Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence.

Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of structural brain aberrations in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine.

Grey matter networks in women and men with dementia with Lewy bodies.

Sex differences permeate many aspects of dementia with Lewy bodies (DLB), yet sex differences in patterns of neurodegeneration in DLB remain largely unexplored. Here, we test whether grey matter networks differ between sexes in DLB and compare these findings to sex differences in healthy controls. In this cross-sectional study, we analysed clinical and neuroimaging data of patients with DLB and cognitively healthy controls matched for age and sex. Grey matter networks were constructed by pairwise correlations between 58 regional volumes after correction for age, intracranial volume, and centre. Network properties were compared between sexes and diagnostic groups. Additional analyses were conducted on w-scored data to identify DLB-specific sex differences. Data from 119 (68.7 ± 8.4 years) men and 45 women (69.9 ± 9.1 years) with DLB, and 164 healthy controls were included in this study. Networks of men had a lower nodal strength compared to women. In comparison to healthy women, the grey matter networks of healthy men showed a higher global efficiency, modularity, and fewer modules. None of the network measures showed significant sex differences in DLB. Comparing DLB patients with healthy controls revealed global differences in women and more local differences in men. Modular analyses showed a more distinct demarcation between cortical and subcortical regions in men compared with women. While topologies of grey matter networks differed between sexes in healthy controls, those sex differences were diluted in DLB patients. These findings suggest a disease-driven convergence of neurodegenerative patterns in women and men with DLB, which may inform precision medicine in DLB.

Altered empathy processing in frontotemporal dementia A task-based fMRI study.

A lack of empathy, and particularly its affective components, is a core symptom of behavioural variant frontotemporal dementia (bvFTD). Visual exposure to images of a needle pricking a hand (pain condition) and Q-tips touching a hand (control condition) is an established functional magnetic resonance imaging (fMRI) paradigm used to investigate empathy for pain (EFP; pain condition minus control condition). EFP has been associated with increased blood oxygen level dependent (BOLD) signal in regions known to become atrophic in the early stages in bvFTD, including the anterior insula and the anterior cingulate. We therefore hypothesized that patients with bvFTD would display altered empathy processing in the EFP paradigm. Here we examined empathy processing using the EFP paradigm in 28 patients with bvFTD and 28 sex and age matched controls. Participants underwent structural MRI, task-based and resting-state fMRI. The Interpersonal Reactivity Index (IRI) was used as a measure of different facets of empathic function outside the scanner. The EFP paradigm was analysed at a whole brain level and using two regions-of-interest approaches, one based on a metanalysis of affective perceptual empathy versus cognitive evaluative empathy and one based on the controls activation pattern. In controls, EFP was linked to an expected increase of BOLD signal that displayed an overlap with the pattern of atrophy in the bvFTD patients (insula and anterior cingulate). Additional regions with increased signal were the supramarginal gyrus and the occipital cortex. These latter regions were the only ones that displayed increased BOLD signal in bvFTD patients. BOLD signal increase under the affective perceptual empathy but not the cognitive evaluative empathy region of interest was significantly greater in controls than in bvFTD patients. The controls rating on their empathic concern subscale of the IRI was significantly correlated with the BOLD signal in the EFP paradigm, as were an informants ratings of the patients empathic concern subscale. This correlation was not observed on other subscales of the IRI or when using the patient's self-ratings. Finally, controls and patients showed different connectivity patterns in empathy related networks during resting-state fMRI, mainly in nodes overlapping the ventral attention network. Our results indicate that reduced neural activity in regions typically affected by pathology in bvFTD is associated with reduced empathy processing, and a predictor of patients capacity to experience affective empathy.

Proportion of Community-Dwelling Individuals Older Than 70 Years Eligible for Lecanemab Initiation: The Gothenburg H70 Birth Cohort Study.

