Vi takker FORUTSE-HD etterforskerne, spesielt Dr. Hans Johnson og Dr. Jane S. Pauslen fra University of Iowa for sin generøsitet i deler MRI data og konstruktiv diskusjon om dataanalyse og resultater.
Dette arbeidet er støttet av NIH gir R21 NS098018, P50 NS16375, NS40068, R01 NS086888, R01 NS084957, P41 EB015909, P41 EB015909, R01 EB000975, R01 EB008171 og U01 NS082085.

1. Atlas-baserte hele hjernen segmentering
<ol><li>Data forberedelse
	<ol>
<li>Konverter tredimensjonale (3D) T1-vektet bilder, vanligvis kjøpt med MPRAGE (magnetization forberedt rask forløpning-echo) rekkefølge, fra leverandørspesifikke DICOM (Digital Imaging og kommunikasjon) format til Analyzed format. Merk at skyen beregningen krever brukernes data overføres til ekstern klynger. Ifølge Health Insurance Portability and Accountability Act (HIPPA), fjerne pasientenes personlig identifiserende i...

<ol>
	<li>Paulsen, J. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+and+Biomarker+Changes+in+Premanifest+Huntington+Disease+Show+Trial+Feasibility:+A+Decade+of+the+PREDICT-HD+Study.">Clinical and Biomarker Changes in Premanifest Huntington Disease Show Trial Feasibility: A Decade of the PREDICT-HD Study.</a> Front Aging Neurosci. 6, 78 (2014).</li><li>Jack, C. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hypothetical+model+of+dynamic+biomarkers+of+the+Alzheimer's+pathological+cascade.">Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade.</a> Lancet Neurol. 9 (1), 119-128 (2010).</li><li>Laakso, M. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hippocampal+volumes+in+Alzheimer's+disease,+Parkinson's+disease+with+and+without+dementia,+and+in+vascular+dementia:+An+MRI+study.">Hippocampal volumes in Alzheimer's disease, Parkinson's disease with and without dementia, and in vascular dementia: An MRI study.</a> Neurology. 46 (3), 678-681 (1996).</li><li>Miller, M. I., Faria, A. V., Oishi, K., Mori, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+neuro-imaging+informatics.">High-throughput neuro-imaging informatics.</a> Front Neuroinform. 7, 31 (2013).</li><li>Mori, S., Oishi, K., Faria, A. V., Miller, M. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Atlas-based+neuroinformatics+via+MRI:+harnessing+information+from+past+clinical+cases+and+quantitative+image+analysis+for+patient+care.">Atlas-based neuroinformatics via MRI: harnessing information from past clinical cases and quantitative image analysis for patient care.</a> Annu Rev Biomed Eng. 15, 71-92 (2013).</li><li>Klein, A., Mensh, B., Ghosh, S., Tourville, J., Hirsch, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mindboggle:+automated+brain+labeling+with+multiple+atlases.">Mindboggle: automated brain labeling with multiple atlases.</a> BMC Med Imaging. 5, 7 (2005).</li><li>Heckemann, R. A., Hajnal, J. V., Aljabar, P., Rueckert, D., Hammers, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+anatomical+brain+MRI+segmentation+combining+label+propagation+and+decision+fusion.">Automatic anatomical brain MRI segmentation combining label propagation and decision fusion.</a> Neuroimage. 33 (1), 115-126 (2006).</li><li>Artaechevarria, X., Munoz-Barrutia, A., Ortiz-de-Solorzano, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combination+strategies+in+multi-atlas+image+segmentation:+application+to+brain+MR+data.">Combination strategies in multi-atlas image segmentation: application to brain MR data.</a> IEEE Trans Med Imaging. 28 (8), 1266-1277 (2009).</li><li>Lotjonen, J. M. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fast+and+robust+multi-atlas+segmentation+of+brain+magnetic+resonance+images.">Fast and robust multi-atlas segmentation of brain magnetic resonance images.</a> Neuroimage. 49 (3), 2352-2365 (2010).