Helge Malmgren

Small baseline volume of left hippocampus is associated with subsequent conversion of MCI into dementia: The Göteborg MCI study

BACKGROUND Earlier studies have reported that hippocampal atrophy can to some extent predict which patients with mild cognitive impairment (MCI) will subsequently convert to dementia, and that converters have an enhanced rate of hippocampal volume loss. OBJECTIVE To further validate the hypothesis that hippocampal atrophy predicts conversion from MCI to dementia, to relate baseline hippocampal volume to different forms of dementia, and to investigate the role of hippocampal side differences and rate of volume loss over time. PATIENTS The subjects (N=68) include patients with MCI at baseline and progression to dementia at the two-year follow-up (N=21), stable MCI patients (N=21), and controls (N=26). Among the progressing patients, 13 were diagnosed as having AD. METHODS The Göteborg MCI study is a clinically based longitudinal study with biannual clinical assessments. Hippocampal volumetry was performed manually on the MRI investigations at baseline and at the two-year follow-up. RESULTS Hippocampal volumetry could predict conversion to dementia in both the AD and the non-AD subgroup of converters. Left hippocampal volume in particular discriminated between converting and stable MCI. Cut off points for individual discrimination were shown to be potentially useful. The converting MCI group had a significantly higher rate of hippocampal volume loss as compared to the stable MCI group. CONCLUSIONS In MCI patients, hippocampal volumetry at baseline gives prognostic information about possible development of AD and non-AD dementia. Contrary to earlier studies, we found that left hippocampal volume has the best predictive power. Reliable predictions appear to be possible in many individual cases.

Music structure determines heart rate variability of singers

Choir singing is known to promote wellbeing. One reason for this may be that singing demands a slower than normal respiration, which may in turn affect heart activity. Coupling of heart rate variability (HRV) to respiration is called Respiratory sinus arrhythmia (RSA). This coupling has a subjective as well as a biologically soothing effect, and it is beneficial for cardiovascular function. RSA is seen to be more marked during slow-paced breathing and at lower respiration rates (0.1 Hz and below). In this study, we investigate how singing, which is a form of guided breathing, affects HRV and RSA. The study comprises a group of healthy 18 year olds of mixed gender. The subjects are asked to; (1) hum a single tone and breathe whenever they need to; (2) sing a hymn with free, unguided breathing; and (3) sing a slow mantra and breathe solely between phrases. Heart rate (HR) is measured continuously during the study. The study design makes it possible to compare above three levels of song structure. In a separate case study, we examine five individuals performing singing tasks (1–3). We collect data with more advanced equipment, simultaneously recording HR, respiration, skin conductance and finger temperature. We show how song structure, respiration and HR are connected. Unison singing of regular song structures makes the hearts of the singers accelerate and decelerate simultaneously. Implications concerning the effect on wellbeing and health are discussed as well as the question how this inner entrainment may affect perception and behavior.

Organic Mental Disorders as Hypothetical Pathogenetic Processes

A new diagnostic system for organic psychiatry is presented. We first define “organic psychiatry”, and then give the theoretical basis for conceiving organic‐psychiatric disorders in terms of hypothetical psychopathogenetic processes, HPP:s. Such hypothetical disorders are not strictly identical to the clusters of symptoms in which they typically manifest themselves, since the symptoms may be concealed or modified by intervening factors in non‐typical circumstances and/or in the simultaneous presence of several disorders. The six basic disorders in our system are Astheno‐Emotional Disorder (AED), Somnolence‐Sopor‐Coma Disorder (SSCD), Hallucination‐Coenestopathy‐Dcpersonalisation Disorder (HCDD), Confusional Disorder (CD), Emotional‐Motivational Blunting Disorder (EMD) and Korsakoffs Amnestic Disorder (KAD). We describe their usual etiologies, their typical symptoms and course, and some forms of interaction between tliem.

Artificial Neural Networks in Medicine and Biology

Artificial neural networks (ANNs) are new mathematical techniques which can be used for modelling real neural networks, but also for data categorisation and inference tasks in any empirical science. This means that they have a twofold interest for the philosopher. First, ANN theory could help us to understand the nature of mental phenomena such as perceiving, thinking, remembering, inferring, knowing, wanting and acting. Second, because ANNs are such powerful instruments for data classification and inference, their use also leads us into the problems of induction and probability. Ever since David Hume expressed his famous doubts about induction, the principles of scientific inference have been a central concern for philosophers.

A Combination of Neuropsychological, Neuroimaging, and Cerebrospinal Fluid Markers Predicts Conversion from Mild Cognitive Impairment to Dementia

BACKGROUND Mild cognitive impairment (MCI) is a condition with increased risk for further cognitive decline. A considerable challenge lies in predicting which patients will eventually convert to dementia. OBJECTIVE To study prediction of dementia in MCI using neuropsychological tests, commonly used cerebrospinal fluid (CSF) biomarkers, and hippocampal volume. METHODS Twenty-one MCI patients converting to dementia, 21 stable MCI patients, and 26 controls were included in the study with a follow-up time of two years. The study participants underwent comprehensive examinations at inclusion: a neuropsychological assessment comprising 20 tests, MRI scanning with subsequent hippocampal volumetry, and CSF analyses of T-tau, P-tau, and Aβ42. RESULTS Neuropsychological tests, hippocampal volume, and the CSF markers Aβ42, P-tau, and T-tau all predicted conversion from MCI to dementia. A combination of all classes of markers was the most successful at predicting dementia (AUC 0.96) with a memory test (RAVLT) as the best individual predictor (AUC 0.93). Similar findings are reported for the prediction of Alzheimers disease. CONCLUSION Neuropsychological tests were the best individual predictors of dementia. A combination of markers improved the predictive ability with the combination of neuropsychological tests, CSF, and hippocampal volume as the best predictors of dementia.

