We would like to thank the whole Service of Neuroradiology. We would like to thank Lis Prussen for her work in the library.

NOTA: Questo protocollo segue le linee guida del Centre Hospitalier de Luxembourg in Lussemburgo. 1 Preparazione del tensore di diffusione Imaging per via visiva di Neurochirurgia e Follow Up <ol style="margin-left: 40px;"><li> Eseguire una risonanza magnetica scansione almeno un giorno prima dell&#39;intervento chirurgico rigorosamente assiale con 32 indicazioni di pendenza e un b0-immagine. Tenere in stretto contatto con l&#39;unità di neuroradiologia in qualsiasi momento. NOTA: Rendere chiaro al neuroradiologo che le immagini dopo l&#39;intervento chirurgico sono le stesse di quelle prima dell&#39;operazione. </li><li> Utilizzando un 3-Tesla MRI, eseguire una scansione 3DT1 ponderate e DTI-sequenza. Eseguire una sequenza 3DT1 ponderato dopo l&#39;intervento pure. </li></ol> 2 Utilizzo della stazione di pianificazione <ol><li> Trasferire i dati di scansione T2-pesate, 3DT1 ponderato e DTI-sequenza per imaging digitale e le comunicazioni in medicina (DICOM). Questa procedura richiede fino a 7 min. NOTA: Don `t fermare la procedura di prire dopo aver trasferito tutte le sequenze. È possibile fermare e continuare successivamente a seconda della data di intervento chirurgico. </li><li> Aprire il programma di sistema di navigazione chirurgica. Fare clic su File e poi su Importa DICOM. Ripetere questa procedura per tre volte per tutte le sequenze di cui sopra. <ol><li> Fare clic su Aggiungi per visualizzare. Aggiungere ogni sequenza separatamente. Don `t cercare di procedere con Vista. </li></ol></li><li> Fare clic su Strumenti. Aprire preparazione DTI Tensor. Osservare una nuova finestra al centro dello schermo. </li><li> Completare le seguenti quattro fasi. <ol><li> Eseguire Assegnazione gradiente come il primo passo. <ol><li> Modificare il valore-b da 1.000 a 800 s / mm ² in basso a destra della finestra. </li><li> Regolare la soglia in alto a destra della finestra. Farlo manualmente semplicemente scrivendo un numero o spostamento di un cursore. 20 potrebbe essere un valore accettabile. Si tratta di una esperienza personale e non è obbligatorio. </li></ol></li><li> Eseguire la registrazione Gradiente nel secondo passo. <ol> &lt;li&gt; Fare clic sul pulsante Tutti Auto. Questa procedura richiede fino a 5 min. </li><li> Fare clic su Verifica tutte le registrazioni. Senza verifica delle registrazioni non è possibile continuare. </li></ol></li><li> Eseguire Coregistrazione come il terzo passo. <ol><li> COREGISTER MR1 e MR2 immagini B0 manualmente. Alla fine Verifica tutte le registrazioni. NOTA: E &#39;possibile eseguire questo passaggio automaticamente. Tuttavia, i risultati non sono sempre soddisfacenti, alla fine. </li></ol></li><li> Eseguire Tensor computazione come il quarto e ultimo passo, <ol><li> Assicurarsi che FA / DEC / ADC sono su. Se non fai clic su ON. </li><li> Fare clic su Calcola. Questa procedura richiederà solo alcuni secondi. </li></ol></li></ol></li><li> Salvare tutti i dati e continuare con fibertracking. Non interrompere senza salvare tutto. </li></ol> 3 Fibertracking NOTA: anatomico conoscenza della via visiva è molto importante per il risultato positivo. <ol style = &quot;margin-left: 40px;&quot;&gt; <li> Preparatevi a scoprire i tre punti importanti in cui le fibre devono passare attraverso. </li><li> Determinare il chiasma ottico utilizzando conoscenze anatomiche. <ol><li> Utilizzare un ROI come punto di partenza e lasciare che le fibre passano attraverso. ROI sono definiti dal medico. </li><li> In alternativa, segmento regione sospetto. Clicca Segmentazione in basso a sinistra e apparirà un&#39;altra finestra. Aree segmentate sono anatomicamente aree definite. <ol><li> Dipingi la regione manualmente. Scorrere verso l&#39;alto e verso il basso per includere tutto il chiasma ottico. Salvare la procedura e tornare indietro. </li></ol></li><li> Traccia le fibre sia della regione di interesse o dalla zona segmentati o entrambi. </li><li> Le fibre raggiungono il nucleo genicolato sinistra (LGN), che è il secondo punto importante della via visiva. L&#39;angolo massimo è stato 50 il rischio di falsi tratti salirà con se l&#39;angolo è troppo alto. <ol><li> C&#39;è la possibilità di segmentare il LGN come mostrato con il chiasma otticoe poi seguire le fibre. Dopo aver segmentato il chiasma ottico, fibre pista che corrono dal LGN e finire nel chiasma ottico o viceversa. </li></ol></li><li> Segmento della corteccia visiva. Procedere come nel caso del chiasma ottico. Questo potrebbe richiedere del tempo come immagine 3DT1 ponderate contiene 160 fette. </li><li> Traccia le fibre della corteccia visiva al LGN. È possibile seguire loro dal LGN alla corteccia visiva pure. </li><li> Se la corteccia visiva è invaso da un tumore o edema quindi utilizzare una regione di interesse in luogo di una superficie segmentata e poi lasciare che le fibre correre in direzione del LGN. NOTA: Se l&#39;edema è segmentato a volte potrebbe invadere la corteccia visiva, allora poi la corteccia visiva potrebbe non essere in grado di segmentazione del tutto perché il computer può `t distinguere tra di loro. Quel `s perché è necessario mettere un ROI. </li><li> Ripetere tutto per l&#39;altro emisfero. </li><li> Inizia con l&#39;emisfero sano prima. NOTA: SiÈ possibile iniziare con l&#39;altra troppo ma potrebbe essere più facile per tenere traccia delle fibre dell&#39;emisfero sano prima di diventare una prima idea della situazione. Non è obbligatorio, è solo un consiglio. </li></ol></li><li> Segmento la lesione cerebrale e l&#39;edema. Procedere come indicato al 3.2.2. <ol><li> Assegnare un colore per ogni area segmentato o lesione per distinguere meglio. </li></ol></li><li> Salvare la procedura dopo ogni passaggio in caso di eventi imprevisti o in caso di emergenza. </li><li> Esportare tutti i dati in locale. E &#39;possibile esportarlo in sala operatoria direttamente, ma `t di isn consigliato. <ol><li> Premere File e quindi esportare oggetti 3D. Assicurarsi di esportare solo l&#39;esame di navigazione. </li><li> Don `t esportare l&#39;esame Hybrid. </li></ol></li><li> Inserisci cranica. Scegli il paziente giusto, quindi premere Stealthmerge. Scegliere le immagini 3DT1 ponderato esame di riferimento. </li><li> Creazione di un modello 3D e inserire tutto. </li><li> Importare il i datin la sala operatoria. </li></ol>

