Name: Forfatter Spotlight: Brobygning mellem huller i anatomi og etablering af et fundament for algoritmiske studier
Uploaded: 2023-12-15T12:40:00
Description: Watch this Scientific Journal Video about Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies at JoVE.com

Dette arbejde blev støttet af en National Institute of Mental Health Award R01 MH131586 (til P.L og M.R), R01 MH078113 (til M.K) og et Sydney R Baer Jr Foundation Grant (til P.L).

Den nuværende protokol blev godkendt af Institutional Review Board på Beth Israel Deaconess Medical Center. En rask forsøgsperson med en hjerne-MR-scanning, der var fri for artefakter eller bevægelse, blev brugt til denne protokoldemonstration, og der blev indhentet skriftligt informeret samtykke. En 3,0 T MR-scanner med en 32-kanals hovedspole (se materialetabellen) blev brugt til at erhverve 3D-T1-billeder med en opløsning på 1 mm x 1 mm x 1,2 mm. MP-RAGE ASSET-sekvensen med et synsfelt på 256 x...

Forbedring af neuroimaging-analyse ved hjernesygdomme

Kritiske trin i protokollen Tre kritiske trin kræver særlig opmærksomhed ved gennemførelsen af denne protokol. For det første er kontrol af kvaliteten og kontrasten af MR-billeder nøglen til at sikre nøjagtig segmentering. Hvis billedets kvalitet er for dårlig, eller kontrasten er for lav eller for høj, kan det føre til unøjagtig afgrænsning af choroid plexus. Kontrasten for billedet kan justeres ved at få vist billedets gråtoneværdi eller ved at kalibrere værdierne for at forbedre kon...