</li><li>Rohlfing, T., Brandt, R., Menzel, R., Maurer, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+atlas+selection+strategies+for+atlas-based+image+segmentation+with+application+to+confocol+microscopy+images+of+bee+brains.">Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocol microscopy images of bee brains.</a> Neuroimage. 21 (4), 1428-1442 (2004).</li><li>Fischl, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Whole+brain+segmentation:+Automated+labeling+of+neuroanatomical+structures+in+the+human+brain.">Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain.</a> Neuron. 33 (3), 341-355 (2002).</li><li>Collins, D. L., Holmes, C. J., Peters, T. M., Evans, A. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+3-D+model-based+neuroanatomical+segmentation.">Automatic 3-D model-based neuroanatomical segmentation.</a> Human Brain Mapping. 3 (3), 190-208 (1995).</li><li>Dawant, B. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+3-D+segmentation+of+internal+structures+of+the+head+in+MR+images+using+a+combination+of+similarity+and+free-form+transformations:+Part+I,+methodology+and+validation+on+normal+subjects.">Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations: Part I, methodology and validation on normal subjects.</a> Ieee Transactions on Medical Imaging. 18 (10), 909-916 (1999).</li><li>Wu, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+generative+probability+model+of+joint+label+fusion+for+multi-atlas+based+brain+segmentation.">A generative probability model of joint label fusion for multi-atlas based brain segmentation.</a> Med Image Anal. 18 (6), 881-890 (2014).</li><li>Miller, M. I., Trouve, A., Younes, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diffeomorphometry+and+geodesic+positioning+systems+for+human+anatomy.">Diffeomorphometry and geodesic positioning systems for human anatomy.</a> Technology. 2, (2013).</li><li>Tang, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bayesian+Parameter+Estimation+and+Segmentation+in+the+Multi-Atlas+Random+Orbit+Model.">Bayesian Parameter Estimation and Segmentation in the Multi-Atlas Random Orbit Model.</a> PLoS One. 8 (6), e65591 (2013).</li><li>Wang, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multi-Atlas+Segmentation+with+Joint+Label+Fusion.">Multi-Atlas Segmentation with Joint Label Fusion.</a> IEEE Trans Pattern Anal Mach Intell. 35 (3), 611-623 (2013).</li><li>Wu, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Resource+atlases+for+multi-atlas+brain+segmentations+with+multiple+ontology+levels+based+on+T1-weighted+MRI.">Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI.</a> Neuroimage. 125, 120-130 (2015).</li><li>Mori, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MRICloud:+Delivering+High-Throughput+MRI+Neuroinformatics+as+Cloud-Based+Software+as+a+Service.">MRICloud: Delivering High-Throughput MRI Neuroinformatics as Cloud-Based Software as a Service.</a> Computing in Science &amp; Engineering. 18 (5), 21-35 (2016).</li><li>Wu, D., Ceritoglu, C., Miller, M. I., Mori, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Direct+estimation+of+patient+attributes+from+anatomical+MRI+based+on+multi-atlas+voting.">Direct estimation of patient attributes from anatomical MRI based on multi-atlas voting.</a> Neuroimage-Clinical. 12, 570-581 (2016).</li><li>Miller, M. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Network+Neurodegeneration+in+Alzheimer's+Disease+via+MRI+Based+Shape+Diffeomorphometry+and+High-Field+Atlasing.">Network Neurodegeneration in Alzheimer's Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing.</a> Front Bioeng Biotechnol. 3, 54 (2015).</li><li>Faria, A. V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Content-based+image+retrieval+for+brain+MRI:+an+image-searching+engine+and+population-based+analysis+to+utilize+past+clinical+data+for+future+diagnosis.">Content-based image retrieval for brain MRI: an image-searching engine and population-based analysis to utilize past clinical data for future diagnosis.