OBJECTIVES: To determine the prevalence of individuals with Alzheimer disease (AD) eligible for treatment with the recently FDA-approved lecanemab based on data from a population-based sample of 70-year-olds and extrapolate an estimation of individuals eligible in Europe and the United States. METHODS: Participants from the Gothenburg H70 Birth Cohort Study with clinical data, CSF-amyloid beta 42, and brain MRI analysis were evaluated for eligibility to receive lecanemab treatment according to FDA-approved recommendations, noting factors requiring special consideration. Results were used to extrapolate the number of eligible individuals in Europe and the United States using public demographic data. RESULTS: Thirty (10.3%) of 290 participants met the indication for treatment of whom 18 (6.2%) were eligible and did not present factors requiring special consideration. Our estimate that 6.2% of all 70-year-olds in the full cohort are eligible for treatment extrapolates to an approximation that around 5.9 million Europeans and 2.2 million US residents could be eligible. DISCUSSION: Information on proportion of individuals eligible for AD treatment with lecanemab in the general public is limited. We provide information on 70-year-olds in Sweden and extrapolate these data to Europe and the United States. This study opens for larger studies on this proportion and implementation of lecanemab treatment.

Multi-pathological contributions toward atrophy patterns in the Alzheimer's disease continuum.

Introduction: Heterogeneity in downstream atrophy in Alzheimer's disease (AD) is predominantly investigated in relation to pathological hallmarks (Aß, tau) and co-pathologies (cerebrovascular burden) independently. However, the proportional contribution of each pathology in determining atrophy pattern remains unclear. We assessed heterogeneity in atrophy using two recently conceptualized dimensions: typicality (typical AD atrophy at the center and deviant atypical atrophy on either extreme including limbic predominant to hippocampal sparing patterns) and severity (overall neurodegeneration spanning minimal atrophy to diffuse typical AD atrophy) in relation to Aß, tau, and cerebrovascular burden. Methods: We included 149 Aß + individuals on the AD continuum (cognitively normal, prodromal AD, AD dementia) and 163 Aß- cognitively normal individuals from the ADNI. We modeled heterogeneity in MRI-based atrophy with continuous-scales of typicality (ratio of hippocampus to cortical volume) and severity (total gray matter volume). Partial correlation models investigated the association of typicality/severity with (a) Aß (global Aß PET centiloid), tau (global tau PET SUVR), cerebrovascular (total white matter hypointensity volume) burden (b) four cognitive domains (memory, executive function, language, visuospatial composites). Using multiple regression, we assessed the association of each pathological burden and typicality/severity with cognition. Results: (a) In the AD continuum, typicality (r = -0.31, p < 0.001) and severity (r = -0.37, p < 0.001) were associated with tau burden after controlling for Aß, cerebrovascular burden and age. Findings imply greater tau pathology in limbic predominant atrophy and diffuse atrophy. (b) Typicality was associated with memory (r = 0.49, p < 0.001) and language scores (r = 0.19, p = 0.02). Severity was associated with memory (r = 0.26, p < 0.001), executive function (r = 0.24, p = 0.003) and language scores (r = 0.29, p < 0.001). Findings imply better cognitive performance in hippocampal sparing and minimal atrophy patterns. Beyond typicality/severity, tau burden but not Aß and cerebrovascular burden explained cognition. Conclusion: In the AD continuum, atrophy-based severity was more strongly associated with tau burden than typicality after accounting for Aß and cerebrovascular burden. Cognitive performance in memory, executive function and language domains was explained by typicality and/or severity and additionally tau pathology. Typicality and severity may differentially reflect burden arising from tau pathology but not Aß or cerebrovascular pathologies which need to be accounted for when investigating AD heterogeneity.

Ketogenic Diet Intervention on Metabolic and Psychiatric Health in Bipolar and Schizophrenia: A Pilot Trial.

The ketogenic diet (KD, also known as metabolic therapy) has been successful in the treatment of obesity, type 2 diabetes, and epilepsy. More recently, this treatment has shown promise in the treatment of psychiatric illness. We conducted a 4-month pilot study to investigate the effects of a KD on individuals with schizophrenia or bipolar disorder with existing metabolic abnormalities. Twenty-three participants were enrolled in a single-arm trial. Results showcased improvements in metabolic health, with no participants meeting metabolic syndrome criteria by study conclusion. Adherent individuals experienced significant reduction in weight (12 %), BMI (12 %), waist circumference (13 %), and visceral adipose tissue (36 %). Observed biomarker enhancements in this population include a 27 % decrease in HOMA-IR, and a 25 % drop in triglyceride levels. In psychiatric measurements, participants with schizophrenia showed a 32 % reduction in Brief Psychiatric Rating Scale scores. Overall Clinical Global Impression (CGI) severity improved by an average of 31 %, and the proportion of participants that started with elevated symptomatology improved at least 1-point on CGI (79 %). Psychiatric outcomes across the cohort encompassed increased life satisfaction (17 %) and enhanced sleep quality (19 %). This pilot trial underscores the potential advantages of adjunctive ketogenic dietary treatment in individuals grappling with serious mental illness.

