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Thomas R Barrick - One of the best experts on this subject based on the ideXlab platform.
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diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to Cognitive Change
NeuroImage: Clinical, 2017Co-Authors: Owen A Williams, Christian Lambert, Philip Benjamin, Eva Zeestraten, Andrew D. Mackinnon, Hugh S Markus, Andrew J Lawrence, Robin G Morris, Rebecca A Charlton, Thomas R BarrickAbstract:Cerebral small vessel disease (SVD) is the primary cause of vascular Cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe Cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related Changes in a single unitary score across the whole cerebrum, to investigate its relationship with Cognitive Change over a three-year period. 98 patients (aged 43-89) with SVD underwent annual MRI scanning and Cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain Change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain Change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to Change in EF and IPS (p < 0.001) and remained significant in multivariate models including other MRI markers of SVD as well as age, gender and premorbid IQ. Of the conventional markers, presence of new lacunes was the only marker to remain a significant predictor of Change in EF and IPS in the multivariate models (p = 0.002). Change in DSEG θ was also related to Change in all other MRI markers (p < 0.017), suggesting it may be used as a surrogate marker of SVD damage across the cerebrum. Sample size estimates indicated that fewer patients would be required to detect treatment effects using DSEG θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain Change in SVD that has a negative impact on cognition and remains a significant predictor of Cognitive Change when other MRI markers of brain Change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural Changes and successfully predicts Cognitive Change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).
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diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to Cognitive Change
NeuroImage: Clinical, 2017Co-Authors: Owen A Williams, Christian Lambert, Philip Benjamin, Eva Zeestraten, Andrew D. Mackinnon, Hugh S Markus, Andrew J Lawrence, Robin G Morris, Rebecca A Charlton, Thomas R BarrickAbstract:Abstract Cerebral small vessel disease (SVD) is the primary cause of vascular Cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe Cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related Changes in a single unitary score across the whole cerebrum, to investigate its relationship with Cognitive Change over a three-year period. 98 patients (aged 43–89) with SVD underwent annual MRI scanning and Cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain Change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain Change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to Change in EF and IPS ( p p = 0.002). Change in DSEG θ was also related to Change in all other MRI markers ( p θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain Change in SVD that has a negative impact on cognition and remains a significant predictor of Cognitive Change when other MRI markers of brain Change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural Changes and successfully predicts Cognitive Change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).
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progression of mri markers in cerebral small vessel disease sample size considerations for clinical trials
Journal of Cerebral Blood Flow and Metabolism, 2016Co-Authors: Philip Benjamin, Bhavini Patel, Christian Lambert, Eva Zeestraten, Owen A Williams, Andrew D. Mackinnon, Thomas R Barrick, Irina Chis Ster, Andrew J Lawrence, Hugh S MarkusAbstract:Detecting treatment efficacy using Cognitive Change in trials of cerebral small vessel disease (SVD) has been challenging, making the use of surrogate markers such as magnetic resonance imaging (MR...
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up the garden path a critique of penke and deary and further exploration concerning the charlton et al path analysis relating loss of white matter integrity to cognition in normal aging
Neurobiology of Aging, 2010Co-Authors: Rebecca A Charlton, Thomas R Barrick, Hugh S Markus, Sabine Landau, Francesca Schiavone, Chris A Clark, R G MorrisAbstract:We reply to criticisms by Penke and Deary (2010) of our model relating loss of white matter integrity in normal aging to Cognitive Change. We identify difficulties in their alternative path analysis in which they attempt to relate age-related loss of integrity of white matter to Changes in general intelligence. We then comment on their general criticisms and their viewpoints concerning use of path analysis.
Hugh S Markus - One of the best experts on this subject based on the ideXlab platform.