</a> Neuroimage Clin. 7, 367-376 (2015).</li><li>Wu, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mapping+the+order+and+pattern+of+brain+structural+MRI+changes+using+change-point+analysis+in+premanifest+Huntington's+disease.">Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.</a> Hum Brain Mapp. , (2017).</li><li>Younes, L., Albert, M., Miller, M. I., Team, B. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inferring+changepoint+times+of+medial+temporal+lobe+morphometric+change+in+preclinical+Alzheimer's+disease.">Inferring changepoint times of medial temporal lobe morphometric change in preclinical Alzheimer's disease.</a> Neuroimage Clin. 5, 178-187 (2014).</li><li>Wu, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mapping+the+critical+gestational+age+at+birth+that+alters+brain+development+in+preterm-born+infants+using+multi-modal+MRI.">Mapping the critical gestational age at birth that alters brain development in preterm-born infants using multi-modal MRI.</a> NeuroImage. 149, 33-43 (2017).</li><li>Zhang, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Indexing+disease+progression+at+study+entry+with+individuals+at-risk+for+Huntington+disease.">Indexing disease progression at study entry with individuals at-risk for Huntington disease.</a> Am J Med Genet B Neuropsychiatr Genet. 156b (7), 751-763 (2011).</li><li>Vonsattel, J. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuropathological+classification+of+Huntington's+disease.">Neuropathological classification of Huntington's disease.</a> J Neuropathol Exp Neurol. 44 (6), 559-577 (1985).</li><li>Paulsen, J. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detection+of+Huntington's+disease+decades+before+diagnosis:+the+Predict-HD+study.">Detection of Huntington's disease decades before diagnosis: the Predict-HD study.</a> J Neurol Neurosurg Psychiatry. 79 (8), 874-880 (2008).</li><li>Paulsen, J. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prediction+of+manifest+Huntington's+disease+with+clinical+and+imaging+measures:+a+prospective+observational+study.">Prediction of manifest Huntington's disease with clinical and imaging measures: a prospective observational study.</a> Lancet Neurol. 13 (12), 1193-1201 (2014).</li><li>Djamanakova, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tools+for+multiple+granularity+analysis+of+brain+MRI+data+for+individualized+image+analysis.">Tools for multiple granularity analysis of brain MRI data for individualized image analysis.</a> Neuroimage. 101, 168-176 (2014).</li><li>. A package for T1 volumetric analysis of MRIcloud output. R package version 0.0.1 Available from: <a target="_blank" href="https://github.com/bcaffo/MRIcloudT1volumetrics">https://github.com/bcaffo/MRIcloudT1volumetrics</a> (2017)</li><li>Aljabar, P., Heckemann, R. A., Hammers, A., Hajnal, J. V., Rueckert, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multi-atlas+based+segmentation+of+brain+images:+atlas+selection+and+its+effect+on+accuracy.">Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy.</a> Neuroimage. 46 (3), 726-738 (2009).</li><li>Huntington Study Group. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unified+Huntington's+Disease+Rating+Scale:+reliability+and+consistency.">Unified Huntington's Disease Rating Scale: reliability and consistency.</a> Mov Disord. 11 (2), 136-142 (1996).</li><li>Liang, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+Cross-Protocol+Stability+of+a+Fully+Automated+Brain+Multi-Atlas+Parcellation+Tool.">Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool.</a> PLoS One. 10 (7), e0133533 (2015).</li></ol>

