Tissue microstructural changes in dementia with Lewy bodies revealed by quantitative MRI

Su, Li; Blamire, Andrew M.; Watson, Rosie; He, Jiabao; Aribisala, Benjamin S.; O’Brien, John

doi:10.1007/s00415-014-7541-2

Cited by 13 publications

(11 citation statements)

References 39 publications

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“…In addition to our previous findings on qMRI changes in DLB [7], as well as the established literature on animal qMRI correlates, the current data provided convergent evidence for the potential ability of quantitative MRI in detecting early changes of tissue property caused by neurodegenerative disease. Being able to apply this novel technique in human using relatively safe MRI method enables new means for early detection of AD and tracking its progression over time.…”

Section: Individual Analysis In Longitudinal Comparisonsupporting

confidence: 81%

“…In our previous cross-sectional study on dementia with Lewy bodies (DLB), we also found a significant reduction of qMRI parameters in DLB compared to controls [7]. In addition, we showed that the spatial pattern of qMRI alteration only partly overlapped with that of atrophy, making the latter an unlikely explanation for the qMRI decreases.…”

Section: Individual Analysis In Longitudinal Comparisonsupporting

confidence: 56%

“…Quantitative MRI provides important information about tissue properties in brain both in normal ageing [4,5], degenerative disorders such as Parkinson's disease [6], AD and dementia with Lewy bodies (DLB) [7], and neuronal loss due to brain and spinal cord injury [8]. In our previous study of DLB using qMRI, we demonstrated that the spatial pattern in the changes of qT1 and qT2 was different from the pattern of atrophy, thus quantitative MRI may provide incremental benefit over and above that of structural MRI [7]. We also argue that quantitative MRI may indirectly detect neuronal and molecular changes in AD that precede the structural brain damage and clinical impairments decades in time [2].…”

Section: Introductionmentioning

confidence: 99%

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Cortical and Subcortical Changes in Alzheimer's Disease: A Longitudinal and Quantitative MRI Study

Blamire²,

Watson³

et al. 2016

CAR

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Quantitative MRI provides important information about tissue properties in brain both in normal ageing and in degenerative disorders. Although it is well known that those with Alzheimer's disease (AD) show a specific pattern and faster rate of atrophy than controls, the precise spatial and temporal patterns of quantitative MRI in AD are unknown. We aimed to investigate neuroimaging correlates of AD using serial quantitative MRI. In our study, twenty-one subjects with AD and thirty-two similar-aged healthy controls underwent two serial MRI scans at baseline and 12 months. Tissue characteristics were captured using two quantitative MRI parameters: longitudinal relaxation time (qT1) and transverse relaxation time (qT2). The two groups (AD and controls) were statistically compared using a voxel based quantification (VBQ) method based on Matlab and SPM8. At baseline, subjects with AD showed a significant reduction of qT1 and qT2 compared to controls in bilateral temporal and parietal lobes, hippocampus, and basal ganglia. This pattern was also observed at follow-up. Longitudinally, in AD we found a significant increase rather than further reduction of qT1 and qT2 from the baseline in bilateral hippocampus, thalamus and right caudate nucleus. In addition, the longitudinal change of qT1 in left hippocampus was negatively correlated with cognitive decline in AD over the 1-year period, and the general disease severity significantly predicted the amount of increase of qT1 in bilateral hippocampus over 12 months. The longitudinal change of qT2 in left parahippocampus correlated with change in neuropsychiatric features over time. In summary, quantitative MRI parameters were reduced in AD cross-sectionally, but increased over time, showing distinct spatiotemporal patterns from the atrophy in AD. We also showed the clinical relevance of quantitative MRI parameters, indicating their potential promise as new imaging markers in AD.

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Section: Individual Analysis In Longitudinal Comparisonsupporting

confidence: 81%

Section: Individual Analysis In Longitudinal Comparisonsupporting

confidence: 56%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cortical and Subcortical Changes in Alzheimer's Disease: A Longitudinal and Quantitative MRI Study

Blamire²,

Watson³

et al. 2016

CAR

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“…In previous work by the same authors, decreased T 1 values were found in patients with dementia with Lewy bodies compared with control subjects, highlighting the potential of T 1 measures in general to detect changes caused by neurodegeneration [21]. Using 5xFAD transgenic mice, a well-recognised AD mouse model [22–24], we have previously shown that at the age of 11 months, 5xFAD mice have reduced MRI T 1 relaxation times in the lower layers of the posterior parietal and primary somatosensory areas of the cortex and the corpus callosum compared with age-matched wild-type controls [25].…”

Section: Introductionmentioning

confidence: 93%

Can MRI T1 be used to detect early changes in 5xFAD Alzheimer’s mouse brain?

