Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding

White matter hyperintensities (WMH) or white matter lesions exhibit high variability in their characteristics both at population- and subject-level, making their detection a challenging task. Population-level factors such as age, vascular risk factors and neurodegenerative diseases affect lesion load and spatial distribution. At the individual level, WMH vary in contrast, amount and distribution in different white matter regions. In this work, we aimed to improve BIANCA, the FSL tool for WMH segmentation, in order to better deal with these sources of variability. We worked on two stages of BIANCA by improving the lesion probability map estimation (classification stage) and making the lesion probability map thresholding stage automated and adaptive to local lesion probabilities. Firstly, in order to take into account the effect of population-level factors, we included population-level lesion probabilities, modelled with respect to a parametric factor (e.g. age), in the classification stage. Secondly, we tested BIANCA performance when using four alternative classifiers commonly used in the literature with respect to K-nearest neighbour algorithm (currently used for lesion probability map estimation in BIANCA). Finally, we propose LOCally Adaptive Threshold Estimation (LOCATE), a supervised method for determining optimal local thresholds to apply to the estimated lesion probability map, as an alternative option to global thresholding (i.e. applying the same threshold to the entire lesion probability map). For these experiments we used data from a neurodegenerative cohort, a vascular cohort and the cohorts available publicly as a part of a segmentation challenge. We observed that including population-level parametric lesion probabilities with respect to age and using alternative machine learning techniques provided negligible improvement. However, LOCATE provided a substantial improvement in the lesion segmentation performance, when compared to the global thresholding. It allowed to detect more deep lesions and provided better segmentation of periventricular lesion boundaries, despite the differences in the lesion spatial distribution and load across datasets. We further validated LOCATE on a cohort of CADASIL (Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy) patients, a genetic form of cerebral small vessel disease, and healthy controls, showing that LOCATE adapts well to wide variations in lesion load and spatial distribution

Validation of White Matter Hyperintensities automatic segmentation methods

Treballs finals del Màster de Fonaments de Ciència de Dades, Facultat de matemàtiques, Universitat de Barcelona, Any: 2020, Tutor: Eloi Puertas i Prats i Joaquim Raduà[en] This master’s thesis seeks to review and objectively evaluate the current white matter hyperintensities (WMH) automatic segmentation methods published journals. To this end, the methods have been systematically searched in scientific databases, and those meeting inclusion criteria have been evaluated. The evaluation has consisted in applying the method to detect WMH in our dataset of patients with bipolar disorder and healthy controls, in which an experienced neuroradiologist had manually coded all WMH. After the systematic search, we selected all available methods that were ready for use with standard MRI data by a standard user. Four methods met these criteria. We then applied these methods to detect WMH in our dataset, and compared the results with the neuroradiologist-based ground truth deriving several evaluation metrics. This master’s thesis also include a discussion section, in which we compare the results of our evaluations with the results of the WMH Segmentation Challenge held in 2017, which included substantially different datasets. The most relevant conclusion of this master’s thesis is that no method seems to be accurate enough for clinical implementation, although the low performance of the methods may be related to the differences between our data and the data that were used to train them. Besides, realizing the huge improvement made in the field during the last few years after the appearance of deep neural networks, we anticipate that a method with sufficient accuracy might be available soon. The codes used to obtain the results and graphs displayed in this project together with some guidelines to run them are available through PFM-WMH 1

Comparing lesion segmentation methods in multiple sclerosis: Input from one manually delineated subject is sufficient for accurate lesion segmentation

