Several anatomical MRI markers for Alzheimer's disease (AD) have been identified. Hippocampal volume, cortical thickness, and grey matter density have been used successfully to discriminate AD... Show moreSeveral anatomical MRI markers for Alzheimer's disease (AD) have been identified. Hippocampal volume, cortical thickness, and grey matter density have been used successfully to discriminate AD patients from controls. These anatomical MRI measures have so far mainly been used separately. The full potential of anatomical MRI scans for AD diagnosis might thus not yet have been used optimally. In this study, we therefore combined multiple anatomical MRI measures to improve diagnostic classification of AD. For 21 clinically diagnosed AD patients and 21 cognitively normal controls, we calculated (i) cortical thickness, (ii) cortical area, (iii) cortical curvature, (iv) grey matter density, (v) subcortical volumes, and (vi) hippocampal shape. These six measures were used separately and combined as predictors in an elastic net logistic regression. We made receiver operating curve plots and calculated the area under the curve (AUC) to determine classification performance. AUC values for the single measures ranged from 0.67 (cortical thickness) to 0.94 (grey matter density). The combination of all six measures resulted in an AUC of 0.98. Our results demonstrate that the different anatomical MRI measures contain complementary information. A combination of these measures may therefore improve accuracy of AD diagnosis in clinical practice. Hum Brain Mapp 37:1920-1929, 2016. (c) 2016 Wiley Periodicals, Inc. Show less
Moller, C.; Hafkemeijer, A.; Pijnenburg, Y.A.L.; Rombouts, S.A.R.B.; Grond, J. van der; Dopper, E.; ... ; Flier, W.M. van der 2016
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.... Show moreMagnetic 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. (C) 2016 The Authors. Published by Elsevier Inc. Show less
Schouten, T.M.; Koini, M.; Vos, F. de; Seiler, S.; Van der Grond, J.; Lechner, A.; ... ; Rombouts, S.A.R.B. 2016
Alzheimer__s disease (AD) is the predominant form of dementia in the aging population and its increasing incidence represents an important socio-economic and public health concern. The hallmarks of... Show moreAlzheimer__s disease (AD) is the predominant form of dementia in the aging population and its increasing incidence represents an important socio-economic and public health concern. The hallmarks of this disease, amyloid plaques and neurofibrillary tangles, are thought to develop early in the disease pathogenesis, up to decades before first clinical symptoms occur. However, these pathological hallmarks are still difficult to detect in vivo, and therefore a definitive diagnosis can only be made post-mortem. A clinical imaging technique or biomarker capable of visualizing and quantifying amyloid plaques and associated early changes thus may enable an earlier diagnosis, better understanding of the pathophysiology and eventually aid therapy development. The work presented in this thesis aimed to develop innovative diagnostic imaging techniques to detect the histological signatures of AD using emerging ultra-high field MRI technologies (Part I) and molecular imaging strategies (Part II). Show less
Nabuurs, R.J.A.; Kapoerchan, V.V.; Metaxas, A.; Jongh, S. de; Backer, M. de; Welling, M.M.; ... ; Weerd, L. van der 2014
The general objective of this thesis was to investigate new (quantitative) MR techniques and MR markers in the light of both AD and cerebral aging. The quantitative MR techniques that we used were... Show moreThe general objective of this thesis was to investigate new (quantitative) MR techniques and MR markers in the light of both AD and cerebral aging. The quantitative MR techniques that we used were MTI, tCBF and WSS measurements. The new markers we studied were cerebral microbleeds and iron accumulation in the basal ganglia. In chapter 2 we investigated whether MTI changes could be detected in the GM, WM or both in patients suffering from MCI or AD. Using MTI we found evidence for structural brain changes in both GM and WM of patients with MCI and AD. Furthermore, these MTI changes were related to cognitive impairment as expressed by the mini mental state examination (MMSE) score. These findings imply that cerebral changes can be detected in both GM and WM even before patients are clinically demented. The finding of MTI changes in the GM might relate to classical AD type pathology, whereas WM MTI changes could indicate concomitant vascular pathology. The findings in chapter 2 raised the question of how the MTI changes found in this study are distributed over the GM and WM. This was investigated in chapter 3. In this study we showed that brain damage, as detected by MTI, is widespread over the lobes in both AD and MCI patients whereas GM damage is more focally present in the temporal and frontal lobe of MCI patients. These findings are compatible with the knowledge that GM damage originates from the temporal lobe in AD. This interpretation is further supported by the observed independent association between temporal GM peak height and cognitive decline. MTI changes were found in all four lobes of the MCI patients investigated in this study and show the involvement of a diffuse process affecting the WM even before patients are clinically demented, a finding potentially explained by the presence of diffuse vascular pathology. Chapter 4 shows that the tCBF is strongly associated with parenchymal volume rather than age and, although much weaker, with the severity of WMHs. Although the association between tCBF and parenchyma volume seems straightforward, this finding has important implications for future studies. Volume flow measurements should be corrected for parenchymal volume ratherthan age in all future studies in which flow measurements are being used as a diagnostic tool. In addition, studies including elderly patients or patients with a pathological increase of WMHs, such as diabetic type II subjects, should also correct their tCBF measurements for WMH volumes. Chapter 5 shows that hemodynamic conditions of the carotid and basilar arteries, as expressed in lower WSS parameters, are worse in both MCI and AD compared to controls. In addition, the WSS parameters were found to correlate strongly with cognition. Again, this study is additional evidence for an important role of vascular pathology in the development of AD. In chapter 6, we found a high prevalence of microbleeds in a population of patients suffering from vascular disease or at high risk of developing this condition. Age, hypertension and WMH were the most important risk factors for microbleeds, especially when located in the cortico-subcortical junction and basal ganglia. Regarding the associations between the presence and location of microbleeds on the one hand and parameters of cognitive functioning on the other, chapter 7 shows that microbleeds located infratentorially are associated with impaired cognitive functioning in the aging population with increased vascular risk factors. This suggests that in elderly individuals microbleeds in the posterior fossa should be considered a sign of small vessel disease with potential functional consequences. The semi-quantative scale for scoring basal ganglia hypo-intensity on T2*- weighted imaging presented in chapter 8 was associated with markers of neurodegeneration. This study showed that low signal intensity of the caudate nucleus T2*-weighted MR is a frequent finding which is associated with more cerebral atrophy, a higher load of WMH and a higher load of invisible changes in both cortical GM and NAWM non-demented elderly. Furthermore, hypo- intensity limited to the globus pallidus and putamen was not associated with any of these parameters of neurodegeneration. In chapter 9 we present a method for automated detection and classification of hypo-intense regions on T2-weighted MR images of the basal ganglia. In this chapter we not only show an association between basal ganglia hypo-intensity and cardiovascular risk factors but also with measures of cognitive functioning. From this we conclude that hypo-intensity of the basal ganglia on T2-weighted MR is not only a radiological finding accompanying cerebral aging but also an independent marker of neurodegeneration. Show less
Shamonin, D.P.; Bron, E.E.; Lelieveldt, B.P.F.; Smits, M.; Klein, S.; Staring, M.; Alzheimer's Dis Neuroimaging In 2014