<ol><li>Fernandez-Miranda, J. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((High-Definition+Fiber+Tractography+of+the+Human+Brain%3A+Neuroanatomical+Validation+and+Neurosurgical+Applications%5BTitle%5D)+AND+%22Neurosurgery%22%5BJournal%5D)">High-Definition Fiber Tractography of the Human Brain: Neuroanatomical Validation and Neurosurgical Applications.</a> Neurosurgery. 71 (2), 430-453 (2012).</li>
<li>Alexander, D. C., Barker, G. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optimal+imaging+parameters+for+fiber-orientation+estimation+in+diffusion+MRI%5BTitle%5D)+AND+%22Neuroimage%22%5BJournal%5D)">Optimal imaging parameters for fiber-orientation estimation in diffusion MRI.</a> Neuroimage. 27 (2), 357-367 (2005).</li>
<li>Le Bihan, D., Poupon, C., Amadon, A., Lethimonnier, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Artifacts+and+pitfalls+in+diffusion+MRI%5BTitle%5D)+AND+%22J+Magn+Reson+Imaging%22%5BJournal%5D)">Artifacts and pitfalls in diffusion MRI.</a> J Magn Reson Imaging. 24 (3), 478-488 (2006).</li>
<li>Abdullah, K. G., Lubelski, D., Nucifora, P. G., Brem, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Use+of+diffusion+tensor+imaging+in+glioma+resection%5BTitle%5D)+AND+%22Neurosurg+Focus%22%5BJournal%5D)">Use of diffusion tensor imaging in glioma resection.</a> Neurosurg Focus. 34 (4), (2013).</li>
<li>Ota, T., Kawai, K., Kamada, K., Kin, T., Saito, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Intraoperative+monitoring+of+cortically+recorded+visual+response+for+posterior+visual+pathway%5BTitle%5D)+AND+%22J+Neurosurg%22%5BJournal%5D)">Intraoperative monitoring of cortically recorded visual response for posterior visual pathway.</a> J Neurosurg. 112, 285-294 (2010).</li>
<li>Gras-Combe, G., Moritz-Gasser, S., Herbet, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Intraoperative+subcortical+electrical+mapping+of+optic+radiations+in+awake+surgery+for+glioma+involving+visual+pathways%5BTitle%5D)+AND+%22J+Neurosurg%22%5BJournal%5D)">Intraoperative subcortical electrical mapping of optic radiations in awake surgery for glioma involving visual pathways.</a> J Neurosurg. 117 (3), 466-473 (2012).</li>
<li>Maruyama, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optic+radiation+tractography+integrated+into+simulated+treatment+planning+for+Gamma+Knife+surgery%5BTitle%5D)+AND+%22J+Neurosurg%22%5BJournal%5D)">Optic radiation tractography integrated into simulated treatment planning for Gamma Knife surgery.</a> J Neurosurg. 107, 721-726 (2007).</li>
<li>Bérubé, J., McLaughlin, N., Bourgouin, P., Beaudoin, G., Bojanowski, M. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Diffusion+tensor+imaging+analysis+of+long+association+bundles+in+the+presence+of+an+arteriovenous+malformation%5BTitle%5D)+AND+%22J+Neurosurg%22%5BJournal%5D)">Diffusion tensor imaging analysis of long association bundles in the presence of an arteriovenous malformation.</a> J Neurosurg. 107 (3), 509-514 (2007).</li>
<li>Sun, G. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Intraoperative+High-Field+Magnetic+Resonance+Imaging+Combined+With+Fiber+Tract+Neuronavigation-Guided+Resection+of+Cerebral+Lesions+Involving+Optic+Radiation%5BTitle%5D)+AND+%22Neurosurgery%22%5BJournal%5D)">Intraoperative High-Field Magnetic Resonance Imaging Combined With Fiber Tract Neuronavigation-Guided Resection of Cerebral Lesions Involving Optic Radiation.</a> Neurosurgery. 69 (5), 1070-1084 (2011).</li>
<li>Kamada, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Functional+Monitoring+For+Visual+Pathway+Using+Real-Time+Visual+Evoked+Potentials+Aand+Optic-Radiation+Tractography%5BTitle%5D)+AND+%22Neurosurgery%22%5BJournal%5D)">Functional Monitoring For Visual Pathway Using Real-Time Visual Evoked Potentials Aand Optic-Radiation Tractography.</a> Neurosurgery. 57 (1 Suppl), 121-127 (2005).</li>