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diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to Cognitive Change
NeuroImage: Clinical, 2017Co-Authors: Owen A Williams, Christian Lambert, Philip Benjamin, Eva Zeestraten, Andrew D. Mackinnon, Hugh S Markus, Andrew J Lawrence, Robin G Morris, Rebecca A Charlton, Thomas R BarrickAbstract:Cerebral small vessel disease (SVD) is the primary cause of vascular Cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe Cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related Changes in a single unitary score across the whole cerebrum, to investigate its relationship with Cognitive Change over a three-year period. 98 patients (aged 43-89) with SVD underwent annual MRI scanning and Cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain Change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain Change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to Change in EF and IPS (p < 0.001) and remained significant in multivariate models including other MRI markers of SVD as well as age, gender and premorbid IQ. Of the conventional markers, presence of new lacunes was the only marker to remain a significant predictor of Change in EF and IPS in the multivariate models (p = 0.002). Change in DSEG θ was also related to Change in all other MRI markers (p < 0.017), suggesting it may be used as a surrogate marker of SVD damage across the cerebrum. Sample size estimates indicated that fewer patients would be required to detect treatment effects using DSEG θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain Change in SVD that has a negative impact on cognition and remains a significant predictor of Cognitive Change when other MRI markers of brain Change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural Changes and successfully predicts Cognitive Change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).
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diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to Cognitive Change
NeuroImage: Clinical, 2017Co-Authors: Owen A Williams, Christian Lambert, Philip Benjamin, Eva Zeestraten, Andrew D. Mackinnon, Hugh S Markus, Andrew J Lawrence, Robin G Morris, Rebecca A Charlton, Thomas R BarrickAbstract:Abstract Cerebral small vessel disease (SVD) is the primary cause of vascular Cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe Cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related Changes in a single unitary score across the whole cerebrum, to investigate its relationship with Cognitive Change over a three-year period. 98 patients (aged 43–89) with SVD underwent annual MRI scanning and Cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain Change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain Change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to Change in EF and IPS ( p p = 0.002). Change in DSEG θ was also related to Change in all other MRI markers ( p θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain Change in SVD that has a negative impact on cognition and remains a significant predictor of Cognitive Change when other MRI markers of brain Change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural Changes and successfully predicts Cognitive Change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).
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progression of mri markers in cerebral small vessel disease sample size considerations for clinical trials
Journal of Cerebral Blood Flow and Metabolism, 2016Co-Authors: Philip Benjamin, Bhavini Patel, Christian Lambert, Eva Zeestraten, Owen A Williams, Andrew D. Mackinnon, Thomas R Barrick, Irina Chis Ster, Andrew J Lawrence, Hugh S MarkusAbstract:Detecting treatment efficacy using Cognitive Change in trials of cerebral small vessel disease (SVD) has been challenging, making the use of surrogate markers such as magnetic resonance imaging (MR...
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up the garden path a critique of penke and deary and further exploration concerning the charlton et al path analysis relating loss of white matter integrity to cognition in normal aging
Neurobiology of Aging, 2010Co-Authors: Rebecca A Charlton, Thomas R Barrick, Hugh S Markus, Sabine Landau, Francesca Schiavone, Chris A Clark, R G MorrisAbstract:We reply to criticisms by Penke and Deary (2010) of our model relating loss of white matter integrity in normal aging to Cognitive Change. We identify difficulties in their alternative path analysis in which they attempt to relate age-related loss of integrity of white matter to Changes in general intelligence. We then comment on their general criticisms and their viewpoints concerning use of path analysis.
Joann E Manson - One of the best experts on this subject based on the ideXlab platform.
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dietary fat types and 4 year Cognitive Change in community dwelling older women
Annals of Neurology, 2012Co-Authors: Olivia I Okereke, Joann E Manson, Bernard Rosner, Dae Hyun Kim, Jae H Kang, Nancy R CookAbstract:Objective To relate dietary fat types to Cognitive Change in healthy community-based elders.