PURPOSE: Accurate lesion segmentation is important for measurements of lesion load and atrophy in subjects with multiple sclerosis (MS). International MS lesion challenges show a preference of convolutional neural networks (CNN) strategies, such as nicMSlesions. However, since the software is trained on fairly homogenous training data, we aimed to test the performance of nicMSlesions in an independent dataset with manual and other automatic lesion segmentations to determine whether this method is suitable for larger, multi-center studies. METHODS: Manual lesion segmentation was performed in fourteen subjects with MS on sagittal 3D FLAIR images from a 3T GE whole-body scanner with 8-channel head coil. We compared five different categories of automated lesion segmentation methods for their volumetric and spatial agreement with manual segmentation: (i) unsupervised, untrained (LesionTOADS); (ii) supervised, untrained (LST-LPA and nicMSlesions with default settings); (iii) supervised, untrained with threshold adjustment (LST-LPA optimized for current data); (iv) supervised, trained with leave-one-out cross-validation on fourteen subjects with MS (nicMSlesions and BIANCA); and (v) supervised, trained on a single subject with MS (nicMSlesions). Volumetric accuracy was determined by the intra-class correlation coefficient (ICC) and spatial accuracy by Dice's similarity index (SI). Volumes and SI were compared between methods using repeated measures ANOVA or Friedman tests with post-hoc pairwise comparison. RESULTS: The best volumetric and spatial agreement with manual was obtained with the supervised and trained methods nicMSlesions and BIANCA (ICC absolute agreement > 0.968 and median SI > 0.643) and the worst with the unsupervised, untrained method LesionTOADS (ICC absolute agreement = 0.140 and median SI = 0.444). Agreement with manual in the single-subject network training of nicMSlesions was poor for input with low lesion volumes (i.e. two subjects with lesion volumes ≤ 3.0 ml). For the other twelve subjects, ICC varied from 0.593 to 0.973 and median SI varied from 0.535 to 0.606. In all cases, the single-subject trained nicMSlesions segmentations outperformed LesionTOADS, and in almost all cases it also outperformed LST-LPA. CONCLUSION: Input from only one subject to re-train the deep learning CNN nicMSlesions is sufficient for adequate lesion segmentation, with on average higher volumetric and spatial agreement with manual than obtained with the untrained methods LesionTOADS and LST-LPA

Multimodal MRI analysis of the whole brain connectome of apathy in cerebral small vessel disease