<li>Wu, W., Rigolo, L., O'Donnell, L. J., Norton, I., Shriver, S., Golby, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Visual+Pathway+Study+Using+In+Vivo+Diffusion+Tensor+Imaging+Tractography+to+Complement+Classic+Anatomy%5BTitle%5D)+AND+%22Neurosurgery%22%5BJournal%5D)">Visual Pathway Study Using In Vivo Diffusion Tensor Imaging Tractography to Complement Classic Anatomy.</a> Neurosurgery. 70 (1 Suppl Operative), 145-156 (2012).</li>
<li>Stieglitz, L. H., Lüdemann, W. O., Giordano, M., Raabe, A., Fahlbusch, R., Samii, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optic+Radiation+Fiber+Tracking+Using+Anteriorly+Angulated+Diffusion+Tensor+Imaging%3A+A+Tested+Algorithm+for+Quick+Application%5BTitle%5D)+AND+%22Neurosurgery%22%5BJournal%5D)">Optic Radiation Fiber Tracking Using Anteriorly Angulated Diffusion Tensor Imaging: A Tested Algorithm for Quick Application.</a> Neurosurgery. 68 (5), 1239-1251 (2011).</li>
<li>Hodaie, M., Quan, J., Chen, D. Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((In+Vivo+Visualization+of+Cranial+Nerve+Pathways+in+Humans+Using+Diffusion-Based+Tractography%5BTitle%5D)+AND+%22Neurosurgery%22%5BJournal%5D)">In Vivo Visualization of Cranial Nerve Pathways in Humans Using Diffusion-Based Tractography.</a> Neurosurgery. 66 (4), 788-795 (2010).</li>
<li>Perrin, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Fiber+tracking+in+Q-ball+fields+using+regularized+particle+trajectories%5BTitle%5D)+AND+%22Inf+Process+Med+Imaging%22%5BJournal%5D)">Fiber tracking in Q-ball fields using regularized particle trajectories.</a> Inf Process Med Imaging. 19, 52-63 (2005).</li>
<li>Wedeen, V. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Diffusion+spectrum+magnetic+resonance+imaging+%28DSI%29+tractography+of+crossing+fibers%5BTitle%5D)+AND+%22Neuroimage%22%5BJournal%5D)">Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers.</a> Neuroimage. 41 (4), 1267-1277 (2008).</li>
<li>Yamamoto, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Diffusion+Tensor+Fiber+Tractography+of+the+Optic+Radiation%3A+Analysis+with+6-%2C+12-%2C+40-%2C+and+81-+Directional+Motion-Probing+Gradients%2C+a+Preliminary+Study%5BTitle%5D)+AND+%22AJNR+Am+J+Neuroradiol%22%5BJournal%5D)">Diffusion Tensor Fiber Tractography of the Optic Radiation: Analysis with 6-, 12-, 40-, and 81- Directional Motion-Probing Gradients, a Preliminary Study.</a> AJNR Am J Neuroradiol. 28 (1), 92-96 (2007).</li>
<li>Okada, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Diffusion+Tensor+Fiber+Tractography+for+Arteriovenous+Malformations%3A+Quantitative+Analyses+to+Evaluate+the+Corticospinal+Tract+and+Optic+Radiation%5BTitle%5D)+AND+%22AJNR+Am+J+Neuroradiol%22%5BJournal%5D)">Diffusion Tensor Fiber Tractography for Arteriovenous Malformations: Quantitative Analyses to Evaluate the Corticospinal Tract and Optic Radiation.</a> AJNR Am J Neuroradiol. 28 (6), 1107-1113 (2007).</li>
<li>Kuhnt, D., Bauer, M. H., Sommer, J., Merhof, D., Nimsky, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optic+Radiation+Fiber+Tractography+in+Glioma+Patients+Based+on+High+Angular+Resolution+Diffusion+Imaging+with+Compressed+Sensing+Compared+with+Diffusion+Tensor+Imaging+-+Initial+Experience%5BTitle%5D)+AND+%22PLoS+One%22%5BJournal%5D)">Optic Radiation Fiber Tractography in Glioma Patients Based on High Angular Resolution Diffusion Imaging with Compressed Sensing Compared with Diffusion Tensor Imaging - Initial Experience.</a> PLoS One. 8 (7), e70973(2013).</li>