Choroid plexus funktion Choroid plexus er en stærkt vaskulariseret struktur i hjernen bestående af fenestrerede kapillærer og et monolag af choroid plexus epitelceller1. Choroid plexus projicerer ind i de laterale, tredje og fjerde cerebrale ventrikler og producerer cerebrospinalvæske (CSF), som spiller en vigtig rolle i neurale mønstre2 og hjernefysiologi 3,4. Choroid plexus udskiller neurovaskulære stoffer, omfatter et stamcellelignende lager og fungerer som en fysisk barriere for at hindre indgangen af toksiske metabolitter, en enzymatisk barriere for at fjerne dele, der omgår den fysiske barriere og en immunologisk barriere for at beskytte mod fremmede angribere5. Choroid plexus modulerer neurogenese6, synaptisk plasticitet7, inflammation8, døgnrytme 9,10, tarmhjerneakse11 og kognition12. Desuden kan perifere cytokiner, stress og infektion (inklusive SARS-CoV-2) forstyrre blod-CSF-barrieren 13,14,15,16. Således er choroid plexus-CSF-systemet integreret til neuroudvikling, neurokredsløbsmodning, hjernehomeostase og reparation17. Da immun-, inflammatoriske, metaboliske og enzymatiske ændringer påvirker hjernen, bruger forskere neuroimaging værktøjer til at vurdere rollen som choroid plexus i hele levetiden og i hjernesygdomme 18,19,20. Der findes dog begrænsninger i almindeligt anvendte automatiserede værktøjer til choroid plexus-segmentering, såsom FreeSurfer, hvilket resulterer i, at choroid plexus er dårligt segmenteret. Der er således et kritisk behov for manuel segmentering af choroid plexus, der kan bruges til at udvikle et nøjagtigt automatiseret værktøj til choroid plexus-segmentering.
Choroid plexus i neurodevelopment og hjernesygdomme Choroid plexus rolle i hjernesygdomme har længe været forsømt, hovedsageligt fordi det blev betragtet som en støttende spiller, hvis rolle var at dæmpe hjernen og opretholde en ordentlig saltbalance 2,21. Imidlertid har choroid plexus fået opmærksomhed som en struktur forbundet med hjerneforstyrrelser såsom smertesyndrom22, SARS-CoV-2 16,23,24, neurodevelopmental 2 og hjernesygdomme19, hvilket tyder på en transdiagnostisk effekt i udviklingen af adfærdsforstyrrelser. I neuroudviklingsforstyrrelser var choroid plexuscyster forbundet med en øget risiko for udviklingsforsinkelse, opmærksomhedsunderskud / hyperaktivitetsforstyrrelse (ADHD) eller autismespektrumforstyrrelse (ASD)25,26. Derudover blev lateral ventrikel choroid plexus volumen fundet at være øget hos patienter med ASD27. I hjernesygdomme,choroid plexus abnormiteter er blevet beskrevet siden 1921 i psykotiske lidelser28,29. Tidligere undersøgelser har identificeret choroid plexusforstørrelse ved hjælp af FreeSurfer-segmentering i en stor stikprøve af patienter med psykotiske lidelser sammenlignet med både deres førstegradsslægtninge og kontroller19. Disse fund blev replikeret ved hjælp af manuelt segmenteret choroid plexusvolumen i en stor prøve af klinisk højrisiko for psykosepopulation og fandt, at disse patienter havde større choroid plexusvolumen sammenlignet med raske kontroller30. Der er et stigende antal undersøgelser, der viser choroid plexusforstørrelse i komplekst regionalt smertesyndrom22, slagtilfælde31, multipel sklerose20,32, Alzheimers33,34 og depression35, hvor nogle viser en sammenhæng mellem perifer og hjerneimmun / inflammatorisk aktivitet. Disse neuroimaging undersøgelser er lovende; dårlig lateral ventrikel choroid plexus segmentering af FreeSurfer21 begrænser imidlertid troværdigheden af automatiseret choroid plexus volumen estimering. Som følge heraf er undersøgelser i multipel sklerose20,32, depression35, Alzheimers34 og tidlig psykose36 begyndt manuelt at segmentere lateral ventrikel choroid plexus, men der er ingen nuværende retningslinjer for, hvordan man gør dette, og det er heller ikke deres vejledning om segmentering af tredje og fjerde ventrikel choroid plexus.
Almindelige segmenteringsværktøjer udelukker choroid plexus Hjernesegmenteringsrørledninger såsom FreeSurfer37,38,39, FMRIB Software Library (FSL)40, SLANT41 og FastSurfer (udviklet af medforfatteren Martin Reuter)42,43, segmenterer nøjagtigt og pålideligt kortikale og subkortikale strukturer, der anvender atlasbaserede (FSL), atlas- og overfladebaserede (FreeSurfer) og deep learning-segmenteringsparadigmer (SLANT og FastSurfer). Svagheder ved nogle af disse tilgange inkluderer behandlingshastighed, begrænset generalisering til forskellige scannere, feltstyrker og voxelstørrelser37,44 og tvungen justering af etiketkortet i et standard atlasrum. Imidlertid behandles evnen til at segmentere choroid plexus og kompatibiliteten med MR med høj opløsning kun af FreeSurfer og FastSurfer. De neurale netværk bag FastSurfer er trænet på FreeSurfer choroid plexus etiketter, så de arver FreeSurfers tidligere diskuterede pålidelighed og dækningsbegrænsninger, hvor den tredje og fjerde ventrikel ignoreres21. Der findes også nuværende begrænsninger for MR i høj opløsning, men FreeSurfers stream45 med høj opløsning og FastSurferVINN43 kan bruges til at håndtere dette problem.