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica), Universidade de Lisboa, Faculdade de Ciências, 2019A revolução dos cuidados médicos do século XX e XXI possibilitou, nas últimas décadas, um crescimento sem precedente na esperança média de vida da população global. Porém, independentemente destes avanços na área da saúde, problemas associados ao declínio da função cognitiva permanecem um problema sem solução à vista. Este declínio é comummente associado ao envelhecimento. No entanto, problemas de função cognitiva são consequência de uma miríade de condições que afetam a população ao longo de todas as faixas etárias, com sintomas distintos, com grande variabilidade entre sujeitos. Demência é um termo com uma definição ampla, sendo que é caracterizada pela combinação de sintomas associados ao declínio de função cognitiva, cuja severidade conduz a uma redução de qualidade de vida. Por este motivo, a patofisiologia que conduz a demência é vasta, sendo que a sua progressão está associada a diversos fatores e condições. A segunda causa mais comum de demência é demência vascular, constituindo 15% dos casos diagnosticados (ficando apenas atrás da doença de Alzheimer). Este tipo de demência é definido pela sua associação a uma redução de fluxo nos vasos sanguíneos do cérebro. O maior contribuidor ao desenvolvimento de demência vascular é doença dos pequenos vasos cerebrais. É uma condição caracterizada pela ocorrência de enfartes lacunares, lacunas, espaços periventriculares, microhemorrogias e lesões da matéria branca. Esta condição pode estar associada ao envelhecimento e problemas de hipertensão (forma esporádica) ou pode resultar de uma mutação genética do gene NOTCH3 (forma genética, ou CADASIL). Ambas se demonstram de formas muito semelhantes, sendo que uma idade mais baixa nos pacientes hereditários esta associado a uma patologia mais limpa (com menos prevalência de outras condições) e por isso é encarado como um modelo puro desta doença. Um dos sintomas mais comuns e mais debilitantes da doença dos pequenos vasos cerebrais é apatia. Esta síndrome é definida como uma redução de motivação no comportamento do individuo (quando comparado com o seu passado) e está fortemente associada com a redução de qualidade de vida. Estudos em animais e em humanos saudáveis possibilitaram a compreensão aproximada de quais os mecanismos neurais associados com o comportamento motivado. Estes foram amplamente estudados e é aceite que possa ser caracterizado por três sistemas individuais: o primeiro sistema determina o valor subjetivo do ambiente em termos dos potenciais ganhos hedónicos e custos (sistema que envolve a parte ventral do corpo estriado e o córtex pré-frontal médio); em segundo lugar, um sistema dopaminérgico (com origem na área tegmental ventral do cérebro) atua como mediador para um último sistema que age sobre o ambiente em busca de recompensas positivas (parte dorsal do corpo estriado e a parte média do giro do cíngulo). Embora este mecanismo seja conhecido, não é consensual quais as partes do sistema interrompidas ou danificadas que causam problemas neste comportamento motivado. Sendo uma condição mal estudada, a apatia em doença dos pequenos vasos abre a possibilidade a várias questões – quais as alterações estruturais associadas a apatia? Quais as alterações funcionais? Qual a relação entre as alterações? Poderá o comportamento apático servir como um bom marcador de progressão de demência vascular? Neste sentido, com o objetivo de estudar as alterações e relações entre a estrutura e função do cérebro na presença de apatia, foi criada uma pipeline de analise de ressonância magnética que visa adquirir métricas sobre a integridade da matéria branca, a degeneração de matéria cinzenta e as alterações no reportório de conectividade funcional em duas populações com diagnostico clínico de doença dos pequenos vasos. Para além dos mais, foi também estudada a relação entre as alterações cerebrais e parâmetros de sensibilidade a recompensa e esforço obtidos através da modelação computacional de uma experiência comportamental. No âmbito deste estudo, foram recrutados 19 pacientes com CADASIL (forma hereditária de doença dos pequenos vasos cerebrais). Deste grupo, devido a incapacidade de completar a visita de ressonância, 2 participantes foram excluídos, sendo que 17 pacientes foram incluídos em todo o estudo. Foram também recrutados 104 pacientes com a forma esporádica de doença dos pequenos vasos cerebrais (associada ao envelhecimento e hipertensão). Deste segundo grupo, devido a ruído excessivo na aquisição de imagem ou complicações com o scan aquando a altura da visita, foram apenas incluídos 65 pacientes. A experiência comportamental foi completada por todos os pacientes e requeria que o doente realizasse decisões sequenciais sobre aceitar ou não uma certa recompensa (representada pelo número de maçãs numa árvore desenhada – sendo que cada maçã se traduzia num valor monetário de 1p) em troca de exercer uma certa quantidade de esforço – exercer certo nível de pressão num dinamómetro de mão, até a um máximo de 80% da capacidade máxima voluntária de cada sujeito. Os graus de recompensa e de esforço foram parametricamente controlados, igualmente distribuídos num espaço de 36 condições (6 níveis de recompensa x 6 níveis de esforço) e pseudo-aleatoriamente apresentados aos participantes. Todos os participantes realizaram um bloco de decisões, onde exploraram todo o espaço de condições para treino. Os dados de ressonância magnética foram adquiridos no mesmo scanner, recorrendo ao mesmo protocolo, para que não houvesse qualquer diferença entre os dados de cada participante. Primeiramente, os dados adquiridos foram pré-processados de forma a eliminar a maior quantidade de ruído possível. A primeira análise realizada consistia em comparar a integridade das fibras de matéria branca através dos parâmetros de difusão do fluido que neles se encontra. Mais especificamente, foi utilizada TBSS (tract-based spatial statistics), uma ferramenta integrada no pacote de software FSL, para comparar os valores de anisotropia de difusão das fibras. Seria esperado observar uma redução de anisotropia no grupo de pacientes com apatia face a sua contraparte não apática. Em segundo lugar, os volumes de matéria cinzenta foram comparados, não só com o objetivo de verificar uma redução entre o grupo apático e o grupo não apático, mas também de averiguar se as regiões afetadas por esta redução coincidiam com as regiões de redução de anisotropia das fibras de matéria branca. Esta análise estrutural realizou-se utilizando VBM (voxel-based morphometry). Em último lugar avaliou-se a conectividade funcional. Esta foi aferida de duas abordagens distintas: em primeiro lugar, utilizou-se uma metodologia que não considera a existência de flutuações de conectividade funcional ao longo da aquisição dos dados (dual regression) e uma que tinha por base a relevância da sua flutuação ao longo da aquisição para a compreensão da conectividade funcional (Leading Eigenvector Dynamics Analysis). Todos os modelos estatísticos aplicados foram controlados com covariáveis sem interesse (idade, género e dano causado na matéria branca) e corrigidas para erros de comparações múltiplas. Os nossos resultados fornecem provas de associação entre apatia e redução de integridade da matéria branca em certas regiões (especificamente no corpo caloso e no cíngulo anterior). Por outro lado, mostram também que o comportamento apático está associado a uma redução de volume da matéria cinzenta em regiões do lobo occipital na população de CADASIL, sendo que o mesmo não foi observado na versão esporádica. É interessante constatar que os nossos resultados parecem indicar uma associação entre a integridade da matéria branca e a degeneração da matéria cinzenta. Além do mais, os resultados demonstram enfraquecimento da conectividade funcional. Estas alterações funcionais parecem ser parcialmente derivadas das alterações estruturais, porém, não são totalmente moduladas por estas. Estes resultados não só fortalecem o argumento de que o conectoma funcional não é inteiramente definido pela anatomia cerebral, mas também que métricas de conectividade funcional podem ser marcadores úteis de diagnóstico de doença e podem conduzir a novas aplicações para tratamento de apatia. Embora as suas limitações sejam evidentes (como por exemplo o número reduzido de sujeitos por grupo, resolução do protocolo de imagem) e bastantes ideias tenham ficado por explorar (por exemplo, o impacto da severidade da condição nos conectomas), este estudo é um primeiro exemplo da utilidade da informação obtida aquando do estudo dos conectomas estruturais e funcionais em simultâneo. É também pioneiro na apresentação do conceito de uma rede funcional ligada a um comportamento motivado.Although human studies have identified the neural mechanisms of motivated behaviour, which part of its circuitry is actually being disrupted in disease is not yet well understood. Primarily, the literature has associated apathy with reduced white matter integrity, however, the relationship between structural and functional brain changes hasn’t been studied extensively in apathy. To address this concern, we’ve developed a comprehensive whole-brain magnetic resonance neuroimaging pipeline with which we’ve analysed two populations of cerebral small vessel disease (CADASIL, n = 19; sporadic SVD, n = 104). We’ve looked at the association between apathy and reduced white matter integrity, making use of tract-based spatial statistics; reduced grey matter volume with voxel-based morphometry; and reduced functional connectivity with a novel dynamic approach (Leading Eigenvector Dynamic Analysis). Furthermore, this project then aims at tying the neuroimaging findings with the parameter estimates of reward and effort sensitivity extracted through computational modelling of an effort-based decision-making task. Our results show that apathy is associated with reduced white matter integrity (reduced fractional anisotropy) of specific regions (particularly the corpus callosum and the anterior cingulum). Reduced grey matter volume of the occipital lobe seems to be associated with apathy, despite not being shown by any literature. Moreover, our results indicate that apathetic patients are associated with a weaker and more incoherent repertoire of functional connectivity than their non-apathetic counterparts. Functional connectivity associated with vmPFC regions and the occipital lobe is reduced in apathy. This shows a strong association between structural and functional changes in the brain. Apathetic patients seem to be characterised by a reduction in reward and effort sensitivity, which is associated with impaired functional connectivity. This study is a unique contributor to the understanding of the neural underpinnings of apathy in cerebral small vessel disease due to the uncommon combination of MRI modalities and relation between consequent structural and functional metrics. However, a lot more has to be done to fully understand the mechanisms of this syndrome and to extract clinically useful markers and therapies

