCD, n = 93), mild cognitive impairment (MCI, n = 357), and ADD (n = 280) patients. Through automated volumetric analyses of global, cortical, and subcortical brain structures on clinical brain MRI T1w (n = 820) images from a retrospective, multi-center study (REMEMBER), icobrain dm's (v.4.4.0) ability to differentiate disease stages via ROC analysis was compared to FreeSurfer (v.6.0). Stepwise backward regression models were constructed to investigate if combined brain volumes can differentiate between AD stages., Results: icobrain dm outperformed FreeSurfer in processing time (15-30 min versus 9-32 h), robustness (0 versus 67 failures), and diagnostic performance for whole brain, hippocampal volumes, and lateral ventricles between HC and ADD patients. Stepwise backward regression showed improved diagnostic accuracy for pairwise group differentiations, with highest performance obtained for distinguishing HC from ADD (AUC = 0.914; Specificity 83.0%; Sensitivity 86.3%)., Conclusion: Automated volumetry has a diagnostic value for ADD diagnosis in routine clinical practice. Our findings indicate that combined brain volumes improve diagnostic accuracy, using real-world imaging data from a clinical setting.

Aim: Dementia with Lewy bodies (DLB) is a common but underdiagnosed type of cognitive impairment and dementia. The current diagnostic criteria for research purposes have a high specificity but lack sensitivity. Moreover, patients who live alone are not always aware that they have core clinical features such as cognitive fluctuations, visual hallucinations, and parasomnia. Anxiety is a common and early manifestation in DLB., Methods: We matched 41 DLB patients with 41 patients with Alzheimer's disease (AD) according to gender, age, and cognitive status and retrospectively analyzed their files for the presence of anxiety, depression, constipation, and the core clinical features of DLB in the documented period before diagnosis., Results: Anxiety, but not depression, occurred significantly more frequently in DLB than in AD (63.4% vs 26.8%). It appears up to 4-5 years before the diagnosis of DLB and is associated with depression and living at home. Anxiety in DLB was often described as intermittent panic attacks without reason or during states of delirium; it was also severe enough to require medical treatment and inpatient or outpatient psychiatric care. It was often mistaken for a psychiatric illness or a manifestation of other common forms of dementia. Anxiety in AD seemed much milder, was often related to the patient's coping with cognitive dysfunction, and was never cited as a specific reason for medical help. The concomitant presence of anxiety with at least one core clinical criterion of DLB enabled us to differentiate it from AD in our study, with a sensitivity of 63.4% but a specificity of 100%., Conclusions: In all patients over 50 who present with cognitive problems and anxiety, DLB should be considered. Patients and informants should be carefully questioned regarding the presence of other typical signs and symptoms of DLB., (© 2019 Japanese Psychogeriatric Society.)

Background: Magnetic resonance imaging (MRI) acquisition/processing techniques assess brain volumes to explore neurodegeneration in Alzheimer's disease (AD)., Objective: We examined the clinical utility of MSmetrix and investigated if automated MRI volumes could discriminate between groups covering the AD continuum and could be used as a predictor for clinical progression., Methods: The Belgian Dementia Council initiated a retrospective, multi-center study and analyzed whole brain (WB), grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), cortical GM (CGM) volumes, and WM hyperintensities (WMH) using MSmetrix in the AD continuum. Baseline (n = 887) and follow-up (FU, n = 95) T1-weighted brain MRIs and time-linked neuropsychological data were available., Results: The cohort consisted of cognitively healthy controls (HC, n = 93), subjective cognitive decline (n = 102), mild cognitive impairment (MCI, n = 379), and AD dementia (n = 313). Baseline WB and GM volumes could accurately discriminate between clinical diagnostic groups and were significantly decreased with increasing cognitive impairment. MCI patients had a significantly larger change in WB, GM, and CGM volumes based on two MRIs (n = 95) compared to HC (FU>24months, p = 0.020). Linear regression models showed that baseline atrophy of WB, GM, CGM, and increased CSF volumes predicted cognitive impairment., Conclusion: WB and GM volumes extracted by MSmetrix could be used to define the clinical spectrum of AD accurately and along with CGM, they are able to predict cognitive impairment based on (decline in) MMSE scores. Therefore, MSmetrix can support clinicians in their diagnostic decisions, is able to detect clinical disease progression, and is of help to stratify populations for clinical trials.