<li>Basser, P. J., Pajevic, S., Pierpaoli, C., Duda, J., Aldroubi, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((In+vivo+fiber+tractography+using+DT-MRI+data%5BTitle%5D)+AND+%22Magn+Reson+Med%22%5BJournal%5D)">In vivo fiber tractography using DT-MRI data.</a> Magn Reson Med. 44 (4), 625-632 (2000).</li>
<li>Friman, O., Farneback, G., Westin, C. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+Bayesian+approach+for+stochastic+white+matter+tractography%5BTitle%5D)+AND+%22IEEE+Trans+Med+Imaging%22%5BJournal%5D)">A Bayesian approach for stochastic white matter tractography.</a> IEEE Trans Med Imaging. 25 (8), 965-978 (2006).</li>
<li>Mori, S., van Zijl, P. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Fiber+tracking%3A+principles+and+strategies+-+a+technical+review%5BTitle%5D)+AND+%22NMR+Biomed%22%5BJournal%5D)">Fiber tracking: principles and strategies - a technical review.</a> NMR Biomed. 15 (7-8), 468-480 (2002).</li>
<li>Alexander, D. C., Barker, G. J., Arridge, S. R. Detection and modeling of non-Gaussian apparent diffusion coefficient profiles in human brain data. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aAlexander%2C+DC+%22Magn+Reson+Med%22">Magn Reson Med</a>. 48 (2), 331-340 (2002).</li>
<li>Mori, S., Crain, B. J., Chacko, V. P., van Zijl, P. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Three-dimensional+tracking+of+axonal+projections+in+the+brain+by+magnetic+resonance+imaging%5BTitle%5D)+AND+%22Ann+Neurol%22%5BJournal%5D)">Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging.</a> Ann Neurol. 45, 265-269 (1999).</li>
<li>Conturo, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Tracking+neuronal+fiber+pathways+in+the+living+human+brain%5BTitle%5D)+AND+%22Proc+Natl+Acad+Sci+U+S+A%22%5BJournal%5D)">Tracking neuronal fiber pathways in the living human brain.</a> Proc Natl Acad Sci U S A. 96, 10422-10427 (1999).</li>
<li>Poupon, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Regularization+of+diffusion-based+direction+maps+for+the+tracking+of+brain+white+matter+fascicles%5BTitle%5D)+AND+%22Neuroimage%22%5BJournal%5D)">Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles.</a> Neuroimage. 12, 184-195 (2000).</li>
<li>Parker, G. J., Haroon, H. A., Wheeler-Kingshott, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+framework+for+a+streamline-based+probabilistic+index+of+connectivity+%28PICo%29+using+a+structural+interpretation+of+MRI+diffusion+measurements%5BTitle%5D)+AND+%22J+Magn+Reson+Imaging%22%5BJournal%5D)">A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements.</a> J Magn Reson Imaging. 18, 242-254 (2003).</li>
<li>Behrens, T. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Non-invasive+mapping+of+connections+between+human+thalamus+and+cortex+using+diffusion+imaging%5BTitle%5D)+AND+%22Nat+Neurosci%22%5BJournal%5D)">Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging.</a> Nat Neurosci. 6, 750-757 (2003).</li>
<li>Reinges, M. H., Schoth, F., Coenen, V. A., Krings, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Imaging+of+postthalamic+visual+fiber+tracts+by+anisotropic+diffusion+weighted+MRI+and+diffusion+tensor+imaging%3A+principles+and+applications%5BTitle%5D)+AND+%22European+Journal+of+Radiology%22%5BJournal%5D)">Imaging of postthalamic visual fiber tracts by anisotropic diffusion weighted MRI and diffusion tensor imaging: principles and applications.</a> European Journal of Radiology. 49, 91-104 (2004).</li>
<li>Sherbondy, A. J., Dougherty, R. F., Napel, S., Wandell, B. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Identifying+the+human+optic+radiation+using+diffusion+imaging+and+fiber%5BTitle%5D)+AND+%22J.+Vis%22%5BJournal%5D)">Identifying the human optic radiation using diffusion imaging and fiber.</a> J. Vis. 8 (10), (2008).</li>
</ol>