Combination of Hippocampal Volume and Cerebrospinal Fluid Biomarkers Improves Predictive Value in Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is a heterogeneous condition, and the prognosis differs within the group. Recent findings suggest that hippocampal volumetry and CSF biomarkers can be used to predict which MCI patients have an underlying neurodegenerative disorder. Objective: To examine the combined predictive value of hippocampal volume and CSF levels of total tau (T-tau) and β-amyloid42 (Aβ42) in stable and converting MCI patients. The participants (n = 68) included patients with MCI at baseline and who converted to dementia by the time of the 2-year follow-up (n = 21), stable MCI patients (n = 21) and healthy controls (n = 26). Methods: The Göteborg MCI study is a clinically based longitudinal study with biannual clinical assessments. Hippocampal volumetry was performed manually, based on data from the 0.5-tesla MRI investigations at baseline. Baseline CSF levels of T-tau and Aβ42 were measured using commercially available, enzyme-linked immunosorbent assays. Results: The converting MCI group had significantly smaller left hippocampi, lower CSF Aβ42 and higher T-tau compared to both the stable MCI group and the healthy controls. Multivariate analysis revealed that a combination of the variables outperformed the prognostic ability of the separate variables. Conclusions: Hippocampal volumes supplement the prognostic accuracy of CSF Aβ42 and T-tau in MCI.

High White Matter Lesion Load Is Associated with Hippocampal Atrophy in Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is a heterogeneous condition suggested as a prodromal state of Alzheimer’s disease (AD) and subcortical vascular dementia (SVD). Recent findings suggest that white matter lesions (WML) may be associated with hippocampal atrophy. The objective of the study was to examine hippocampal and WML volumes in MCI patients and to examine if WML were linked to hippocampal atrophy. Methods: The Gothenburg MCI study is a clinically based longitudinal study with biennial clinical assessments. The participants (n = 166) consist of 92 patients with stable MCI, 30 patients with converting MCI, and 44 healthy controls. WML volumes was measured manually using MRIcron. Automated segmentation of hippocampal and total white matter volumes was performed using FreeSurfer. Results: The patients converting from MCI to dementia had reduced hippocampal volume. Stable MCI patients had fewer WML and converting MCI patients had more WML compared to controls. Hippocampal volume was only correlated to WML volume (ρ = 0.57; p < 0.01) in the quartile (n = 42) with the most WML. Conclusions: Hippocampal atrophy is present in both AD and SVD. Hippocampal volume was associated with WML volume only in the high WML quartile, suggesting that the WML volume must reach a threshold before hippocampal atrophy is seen.

White Matter Lesion Assessment in Patients with Cognitive Impairment and Healthy Controls: Reliability Comparisons between Visual Rating, a Manual, and an Automatic Volumetrical MRI Method—The Gothenburg MCI Study

Age-related white matter lesions (WML) are a risk factor for stroke, cognitive decline, and dementia. Different requirements are imposed on methods for the assessment of WML in clinical settings and for research purposes, but reliability analysis is of major importance. In this study, WML assessment with three different methods was evaluated. In the Gothenburg mild cognitive impairment study, MRI scans from 152 participants were used to assess WML with the Fazekas visual rating scale on T2 images, a manual volumetric method on FLAIR images, and FreeSurfer volumetry on T1 images. Reliability was acceptable for all three methods. For low WML volumes (2/3 of the patients), reliability was overall lower and nonsignificant for the manual volumetric method. Unreliability in the assessment of patients with low WML with manual volumetry may mainly be due to intensity variation in the FLAIR sequence used; hence, intensity standardization and normalization methods must be used for more accurate assessments. The FreeSurfer segmentations resulted in smaller WML volumes than the volumes acquired with the manual method and showed deviations from visible hypointensities in the T1 images, which quite likely reduces validity.

Effects of a Curricular Physical Activity Intervention on Children's School Performance, Wellness, and Brain Development

BACKGROUND Physical activity and structural differences in the hippocampus have been linked to educational outcome. We investigated whether a curriculum-based physical activity intervention correlates positively with childrens academic achievement, psychological well-being, health-related quality of life (HRQoL), fitness, and structural development of the brain. METHODS The study had a quasi-experimental design and a control group. National test results were gathered from 545 students, 122 in the intervention school, and 423 in 3 control schools. HRQoL and socioemotional data were collected with child and proxy versions of KIDSCREEN and the Strength and Difficulties Questionnaire. Overall, 79 students in grades 5 and 6 were recruited for an in-depth study, consisting of a submaximal oxygen consumption test and magnetic resonance imaging of the brain. HRQoL and socioemotional data were collected from 349 students (65%), 182 (52%) in the intervention school, and 167 (48%) in one of the control schools. RESULTS Girls attending the intervention school were more likely to pass national tests in Swedish (odds ratio 5.7) and Mathematics (odds ratio 3.2). The fourth to sixth graders in the intervention school reported lower levels of conduct problems (p < .05), and the girls were also less likely to report hyperactivity (p < .05). Girls reported higher levels of emotional problems (p < .05) than boys. Boys in the intervention group had significantly higher levels of estimated maximal oxygen uptake (p < .05) than controls. No difference in hippocampal structure was seen. CONCLUSIONS Curriculum-based physical activity in school may improve the academic achievement and psychological health of children, particularly for girls.

FSED-feature selective edge detection

We present a method that finds edges between certain image features, e.g. gray-levels, and disregards edges between other features. The method uses a channel representation of the features and performs normalized convolution using the channel values as certainties. This means that areas with certain features can be disregarded by the edge filter. The method provides an important tool for finding tissue specific edges in medical images, as demonstrated by an MR-image example.