Nuværende choroid plexus segmenteringsværktøjer Der er kun et frit tilgængeligt segmenteringsværktøj til choroid plexus, men segmenteringsnøjagtigheden er begrænset. Nøjagtig choroid plexus segmentering kan påvirkes af en række faktorer, herunder (1) variabilitet i choroid plexus placering (rumligt ikke-stationær) på grund af dens placering i ventriklerne, (2) forskelle i voxel intensitet, kontrast, opløsning (inden for struktur heterogenitet) på grund af cellulær heterogenitet, dynamisk choroid plexus funktion, patologiske ændringer, eller delvis volumen effekter, (3) alders- eller patologi-relaterede ventrikulære størrelsesforskelle, der påvirker choroid plexus størrelse, og (4) nærhed til tilstødende subkortikale strukturer (hippocampus, amygdala, caudat og cerebellum), som også er vanskelige at segmentere. I betragtning af disse udfordringer undervurderer eller overvurderer FreeSurfer-segmenteringer ofte, fejlmærker eller ignorerer choroid plexus.
Tre nylige publikationer behandlede kløften mellem pålidelig choroid plexus-segmentering med en Gaussian Mixture Model (GMM)46, en Axial-MLP47 og U-Net-baserede deep learning-tilgange48. Hver model blev trænet og evalueret ved hjælp af private, manuelt mærkede datasæt på højst 150 forsøgspersoner med en begrænset mangfoldighed af scannere, websteder, demografi og lidelser. Mens disse publikationer 46,48,49 opnåede betydelige forbedringer i forhold til FreeSurfers choroid plexus-segmentering - undertiden fordobling af skæringspunktet mellem forudsigelse og jordsandhed, er ingen af metoderne (1) valideret i MR med høj opløsning, (2) har dedikerede generaliserings- og pålidelighedsanalyser, (3) indeholder store repræsentative trænings- og testdatasæt, (4) adresserer eller analyserer choroid plexus-segmenteringsudfordringer såsom delvise volumeneffekter, eller (5) er offentligt tilgængelig som et brugsklart værktøj. Den nuværende "guldstandard" for plexussegmentering af choroid er således manuel sporing, f.eks. ved hjælp af 3D Slicer50 eller ITK-SNAP51, som ikke tidligere er beskrevet og har været en stor udfordring for forskere, der ønsker at undersøge choroid plexus' rolle i deres studier. 3D Slicer blev valgt til manuel segmentering på grund af forfatterens fortrolighed med softwaren, og fordi det giver brugeren forskellige værktøjer baseret på forskellige tilgange, der kan kombineres for at opnå det ønskede resultat. Andre værktøjer kan bruges, såsom ITK-SNAP, som primært er orienteret mod billedsegmentering, og når værktøjet er mestret, kan brugeren opnå gode resultater. Derudover har forfatterne gennemført en case-control-undersøgelse, der demonstrerer den høje nøjagtighed og pålidelighed af deres manuelle segmenteringsteknik ved hjælp af 3D Slicer30, og den specifikke metode er beskrevet heri.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>3D Slicer</td>
			<td>3D Slicer</td>
			<td>https://www.slicer.org/</td>
			<td>A free, open source software for visualization, processing, segmentation, registration, and analysis of medical, biomedical, and other 3D images and meshes; and planning and navigating image-guided procedures.</td>
		</tr>
		<tr>
			<td>FreeSurfer</td>
			<td>FreeSurfer</td>
			<td>https://surfer.nmr.mgh.harvard.edu/</td>
			<td>An open source neuroimaging toolkit for processing, analyzing, and visualizing human brain MR images</td>
		</tr>
		<tr>
			<td>ITK-SNAP</td>
			<td>ITK-SNAP</td>
			<td>http://www.itksnap.org/pmwiki/pmwiki.php</td>
			<td>A free, open-source, multi-platform software application used to segment structures in 3D and 4D biomedical images.&#160;</td>
		</tr>
		<tr>
			<td>Monai Package</td>
			<td>Monai Consortium</td>
			<td>https://docs.monai.io/en/stable/metrics.html</td>
			<td>Use for Dice Coefficient and DeepMind average Surface Distance.&#160;</td>
		</tr>
		<tr>
			<td>MRI scanner</td>
			<td>GE</td>
			<td>Discovery MR750&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>Psych Package</td>
			<td>R-Project</td>
			<td>https://cran.r-project.org/web/packages/psych/index.html</td>
			<td>A general purpose toolbox developed originally for personality, psychometric theory and experimental psychology.</td>
		</tr>
		<tr>
			<td>R Software</td>
			<td>R-Project</td>
			<td>https://www.r-project.org/</td>
			<td>R is a free software environment for statistical computing and graphics.&#160;</td>
		</tr>
		<tr>
			<td>RStudio</td>
			<td>Posit</td>
			<td>https://posit.co/</td>
			<td>An RStudio integrated development environment (IDE) is a set of tools built to help you be more productive with R and Python.&#160;</td>
		</tr>
		<tr>
			<td>Windows or Apple OS Desktop or Laptop</td>
			<td>Any company</td>
			<td>n/a</td>
			<td>Needed for running the software used in this protocol.&#160;</td>
		</tr>
	</tbody>
</table>