Temporal Muscle Thickness: A Practical Approximation for Assessing Muscle Mass in Older Adults.

OBJECTIVE: Ongoing research has evidenced the importance of muscle measurement in predicting adverse outcomes. Measurement of other muscles is promising in current research. This study aimed to determine the correlation between temporal muscle thickness (TMT) and appendicular lean soft tissue (ALSTI) in older adults. DESIGN: Cross-sectional study. SETTINGS AND PARTICIPANTS: Single cohort gathered in Gothenburg, Sweden, consisting of individuals born in 1944 (n = 1203). METHODS: We studied 657 magnetic resonance images to measure TMT. Comparisons of TMT with dual-energy X-ray absorptiometry ALSTI (kg/m2) as a reference standard were performed. Finally, TMT associations with cognition evaluated using the Mini-Mental State Examination (MMSE), gait speed, and handgrip strength were explored with linear regressions. RESULTS: The correlation between TMT and ALSTI was weak yet significant (r = 0.277, P < .001). TMT exhibited significant associations with MMSE (estimate = 0.168, P = .002), gait speed (estimate = 1.795, P < .001), and ALSTI (estimate = 0.508, P < .001). These associations varied when analyzed by sex. In women, TMT was significantly associated with gait speed (estimate = 1.857, P = .005) and MMSE (estimate = 0.223, P = .003). In men, TMT scores were significantly correlated with ALSTI scores (estimate = 0.571, P < .001). CONCLUSION AND IMPLICATIONS: Repurposing head images can be an accessible alternative to detect muscle mass and ultimately detect sarcopenia. These studies have the potential to trigger interventions or further evaluation to improve the muscle and overall health of individuals. However, additional research is warranted before translating these findings into clinical practice.

Putaminal T1/T2-weighted ratio is increased in PSP compared to PD and healthy controls, a multi-cohort study.

INTRODUCTION: Differentiating Parkinson's disease (PD) from progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) is a common clinical problem. We aimed to apply the T1-/T2-weighted ratio imaging technique, based on standard clinical MRI, to reveal differences in neurodegeneration in three large cohorts. METHODS: Three cohorts, with a total of 405 participants (269 PD, 44 PSP, 38 MSA, 54 controls), were combined and T1/T2-weighted ratio image analyses were carried out. A combination of automatic segmentation and atlas-based ROI were used in this study. The cohorts were combined using the ComBat batch correction procedure. RESULTS: Group differences were found in the putamen (p = 0.040), with higher T1/T2-weighted ratio in this region in PSP compared to PD and healthy controls (p-values 0.010 and 0.007 respectively). Using putaminal T1/T2-weighted ratio for diagnostic separation, a fair performance was found in separating PSP from healthy controls, with an area under the receiver operating characteristic curve of 0.701. CONCLUSION: Different patterns of T1/T2-weighted ratio, reflecting differences in underlying pathophysiology, were found between the groups. Since T1/T2-weighted ratio can be applied to standard clinical MRI sequences to allow more quantitative analyses, this seems to be a promising biomarker for diagnostics and treatment evaluation of parkinsonian disorders for clinical trials.

Association of CSF biomarkers with MRI brain changes in Alzheimer's disease.

The relation between cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) and magnetic resonance imaging (MRI) measures is poorly understood in cognitively healthy individuals from the general population. Participants' (n = 226) mean age was 70.9 years (SD = 0.4). CSF concentrations of amyloid beta (Aß)1-42, total tau (t-tau), phosphorylated tau (p-tau), neurogranin, and neurofilament light, and volumes of hippocampus, amygdala, total basal forebrain (TBF), and cortical thickness were measured. Linear associations between CSF biomarkers and MRI measures were investigated. In Aß1-42 positives, higher t-tau and p-tau were associated with smaller hippocampus (P = 0.001 and P = 0.003) and amygdala (P = 0.005 and P = 0.01). In Aß1-42 negatives, higher t-tau, p-tau, and neurogranin were associated with larger TBF volume (P = 0.001, P = 0.001, and P = 0.01). No associations were observed between the CSF biomarkers and an AD signature score of cortical thickness. AD-specific biomarkers in cognitively healthy 70-year-olds may be related to TBF, hippocampus, and amygdala. Lack of association with cortical thickness might be due to early stage of disease.