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vitamin e vitamin c beta carotene and Cognitive function among women with or at risk of cardiovascular disease the women s antioxidant and cardiovascular study
Circulation, 2009Co-Authors: Jae H Kang, Joann E Manson, Nancy R Cook, Julie E Buring, Christine M Albert, Francine GrodsteinAbstract:Background—Cardiovascular factors are associated with Cognitive decline. Antioxidants may be beneficial. Methods and Results—The Women’s Antioxidant Cardiovascular Study was a trial of vitamin E (402 mg every other day), beta carotene (50 mg every other day), and vitamin C (500 mg daily) for the secondary prevention of cardiovascular disease. From 1995 to 1996, women 40 years of age with cardiovascular disease or 3 coronary risk factors were randomized. From 1998 to 1999, a Cognitive function substudy was initiated among 2824 participants 65 years of age. With 5 Cognitive tests, cognition was assessed by telephone 4 times over 5.4 years. The primary outcome was a global composite score averaging all scores; repeated-measures analyses were used to examine Cognitive Change over time. Vitamin E supplementation and beta carotene supplementation were not associated with slower rates of Cognitive Change (mean difference in Change for vitamin E versus placebo, 0.01; 95% confidence interval, 0.05 to 0.04; P0.78; for beta carotene, 0.03; 95% confidence interval, 0.02 to 0.07; P0.28). Although vitamin C supplementation was associated with better performance at the last assessment (mean difference, 0.13; 95% confidence interval, 0.06 to 0.20; P0.0005), it was not associated with Cognitive Change over time (mean difference in Change, 0.02; 95% confidence interval, 0.03 to 0.07; P0.39). Vitamin C was more protective against Cognitive Change among those with new cardiovascular events during the trial (P for interaction0.009). Conclusions—Antioxidant supplementation did not slow Cognitive Change among women with preexisting cardiovascular disease or cardiovascular disease risk factors. A possible late effect of vitamin C or beta carotene among those with low dietary intake on cognition warrants further study. (Circulation. 2009;119:2772-2780.)
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vitamin e vitamin c beta carotene and Cognitive function among women with or at risk of cardiovascular disease the women s antioxidant and cardiovascular study
Circulation, 2009Co-Authors: Jae H Kang, Joann E Manson, Nancy R Cook, Julie E Buring, Christine M Albert, Francine GrodsteinAbstract:Background— Cardiovascular factors are associated with Cognitive decline. Antioxidants may be beneficial. Methods and Results— The Women’s Antioxidant Cardiovascular Study was a trial of vitamin E (402 mg every other day), beta carotene (50 mg every other day), and vitamin C (500 mg daily) for the secondary prevention of cardiovascular disease. From 1995 to 1996, women ≥40 years of age with cardiovascular disease or ≥3 coronary risk factors were randomized. From 1998 to 1999, a Cognitive function substudy was initiated among 2824 participants ≥65 years of age. With 5 Cognitive tests, cognition was assessed by telephone 4 times over 5.4 years. The primary outcome was a global composite score averaging all scores; repeated-measures analyses were used to examine Cognitive Change over time. Vitamin E supplementation and beta carotene supplementation were not associated with slower rates of Cognitive Change (mean difference in Change for vitamin E versus placebo, −0.01; 95% confidence interval, −0.05 to 0.04; ...
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a randomized trial of vitamin e supplementation and Cognitive function in women
JAMA Internal Medicine, 2006Co-Authors: Jae H Kang, Joann E Manson, Nancy R Cook, Julie E Buring, Francine GrodsteinAbstract:Methods: The Women’s Health Study is a randomized, double-blind, placebo-controlled trial of vitamin E supplementation (600 IU [-tocopherol acetate], on alternate days) begun between 1992 and 1995 among 39 876 healthy US women. From 1998, 6377 women 65 years or older participated in a Cognitive substudy. Three Cognitive assessments of general cognition, verbal memory, and category fluency were administered by telephone at 2-year intervals. The primary outcome was a global composite score averaging performance on all tests. Repeated measures analyses were conducted to examine mean performance and mean differences in Cognitive Change, and logistic regression was used to estimate relative risks of substantial decline. Results: There were no differences in global score between the vitamin E and placebo groups at the first assessment (5.6 years after randomization: mean difference, �0.01; 95% confidence interval [CI], �0.04 to 0.03) or at the last assessment (9.6 years of treatment: mean difference, 0.00; 95% CI, �0.04 to 0.04). Mean Cognitive Change over time was also similar in the vitamin E group compared with the placebo group for the global score (mean difference in Change, 0.02; 95% CI, �0.01 to 0.05; P=.16). The relative risk of substantial decline in the global score in the vitamin E group compared with the placebo group was 0.92 (95% CI, 0.77 to 1.10). Conclusion: Long-term use of vitamin E supplements did not provide Cognitive benefits among generally healthy older women. Arch Intern Med. 2006;166:2462-2468
Philip Benjamin - One of the best experts on this subject based on the ideXlab platform.