manual segmentation of the human choroid plexus using brain mri

Choroid plexus har været impliceret i neurodevelopment og en række hjernesygdomme. Beviser viser, at choroid plexus er kritisk for hjernens modning, immun / inflammatorisk regulering og adfærdsmæssig / kognitiv funktion. Imidlertid er de nuværende automatiserede neuroimaging segmenteringsværktøjer dårlige til nøjagtigt og pålideligt segmentering af lateral ventrikel choroid plexus. Desuden er der ikke noget eksisterende værktøj, der segmenterer choroid plexus placeret i hjernens tredje og fjerde ventrikler. Således er der behov for en protokol, der afgrænser, hvordan man segmenterer choroid plexus i den laterale, tredje og fjerde ventrikel for at øge pålideligheden og replikabiliteten af undersøgelser, der undersøger choroid plexus i neuroudviklings- og hjernesygdomme. Denne protokol indeholder detaljerede trin til oprettelse af separat mærkede filer i 3D Slicer til choroid plexus baseret på DICOM- eller NIFTI-billeder. Choroid plexus vil blive segmenteret manuelt ved hjælp af de aksiale, sagittale og koronale planer af T1w-billeder, og sørg for at udelukke voxels fra grå eller hvide stofstrukturer, der grænser op til ventriklerne. Vinduer vil blive justeret for at hjælpe med lokalisering af choroid plexus og dens anatomiske grænser. Metoder til vurdering af nøjagtighed og pålidelighed vil blive demonstreret som en del af denne protokol. Guldstandardsegmentering af choroid plexus ved hjælp af manuelle afgrænsninger kan bruges til at udvikle bedre og mere pålidelige automatiserede segmenteringsværktøjer, der åbent kan deles for at belyse ændringer i choroid plexus over hele levetiden og inden for forskellige hjernesygdomme.

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.

Forfatter Spotlight: Brobygning mellem huller i anatomi og etablering af et fundament for algoritmiske studier 

Manuel segmentering af den humane choroid plexus ved hjælp af hjerne MR

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.

Den foreslåede metode har gennemgået iterativ forfining for lateral ventrikel choroid plexus, der involverer omfattende test på en kohorte på 169 raske kontroller og 340 patienter med klinisk høj risiko for psykose30. Ved hjælp af teknikken beskrevet ovenfor opnåede forfatterne høj intra-rater nøjagtighed og pålidelighed med en DC = 0,89, avgHD = 3,27 mm3 og single-rater ICC = 0,9730, hvilket demonstrerer styrken af protokollen beskrevet heri.
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Watch this Scientific Journal Video about Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies at JoVE.com

På trods af den afgørende rolle, som choroid plexus spiller i hjernen, er neuroimaging undersøgelser af denne struktur knappe på grund af manglen på pålidelige automatiserede segmenteringsværktøjer. Denne protokol har til formål at sikre guldstandard manuel segmentering af choroid plexus, der kan informere fremtidige neuroimaging undersøgelser.

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

Vi sigter mod at etablere en tilgængelig og standardiseret protokol til manuel segmentering af choroid plexus i hjernens laterale, tredje og fjerde ventrikler. Vi håber at løse eventuelle almindelige spørgsmål eller problemer, der kan opstå, når man manuelt segmenterer choroid plexus, især i betragtning af den komplekse karakter af dens placering i hjernen. Udvikling af denne protokol vil føre til oprettelsen af et stort nok datasæt bestående af jordsandhedssegmenteringskort, som vi derefter kan bruge til at træne og udvikle algoritmer, der nøjagtigt og automatisk kan segmentere choroid plexus.I fremtiden vil dette føre til undersøgelser, der undersøger choroid plexus rolle inden for forskellige neurologiske og neuropsykiatriske lidelser.

