scholarly journals A Role for New Brain Magnetic Resonance Imaging Modalities in Daily Clinical Practice: Protocol of the Prediction of Cognitive Recovery After Stroke (PROCRAS) Study (Preprint)

2017 ◽  
Author(s):  
Hugo P Aben ◽  
Yael D Reijmer ◽  
Johanna MA Visser-Meily ◽  
Jacoba M Spikman ◽  
Jeroen de Bresser ◽  
...  

BACKGROUND Cognitive impairment is common after acute ischemic stroke, affecting up to 75% of the patients. About half of the patients will show recovery, whereas the others will remain cognitively impaired or deteriorate. It is difficult to predict these different cognitive outcomes. OBJECTIVE The objective of this study is to investigate whether diffusion tensor imaging–based measures of brain connectivity predict cognitive recovery after 1 year, in addition to patient characteristics and stroke severity. A specific premise of the Prediction of Cognitive Recovery After Stroke (PROCRAS) study is that it is conducted in a daily practice setting. METHODS The PROCRAS study is a prospective, mono-center cohort study conducted in a large teaching hospital in the Netherlands. A total of 350 patients suffering from an ischemic stroke who screen positive for cognitive impairment on the Montreal Cognitive Assessment (MoCA<26) in the acute stage will undergo a 3Tesla-Magnetic Resonance Imaging (3T-MRI) with a diffusion-weighted sequence and a neuropsychological assessment. Patients will be classified as being unimpaired, as having a mild vascular cognitive disorder, or as having a major vascular cognitive disorder. One year after stroke, patients will undergo follow-up neuropsychological assessment. The primary endpoint is recovery of cognitive function 1 year after stroke in patients with a confirmed poststroke cognitive disorder. The secondary endpoint is deterioration of cognitive function in the first year after stroke. RESULTS The study is already ongoing for 1.5 years, and thus far, 252 patients have provided written informed consent. Final results are expected in June 2019. CONCLUSIONS The PROCRAS study will show the additional predictive value of diffusion tensor imaging-based measures of brain connectivity for cognitive outcome at 1 year in patients with a poststroke cognitive disorder in a daily clinical practice setting. REGISTERED REPORT IDENTIFIER RR1-10.2196/9431

Stroke ◽  
2021 ◽  
Author(s):  
Hugo P. Aben ◽  
Leonie De Munter ◽  
Yael D. Reijmer ◽  
Jacoba M. Spikman ◽  
Johanna M.A. Visser-Meily ◽  
...  

Background and Purpose: Prediction of long-term recovery of a poststroke cognitive disorder (PSCD) is currently inaccurate. We assessed whether diffusion-weighted imaging (DWI)–based measures of brain connectivity predict cognitive recovery 1 year after stroke in patients with PSCD in addition to conventional clinical, neuropsychological, and imaging variables. Methods: This prospective monocenter cohort study included 217 consecutive patients with a clinical diagnosis of ischemic stroke, aged ≥50 years, and Montreal Cognitive Assessment score below 26 during hospitalization. Five weeks after stroke, patients underwent DWI magnetic resonance imaging. Neuropsychological assessment was performed 5 weeks and 1 year after stroke and was used to classify PSCD as absent, modest, or marked. Cognitive recovery was operationalized as a shift to a better PSCD category over time. We evaluated 4 DWI-based measures of brain connectivity: global network efficiency and mean connectivity strength, both weighted for mean diffusivity and fractional anisotropy. Conventional predictors were age, sex, level of education, clinical stroke characteristics, neuropsychological variables, and magnetic resonance imaging findings (eg, infarct size). DWI-based measures of brain connectivity were added to a multivariable model to assess additive predictive value. Results: Of 135 patients (mean age, 71 years; 95 men [70%]) with PSCD 5 weeks after ischemic stroke, 41 (30%) showed cognitive recovery. Three of 4 brain connectivity measures met the predefined threshold of P <0.1 in univariable regression analysis. There was no added value of these measures to a multivariable model that included level of education and infarct size as significant predictors of cognitive recovery. Conclusions: Current DWI-based measures of brain connectivity appear to predict recovery of PSCD but at present have no added value over conventional predictors.


