Optimising 7T MRI perivascular space segmentation to explore brain clearance in Lewy Body disorders
Poster No:
163
Submission Type:
Abstract Submission
Authors:
Eva van Heese1, Max Laansma1, Ashni Ramesar2, Karin van Dijk3, Evelien Lemstra4, Miranda Ringnalda5, Julia de Groot3, Juliette van Alphen4, Odile van den Heuvel6, Ysbrand van der Werf6
Institutions:
1Amsterdam UMC, Amsterdam, NA, 2Amsterdam UMC, Amsterdam, Netherlands, 3Stichting Epilepsie Instellingen Nederland (SEIN), Sleep-Wake Centre, Heemstede, Netherlands, 4Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, Alzheimer Center Amsterdam, Amsterdam, Netherlands, 5Stichting Epilepsie Instellingen Nederland (SEIN), Sleep-Wake Centre, Zwolle, Netherlands, 6Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam, NA
First Author:
Co-Author(s):
Karin van Dijk
Stichting Epilepsie Instellingen Nederland (SEIN), Sleep-Wake Centre
Heemstede, Netherlands
Stichting Epilepsie Instellingen Nederland (SEIN), Sleep-Wake Centre
Heemstede, Netherlands
Evelien Lemstra
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, Alzheimer Center Amsterdam
Amsterdam, Netherlands
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, Alzheimer Center Amsterdam
Amsterdam, Netherlands
Miranda Ringnalda
Stichting Epilepsie Instellingen Nederland (SEIN), Sleep-Wake Centre
Zwolle, Netherlands
Stichting Epilepsie Instellingen Nederland (SEIN), Sleep-Wake Centre
Zwolle, Netherlands
Julia de Groot
Stichting Epilepsie Instellingen Nederland (SEIN), Sleep-Wake Centre
Heemstede, Netherlands
Stichting Epilepsie Instellingen Nederland (SEIN), Sleep-Wake Centre
Heemstede, Netherlands
Juliette van Alphen
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, Alzheimer Center Amsterdam
Amsterdam, Netherlands
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, Alzheimer Center Amsterdam
Amsterdam, Netherlands
Odile van den Heuvel
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences
Amsterdam, NA
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences
Amsterdam, NA
Ysbrand van der Werf
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences
Amsterdam, NA
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences
Amsterdam, NA
Introduction:
REM sleep behaviour disorder (RBD) is characterised by often violent dream enactments, following REM sleep without atonia. RBD is strongly linked to Lewy body diseases, including Parkinson's disease (PD; estimated prevalence of RBD: 30-50%) and dementia with Lewy bodies (DLB; 76%). Perivascular spaces (PVS), surrounding blood vessels, play a role in brain clearance by facilitating the removal of waste, including alpha-synuclein protein accumulations. When enlarged, PVS can be detected and segmented in MR images, as previously done in Parkinson's Disease (Chen et al., 2022; Kim et al., 2024; Ramirez et al., 2022) and Dementia with Lewy Bodies (Choe et al., 2022; Saji et al., 2024). While the mechanisms behind PVS enlargement remain unclear, it is suggested that it may reflect impaired brain clearance and is proposed as a relevant marker in the context of neurodegeneration (Bakker et al., 2016; van Veluw & Perosa, 2022). The current study aimed to optimise the segmentation of MR-visible perivascular spaces on 7T MRI in healthy controls, in preparation for further analysis in Lewy body diseases.
Methods:
Individuals with PD and DLB, as well as healthy controls from the openly available AHEAD dataset (Alkemade et al., 2020) were scanned on a Philips Achieva 7T MRI, with T1-weighted and T2* contrasts acquired using the same multi-echo magnetization-prepared rapid gradient echo (MP2RAGEME) sequence. White matter segmentation was performed on the T1-weighted image using FastSurfer (Henschel et al., 2020), while PVS were identified on the T2*-map using a Frangi filter (Frangi et al., 1998), with parameter optimization based on different sigma ranges, step size, and thresholds utilizing open-source Python code (github.com/hufsaim/pvsseg). The sigma range determines the size of PVS being detected, whereas the step size reflects the incremental progression between sigma values, determining the granularity of the PVS detection. Thresholding functions as a filter to isolate PVS of interest from noise and irrelevant features.
Results:
Initial testing of the Frangi filter for identifying PVS on T2*-map showed variability in PVS segmentation based on different filter parameters, including the sigmas and threshold. Both sigma ranges show very similar results, but the sigma 1-4 with step size 1 shows some more densely packed red regions, emphasising the small-scale structures, compared to the sigma 5-15 with step size 5. These differences between the filter settings are even less visible when the thresholding is increased (see Figure 1). The optimal filter settings were found with a sigma lower bound of 1, upper bound of 4, and steps of 1. Optimal thresholding settings varied by individual and were determined case by case, considering anatomy and imaging quality. This optimal set of parameters together were both sensitive and specific to PVS, based on visual inspection of the data.
·Figure 1
Conclusions:
We have successfully optimized the parameters to apply a Frangi filter for PVS segmentation on this 7T MR dataset of healthy controls. Based on the different Frangi filter settings, we conclude that medium thresholding suppresses subtle differences caused by sigma and step size variations. Moving forward, this method will be applied to the Lewy body diseases cohort (n≈80) to investigate PVS in the context of neurodegeneration. Future analyses will focus on exploring correlations between PVS volume and clinical measures of cognition and sleep, with the goal of understanding the role of enlarged MR-visible PVS in Lewy body diseases.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Modeling and Analysis Methods:
Methods Development
Segmentation and Parcellation 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems
Keywords:
Aging
Cerebro Spinal Fluid (CSF)
Data analysis
Degenerative Disease
HIGH FIELD MR
Segmentation
Sleep
STRUCTURAL MRI
1|2Indicates the priority used for review
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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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Provide references using APA citation style.
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