The authors declare that they have no competing financial interests.

DTI è una tecnica che consente di visualizzare il neurochirurgo tratti di sostanza bianca in vivo 8. Il percorso visivo è uno di questi tratti. Anche se questo metodo fornisce ai medici con nuove possibilità per quanto riguarda il trattamento di pazienti con lesioni riguardanti le regioni eloquenti del cervello dobbiamo dire che alcuni limiti di questa tecnica esistono ancora. La prima e più ovvia sfida è spostamento del cervello, che rimane una questione in esame 4. Dopo l&#39;apertu...

Diffusione tensore di imaging (DTI) è utilizzato per ritrarre WMT non invasivo nel cervello umano 1. E &#39;stato utilizzato negli ultimi dieci anni per ridurre il rischio di danneggiare le aree eloquenti del cervello durante l&#39;intervento chirurgico 1. DTI è stata eseguita in una cinquantina di pazienti tra il marzo 2012 e il gennaio 2014 e il ritrarre il percorso visivo. DTI potrebbe migliorare la conservazione delle aree eloquenti del cervello durante l&#39;intervento chirurgico, fornendo importanti informazioni sulla localizzazione anatomica dei tratti di sostanza bianca. E &#39;stato inserito nella pianificazione strategica per la resezione di lesioni cerebrali complesse 1. Tuttavia, la rappresentazione del percorso visivo rimane una sfida, perché non esiste uno standard per i parametri del DTI, la collocazione dei volumi di semi e interpretazione dei risultati 12. Diversi algoritmi sono stati implementati finora 19-21. Alcuni approcci concentrati su metodi deterministici 19, 22-25. Altri usavano metodi probabilistici, 26,27,29. Più di recente, le tecniche che utilizzano campi tensoriali Q-ball, immagini spettrali diffusione e ad alta risoluzione angolare Diffusion Imaging (HARDI) vengono utilizzati per raffigurare tratti di sostanza bianca tra gli altri il percorso visivo 1,13-15,18. Tuttavia, il tempo necessario per HARDI è significativamente più lungo di 45 min, il software non è disponibile in commercio e sottolinea applicazioni scientifiche 18. Il periodo di insegnamento per HARDI sembra essere più lungo per DTI 18. Il protocollo presentato è facilmente realizzabile e può essere utilizzato per la routine quotidiana in operazioni neurochirurgiche per evitare morbilità e migliorare il risultato postoperatorio. Il tempo supplementare per questo protocollo è inferiore a 9 min, che è significativamente più veloce rispetto ad altri protocolli 1,9,12,16. Riconoscendo il fatto che molti algoritmi sofisticati sono stati sviluppati recentemente le limita cartastesso per l&#39;utilizzo di un software disponibile in commercio e approvato dalla FDA. Tuttavia è obbligatorio per tener conto delle limitazioni di questa tecnica che sono menzionati sopra.

