Name: Segmentation of the Choroid Plexus Using Manual Delineations
Uploaded: 2023-12-15T12:40:00
Description: Watch this Scientific Journal Video about Segmentation of the Choroid Plexus Using Manual Delineations at JoVE.com

segmentation of the choroid plexus using manual delineations

Améliorer l’analyse de la neuroimagerie dans les troubles cérébraux

Choroid plexus function 
The choroid plexus is a highly vascularized structure in the brain consisting of fenestrated capillaries and a monolayer of choroid plexus epithelial cells1. The choroid plexus projects into the lateral, third, and fourth cerebral ventricles and produces cerebrospinal fluid (CSF), which plays an important role in neural patterning2 and brain physiology3,4. The choroid plexus secretes neurovascular substances, encompasses a stem-cell like repository, and acts as a physical barrier to impede the entrance of toxic metabolites, an enzymatic barrier to remove moieties that circumvent the physical barrier, and an immunological barrier to protect against foreign invaders5. The choroid plexus modulates neurogenesis6, synaptic plasticity7, inflammation8, circadian rhythm9,10, gut brain-axis11, and cognition12. Moreover, peripheral cytokines, stress, and infection (including SARS-CoV-2) can disrupt the blood-CSF barrier13,14,15,16. Thus, the choroid plexus-CSF system is integral for neurodevelopment, neurocircuit maturation, brain homeostasis, and repair17. Since immune, inflammatory, metabolic, and enzymatic alterations impact the brain, researchers are using neuroimaging tools to assess the role of the choroid plexus across the lifespan and in brain disorders18,19,20. However, limitations exist in commonly used automated tools for choroid plexus segmentation, such as FreeSurfer, which result in the choroid plexus being poorly segmented. Thus, there is a critical need for ground truth manual segmentation of the choroid plexus that can be used to develop an accurate automated tool for choroid plexus segmentation.
Choroid plexus in neurodevelopment and brain disorders 
The role of the choroid plexus in brain disorders has long been neglected, mainly because it was regarded as a supporting player whose role was to cushion the brain and maintain a proper salt balance2,21. However, the choroid plexus has gained attention as a structure linked to brain disorders such as pain syndromes22, SARS-CoV-216,23,24, neurodevelopmental2, and brain disorders19, suggesting a transdiagnostic effect in the development of behavioral disorders. In neurodevelopmental disorders, choroid plexus cysts were associated with an increased risk of developmental delay, attention-deficit/hyperactivity disorder (ADHD), or autism spectrum disorder (ASD)25,26. Additionally, lateral ventricle choroid plexus volume was found to be increased in patients with ASD27. In brain disorders,choroid plexus abnormalities have been described since 1921 in psychotic disorders28,29. Previous studies have identified choroid plexus enlargement using FreeSurfer segmentation in a large sample of patients with psychotic disorders compared to both their first-degree relatives and controls19. These findings were replicated using manually segmented choroid plexus volume in a large sample of clinical high-risk for psychosis population and found that these patients had larger choroid plexus volume compared to healthy controls30. There are a growing number of studies demonstrating choroid plexus enlargement in complex regional pain syndrome22, stroke31, multiple sclerosis20,32, Alzheimer&#39;s33,34, and depression35, with some demonstrating a link between peripheral and brain immune/inflammatory activity. These neuroimaging studies are promising; however, poor lateral ventricle choroid plexus segmentation by FreeSurfer21 limits the trustworthiness of automated choroid plexus volume estimation. As a result, studies in multiple sclerosis20,32, depression35, Alzheimer&#39;s34, and early psychosis36 have begun manually segmenting the lateral ventricle choroid plexus, but there are no current guidelines for how to do this, nor is their guidance on segmenting the third and fourth ventricle choroid plexus.