In vivo microstructural heterogeneity of white matter and cognitive correlates in aging using tissue compositional analysis of diffusion magnetic resonance imaging.

BACKGROUND: Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition. METHODS: A total of 189 individuals from the GENIC cohort were included. MRI data, including T1-weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T-CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3-tissue signal fractions (Tw , TG , and TC ), and neuropsychological variables. RESULTS: Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p < .001). Age was negatively associated with Tw in normal-appearing white matter (p < .001) and positively associated with TG in both WMSA (p < .01) and normal-appearing white matter (p < .001). Age was also significantly associated with WMSA volume (p < .001). Higher processing speed was associated with lower Tw and higher TG , in normal-appearing white matter (p < .01 and p < .001, respectively), as well as increased WMSA volume (p < .001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal-appearing white matter (p < .05). High cholesterol and hypertension were associated with higher WMSA volume (p < .05). CONCLUSION: The microstructural heterogeneity within normal-appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3-tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3-tissue metrics. Finally, the 3-tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance.

Dynamic multilayer functional connectivity detects preclinical and clinical Alzheimer's disease.

Increasing evidence suggests that patients with Alzheimer's disease present alterations in functional connectivity but previous results have not always been consistent. One of the reasons that may account for this inconsistency is the lack of consideration of temporal dynamics. To address this limitation, here we studied the dynamic modular organization on resting-state functional magnetic resonance imaging across different stages of Alzheimer's disease using a novel multilayer brain network approach. Participants from preclinical and clinical Alzheimer's disease stages were included. Temporal multilayer networks were used to assess time-varying modular organization. Logistic regression models were employed for disease stage discrimination, and partial least squares analyses examined associations between dynamic measures with cognition and pathology. Temporal multilayer functional measures distinguished all groups, particularly preclinical stages, overcoming the discriminatory power of risk factors such as age, sex, and APOE ϵ4 carriership. Dynamic multilayer functional measures exhibited strong associations with cognition as well as amyloid and tau pathology. Dynamic multilayer functional connectivity shows promise as a functional imaging biomarker for both early- and late-stage Alzheimer's disease diagnosis.

Prevalence of Possible Idiopathic Normal Pressure Hydrocephalus in Sweden: A Population-Based MRI Study in 791 70-Year-Old Participants

BACKGROUND AND OBJECTIVES: Very divergent prevalence rates for idiopathic normal pressure hydrocephalus (iNPH) are reported, probably due to differences in study sample selection and diagnostic criteria. This MRI-based study aimed to determine the prevalence of iNPH and iNPH-specific radiologic changes and their association with clinical symptoms in a large, 70-year-old population-based cohort (Gothenburg H70). METHODS: In this cross-sectional study, disturbances in gait and balance, cognition, and urinary continence were assessed using clinical examination and self-report. MRI was evaluated for iNPH-specific imaging markers. iNPH was diagnosed according to International Guidelines (I.G.). Based on radiologic findings, participants were allocated to 1 of 4 groups: (A) Evans index (EI) ≤0.3 (reference), (B) EI >0.3 without other iNPH-typical radiologic findings, (C) radiologically probable iNPH according to I.G., and (D) radiologically holistically probable (h-probable) iNPH fulfilling radiologic criteria according to I.G. plus highly iNPH-specific changes according to an experienced neuroradiologist. RESULTS: The Gothenburg H70 Studies include 791 individuals (377 men, 414 women) born in 1944 who underwent brain MRI. The prevalence of iNPH was 1.5% (2.1% for men, 0.96% for women) according to I.G. Ninety participants (11%) had EI >0.3 without other iNPH-typical radiologic findings, 29 (3.7%) fulfilled the I.G. radiologic probable iNPH criteria alone, and 11 (1.4%) were classified as radiologically h-probable iNPH. Forty participants (5.1%) had I.G. radiologic features of iNPH (70% men vs 30% women, p = 0.005). Gait disturbances were more common in participants with EI >0.3 without other radiologic iNPH features (B) (33%) compared with the reference group (A) (19%) (p = 0.006). All clinical symptoms were more common in participants with I.G. radiologic features of iNPH (C + D) than they were in the reference group (A) (p < 0.03). DISCUSSION: The iNPH prevalence of 1.5% among 70-year-olds, which is considerably higher than earlier reported in this age group, suggests that iNPH may be more common than previously assumed. This is supported by the 5.1% total prevalence of imaging signs of iNPH. Ventriculomegaly without other iNPH-typical radiologic findings may be an early sign of developing iNPH in some patients.