Neuroimaging methods for analysing connectivity in the presence of white matter lesions

White Matter Hyperintensities (WMHs) are often observed in the MRI scans of the ageing brain. Previous studies show that the WMH load correlates with cognitive decline, as well as with an increased risk of stroke and dementia. Most of the studies use a global WMH load across the whole brain as the only metric. This thesis proposes new insight into such data by introducing a methodology to analyse the WMH impact on the structural and functional brain connectivity in a localised manner, using white matter tracts. The thesis also supports other studies by exploring the potential impact of WMHs presence on tractography modelling, as well as adapts the method to Multiple Sclerosis (MS) lesion data. In the first part of the thesis, we presented and evaluated two possible measures of the WMHs impact on the WM tracts from the structural perspective. We showed that despite the different distributions of the two measures, both show a similar relationship with the functional connectivity measure. We explored several possible options for quantifying the resting state functional connectivity between the endpoints of the WM tract in the presence of WMHs. We showed that the choice of connectivity measure (full or partial correlation), as well as gray matter parcellation, made a substantial difference in the results. We also observed variability in the results among the tracts and compared our findings to the results from the literature. The majority of this work depends on the correct definition of the white matter tracts. Therefore, the second part of the thesis focuses on evaluating the impact of the presence of WMHs on tractography modelling. Despite changes in the microstructural parameters within the WMHs and their proximity, we found no meaningful alterations in the shape of the WM tracts in the presence of WMHs on the tract. Finally, we explored the possibility to apply some of this methodology to data from patients with Multiple Sclerosis, which is the most common cause of neurological disability in young adults. MS lesions have different aetiology to the WMHs but may have a similar appearance. We showed that directly applying the method between those two conditions may not be possible, and we proposed an alternative approach, suited to the MS data

