Magnetic resonance imaging (MRI) is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD), and can therefore be used to help in diagnosing the disease. ...Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N = 77) from the prospective registry on dementia study and controls (N = 173) from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC) of 0.760 (full correlations between functional networks) to 0.909 (grey matter density). When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.
To assess the influence of cognitive, functional and behavioral factors, co-morbidities as well as caregiver characteristics on driving cessation in dementia patients.
The study cohort consists of ...those 240 dementia cases of the ongoing prospective registry on dementia in Austria (PRODEM) who were former or current car-drivers (mean age 74.2 (±8.8) years, 39.6% females, 80.8% Alzheimer's disease). Reasons for driving cessation were assessed with the patients' caregivers. Standardized questionnaires were used to evaluate patient- and caregiver characteristics. Cognitive functioning was determined by Mini-Mental State Examination (MMSE), the CERAD neuropsychological test battery and Clinical Dementia Rating (CDR), activities of daily living (ADL) by the Disability Assessment for Dementia, behavior by the Neuropsychiatric Inventory (NPI) and caregiver burden by the Zarit burden scale.
Among subjects who had ceased driving, 136 (93.8%) did so because of "Unacceptable risk" according to caregiver's judgment. Car accidents and revocation of the driving license were responsible in 8 (5.5%) and 1(0.7%) participant, respectively. Female gender (OR 5.057; 95%CI 1.803-14.180; p = 0.002), constructional abilities (OR 0.611; 95%CI 0.445-0.839; p = 0.002) and impairment in Activities of Daily Living (OR 0.941; 95%CI 0.911-0.973; p<0.001) were the only significant and independent associates of driving cessation. In multivariate analysis none of the currently proposed screening tools for assessment of fitness to drive in elderly subjects including the MMSE and CDR were significantly associated with driving cessation.
The risk-estimate of caregivers, but not car accidents or revocation of the driving license determines if dementia patients cease driving. Female gender and increasing impairment in constructional abilities and ADL raise the probability for driving cessation. If any of these factors also relates to undesired traffic situations needs to be determined before recommendations for their inclusion into practice parameters for the assessment of driving abilities in the elderly can be derived from our data.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Migraine is a complex, multifactorial, neurovascular disorder of the brain. Patients frequently have pericranial trigger points, but trigger point (TP) therapy for migraine has not yet been ...adequately studied. In contrast, lymphatic drainage (LD) has been studied in patients with migraine. The multifactorial origin of migraine suggests using a combination of approaches such as TP therapy and lymphatic drainage. The present study evaluated the effectiveness of TP therapy alone and in combination with LD in preventing migraine during treatment period and over an 8‑week period after completion of treatment. A wait list control group served as a control group. Patients completed a headache calendar. The results of this pilot study suggest a beneficial effect for TP alone and TP combined with LD for migraine prophylaxis for 8 weeks after completion of treatment.
•Multimodal MRI AD classification models were pre-trained on AD patients and controls.•Generalisation of these models was tested on a multi-centre memory clinic data set.•AD scores were assigned to ...AD patients, MCI patients and memory complainers.•Anatomical MRI performed better than diffusion MRI and resting state fMRI.•Combining imaging modalities did not improve the results over anatomical MRI only.
Anatomical magnetic resonance imaging (MRI), diffusion MRI and resting state functional MRI (rs-fMRI) have been used for Alzheimer’s disease (AD) classification. These scans are typically used to build models for discriminating AD patients from control subjects, but it is not clear if these models can also discriminate AD in diverse clinical populations as found in memory clinics.
To study this, we trained MRI-based AD classification models on a single centre data set consisting of AD patients (N = 76) and controls (N = 173), and used these models to assign AD scores to subjective memory complainers (N = 67), mild cognitive impairment (MCI) patients (N = 61), and AD patients (N = 61) from a multi-centre memory clinic data set. The anatomical MRI scans were used to calculate grey matter density, subcortical volumes and cortical thickness, the diffusion MRI scans were used to calculate fractional anisotropy, mean, axial and radial diffusivity, and the rs-fMRI scans were used to calculate functional connectivity between resting state networks and amplitude of low frequency fluctuations. Within the multi-centre memory clinic data set we removed scan site differences prior to applying the models.
For all models, on average, the AD patients were assigned the highest AD scores, followed by MCI patients, and later followed by SMC subjects. The anatomical MRI models performed best, and the best performing anatomical MRI measure was grey matter density, separating SMC subjects from MCI patients with an AUC of 0.69, MCI patients from AD patients with an AUC of 0.70, and SMC patients from AD patients with an AUC of 0.86. The diffusion MRI models did not generalise well to the memory clinic data, possibly because of large scan site differences. The functional connectivity model separated SMC subjects and MCI patients relatively good (AUC = 0.66). The multimodal MRI model did not improve upon the anatomical MRI model.