2019 ◽  
Vol 11 (3) ◽  
pp. 26-34 ◽  
Author(s):  
A. A. Kulesh ◽  
V. E. Drobakha ◽  
K. V. Sobyanin ◽  
S. P. Kulikova ◽  
A. Yu. Bykova ◽  
...  

Fractional anisotropy (FA) estimated using diffusion tensor magnetic resonance imaging (dMRI) is considered as a promising biomarker in ischemic stroke (IS). The basis of this study is the assumption that the assessment of FA indices for different white matter tracts will be able to predict the main aspects of the rehabilitation potential even without determining the structural and functional bases of these influences.Objective: to study the diagnostic significance of changes in FA indices to assess various aspects of the rehabilitation potential in acute IS.Patients and methods. Examinations were made in 100 patients with IS and in 10 individuals without stroke and cognitive impairment. All the patients underwent dMRI and assessments of rehabilitation potential indicators on days 3 and 10 of the disease and at discharge.Results and discussion. The indices of FA of the ipsilateral upper longitudinal and cingulum bundles, FA and the size of an infarct focus, asymmetry of FA of the cingulum bundle (rFA), corticospinal tract (at the level of the knee of the internal capsule and bridge) and the anterior limb of the internal capsule, as well as the FA of the splenium and knee of the internal capsule of the intact hemisphere are of the most value for the functional outcome of acute IS. The microstructure of these zones determines the state of most rehabilitation domains. With respect to global outcome, the integrity of the associative tracts of the affected hemisphere is more valuable than the microstructure of the intact hemisphere and rFA. The tracts of the intact hemisphere are of particular importance for the restoration of complex rehabilitation spheres, such as cognitive status and daily living and social skills, which is necessary to ensure patient independence.Conclusion. The FA indices of the tracts under study seem to be a clinically acceptable biomarker of various aspects of the rehabilitation potential in acute IS. 


2021 ◽  
Author(s):  
Federica Ribaldi ◽  
Christian Chicherio ◽  
Daniele Altomare ◽  
Marta Martins ◽  
Szymon Tomczyk ◽  
...  

Abstract BACKGROUND. Subjective cognitive decline (SCD) is the subjective perception of a decline in memory and/or other cognitive functions in the absence of objective evidence. Some SCD individuals however may suffer from very early stages of neurodegenerative diseases (such as Alzheimer’s disease, AD), minor psychiatric conditions, neurological, and/or somatic comorbidities. Even if a theoretical framework has been established, the etiology of SCD remains far from elucidated. Clinical observations recently lead to the hypothesis that patients with incipient AD may have overestimated metacognitive judgements of their own cognitive performance, while psychiatric patients typically present underestimated metacognitive judgements. Moreover, brain connectivity changes are known correlates of AD and psychiatric conditions, and might be used as biomarkers to discriminate SCD patients of different etiologies. The aim of the COSCODE study is to identify metacognition, connectivity, behavioural, and biomarker profiles associated with different etiologies of SCD. Here we present its rationale and study design.METHODS. COSCODE is an observational, longitudinal (4 years), prospective clinical cohort study involving 120 SCD, and 80 control subjects (40 persons with no cognitive impairment, and 40 mild cognitive impairment - MCI, or dementia patients), all of which will undergo 3T and 7T diffusion magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) as well as behavioural and biomarker assessments at baseline and after 1 and 2 years. Both hypothesis-driven and data-driven cluster analysis approaches will be used to identify SCD sub-types based on metacognition, connectivity, behavioural and biomarkers features.CONCLUSION. COSCODE will allow defining and interpreting the constellation of signs and symptoms associated with different etiologies of SCD, paving the way to the development of cost-effective risk assessment and prevention protocols.


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