<table><tbody><tr><td>3-Tesla-MRI</td><td>General Electric</td><td>Signa LX version 9.1</td><td></td></tr><tr><td>Surgical Navigation System Program</td><td>Medtronic</td><td>9734478</td><td></td></tr><tr><td>Surgical Navigation System Program</td><td>Medtronic</td><td>4500810331&amp;nbsp; 20016318</td><td></td></tr></tbody></table>

dti of the visual pathway - white matter tracts and cerebral lesions

<html> DTI è una tecnica che identifica tratti di sostanza bianca (WMT) non invasiva in pazienti sani e non sani, utilizzando misure di diffusione. Simile a vie ottiche (VP), WMT non sono visibili con la risonanza magnetica classica o intra-operatoria con il microscopio. DIT aiuterà neurochirurghi per impedire la distruzione del VP, mentre la rimozione di lesioni adiacenti a questa WMT. Abbiamo effettuato DTI su cinquanta pazienti prima e dopo l&#39;intervento chirurgico tra il marzo 2012 al gennaio 2014 Per navigare abbiamo utilizzato una sequenza 3DT1 ponderato. Inoltre, abbiamo effettuato un T2-pesate e DTI-sequenze. I parametri utilizzati sono stati, FOV: 200 x 200 mm, spessore di strato: 2 mm, e matrice di acquisizione: 96 x 96 cedendo voxel quasi isotropico di 2 x 2 x 2 mm. Assiale MRI è stata effettuata utilizzando un gradiente di direzione 32 e uno b0-immagine. Abbiamo usato Echo-Planar-Imaging (EPI) e ASSET imaging parallelo con un fattore di accelerazione di 2 e B-valore di 800 s / mm ². Il tempo di scansione è inferiore a 9 min. ent &quot;&gt; I DTI-dati ottenuti sono stati elaborati utilizzando un programma approvato dalla FDA chirurgico sistema di navigazione che utilizza un approccio diretto fibra-tracking noto come l&#39;assegnazione di fibra da inseguimento continuo (FACT). Questa si basa sulla propagazione delle linee tra le regioni di interesse ( ROI) che è definito da un medico. un angolo massimo di 50, FA valore di 0,10 e ADC valore di arresto di 0,20 mm ² / s iniziare sono stati i parametri utilizzati per trattografia. Ci sono alcune limitazioni a questa tecnica. Il telaio limitato tempo di acquisizione impone compromessi nella qualità dell&#39;immagine. Un altro punto importante da non trascurare è il turno del cervello durante l&#39;intervento chirurgico. Per quanto riguarda la seconda risonanza magnetica intraoperatoria potrebbe essere utile. Inoltre, il rischio di falsi tratti positivi o falsi negativi deve essere preso in considerazione che potrebbero compromettere i risultati finali.

<html> Questo protocollo consente al medico di rappresentare adeguatamente le parti principali del VP. Può essere utilizzato con una piccola quantità di tempo al fine di evitare danni in pazienti con lesioni cerebrali prossimi alle aree eloquenti. Controlli postoperatori mostrano anche buoni risultati. VP è ritratto in figura 7 dopo che il paziente è stato operato da un glioblastoma. Figura 2 mostra il VP dopo recidiva di un glioblastoma. Gli autori riconoscono il fatto delle diffico...

Watch this Scientific Journal Video about DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions at JoVE.com

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

Diffusione tensore di imaging (DTI) è stata eseguita per provare a descrivere le parti principali del percorso visivo. L&#39;obiettivo era quello di utilizzare un farmaco approvato dalla workstation commerciale standard che potrebbe essere utilizzato per la routine di tutti i giorni per cercare di ridurre i danni post-operatoria del percorso visivo nei pazienti.