Development of dementia in older adults : the body-mind connection

Over the past years, two major lines have emerged in the field of dementia research that are focused on: (1) The accurate and early prediction of dementia, and (2) The identification of modifiable factors for dementia prevention. This thesis has contributed to both. We explored the role played by the body-mind connection in cognitive aging by investigating whether motor functioning is a predictor of dementia and if different co-occurring diseases (i.e., multimorbidity [MM] patterns) are risk factors for dementia. We carried out four longitudinal studies, two for each research line, using 12 years of data from SNAC-K, a population-based study involving 3363 older adults, clinically assessed at regular intervals. Study I. Participants with both cognitive and motor dysfunctions demonstrated the highest hazard of developing dementia. After gait speed was added to cognitive assessment, the area under the curve (AUC) increased from 0.69 to 0.83 among the oldest participants. This increase was driven by a reduction in the proportion of false negatives, while the number of false positives (high specificity) remained low. Adding gait speed did not improve the predictive power of the cognitive battery in identifying dementia among younger-old adults. Study II. Individuals with concurrent cognitive and motor decline presented with a mixed and more rapidly evolving brain pathology on magnetic resonance imaging, affecting both gray and white matter. Adults experiencing only cognitive decline had a steeper hippocampal volume loss, whereas those exhibiting only motor decline displayed greater white matter hyperintensity burden. Study III. Individuals belonging to the neuropsychiatric, cardiovascular, and sensory impairment/cancer MM-patterns had the highest hazards of dementia, among those with MM. Inflammation (high C-reactive protein levels) increased dementia hazard within these three patterns, whereas being an APOE ε4-carrier heightened dementia hazard for neuropsychiatric and cardiovascular MM-patterns. Study IV. Exposure to air particulate matter ≤ 2.5μm [PM2.5] was found to increase dementia hazard by up to 50%. The presence of heart diseases (heart failure and ischemic heart disease) further amplified the risk, whereas stroke mediated up to 50% of the PM2.5-dementia association. Conclusions. The findings from these four studies underline the relevance of the body-mind connection in dementia development. An easy-to-obtain motor marker (gait speed) improved the ability of the cognitive test to detect future dementia. This could be explained by the mixed brain pathology, which we found to develop in individuals with fast and concomitant cognitive and motor decline. Specific MM-patterns seemed to increase dementia risk, an effect that was further accentuated by the presence of inflammation and genetic predisposition. Finally, cardiovascular diseases could be important in explaining the relation between PM2.5 and dementia risk. Further exploring the relation between body- and mind- related conditions could be essential in identifying at-risk populations and biomarkers for incipient dementia, and thus, in advancing our understanding of dementia in older adults

Enhancing microstructural specificity in diffusion MRI analysis

Enclosed within a protective bony shell, the human brain poses a significant challenge for direct physical examination. Therefore, non-invasive methods, such as Magnetic Resonance Imaging (MRI), have become very important tools for exploring the brain’s structure and functionality. Nevertheless, these indirect techniques are not without their limitations, notably a lack of specificity. Although they are sensitive to microstructural variations, their capacity to link changes in signals to meaningful biophysical processes is limited. Microstructural modelling has risen to address this problem, offering a means to correlate these otherwise abstract measurements with meaningful biophysical parameters. However, as the complexity of these models, either in terms of geometry or physical properties, improves, so does the number of free parameters required, posing a substantial challenge for reliable parameter estimation. This thesis seeks to address two substantial issues within the field of microstructural modelling of diffusion MRI data. Firstly, it proposes a novel approach to identify the microstructural parameter alterations that can explain observed differences in diffusion MRI between diseased and control group. This approach enables the application of highly specific models without the associated concerns about parameter estimation. Secondly, it advocates for the development of a tool that extracts fibre-specific features from diffusion MRI data in a manner that promotes comparability across different subjects, facilitated by the use of hierarchical Bayesian models. By offering these approaches to analyze diffusion MRI data, this research aims to circumventing the constraints imposed by existing microstructural modeling techniques, thus improve the precision of brain structure diagnosis and comprehension