Som vist i dette papiret, oppnås hele-hjerne segmentering av hjernen Mr enkelt ved hjelp av våre online plattform MRICloud. T1-vektet MRI basert volumetriske markør har vist seg for å være robust og sensitive for nevrodegenerative sykdommer1,2,3. Volumetrisk tiltak brukes for ulike nedstrøms analyse, som matematisk modellering og funksjon-utvalg og klassifisering for å hjelpe klinisk diagnose og prognose. Viser analyse av...

Magnetisk resonans imaging (MRI) har betydelig forbedret vår evne til å undersøke hjernen anatomi og funksjoner i nevrodegenerative sykdommer1,2,3. T1-vektet strukturelle Mr er en av mest vedtatt bildebehandlingsverktøy i rutinemessige klinisk praksis å vurdere hjernen anatomi og relaterte patologi. Kvantitativ analyse av T1-vektet oppløsning gir nyttige indikatorer for å måle anatomiske endringer under brain degenerasjon. Spesielt segmentering basert kvantifisering tilnærminger effektivt reduserer bildet dimensionality fra voxel nivå (på rekkefølgen av (106)) til anatomiske strukturelle nivå ((102)) for høy gjennomstrømming neuroinformatics4 , 5. automatisert hjernen segmentering kan oppnås med atlas-baserte metoder6,7,8,9 som forhåndsdefinerte anatomiske etikettene fra en atlas på pasienten bildene . Blant de atlas-baserte metodene, har flere atlas algoritmer10,11,12,13,14 gitt overlegen segmentering nøyaktighet og robusthet. Vår gruppe har utviklet en helautomatisk T1 multi atlas segmentering rørledning, med avanserte diffeomorphic bilde registrering algoritmer15, flere atlas fusion metoder16,17og rikt multi atlas biblioteker 18. rørledningen har blitt distribuert på en cloud-computing plattform, MRICloud19, siden 2015, og det har blitt brukt til å studere nevrodegenerative sykdommer, som Alzheimers sykdom (AD)20,21, primær Progressiv afasi22og Huntingtons sykdom23.
Når de høyoppløselige bildene er segmentert i hjernen strukturer, kan regionale funksjoner, for eksempel volumer, brukes til å opprette matematiske modeller for å karakterisere nevroanatomi endringene. En viser analysemetode ble nylig etablert av vår gruppe å analysere den timelige rekkefølgen, statistisk signifikant brain morphometric endringer, basert på langsgående og/eller cross-sectional MRI data. Denne statistiske modellen ble først utviklet for å kvantifisere form-basert diffeomorphometry over alder i AD pasienter21,24; og det ble senere gjort for å undersøke hjernen strukturelle endringer i Huntingtons sykdom (HD), samt å beskrive hjernen utviklingsmessige endringer i neonatal hjerner25. I HD pasienter, ble viser definert med hensyn til CAG-alder produkt (CAP) score, som en indikator på omfanget av eksponering for CAG utvidelsen i HTT 26. Det er kjent at striatal atrofi er en av de tidligste markørene i HD, etterfulgt av globus pallidus27. Likevel, endringene i striatum i forhold til andre grå og hvit sak strukturer i hjernen er fortsatt uklart. Slike forhold er avgjørende for oss å forstå sykdomsprogresjon. Viser analyse av volumetriske endringer i alle hjernen strukturer gir systematisk informasjon på hjernen atrofi i premanifest fase av HD.
Her viser vi fremgangsmåtene for å utføre hele-hjerne segmentering bruker MRICloud (www.mricloud.org), og skritt for å utføre viser analyse av volumetriske data i premanifest HD fag. Mr data var samlet inn fra en stor befolkning multisenter FORUTSE-HD studere28,29 med ca 400 kontroller og premanifest HD fag. Kombinasjonen av atlas-basert segmentering og viser analysen gir unik informasjon om spatiotemporal rekkefølgen av hjernen strukturelle endringer og sykdom progresjon mønster over hjernen. Teknikkene er potensielt gjelder en rekke nevrodegenerative sykdommer med ulike biomarkers tilordne brain degenerasjon.

<table border="0" cellpadding="0" cellspacing="0" width="849">
	<tbody>
		<tr height="40">
			<td height="40" style="height:40px;width:216px;">MATLAB</td>
			<td style="width:123px;">Mathworks</td>
			<td style="width:344px;">N/A</td>
			<td style="width:167px;">Version 2015b and above</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">Dell Workstation</td>
			<td>Dell</td>
			<td></td>
			<td>Dell Precision T5500 (Intel Xeon CPU)</td>
		</tr>
	</tbody>
</table>

whole-brain segmentation and change-point analysis of anatomical brain mri&#8212;application in premanifest huntington's disease

Nylige fremskritt innen MRI tilbyr en rekke nyttige indikatorer for å identifisere nevrodegenerative sykdommer. Huntingtons sykdom (HD), regionale hjernen atrofi begynner mange år før motor utbruddet (under "premanifest" perioden), men spatiotemporal mønster av regionale atrofi over hjernen ikke har vært fullt preget. Her viser vi en online cloud-computing plattform, "MRICloud", som gir atlas-baserte hele-hjerne segmentering av T1-vektet bilder på flere nivåer nivåer, og dermed kan vi tilgang til regionale funksjoner hjernen anatomi. Vi beskriver en regresjonsmodell som oppdager statistisk signifikant Bøyning poeng, som regionale hjernen atrofi begynner å bli merkbar, dvs. det "viser", med hensyn til en sykdom progresjon indeks. Vi brukte CAG-alder produkt (CAP) score indeksere sykdomsprogresjon i HD pasienter. Viser analyse av volumetriske målinger fra segmentering rørledningen, derfor inneholder viktig informasjon for den orden og mønster av strukturelle atrofi over hjernen. Papiret illustrerer bruken av disse teknikkene på T1-vektet MRI data av premanifest HD fag fra en stor FORUTSE-HD multisenterstudie. Denne utformingen har potensielt bred programmer i en rekke nevrodegenerative sykdommer å undersøke de dynamiske endringene av hjernen anatomi.

Bruke fremgangsmåtene i 1,1-1,3, kan hele hjernen segmentering kart fås fra MRICloud. I gjeldende versjon av atlas (V9B), 283 pakker er segmentert på de fineste detaljene (nivå 5), som kan grupperes på forskjellige nivåer av detaljnivå, f.eks., fra halvkule lobules former og pakker, i henhold til bestemte ontologi definisjoner. Figur 3 viser to typer multi-level segmentations på fem nivåer, i aksial og koronale. For eksempel på råeste niv?...