manual-segmentation-of-the-human-choroid-plexus-using-brain-mri

Research

JoVE Journal

Neuroscience

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 brain maturation, immune/ inflammatory regulation, and behavioral/cognitive functioning. However, current automated neuroimaging segmentation tools are poor at accurately and reliably segmenting the lateral ventricle choroid plexus. Furthermore, there is no existing tool that segments the choroid plexus located in the third and fourth ventricles of the brain. Thus, a protocol delineating how to segment the choroid plexus in the lateral, third, and fourth ventricle is needed to increase the reliability and replicability of studies examining the choroid plexus in neurodevelopmental and brain disorders. This protocol provides detailed steps to create separately labeled files in 3D Slicer for the choroid plexus based on DICOM or NIFTI images. The choroid plexus will be manually segmented using the axial, sagittal, and coronal planes of T1w images making sure to exclude voxels from gray or white matter structures bordering the ventricles. Windowing will be adjusted to assist in the localization of the choroid plexus and its anatomical boundaries. Methods for assessing accuracy and reliability will be demonstrated as part of this protocol. Gold standard segmentation of the choroid plexus using manual delineations can be used to develop better and more reliable automated segmentation tools that can be openly shared to elucidate changes in the choroid plexus across the lifespan and within various brain disorders.

Despite the crucial role of the choroid plexus in the brain, neuroimaging studies of this structure are scarce due to the lack of reliable automated segmentation tools. The present protocol aims to ensure gold-standard manual segmentation of the choroid plexus that can inform future neuroimaging studies.

Segmentation of the Choroid Plexus Using Manual Delineations

To begin, import digital imaging and communications in medicine or DICOM data by clicking on the DCM button located at the upper left corner of the toolbar and clicking the import DICOM files button. To adjust the brightness of an image, click adjust window and level of volume or left click on the image and drag the mouse up or down. Then left click on the image slice and move the mouse to the left or right to adjust the contrast.Refer to the deep gray matter nuclei or the contrast scale bars signal intensity and ensure that it remains consistent throughout the segmentation to choose the suitable contrast for the choroid plexus. To start the segmentation of the lateral third and fourth ventricle choroid plexus, select the segment editor from the module's dropdown menu. Now click on the dropdown menu for segmentation to select different segmentations and rename the selected one.Use the master volume dropdown and pick the NIfTI or DICOM sets that need editing. Click the add button two times to include two segments for the lateral ventricle choroid plexus. Double click on their titles and rename them as right lateral ventricle choroid plexus and left lateral ventricle choroid plexus.Click on the add button once more to introduce segments for the choroid plexus of the third and fourth ventricles. Afterward, rename them as the third ventricle choroid plexus and the fourth ventricle choroid plexus respectively. Begin with the lateral ventricle choroid plexus in the axial plane and ensure to position images based on the bicommissural line.Use the trigonum collaterale as a reference point to locate the lateral ventricle choroid plexus. To start manual segmentation, select either the paint or draw tool located in the effects section of the segment editor. While using the paint tool, select the desired brush diameter for painting.Use the red nucleus level to determine when to stop segmenting the choroid plexus in the lateral ventricles. To locate the third ventricle choroid plexus, commence in the sagittal plane, and use the foramen of Monro, fornix, corpus callosum, thalamus, and internal cerebral vein as landmarks. Similarly, for the fourth ventricle choroid plexus, begin in the sagittal plane and use the superior cerebellar peduncle, pons and medulla as reference points to pinpoint the choroid plexus in the fourth ventricle.From the modules dropdown menu, navigate to quantification and select segment statistics. Then under the input section, select the newly created segmentation map for quantification under the segmentation tool and select the MRI volume from the scaler volume. For the output table, select the table option under output and hit apply.A table displaying the choroid plexus volume in different units will appear. Click on the save button located in the top left part of the toolbar to store the generated files. Preserve the segmentation files in the formats nrrd, nii.gz, or tsv.