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Robin Lemmens

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5 papers

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YNICL Journal 2022 Journal Article

Early white matter connectivity and plasticity in post stroke aphasia recovery

Klara Schevenels
Robin Gerrits
Robin Lemmens
Bert De Smedt
Inge Zink
Maaike Vandermosten

A disruption of white matter connectivity is negatively associated with language (recovery) in patients with aphasia after stroke, and behavioral gains have been shown to coincide with white matter neuroplasticity. However, most brain-behavior studies have been carried out in the chronic phase after stroke, with limited generalizability to earlier phases. Furthermore, few studies have investigated neuroplasticity patterns during spontaneous recovery (i.e., not related to a specific treatment) in the first months after stroke, hindering the investigation of potential early compensatory mechanisms. Finally, the majority of previous research has focused on damaged left hemisphere pathways, while neglecting the potential protective value of their right hemisphere counterparts for language recovery. To address these outstanding issues, we present a longitudinal study of thirty-two patients with aphasia (21 males and 11 females, M = 69.47 years, SD = 10.60 years) who were followed up for a period of 1 year with test moments in the acute (1-2 weeks), subacute (3-6 months) and chronic phase (9-12 months) after stroke. Constrained Spherical Deconvolution-based tractography was performed in the acute and subacute phase to measure Fiber Bundle Capacity (FBC), a quantitative connectivity measure that is valid in crossing fiber regions, in the bilateral dorsal arcuate fasciculus (AF) and the bilateral ventral inferior fronto-occipital fasciculus (IFOF). First, concurrent analyses revealed positive associations between the left AF and phonology, and between the bilateral IFOF and semantics in the acute - but not subacute - phase, supporting the dual-stream language model. Second, neuroplasticity analyses revealed a decrease in connection density of the bilateral AF - but not the IFOF - from the acute to the subacute phase, possibly reflecting post stroke white matter degeneration in areas adjacent to the lesion. Third, predictive analyses revealed no contribution of acute FBC measures to the prediction of later language outcomes over and above the initial language scores, suggesting no added value ofthe diffusion measures for languageprediction. Our study provides new insights on (changes in) connectivity of damaged and undamaged language pathways in patients with aphasia in the first months after stroke, as well as if/how such measures are related to language outcomes at different stages of recovery. Individual results are discussed in the light of current frameworks of language processing and aphasia recovery.

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YNICL Journal 2022 Journal Article

Simplified Edinburgh and modified Boston criteria in relation to amyloid PET for lobar intracerebral hemorrhage

Laura Michiels
Laurens Dobbels
Jelle Demeestere
Philippe Demaerel
Koen Van Laere
Robin Lemmens

BACKGROUND: Histopathological evidence of cerebral vascular amyloid β accumulation is the gold standard to diagnose cerebral amyloid angiopathy (CAA). Neuroimaging findings obtained with CT and MRI can suggest the presence of CAA when histopathology is lacking. We explored the role of amyloid PET in patients with lobar intracerebral hemorrhage (ICH) as this may provide molecular evidence for CAA as well. METHODS: In this retrospective, monocenter analysis, we included consecutive patients with non-traumatic lobar ICH who had undergone amyloid PET. We categorized patients according to amyloid PET status and compared demographics and neuroimaging findings. We calculated sensitivity and specificity of the simplified Edinburgh criteria and amyloid PET with probable modified Boston criteria as reference standard, as well as sensitivity and specificity of the simplified Edinburgh and modified Boston criteria with amyloid PET status as molecular marker for presence or absence of CAA. RESULTS: We included 38 patients of whom 24 (63%) were amyloid PET positive. Amyloid PET positive patients were older at presentation (p = 0.004). We observed no difference in prevalence of subarachnoid hemorrhages, fingerlike projections or microbleeds between both groups, but cortical superficial siderosis (p = 0.003) was more frequent in the amyloid PET positive group. In 5 out of 38 patients (13%), the modified Boston criteria were not fulfilled due to young age or concomitant vitamin K antagonist use with INR > 3.0. With the modified Boston criteria as reference standard, there was no difference in sensitivity nor specificity between the simplified Edinburgh criteria and amyloid PET status. With amyloid PET status as reference standard, there was also no difference in sensitivity nor specificity between the simplified Edinburgh and modified Boston criteria. CONCLUSIONS: Amyloid PET was positive in 63% of lobar ICH patients. Under certain circumstances, patients might not be diagnosed with probable CAA according to the modified Boston criteria and in these cases, amyloid PET may be useful. Accuracy to predict CAA based on amyloid PET status did not differ between the simplified Edinburgh and modified Boston criteria.