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diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to Cognitive Change
NeuroImage: Clinical, 2017Co-Authors: Owen A Williams, Christian Lambert, Philip Benjamin, Eva Zeestraten, Andrew D. Mackinnon, Hugh S Markus, Andrew J Lawrence, Robin G Morris, Rebecca A Charlton, Thomas R BarrickAbstract:Cerebral small vessel disease (SVD) is the primary cause of vascular Cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe Cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related Changes in a single unitary score across the whole cerebrum, to investigate its relationship with Cognitive Change over a three-year period. 98 patients (aged 43-89) with SVD underwent annual MRI scanning and Cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain Change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain Change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to Change in EF and IPS (p < 0.001) and remained significant in multivariate models including other MRI markers of SVD as well as age, gender and premorbid IQ. Of the conventional markers, presence of new lacunes was the only marker to remain a significant predictor of Change in EF and IPS in the multivariate models (p = 0.002). Change in DSEG θ was also related to Change in all other MRI markers (p < 0.017), suggesting it may be used as a surrogate marker of SVD damage across the cerebrum. Sample size estimates indicated that fewer patients would be required to detect treatment effects using DSEG θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain Change in SVD that has a negative impact on cognition and remains a significant predictor of Cognitive Change when other MRI markers of brain Change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural Changes and successfully predicts Cognitive Change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).
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diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to Cognitive Change
NeuroImage: Clinical, 2017Co-Authors: Owen A Williams, Christian Lambert, Philip Benjamin, Eva Zeestraten, Andrew D. Mackinnon, Hugh S Markus, Andrew J Lawrence, Robin G Morris, Rebecca A Charlton, Thomas R BarrickAbstract:Abstract Cerebral small vessel disease (SVD) is the primary cause of vascular Cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe Cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related Changes in a single unitary score across the whole cerebrum, to investigate its relationship with Cognitive Change over a three-year period. 98 patients (aged 43–89) with SVD underwent annual MRI scanning and Cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain Change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain Change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to Change in EF and IPS ( p p = 0.002). Change in DSEG θ was also related to Change in all other MRI markers ( p θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain Change in SVD that has a negative impact on cognition and remains a significant predictor of Cognitive Change when other MRI markers of brain Change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural Changes and successfully predicts Cognitive Change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).
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progression of mri markers in cerebral small vessel disease sample size considerations for clinical trials
Journal of Cerebral Blood Flow and Metabolism, 2016Co-Authors: Philip Benjamin, Bhavini Patel, Christian Lambert, Eva Zeestraten, Owen A Williams, Andrew D. Mackinnon, Thomas R Barrick, Irina Chis Ster, Andrew J Lawrence, Hugh S MarkusAbstract:Detecting treatment efficacy using Cognitive Change in trials of cerebral small vessel disease (SVD) has been challenging, making the use of surrogate markers such as magnetic resonance imaging (MR...
Owen A Williams - One of the best experts on this subject based on the ideXlab platform.
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profiles of Cognitive Change in preclinical and prodromal alzheimer s disease using Change point analysis
Journal of Alzheimer's Disease, 2020Co-Authors: Owen A Williams, Luigi Ferrucci, Nicole M Armstrong, Melissa H Kitnertriolo, Susan M ResnickAbstract:Background Alzheimer's disease (AD) is now understood to have a long preclinical phase in which pathology starts to accumulate in the absence of clinical symptoms. Identifying the temporal stages of accelerated Cognitive decline in this phase may help in developing more sensitive neuropsychological tools for early screening of preclinical Cognitive decline. Change-point analyses are increasingly used to characterize the temporal stages of accelerated Cognitive decline in the preclinical stages of AD. However, statistical comparisons of Change-points between specific Cognitive measures have not been reported. Objective To characterize and compare the temporal stages of accelerated decline in performance on multiple Cognitive tests in a sample of participants from the Baltimore Longitudinal Study on Aging (BLSA) who later developed AD. Methods 165 older adults (baseline age range: 61.1-91.2) from the BLSA developed AD during follow-up. Linear and non-linear mixed models were fit for 11 Cognitive measures to determine Change-points in rates of decline before AD diagnosis. Bootstrapping was used to compare the timing of Change-points across Cognitive measures. Results Change-points followed by accelerated decline ranged from 15.5 years (Standard Error (S.E.) = 1.72) for Card Rotations to 1.9 years (S.E. = 0.68) for the Trail-Making Test Part A before AD diagnosis. Accelerated decline in Card Rotations occurred significantly earlier than all other measures, including learning and memory measures. Conclusion Results suggest that visuospatial ability, as assessed by Card Rotations, may have the greatest utility as an early predictive tool in identifying preclinical AD.