In conclusion, we showed that the grey matter density model generalises best to memory clinic subjects. When also considering the fact that grey matter density generally performs well in AD classification studies, this feature is probably the best MRI-based feature for AD diagnosis in clinical practice.
Alzheimer's disease (AD) patients show altered patterns of functional connectivity (FC) on resting state functional magnetic resonance imaging (RSfMRI) scans. It is yet unclear which RSfMRI measures ...are most informative for the individual classification of AD patients. We investigated this using RSfMRI scans from 77 AD patients (MMSE = 20.4 ± 4.5) and 173 controls (MMSE = 27.5 ± 1.8). We calculated i) FC matrices between resting state components as obtained with independent component analysis (ICA), ii) the dynamics of these FC matrices using a sliding window approach, iii) the graph properties (e.g., connection degree, and clustering coefficient) of the FC matrices, and iv) we distinguished five FC states and administered how long each subject resided in each of these five states. Furthermore, for each voxel we calculated v) FC with 10 resting state networks using dual regression, vi) FC with the hippocampus, vii) eigenvector centrality, and viii) the amplitude of low frequency fluctuations (ALFF). These eight measures were used separately as predictors in an elastic net logistic regression, and combined in a group lasso logistic regression model. We calculated the area under the receiver operating characteristic curve plots (AUC) to determine classification performance. The AUC values ranged between 0.51 and 0.84 and the highest were found for the FC matrices (0.82), FC dynamics (0.84) and ALFF (0.82). The combination of all measures resulted in an AUC of 0.85. We show that it is possible to obtain moderate to good AD classification using RSfMRI scans. FC matrices, FC dynamics and ALFF are most discriminative and the combination of all the resting state measures improves classification accuracy slightly.
•We calculated resting state fMRI measures for Alzheimer patients and controls.•The resting state measures were used in elastic net classification analyses.•Functional connectivity and functional connectivity dynamics perform best.•Classification performance improves slightly when combining all measures.
Diffusion magnetic resonance imaging (MRI) is a powerful non-invasive method to study white matter integrity, and is sensitive to detect differences in Alzheimer's disease (AD) patients. Diffusion ...MRI may be able to contribute towards reliable diagnosis of AD. We used diffusion MRI to classify AD patients (N=77), and controls (N=173). We use different methods to extract information from the diffusion MRI data. First, we use the voxel-wise diffusion tensor measures that have been skeletonised using tract based spatial statistics. Second, we clustered the voxel-wise diffusion measures with independent component analysis (ICA), and extracted the mixing weights. Third, we determined structural connectivity between Harvard Oxford atlas regions with probabilistic tractography, as well as graph measures based on these structural connectivity graphs. Classification performance for voxel-wise measures ranged between an AUC of 0.888, and 0.902. The ICA-clustered measures ranged between an AUC of 0.893, and 0.920. The AUC for the structural connectivity graph was 0.900, while graph measures based upon this graph ranged between an AUC of 0.531, and 0.840. All measures combined with a sparse group lasso resulted in an AUC of 0.896. Overall, fractional anisotropy clustered into ICA components was the best performing measure. These findings may be useful for future incorporation of diffusion MRI into protocols for AD classification, or as a starting point for early detection of AD using diffusion MRI.
•We use machine learning classification to classify Alzheimer's disease.•We use diffusion MRI based measures for classification.•Tract based diffusion tensor measures are excellent for classification.•Clustering fractional anisotropy into independent components can improve classification.
The angiotensinogen M235T polymorphism has been linked to hypertension and cardiovascular disease. We studied the role of this polymorphism as a risk factor for carotid atherosclerosis and ...small-vessel disease-related brain abnormalities. A total of 431 randomly selected community-dwelling subjects without clinical evidence for strokes underwent angiotensinogen genotyping and carotid Duplex scanning; 1.5-T brain magnetic resonance imaging (MRI) was done in 396 individuals. At 3-year follow-up, we reexamined 343 and 267 study participants by ultrasound and brain MRI, respectively. Carotid atherosclerosis was graded on a 5-point scale. Small-vessel disease-related brain abnormalities were deep or subcortical white matter lesions or lacunes. Progression of carotid atherosclerosis and MRI findings was rated by direct imaging comparison by 3 independent raters. The M/M, M/T, and T/T genotypes were seen in 20.9%, 52.9%, and 18.1% of subjects, respectively. The M235T polymorphism was neither associated with baseline carotid findings nor with progression of carotid atherosclerosis. There was a trend toward more frequent small-vessel disease-related MRI abnormalities in the T/T than in the other genotypes at the baseline examination. Progression of brain lesions occurred significantly more commonly in T/T than in M/M and M/T carriers (P <0.001). Logistic regression analysis identified the T/T genotype (odds ratio, 3.19;P =0.002) and arterial hypertension (odds ratio, 3.06;P =0.03) as significant independent predictors of lesion progression. These data suggest that the angiotensinogen T/T genotype at position 235 is a genetic marker for brain lesions from and progression of small vessel disease but not for extracranial carotid atherosclerosis.