Common segmentation tools exclude the choroid plexus 
Brain segmentation pipelines such as FreeSurfer37,38,39, FMRIB Software Library (FSL)40, SLANT41, and FastSurfer (developed by the co-author Martin Reuter)42,43, accurately and reliably segment cortical and subcortical structures employing atlas-based (FSL), atlas- and surface-based (FreeSurfer), and deep learning segmentation paradigms (SLANT and FastSurfer). Weaknesses of some of these approaches include processing speed, limited generalization to different scanners, field strengths and voxel sizes37,44, and forced alignment of the label map in a standard atlas space. However, the capability to segment the choroid plexus and the compatibility with high-resolution MRI is only addressed by FreeSurfer and FastSurfer. The neural networks behind FastSurfer, are trained on FreeSurfer choroid plexus labels, so they inherit FreeSurfer&#39;s previously discussed reliability and coverage limitations, with the third and fourth ventricles being ignored21. Current limitations for high-resolution MRI also exist, but FreeSurfer&#39;s high-resolution stream45 and FastSurferVINN43 can be used to handle this issue.
Current choroid plexus segmentation tools 
There is only one freely available segmentation tool for the choroid plexus, but segmentation accuracy is limited. Accurate choroid plexus segmentation can be impacted by a variety of factors, including (1) variability in choroid plexus location (spatially non-stationary) due to its location within the ventricles, (2) differences in voxel intensity, contrast, resolution (within-structure heterogeneity) due to cellular heterogeneity, dynamic choroid plexus function, pathological changes, or partial volume effects, (3) age- or pathology-related ventricular size differences impacting choroid plexus size, and (4) proximity to adjacent subcortical structures (hippocampus, amygdala, caudate, and cerebellum), which are also difficult to segment. Given these challenges, FreeSurfer segmentations often under or over-estimate, mislabel or ignore the choroid plexus.
Three recent publications addressed the gap of reliable choroid plexus segmentation with a Gaussian Mixture Model (GMM)46, an Axial-MLP47, and U-Net-based deep learning approaches48. Each model was trained and evaluated using private, manually labeled datasets of at most 150 subjects with a limited diversity of scanners, sites, demographics, and disorders. While these publications46,48,49 achieved significant improvements over FreeSurfer&#39;s choroid plexus segmentation - sometimes doubling the intersection of prediction and ground truth, neither method is (1) validated in high-resolution MRI, (2) has dedicated generalization and reliability analyses, (3) features large representative training and testing datasets, (4) specifically addresses or analyzes choroid plexus segmentation challenges such as partial volume effects, or (5) is publicly available as a ready-to-use tool. Thus, the current &#34;gold standard&#34; for choroid plexus segmentation is manual tracing, e.g., using 3D Slicer50 or ITK-SNAP51, which has not been previously described and has been a major challenge for researchers wishing to examine the role of the choroid plexus in their studies. 3D Slicer was chosen for manual segmentation due to the author&#39;s familiarity with the software and because it provides the user with various tools based on different approaches that can be combined to obtain the desired result. Other tools can be used, such as ITK-SNAP, which is primarily oriented on image segmentation, and once the tool is mastered, good results can be obtained by the user. Additionally, the authors have conducted a case-control study demonstrating the high accuracy and reliability of their manual segmentation technique using 3D Slicer30, and that specific methodology is described herein.

