Alterations in Cortical Morphology after Neonatal Stroke: Compensation in the Contralesional Hemisphere?

Harrach, Mariam Al; Rousseau, François; Groeschel, Samuel; Wang, Xiaoyu; Hertz‐Pannier, Lucie; Chabrier, Stéphane; Bohi, Amine; Lefèvre, Julien; Dinomais, Mickaël

doi:10.1002/dneu.22679

Cited by 20 publications

(20 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on a previous study that indicates different outcomes following the side of the lesion, 31 Patients were divided into two groups: patients with lesions in the left hemisphere (LLP) and patients with lesions in the right hemisphere (RLP). In addition to the LLP and RLP patients, we recruited 30 healthy controls (HC).…”

Section: Methodsmentioning

confidence: 99%

A connectome‐based approach to assess motor outcome after neonatal arterial ischemic stroke

Harrach

Pretzel

Groeschel

et al. 2021

Ann Clin Transl Neurol

Self Cite

View full text Add to dashboard Cite

Objective Studies of motor outcome after Neonatal Arterial Ischemic Stroke (NAIS) often rely on lesion mapping using MRI. However, clinical measurements indicate that motor deficit can be different than what would solely be anticipated by the lesion extent and location. Because this may be explained by the cortical disconnections between motor areas due to necrosis following the stroke, the investigation of the motor network can help in the understanding of visual inspection and outcome discrepancy. In this study, we propose to examine the structural connectivity between motor areas in NAIS patients compared to healthy controls in order to define the cortical and subcortical connections that can reflect the motor outcome. Methods Thirty healthy controls and 32 NAIS patients with and without Cerebral Palsy (CP) underwent MRI acquisition and manual assessment. The connectome of all participants was obtained from T1‐weighted and diffusion‐weighted imaging. Results Significant disconnections in the lesioned and contra‐lesioned hemispheres of patients were found. Furthermore, significant correlations were detected between the structural connectivity metric of specific motor areas and manuality assessed by the Box and Block Test (BBT) scores in patients. Interpretation Using the connectivity measures of these links, the BBT score can be estimated using a multiple linear regression model. In addition, the presence or not of CP can also be predicted using the KNN classification algorithm. According to our results, the structural connectome can be an asset in the estimation of gross manual dexterity and can help uncover structural changes between brain regions related to NAIS.

show abstract

Section: Methodsmentioning

confidence: 99%

A connectome‐based approach to assess motor outcome after neonatal arterial ischemic stroke

Harrach

Pretzel

Groeschel

et al. 2021

Ann Clin Transl Neurol

Self Cite

View full text Add to dashboard Cite

show abstract

“…Based on a previous study that indicates different outcomes following the side of the lesion (Harrach et al, 2019), Patients were divided into two groups: patients with lesion in the left hemisphere (LLP) and patients with lesions in the right hemisphere (RLP). In addition to the LLP and RLP patients we recruited 30 healthy controls (HC).…”

Section: Subjectsmentioning

confidence: 99%

A Connectome-Based Approach to Assess Motor Outcome after Neonatal Arterial Ischemic Stroke

Harrach

Pretzel²,

Groeschel³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Studies of motor outcome after Neonatal Arterial Ischemic Stroke (NAIS) often rely on lesion mapping using MRI. However, clinical measurements indicate that motor deficit can be different than what would solely be anticipated by the lesion extent and location. Because, this may be explained by the cortical disconnections between motor areas due to necrosis following the stroke, the investigation of motor network can help in the understanding of this discrepancy between visual inspection and outcome. In this study, we propose to examine the structural connectivity between motor areas in NAIS patients in comparison to healthy controls in order to define the cortical and subcortical connections that are can depict motor outcome. Accordingly, 30 healthy controls and 32 NAIS patients with and without Cerebral Palsy (CP) underwent MRI acquisition and manual assessment. The connectome of all participants was obtained from T1-weigted and diffusion weighted imaging. Results showed significant disconnections in the lesioned as well as the contra-lesioned hemisphere of patients. Furthermore, significant correlations were found between the structural connectivity metric of specific motor areas and manuality assessed by the Box and Block Test (BBT) scores in patients. Using the connectivity measures of these links we were able to estimate the BBT score using a multiple linear regression model. Based on one connection value we were also able to predict the presence or not of CP. According to our results, structural connectome, can be an asset in the estimation of gross manual dexterity after neonatal stroke.

show abstract

“…FreeSurfer 1 is an open source software suite for processing brain MRI images that is commonly used in pediatric neuroimaging ( Ghosh et al, 2010 ; Black et al, 2012 ; Ranger et al, 2013 ; Clark et al, 2014 ; Roos et al, 2014 ; El Marroun et al, 2016 ; Lee et al, 2017 ; Garnett et al, 2018 ; Nwosu et al, 2018 ; Phan et al, 2018b ; Al Harrach et al, 2019 ; Barnes-Davis et al, 2020 ; Boutzoukas et al, 2020 ; Wedderburn et al, 2020 ). The automated FreeSurfer segmentation protocol utilizes surface-based parcellation of cortical regions based on cortical folding patterns and a priori knowledge of anatomical structures (further technical information in Dale et al, 1999 ; Fischl et al, 1999a ).…”

Section: Introductionmentioning

confidence: 99%

Feasibility of FreeSurfer Processing for T1-Weighted Brain Images of 5-Year-Olds: Semiautomated Protocol of FinnBrain Neuroimaging Lab

et al. 2022

View full text Add to dashboard Cite

Pediatric neuroimaging is a quickly developing field that still faces important methodological challenges. Pediatric images usually have more motion artifact than adult images. The artifact can cause visible errors in brain segmentation, and one way to address it is to manually edit the segmented images. Variability in editing and quality control protocols may complicate comparisons between studies. In this article, we describe in detail the semiautomated segmentation and quality control protocol of structural brain images that was used in FinnBrain Birth Cohort Study and relies on the well-established FreeSurfer v6.0 and ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium tools. The participants were typically developing 5-year-olds [n = 134, 5.34 (SD 0.06) years, 62 girls]. Following a dichotomous quality rating scale for inclusion and exclusion of images, we explored the quality on a region of interest level to exclude all regions with major segmentation errors. The effects of manual edits on cortical thickness values were relatively minor: less than 2% in all regions. Supplementary Material cover registration and additional edit options in FreeSurfer and comparison to the computational anatomy toolbox (CAT12). Overall, we conclude that despite minor imperfections FreeSurfer can be reliably used to segment cortical metrics from T1-weighted images of 5-year-old children with appropriate quality assessment in place. However, custom templates may be needed to optimize the results for the subcortical areas. Through visual assessment on a level of individual regions of interest, our semiautomated segmentation protocol is hopefully helpful for investigators working with similar data sets, and for ensuring high quality pediatric neuroimaging data.

show abstract

Alterations in Cortical Morphology after Neonatal Stroke: Compensation in the Contralesional Hemisphere?

Cited by 20 publications

References 42 publications

A connectome‐based approach to assess motor outcome after neonatal arterial ischemic stroke

A connectome‐based approach to assess motor outcome after neonatal arterial ischemic stroke

A Connectome-Based Approach to Assess Motor Outcome after Neonatal Arterial Ischemic Stroke

Feasibility of FreeSurfer Processing for T1-Weighted Brain Images of 5-Year-Olds: Semiautomated Protocol of FinnBrain Neuroimaging Lab

Contact Info

Product

Resources

About