DTI della via visiva - White Matter Tracts e lesioni cerebrali

DTI is a technique that identifies white matter tracts (WMT) non-invasively in healthy and non-healthy patients using diffusion measurements. Similar to ...

dti-of-the-visual-pathway-white-matter-tracts-and-cerebral-lesions

Universidad de Cartagena UDEC

Research

JoVE Journal

Medicine

14.0K Views.  Centre Hospitalier de Luxembourg.  Diffusione tensore di imaging (DTI) è stata eseguita per provare a descrivere le parti principali del percorso visivo. L'obiettivo era quello di utilizzare un farmaco approvato dalla workstation commerciale standard che potrebbe essere utilizzato per la routine di tutti i giorni per cercare di ridurre i danni post-operatoria del percorso visivo nei pazienti. 

Video: DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

Dissection of Human Vitreous Body Elements for Proteomic Analysis

The vitreous is an optically clear, collagenous extracellular matrix that fills the inside of the eye and overlies the retina. 1,2 Abnormal interactions between vitreous substructures and the retina underlie several vitreoretinal diseases, including retinal tear and detachment, macular pucker, macular hole, age-related macular degeneration, vitreomacular traction, proliferative vitreoretinopathy, proliferative diabetic retinopathy, and inherited vitreoretinopathies. 1,2 The molecular composition of the vitreous substructures is not known. Since the vitreous body is transparent with limited surgical access, it has been difficult to study its substructures at the molecular level. We developed a method to separate and preserve these tissues for proteomic and biochemical analysis. The dissection technique in this experimental video shows how to isolate vitreous base, anterior hyaloid, vitreous core, and vitreous cortex from postmortem human eyes. One-dimensional SDS-PAGE analyses of each vitreous component showed that our dissection technique resulted in four unique protein profiles corresponding to each substructure of the human vitreous body. Identification of differentially compartmentalized proteins will reveal candidate molecules underlying various vitreoretinal diseases.

This video shows an effective technique for differentiating and dissecting the various semi-transparent structures of the human vitreous body in post mortem eyes.

Dissezione di Human Elements corpo vitreo per l&#39;analisi proteomica

The vitreous is an optically clear, collagenous extracellular matrix that fills the inside of the eye and overlies the retina. 1,2 Abnormal interactions ...

Ricerca

Medicina

The Application Of Permanent Middle Cerebral Artery Ligation in the Mouse

Focal cerebral ischemia is among the most common type of stroke seen in patients. Due to the clinical significance there has been a prolonged effort to develop suitable animal models to study the events that unfold during ischemic insult. These techniques include transient or permanent, focal or global ischemia models using many different animal models, with the most common being rodents.
The permanent MCA ligation method which is also referred as pMCAo in the literature is used extensively as a focal ischemia model in rodents 1-6. This method was originally described for rats by Tamura et al. in 1981 7. In this protocol a craniotomy was used to access the MCA and the proximal regions were occluded by electrocoagulation. The infarcts involve mostly cortical and sometimes striatal regions depending on the location of the occlusion. This technique is now well established and used in many laboratories 8-13. Early use of this technique led to the definition and description of &#x201C;infarct core&#x201D; and &#x201C;penumbra&#x201D; 14-16, and it is often used to evaluate potential neuroprotective compounds 10, 12, 13, 17. Although the initial studies were performed in rats, permanent MCA ligation has been used successfully in mice with slight modifications 18-20 .
This model yields reproducible infarcts and increased post-survival rates. Approximately 80% of the ischemic strokes in humans happen in the MCA area 21 and thus this is a very relevant model for stroke studies. Currently, there is a paucity of effective treatments available to stroke patients, and thus there is a need for good models to test potential pharmacological compounds and evaluate physiological outcomes. This method can also be used for studying intracellular hypoxia response mechanisms in vivo. 
Here, we present the MCA ligation surgery in a C57/BL6 mouse. We describe the pre-surgical preparation, MCA ligation surgery and 2,3,5 Triphenyltetrazolium chloride (TTC) staining for quantification of infarct volumes.

Middle cerebral artery (MCA) ligation is a technique to study focal cerebral ischemia in animal models. In this method, the middle cerebral artery is exposed by craniotomy and ligated by cauterization. This method gives highly reproducible infarct volumes and increased post-operative survival rates compared to other methods available.

L&#39;applicazione di permanente legatura dell&#39;arteria cerebrale media nel mouse

Focal cerebral ischemia is among the most common type of stroke seen in patients. Due to the clinical significance there has been a prolonged effort to ...