Pleins feux sur l’auteur : Combler les lacunes en anatomie et établir une base pour les études algorithmiques 

Segmentation manuelle du plexus choroïde humain à l’aide de l’IRM cérébrale

We aim to establish an accessible and standardized protocol for manually segmenting the choroid plexus within the lateral third and fourth ventricles of the brain. We hope to address any common questions or problems that can arise when manually segmenting the choroid plexus, especially considering the complex nature of its location within the brain. Developing this protocol will lead to the creation of a large enough data set consisting of ground truth segmentation maps that we can then use to train and develop algorithms that can accurately and automatically segment the choroid plexus.In the future, this will lead to studies that investigate the role of the choroid plexus within various neurologic and neuropsychiatric disorders.

Watch this Scientific Journal Video about Segmentation of the Choroid Plexus Using Manual Delineations at JoVE.com

Segmentation of the Choroid Plexus Using Manual Delineations  

Segmentation du plexus choroïde à l’aide de délimitations manuelles

Pour commencer, importez l’imagerie numérique et les communications en médecine ou les données DICOM en cliquant sur le bouton DCM situé dans le coin supérieur gauche de la barre d’outils et en cliquant sur le bouton d’importation de fichiers DICOM. Pour régler la luminosité d’une image, cliquez sur Ajuster la fenêtre et le niveau de volume ou cliquez avec le bouton gauche de la souris sur l’image et faites glisser la souris vers le haut ou vers le bas. Cliquez ensuite avec le bouton gauche de la souris sur la tranche d’image et déplacez la souris vers la gauche ou la droite pour ajuster le contraste.Référez-vous aux noyaux de matière grise profonde ou aux barres d’échelle de contraste de l’intensité du signal et assurez-vous qu’elle reste cohérente tout au long de la segmentation pour choisir le contraste approprié pour le plexus choroïde. Pour démarrer la segmentation du plexus choroïde latéral des troisième et quatrième ventricules, sélectionnez l’éditeur de segments dans le menu déroulant du module. Cliquez maintenant sur le menu déroulant de la segmentation pour sélectionner différentes segmentations et renommer celle sélectionnée.Utilisez la liste déroulante du volume principal et sélectionnez les ensembles NIfTI ou DICOM qui doivent être modifiés. Cliquez deux fois sur le bouton d’ajout pour inclure deux segments pour le plexus choroïde du ventricule latéral. Double-cliquez sur leurs titres et renommez-les plexus choroïde du ventricule latéral droit et plexus choroïde du ventricule latéral gauche.Cliquez à nouveau sur le bouton d’ajout pour introduire des segments pour le plexus choroïde des troisième et quatrième ventricules. Ensuite, renommez-les respectivement le troisième plexus choroïde ventriculaire et le plexus choroïde du quatrième ventricule. Commencez par le plexus choroïde du ventricule latéral dans le plan axial et assurez-vous de positionner les images en fonction de la ligne bicommissurale.Utilisez le trigonum collatéral comme point de référence pour localiser le plexus choroïde du ventricule latéral. Pour démarrer la segmentation manuelle, sélectionnez l’outil de peinture ou de dessin situé dans la section des effets de l’éditeur de segments. Lors de l’utilisation de l’outil de peinture, sélectionnez le diamètre de pinceau souhaité pour la peinture.Utilisez le niveau du noyau rouge pour déterminer quand arrêter de segmenter le plexus choroïde dans les ventricules latéraux. Pour localiser le plexus choroïde du troisième ventricule, commencez dans le plan sagittal et utilisez le foramen de Monro, le fornix, le corps calleux, le thalamus et la veine cérébrale interne comme points de repère. De même, pour le plexus choroïde du quatrième ventricule, commencez dans le plan sagittal et utilisez le pédoncule cérébelleux supérieur, le pont et la moelle épinière comme points de référence pour localiser le plexus choroïde dans le quatrième ventricule.Dans le menu déroulant des modules, accédez à Quantification et sélectionnez Statistiques de segment. Ensuite, dans la section d’entrée, sélectionnez la carte de segmentation nouvellement créée pour la quantification sous l’outil de segmentation et sélectionnez le volume IRM dans le volume du détartreur. Pour la table de sortie, sélectionnez l’option de table sous Sortie et appuyez sur Appliquer.Un tableau affichant le volume du plexus choroïde en différentes unités apparaîtra. Cliquez sur le bouton d’enregistrement situé dans la partie supérieure gauche de la barre d’outils pour stocker les fichiers générés. Conservez les fichiers de segmentation dans les formats nrrd, nii.GZ, ou TSV.

Research

JoVE Journal

Neuroscience

Segmentation of the Choroid Plexus Using Manual Delineations

Manual Segmentation of the Human Choroid Plexus Using Brain MRI

The choroid plexus has been implicated in neurodevelopment and a range of brain disorders. Evidence demonstrates that the choroid plexus is critical for ...