Spencer

Lovell

Elderfield

et al. 2016

Magn Reson Mater Phy

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ObjectivesIn the present study, we have tested whether MRI T1 relaxation time is a sensitive marker to detect early stages of amyloidosis and gliosis in the young 5xFAD transgenic mouse, a well-established animal model for Alzheimer’s disease.Materials and methods5xFAD and wild-type mice were imaged in a 4.7 T Varian horizontal bore MRI system to generate T1 quantitative maps using the spin-echo multi-slice sequence. Following immunostaining for glial fibrillary acidic protein, Iba-1, and amyloid-β, T1 and area fraction of staining were quantified in the posterior parietal and primary somatosensory cortex and corpus callosum.ResultsIn comparison with age-matched wild-type mice, we observed first signs of amyloidosis in 2.5-month-old 5xFAD mice, and development of gliosis in 5-month-old 5xFAD mice. In contrast, MRI T1 relaxation times of young, i.e., 2.5- and 5-month-old, 5xFAD mice were not significantly different to those of age-matched wild-type controls. Furthermore, although disease progression was detectable by increased amyloid-β load in the brain of 5-month-old 5xFAD mice compared with 2.5-month-old 5xFAD mice, MRI T1 relaxation time did not change.ConclusionsIn summary, our data suggest that MRI T1 relaxation time is neither a sensitive measure of disease onset nor progression at early stages in the 5xFAD mouse transgenic mouse model.

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“…Differences in MTL atrophy between AD and healthy controls measured using semi-quantitative techniques on MRI has shown sensitivity and specificity greater than 85% [56,57,58]. Significant alterations in tissue microstructure measured by longitudinal and transversal relaxation times was found in patients with DLB compared to healthy controls [59]. Differences between AD and other dementias could not be found with similar sensitivity and specificity though [60,61,62].…”

Section: Mri In Dementiamentioning

confidence: 99%

Classifying Alzheimer's disease, Lewy body dementia, and normal controls using 3D texture analysis in magnetic resonance images

Oppedal

Engan

Eftestøl

et al. 2017

Biomedical Signal Processing and Control

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IntroductionExpected age is increasing globally and dementia is a common outcome for an increasing number of people. Dementia is a demanding syndrome for the patient and the environment as well as it is costly for society. Damaging changes to the cerebral blood flow also called white matter lesions (WML) are common in the elderly and is expected to increase as age advances. It has been reported that these types of lesions affect cognition in healthy elderly. They are also associated to Alzheimer's disease but have not been much studied in DLB. Quantitative analysis and machine learning have a potential to contribute in understanding the disease process as well as aid in diagnosis. MethodsQuantitative analysis of WML volumes were calculated using an automatic segmentation routine on magnetic resonance images (MRI) of subjects with Alzheimer's disease (AD), Lewy body dementia (LBD), and normal controls (NC). Statistical tests were performed to compare groups as well as to investigate relations to cognition. Additionally, WML volumes were used as features in a machine learning (ML) environment to check whether WML volume were able to classify subjects with AD and LBD from NC. Texture analysis (TA) may be able to document changes at a microstructural level and was performed in WML an non-WML regions of the different types of MRI's (FLAIR and T1). 2D-and 3D TA features were calculated and used in classification with the aim to serve as a tool for computer aided diagnosis (CAD) in dementia. The dataset used was imbalanced meaning that the number of subjects in each group were very different. Two methods for handling the imbalanced data were tested, namely upsampling and cost-sensitive classification.v Results and conclusionsSeverity of WML did neither differ significantly between subjects with dementia and NC nor between mildly demented patients with AD and LBD. WML severity were associated with cognitive decline in AD, but not LBD suggesting that WML contributes to cognitive decline in AD, but not LBD. More studies of the potential clinical impact of WML in patients with LBD are needed.The best classification results obtained using WML volumes as features in an ML framework discerning subjects with dementia from healthy controls were an area under curve (AUC) of 0.73 and 95% confidence interval of 0.57 to 0.83.We experienced better classification results when using TA features compared to WML volumes in classification and better results when performing classification on TA features calculated from T1 MRI compared to FLAIR MRI. A total accuracy, reported as mean with standard deviation in brackets over cross validation folds, of 0.97(0.07) or higher was reported for the dementia vs. NC, AD vs. NC, and LBD vs. NC classification problems for both the 2D-and 3D texture analysis approaches. In the AD vs. LBD case a total accuracy of 0.73(0.16) was reported using the 2D TA approach slightly exceeded by the 3D TA approach were 0.79(0.15) was reported.It seems like the results do not differ much when performing anal...

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Tissue microstructural changes in dementia with Lewy bodies revealed by quantitative MRI

Cited by 13 publications

References 39 publications

Cortical and Subcortical Changes in Alzheimer's Disease: A Longitudinal and Quantitative MRI Study

Cortical and Subcortical Changes in Alzheimer's Disease: A Longitudinal and Quantitative MRI Study

Can MRI T1 be used to detect early changes in 5xFAD Alzheimer’s mouse brain?

Classifying Alzheimer's disease, Lewy body dementia, and normal controls using 3D texture analysis in magnetic resonance images

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