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profiles of Cognitive Change in preclinical alzheimer s disease using Change point analysis
medRxiv, 2019Co-Authors: Owen A Williams, Luigi Ferrucci, Nicole M Armstrong, Melissa H Kitnertriolo, Susan M ResnickAbstract:Abstract Introduction Change-point analyses are increasingly used to identify the temporal stages of accelerated Cognitive decline in the preclinical stages of Alzheimer’s Disease (AD). However, statistical comparisons of Change-points between specific Cognitive measures have not been reported. Methods 165 older adults (baseline age range: 61.1-91.2) from the Baltimore Longitudinal Study of Aging developed AD during follow-up. Linear and non-linear mixed models were fit for 11 Cognitive measures to determine Change-points in rates of decline before AD diagnosis. Bootstrapping was used to compare the timing of Change-points across Cognitive measures. Results Change-points followed by accelerated decline ranged from 15.5 years (Card Rotations) to 1.9 years (Trail-Making A) before AD diagnosis. Accelerated decline in Card Rotations occurred significantly earlier than all other measures, including learning and memory measures. Discussion Results suggest that visuospatial ability, as assessed by Card Rotations, may have the greatest utility as an early predictive tool in identifying preclinical AD.
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diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to Cognitive Change
NeuroImage: Clinical, 2017Co-Authors: Owen A Williams, Christian Lambert, Philip Benjamin, Eva Zeestraten, Andrew D. Mackinnon, Hugh S Markus, Andrew J Lawrence, Robin G Morris, Rebecca A Charlton, Thomas R BarrickAbstract:Cerebral small vessel disease (SVD) is the primary cause of vascular Cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe Cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related Changes in a single unitary score across the whole cerebrum, to investigate its relationship with Cognitive Change over a three-year period. 98 patients (aged 43-89) with SVD underwent annual MRI scanning and Cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain Change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain Change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to Change in EF and IPS (p < 0.001) and remained significant in multivariate models including other MRI markers of SVD as well as age, gender and premorbid IQ. Of the conventional markers, presence of new lacunes was the only marker to remain a significant predictor of Change in EF and IPS in the multivariate models (p = 0.002). Change in DSEG θ was also related to Change in all other MRI markers (p < 0.017), suggesting it may be used as a surrogate marker of SVD damage across the cerebrum. Sample size estimates indicated that fewer patients would be required to detect treatment effects using DSEG θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain Change in SVD that has a negative impact on cognition and remains a significant predictor of Cognitive Change when other MRI markers of brain Change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural Changes and successfully predicts Cognitive Change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).
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diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to Cognitive Change
NeuroImage: Clinical, 2017Co-Authors: Owen A Williams, Christian Lambert, Philip Benjamin, Eva Zeestraten, Andrew D. Mackinnon, Hugh S Markus, Andrew J Lawrence, Robin G Morris, Rebecca A Charlton, Thomas R BarrickAbstract:Abstract Cerebral small vessel disease (SVD) is the primary cause of vascular Cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe Cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related Changes in a single unitary score across the whole cerebrum, to investigate its relationship with Cognitive Change over a three-year period. 98 patients (aged 43–89) with SVD underwent annual MRI scanning and Cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain Change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain Change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to Change in EF and IPS ( p p = 0.002). Change in DSEG θ was also related to Change in all other MRI markers ( p θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain Change in SVD that has a negative impact on cognition and remains a significant predictor of Cognitive Change when other MRI markers of brain Change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural Changes and successfully predicts Cognitive Change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).
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progression of mri markers in cerebral small vessel disease sample size considerations for clinical trials
Journal of Cerebral Blood Flow and Metabolism, 2016Co-Authors: Philip Benjamin, Bhavini Patel, Christian Lambert, Eva Zeestraten, Owen A Williams, Andrew D. Mackinnon, Thomas R Barrick, Irina Chis Ster, Andrew J Lawrence, Hugh S MarkusAbstract:Detecting treatment efficacy using Cognitive Change in trials of cerebral small vessel disease (SVD) has been challenging, making the use of surrogate markers such as magnetic resonance imaging (MR...