Background
Recurrent and especially chronic headaches are associated with psychiatric comorbidities such as depression and anxiety. Only few studies examined the impact of depression and anxiety on ...episodic (EH) and chronic headache (CH), and data for Austria are missing at all. Therefore, the aim of the present study was to assess the impact of depression and anxiety on burden and management of EH and CH in patients from eight Austrian headache centres.
Methods
We included 392 patients (84.1 % female, mean age 40.4 ± 14.0 years) who completed the Eurolight questionnaire. The treating physician recorded details about ever-before prophylactic medications. We used Hospital Anxiety and Depression Scale to assess depression and anxiety and compared patients with anxiety and/or depression to those without.
Results
Depression and anxiety were more common in CH than in EH (64 % vs. 41 %,
p
< 0.0001). Presence compared to absence of depression and anxiety increased the prevalence of poor or very poor quality of life from 0.7 % to 13.1 % in EH and from 3.6 % to 40.3 % in CH (
p
= 0.001;
p
< 0.0001). Depression and anxiety had a statistically significant impact on employment status and on variables related to the burden of headache such as reduced earnings, being less successful in career, or feeling less understood. Neither in EH nor in CH health care use and the ever-before use of prophylactic medication was correlated with anxiety and/or depression.
Conclusion
Depression and anxiety have a significant impact on quality of life and increase the burden in patients with EH and CH. Improved multidimensional treatment approaches are necessary to decrease disability on the personal, social and occupational level in these patients.
Background
Episodic and chronic headaches (EH, CH) are highly prevalent disorders. Severely affected patients are usually referred to headache centres. In Austria, at least one headache centre is ...available in seven of nine states, but detailed multicentre data are missing. Therefore we studied prevalence rates, use of medication and health care services, impact of headaches, and comorbid depression and anxiety.
Methods
We included consecutive patients from eight Austrian outpatient headache centres. The patients filled-in the Eurolight questionnaire. In addition, the treating neurologist completed a questionnaire on clinical diagnoses and ever-before prophylactic medications.
Results
Of 598 patients screened, 441 questionnaires were analysed (79 % female, mean age 41.1 years). According to the Eurolight algorithm, 56.4 % of the patients had EH, 38.3 % had CH and 5.2 % did not give their headache frequency. The prevalence rates of migraine, tension-type headache, and probable medication overuse headache (pMOH) were 48.5 %, 6.3 % and 15.9 %, respectively. The concordance between clinical and Eurolight diagnoses was good for EH and moderate for CH. During the preceding month, acute medication was used by 90.9 % of the patients and prophylactic medication by 34 %. Ever-before use of five standard prophylactic drugs was recorded in 52.3 %. The proportion of patients with current pharmacoprophylaxis did not differ in EH and CH, whereas ever-before use was more common in CH (62.5 % was 45,3 %,
p
= 0.02). Patients with CH significantly more often consulted general practitioners and emergency departments, had a lower quality of life and more often signs of depression and anxiety.
Conclusion
This study provides comprehensive data from eight Austrian headache centres for the first time. We found a substantial number of patients with CH including pMOH and its association with more common utilization of health care facilities and greater burden. The low use of prophylactic medication requires further examination.
Background: Functional (un-)coupling (task-related change of functional connectivity) between different sites of the brain is a mechanism of general importance for cognitive processes. In Alzheimer's ...disease (AD), prior research identified diminished cortical connectivity as a hallmark of the disease. However, little is known about the relation between the amount of functional (un-)coupling and cognitive performance and decline in AD. Method: Cognitive performance (based on CERAD-Plus scores) and electroencephalogram (EEG)-based functional (un-)coupling measures (connectivity changes from rest to a Face-Name-Encoding task) were assessed in 135 AD patients (age: M = 73.8 years; SD = 9.0). Of these, 68 patients (M = 73.9 years; SD = 8.9) participated in a follow-up assessment of their cognitive performance 1.5 years later. Results: The amounts of functional (un-)coupling in left anterior-posterior and homotopic interhemispheric connections in beta1-band were related to cognitive performance at baseline (β = .340; p < .001; β = .274; P = .001, respectively). For both markers, a higher amount of functional coupling was associated with better cognitive performance. Both markers also were significant predictors for cognitive decline. However, while patients with greater functional coupling in left anterior-posterior connections declined less in cognitive performance (β = .329; P = .035) those with greater functional coupling in interhemispheric connections declined more (β = −.402; P = .010). Conclusion: These findings suggest an important role of functional coupling mechanisms in left anterior–posterior and interhemispheric connections in AD. Especially the complex relationship with cognitive decline in AD patients might be an interesting aspect for future studies.
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