Degeneration of the cholinergic system in individuals with subjective cognitive decline: A systematic review.

BACKGROUND: Subjective cognitive decline (SCD) is a risk factor for future cognitive impairment and dementia. It is uncertain whether the neurodegeneration of the cholinergic system is already present in SCD individuals. We aimed to review the current evidence about the association between SCD and biomarkers of degeneration in the cholinergic system. METHOD: Original articles were extracted from three databases: Pubmed, Web of Sciences, and Scopus, in January 2023. Two researchers screened the studies independently. RESULTS: A total of 11 research articles were selected. SCD was mostly based on amnestic cognitive complaints. Cholinergic system biomarkers included neuroimaging markers of basal forebrain volume, functional connectivity, transcranial magnetic stimulation, or biofluid. The evidence showed associations between basal forebrain atrophy, poorer connectivity of the cholinergic system, and SCD CONCLUSIONS: Degenerative changes in the cholinergic system can be present in SCD. Subjective complaints may help when identifying individuals with brain changes that are associated with cognitive impairment. These findings may have important implications in targeting individuals that may benefit from cholinergic-target treatments at very early stages of neurodegenerative diseases.

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration.

INTRODUCTION: Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification. MATERIALS AND METHODS: We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition. RESULTS: CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration. DISCUSSION: These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation. HIGHLIGHTS: Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.

Effects of current alcohol use on brain volume among older adults in the Gothenburg H70 Birth Cohort study 2014-16.

Brain gray- and white matter changes is well described in alcohol-dependent elderly subjects; however, the effect of lower levels of alcohol consumption on the brain is poorly understood. We investigated the impact of different amounts of weekly alcohol consumption on brain structure in a population-based sample of 70-year-olds living in Gothenburg, Sweden. Cross-sectional data from 676 participants from The Gothenburg H70 Birth Cohort Study 2014-16 were included. Current alcohol consumers were divided into seven groups based on self-reported weekly amounts of alcohol consumption in grams (g) (0-50 g/week, used as reference group, 51-100 g/week, 101-150 g/week, 151-200 g/week, 201-250 g/week, 251-300 g/week, and > 300 g/week). Subcortical volumes and cortical thickness were assessed on T1-weighted structural magnetic resonance images using FreeSurfer 5.3, and white matter integrity assessed on diffusion tensor images, using tract-based statistics in FSL. General linear models were carried out to estimate associations between alcohol consumption and gray- and white matter changes in the brain. Self-reported consumption above 250 g/week was associated with thinning in the bilateral superior frontal gyrus, the right precentral gyrus, and the right lateral occipital cortex, in addition to reduced fractional anisotropy (FA) and increased mean diffusivity (MD) diffusively spread in many tracts all over the brain. No changes were found in subcortical gray matter structures. These results suggest that there is a non-linear relationship between alcohol consumption and structural brain changes, in which loss of cortical thickness only occur in non-demented 70-year-olds who consume more than 250 g/week.

Biomarkers of Alzheimer's Disease and Cerebrovascular Disease in Relation to Depressive Symptomatology in Individuals With Subjective Cognitive Decline.