Watch this Scientific Journal Video about Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRIÃ¢â‚¬â€Application in Premanifest Huntington's Disease at JoVE.com

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRIÃƒÆ’Ã‚Â¢ÃƒÂ¢Ã¢â‚¬Å¡Ã‚Â¬ÃƒÂ¢Ã¢â€šÂ¬Ã‚ÂApplication in Premanifest Huntington's Disease

Dette dokumentet beskriver en statistisk modell for volumetriske MRI dataanalyse, som identifiserer det "viser" når hjernen atrofi begynner i premanifest Huntingtons sykdom. Hele-hjerne kartlegging av endre-poeng oppnås basert på hjernen volumer får en atlas-basert segmentering rørledning T1-vektet bilder.

Hele-hjerne segmentering og viser analyse av anatomiske hjernen MRI-programmet i Premanifest Huntingtons sykdom

Recent advances in MRI offer a variety of useful markers to identify neurodegenerative diseases. In Huntington&#39;s disease (HD), regional brain atrophy ...

Research

JoVE Journal

Medicine

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI&#8212;Application in Premanifest Huntington's Disease

Isolation of Soluble and Insoluble PrP Oligomers in the Normal Human Brain

Isolering av oppløselige og uoppløselige PrP oligomerer i Normal Human Brain

The central event in the pathogenesis of prion diseases involves a conversion of the host-encoded cellular prion protein PrPC into its pathogenic isoform ...

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester (CFSE)

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester CFSE

Tumor heterogeneity represents a fundamental feature supporting tumor robustness and presents a central obstacle to the development of therapeutic ...

The Use of Primary Human Fibroblasts for Monitoring Mitochondrial Phenotypes in the Field of Parkinson's Disease

Bruk av primære humane fibroblaster for overvåking Mitokondrielle Fenotyper i feltet av Parkinsons sykdom

Parkinson's disease (PD) is the second most  common movement disorder and affects 1% of people over the age of 60 1. Because ageing is  the most important ...

Quantitative Analysis of Chromatin Proteomes in Disease

Kvantitativ analyse av Chromatin Proteomes i sykdom

In the nucleus reside the proteomes whose functions are most intimately linked with gene regulation. Adult mammalian cardiomyocyte nuclei are unique due ...

Utilizing a Cranial Window to Visualize the Middle Cerebral Artery During Endothelin-1 Induced Middle Cerebral Artery Occlusion

Utnytte en Kranio vindu for å visualisere Midt Cerebral arterie under Endotelin-1 Induced Middle Cerebral arterieokklusjon

Creation of a cranial window is a method that allows direct visualization of structures on the cortical surface of the brain1-3. This technique can be ...

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Lesjon Explorer: En video-guidet, Standardisert protokoll for nøyaktig og pålitelig MRI-avledet Volumetrics i Alzheimers sykdom og Normal eldreomsorg

Obtaining in vivo human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are ...

Controlling Parkinson's Disease With Adaptive Deep Brain Stimulation

Kontrollere Parkinsons sykdom med Adaptive dyp hjernestimulering

Adaptive deep brain stimulation (aDBS) has the potential to improve the treatment of Parkinson&#39;s disease by optimizing stimulation in real time ...

Carotid Artery Infusions for Pharmacokinetic and Pharmacodynamic Analysis of Taxanes in Mice

Carotisar infusjoner for farmakokinetiske og farmakodynamiske Analyse av Taxaner i Mus

When proposing the use of a drug, drug combination, or drug delivery into a novel system, one must assess the pharmacokinetics of the drug in the study ...

Detection of Disease-associated &#945;-synuclein by Enhanced ELISA in the Brain of Transgenic Mice Overexpressing Human A53T Mutated &#945;-synuclein

Detection of Disease-associated ÃƒÅ½Ã‚Â±-synuclein by Enhanced ELISA in the Brain of Transgenic Mice Overexpressing Human A53T Mutated ÃƒÅ½Ã‚Â±-synuclein

Påvisning av sykdomsassosierte α-synuclein med utvidet ELISA i hjernen hos transgene mus som overuttrykker humant A53T Mutert α-synuclein

In addition to established methods like Western blot, new methods are needed to quickly and easily quantify disease-associated &#945;-synuclein (&#945;SD) ...

A Tissue Displacement-based Contusive Spinal Cord Injury Model in Mice

En Tissue Displacement-basert Contusive Spinal Cord Injury Model i mus

Producing a consistent and reproducible contusive spinal cord injury (SCI) is critical to minimizing behavioral and histological variabilities between ...