Equitable modelling of brain imaging by counterfactual augmentation with morphologically constrained 3D deep generative models

We describe CounterSynth, a conditional generative model of diffeomorphic deformations that induce label-driven, biologically plausible changes in volumetric brain images. The model is intended to synthesise counterfactual training data augmentations for downstream discriminative modelling tasks where fidelity is limited by data imbalance, distributional instability, confounding, or underspecification, and exhibits inequitable performance across distinct subpopulations. Focusing on demographic attributes, we evaluate the quality of synthesised counterfactuals with voxel-based morphometry, classification and regression of the conditioning attributes, and the Fréchet inception distance. Examining downstream discriminative performance in the context of engineered demographic imbalance and confounding, we use UK Biobank and OASIS magnetic resonance imaging data to benchmark CounterSynth augmentation against current solutions to these problems. We achieve state-of-the-art improvements, both in overall fidelity and equity. The source code for CounterSynth is available at https://github.com/guilherme-pombo/CounterSynth

Cerebrovascular dysfunction in cerebral small vessel disease

INTRODUCTION: Cerebral small vessel disease (SVD) is the cause of a quarter of all ischaemic strokes and is postulated to have a role in up to half of all dementias. SVD pathophysiology remains unclear but cerebrovascular dysfunction may be important. If confirmed many licensed medications have mechanisms of action targeting vascular function, potentially enabling new treatments via drug repurposing. Knowledge is limited however, as most studies assessing cerebrovascular dysfunction are small, single centre, single imaging modality studies due to the complexities in measuring cerebrovascular dysfunctions in humans. This thesis describes the development and application of imaging techniques measuring several cerebrovascular dysfunctions to investigate SVD pathophysiology and trial medications that may improve small blood vessel function in SVD. METHODS: Participants with minor ischaemic strokes were recruited to a series of studies utilising advanced MRI techniques to measure cerebrovascular dysfunction. Specifically MRI scans measured the ability of different tissues in the brain to change blood flow in response to breathing carbon dioxide (cerebrovascular reactivity; CVR) and the flow and pulsatility through the cerebral arteries, venous sinuses and CSF spaces. A single centre observational study optimised and established feasibility of the techniques and tested associations of cerebrovascular dysfunctions with clinical and imaging phenotypes. Then a randomised pilot clinical trial tested two medications’ (cilostazol and isosorbide mononitrate) ability to improve CVR and pulsatility over a period of eight weeks. The techniques were then expanded to include imaging of blood brain barrier permeability and utilised in multi-centre studies investigating cerebrovascular dysfunction in both sporadic and monogenetic SVDs. RESULTS: Imaging protocols were feasible, consistently being completed with usable data in over 85% of participants. After correcting for the effects of age, sex and systolic blood pressure, lower CVR was associated with higher white matter hyperintensity volume, Fazekas score and perivascular space counts. Lower CVR was associated with higher pulsatility of blood flow in the superior sagittal sinus and lower CSF flow stroke volume at the foramen magnum. Cilostazol and isosorbide mononitrate increased CVR in white matter. The CVR, intra-cranial flow and pulsatility techniques, alongside blood brain barrier permeability and microstructural integrity imaging were successfully employed in a multi-centre observational study. A clinical trial assessing the effects of drugs targeting blood pressure variability is nearing completion. DISCUSSION: Cerebrovascular dysfunction in SVD has been confirmed and may play a more direct role in disease pathogenesis than previously established risk factors. Advanced imaging measures assessing cerebrovascular dysfunction are feasible in multi-centre studies and trials. Identifying drugs that improve cerebrovascular dysfunction using these techniques may be useful in selecting candidates for definitive clinical trials which require large sample sizes and long follow up periods to show improvement against outcomes of stroke and dementia incidence and cognitive function