BACKGROUND: Subjective cognitive decline (SCD) has gained recent interest as a potential harbinger of neurodegenerative diseases such as Alzheimer's disease (AD) and cerebrovascular disease (CVD). In addition, SCD can be related to depressive symptomatology. However, the association between AD and CVD biomarkers, depressive symptomatology, and SCD is still unclear. We investigated the association of AD and CVD biomarkers and depressive symptomatology with SCD in individuals with subjective memory complaints (SCD-memory group) and individuals with subjective concentration complaints (SCD-concentration group). METHODS: We recruited a population-based cohort of 217 individuals (all aged 70 years, 53% female participants, 119 SCD-memory individuals, 23 SCD-concentration individuals, and 89 controls). AD and CVD were assessed through cerebrospinal fluid levels of the Aß42/40 ratio and phosphorylated tau, and white matter signal abnormalities on magnetic resonance imaging, respectively. Associations between biomarkers, depressive symptomatology, and SCD were tested via logistic regression and correlation analyses. RESULTS: We found a significant association between depressive symptomatology with SCD-memory and SCD-concentration. Depressive symptomatology was not associated with AD and CVD biomarkers. Both the phosphorylated tau biomarker and depressive symptomatology predicted SCD-memory, and the Aß42/40 ratio and depressive symptomatology predicted SCD-concentration. CONCLUSIONS: The role of depressive symptomatology in SCD may differ depending on the stage within the spectrum of preclinical AD (as determined by amyloid-beta and tau positivity), and does not seem to reflect AD pathology. Our findings contribute to the emerging field of subclinical depressive symptomatology in SCD and clarify the association of different types of subjective complaints with distinct syndromic and biomarker profiles.

Using magnetic resonance imaging to measure head muscles: An innovative method to opportunistically determine muscle mass and detect sarcopenia.

BACKGROUND: Sarcopenia is associated with multiple adverse outcomes. Traditional methods to determine low muscle mass for the diagnosis of sarcopenia are mainly based on dual-energy X-ray absorptiometry (DXA), whole-body magnetic resonance imaging (MRI) and bioelectrical impedance analysis. These tests are not always available and are rather time consuming and expensive. However, many brain and head diseases require a head MRI. In this study, we aim to provide a more accessible way to detect sarcopenia by comparing the traditional method of DXA lean mass estimation versus the tongue and masseter muscle mass assessed in a standard brain MRI. METHODS: The H70 study is a longitudinal study of older people living in Gothenburg, Sweden. In this cross-sectional analysis, from 1203 participants aged 70 years at baseline, we included 495 with clinical data and MRI images available. We used the appendicular lean soft tissue index (ALSTI) in DXA images as our reference measure of lean mass. Images from the masseter and tongue were analysed and segmented using 3D Slicer. For the statistical analysis, the Spearman correlation coefficient was used, and concordance was estimated with the Kappa coefficient. RESULTS: The final sample consisted of 495 participants, of which 52.3% were females. We found a significant correlation coefficient between both tongue (0.26) and masseter (0.33) with ALSTI (P < 0.001). The sarcopenia prevalence confirmed using the alternative muscle measure in MRI was calculated using the ALSTI (tongue = 2.0%, masseter = 2.2%, ALSTI = 2.4%). Concordance between sarcopenia with masseter and tongue versus sarcopenia with ALSTI as reference has a Kappa of 0.989 (P < 0.001) for masseter and a Kappa of 1 for the tongue muscle (P < 0.001). Comorbidities evaluated with the Cumulative Illness Rating Scale were significantly associated with all the muscle measurements: ALSTI (odds ratio [OR] 1.16, 95% confidence interval [CI] 1.07-1.26, P < 0.001), masseter (OR 1.16, 95% CI 1.07-1.26, P < 0.001) and tongue (OR 1.13, 95% CI 1.04-1.22, P = 0.002); the higher the comorbidities, the higher the probability of having abnormal muscle mass. CONCLUSIONS: ALSTI was significantly correlated with tongue and masseter muscle mass. When performing the sarcopenia diagnostic algorithm, the prevalence of sarcopenia calculated with head muscles did not differ from sarcopenia calculated using DXA, and almost all participants were correctly classified using both methods.

Sex differences in brain atrophy in dementia with Lewy bodies.