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YNICL Journal 2022 Journal Article

The role of the hippocampus in statistical learning and language recovery in persons with post stroke aphasia

Klara Schevenels
Laura Michiels
Robin Lemmens
Bert De Smedt
Inge Zink
Maaike Vandermosten

Although several studies have aimed for accurate predictions of language recovery in post stroke aphasia, individual language outcomes remain hard to predict. Large-scale prediction models are built using data from patients mainly in the chronic phase after stroke, although it is clinically more relevant to consider data from the acute phase. Previous research has mainly focused on deficits, i.e., behavioral deficits or specific brain damage, rather than compensatory mechanisms, i.e., intact cognitive skills or undamaged brain regions. One such unexplored brain region that might support language (re)learning in aphasia is the hippocampus, a region that has commonly been associated with an individual's learning potential, including statistical learning. This refers to a set of mechanisms upon which we rely heavily in daily life to learn a range of regularities across cognitive domains. Against this background, thirty-three patients with aphasia (22 males and 11 females, M = 69.76 years, SD = 10.57 years) were followed for 1 year in the acute (1-2 weeks), subacute (3-6 months) and chronic phase (9-12 months) post stroke. We evaluated the unique predictive value of early structural hippocampal measures for short-term and long-term language outcomes (measured by the ANELT). In addition, we investigated whether statistical learning abilities were intact in patients with aphasia using three different tasks: an auditory-linguistic and visual task based on the computation of transitional probabilities and a visuomotor serial reaction time task. Finally, we examined the association of individuals' statistical learning potential with acute measures of hippocampal gray and white matter. Using Bayesian statistics, we found moderate evidence for the contribution of left hippocampal gray matter in the acute phase to the prediction of long-term language outcomes, over and above information on the lesion and the initial language deficit (measured by the ScreeLing). Non-linguistic statistical learning in patients with aphasia, measured in the subacute phase, was intact at the group level compared to 23 healthy older controls (8 males and 15 females, M = 74.09 years, SD = 6.76 years). Visuomotor statistical learning correlated with acute hippocampal gray and white matter. These findings reveal that particularly left hippocampal gray matter in the acute phase is a potential marker of language recovery after stroke, possibly through its statistical learning ability.

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YNIMG Journal 2021 Journal Article

Synaptic density in healthy human aging is not influenced by age or sex: a 11C-UCB-J PET study

Laura Michiels
Aline Delva
June van Aalst
Jenny Ceccarini
Wim Vandenberghe
Mathieu Vandenbulcke
Michel Koole
Robin Lemmens

RATIONALE: C-UCB-J binding were investigated in healthy volunteers over 7 adult decades, assuming that the number of SV2A vesicles per synapse is not influenced by age or sex. METHODS: C-UCB-J binding with age and with sex were investigated by a voxel-based and volume-of-interest (VOI)-based approach, and with and without PVC to assess the contribution of underlying morphology changes upon aging. RESULTS: C-UCB-J SUVR, nor an interaction between aging and sex for this parameter. CONCLUSION: C-UCB-J does not support a cortical decrease of synaptic density with aging, whereas subcortically a small effect with aging in the caudate nucleus was observed. In addition, no association between synaptic density and sex was detected, which allows pooling of datasets of both sexes.

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YNICL Journal 2019 Journal Article

White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts – The MRI-GENIE study

Markus D. Schirmer
Adrian V. Dalca
Ramesh Sridharan
Anne-Katrin Giese
Kathleen L. Donahue
Marco J. Nardin
Steven J.T. Mocking
Elissa C. McIntosh

White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery. In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95; p < 0.01) and Pearson correlation of total brain volume (r = 0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N = 2783) and identify a decrease in total brain volume of -2.4 cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing. Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited.

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