INTRODUCTION: Sex influences neurodegeneration, but it has been poorly investigated in dementia with Lewy bodies (DLB). We investigated sex differences in brain atrophy in DLB using magnetic resonance imaging (MRI). METHODS: We included 436 patients from the European-DLB consortium and the Mayo Clinic. Sex differences and sex-by-age interactions were assessed through visual atrophy rating scales (n = 327; 73 ± 8 years, 62% males) and automated estimations of regional gray matter volume and cortical thickness (n = 165; 69 ± 9 years, 72% males). RESULTS: We found a higher likelihood of frontal atrophy and smaller volumes in six cortical regions in males and thinner olfactory cortices in females. There were significant sex-by-age interactions in volume (six regions) and cortical thickness (seven regions) across the entire cortex. DISCUSSION: We demonstrate that males have more widespread cortical atrophy at younger ages, but differences tend to disappear with increasing age, with males and females converging around the age of 75. HIGHLIGHTS: Male DLB patients had higher odds for frontal atrophy on radiological visual rating scales. Male DLB patients displayed a widespread pattern of cortical gray matter alterations on automated methods. Sex differences in gray matter measures in DLB tended to disappear with increasing age.

Predicting amyloid-PET status in a memory clinic: The role of the novel antero-posterior index and visual rating scales.

INTRODUCTION: Visual rating scales are increasingly utilized in clinical practice to assess atrophy in crucial brain regions among patients with cognitive disorders. However, their capacity to predict Alzheimer's disease (AD)-related pathology remains unexplored, particularly within a heterogeneous memory clinic population. This study aims to assess the accuracy of a novel visual rating assessment, the antero-posterior index (API) scale, in predicting amyloid-PET status. Furthermore, the study seeks to determine the optimal cohort-based cutoffs for the medial temporal atrophy (MTA) and parietal atrophy (PA) scales and to integrate the main visual rating scores into a predictive model. METHODS: We conducted a retrospective analysis of brain MRI and high-resolution TC scans from 153 patients with cognitive disorders who had undergone amyloid-PET assessments due to suspected AD pathology in a real-world memory clinic setting. RESULTS: The API scale (cutoff ≥1) exhibited the highest accuracy (AUC = 0.721) among the visual rating scales. The combination of the cohort-based MTA and PA threshold with the API yielded favorable accuracy (AUC = 0.787). Analyzing a cohort of MCI/Mild dementia patients below 75 years of age, the API scale and the predictive model improved their accuracy (AUC = 0.741 and 0.813, respectively), achieving excellent results in the early-onset population (AUC = 0.857 and 0.949, respectively). CONCLUSION: Our study emphasizes the significance of visual rating scales in predicting amyloid-PET positivity within a real-world memory clinic. Implementing the novel API scale, alongside our cohort-based MTA and PA thresholds, has the potential to substantially enhance diagnostic accuracy.

Lifelong olfactory deprivation-dependent cortical reorganization restricted to orbitofrontal cortex.

Prolonged sensory deprivation has repeatedly been linked to cortical reorganization. We recently demonstrated that individuals with congenital anosmia (CA, complete olfactory deprivation since birth) have seemingly normal morphology in piriform (olfactory) cortex despite profound morphological deviations in the orbitofrontal cortex (OFC), a finding contradictory to both the known effects of blindness on visual cortex and to the sparse literature on brain morphology in anosmia. To establish whether these unexpected findings reflect the true brain morphology in CA, we first performed a direct replication of our previous study to determine if lack of results was due to a deviant control group, a confound in cross sectional studies. Individuals with CA (n = 30) were compared to age and sex matched controls (n = 30) using voxel- and surface-based morphometry. The replication results were near identical to the original study: bilateral clusters of group differences in the OFC, including CA atrophy around the olfactory sulci and volume increases in the medial orbital gyri. Importantly, no group differences in piriform cortex were detected. Subsequently, to assess any subtle patterns of group differences not detectable by our mass-univariate analysis, we explored the data from a multivariate perspective. Combining the newly collected data with data from the replicated study (CA = 49, control = 49), we performed support vector machine classification based on gray matter volume. In line with the mass-univariate analyses, the multivariate analysis could accurately differentiate between the groups in bilateral OFC, whereas the classification accuracy in piriform cortex was at chance level. Our results suggest that despite lifelong olfactory deprivation, piriform (olfactory) cortex is morphologically unaltered and the morphological deviations in CA are confined to the OFC.