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Newly emerging theories suggest that the brain does not function as a cohesive unit in autism, and this discordance is reflected in the behavioral symptoms displayed by individuals with autism. While structural neuroimaging findings have provided some insights into brain abnormalities in autism, the consistency of such findings is questionable. Functional neuroimaging, on the other hand, has been more fruitful in this regard because autism is a disorder of dynamic processing and allows examination of communication between cortical networks, which appears to be where the underlying problem occurs in autism. Functional connectivity is defined as the temporal correlation of spatially separate neurological events1. Findings from a number of recent fMRI studies have supported the idea that there is weaker coordination between different parts of the brain that should be working together to accomplish complex social or language problems2,3,4,5,6. One of the mysteries of autism is the coexistence of deficits in several domains along with relatively intact, sometimes enhanced, abilities. Such complex manifestation of autism calls for a global and comprehensive examination of the disorder at the neural level. A compelling recent account of the brain functioning in autism, the cortical underconnectivity theory,2,7 provides an integrating framework for the neurobiological bases of autism. The cortical underconnectivity theory of autism suggests that any language, social, or psychological function that is dependent on the integration of multiple brain regions is susceptible to disruption as the processing demand increases. In autism, the underfunctioning of integrative circuitry in the brain may cause widespread underconnectivity. In other words, people with autism may interpret information in a piecemeal fashion at the expense of the whole. Since cortical underconnectivity among brain regions, especially the frontal cortex and more posterior areas 3,6, has now been relatively well established, we can begin to further understand brain connectivity as a critical component of autism symptomatology.
A logical next step in this direction is to examine the anatomical connections that may mediate the functional connections mentioned above. Diffusion Tensor Imaging (DTI) is a relatively novel neuroimaging technique that helps probe the diffusion of water in the brain to infer the integrity of white matter fibers. In this technique, water diffusion in the brain is examined in several directions using diffusion gradients. While functional connectivity provides information about the synchronization of brain activation across different brain areas during a task or during rest, DTI helps in understanding the underlying axonal organization which may facilitate the cross-talk among brain areas. This paper will describe these techniques as valuable tools in understanding the brain in autism and the challenges involved in this line of research.

Neuroimaging techniques, such as functional MRI and Diffusion Tensor Imaging have become increasingly useful in characterizing the cognitive and neural deficits in autism. An examination of brain connectivity in autism at a network level along with adaptations for scanning children with developmental disabilities is presented.

Probing the Brain in Autismo Utilizzando fMRI e imaging del tensore di diffusione

Newly emerging theories suggest that the brain does not function as a cohesive unit in autism, and this discordance is reflected in the behavioral ...

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)1, 2 protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for the purpose of monitoring task-relevant brain activity in networks of interest.

We describe a novel approach for simultaneous analysis of brain function and structure using magnetic resonance imaging (MRI). We assess brain structure with high-resolution diffusion-weighted imaging and white-matter fiber tractography. Unlike standard structural MRI, these techniques allow us to directly relate anatomical connectivity to functional properties of brain networks.

Co-analisi della struttura e delle funzioni cerebrali con fMRI e Diffusion-weighted imaging

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when ...

Neuroscienze

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. 	
DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels.	
In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.

Diffusion tensor imaging (DTI) basically serves as an MRI-based tool to identify in vivo the microstructure of the brain and pathological processes due to neurological disorders within the cerebral white matter. DTI-based analyses allow for application to brain diseases both at the group level and in single subject data.

Diffusion Tensor Imaging a risonanza magnetica in Analisi delle Malattie Neurodegenerative

Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present ...

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

In albinism, the number of ipsilaterally projecting retinal ganglion cells (RGCs) is significantly reduced. The retina and optic chiasm have been proposed as candidate sites for misrouting. Since a correlation between the number of lateral geniculate nucleus (LGN) relay neurons and LGN size has been shown, and based on previously reported reductions in LGN volumes in human albinism, we suggest that fiber projections from LGN to the primary visual cortex (V1) are also reduced. Studying structural differences in the visual system of albinism can improve the understanding of the mechanism of misrouting and subsequent clinical applications. Diffusion data and tractography are useful for mapping the OR (optic radiation). This manuscript describes two algorithms for OR reconstruction in order to compare brain connectivity in albinism and controls.An MRI scanner with a 32-channel head coil was used to acquire structural scans. A T1-weighted 3D-MPRAGE sequence with 1 mm3 isotropic voxel size was used to generate high-resolution images for V1 segmentation. Multiple proton density (PD) weighted images were acquired coronally for right and left LGN localization. Diffusion tensor imaging (DTI) scans were acquired with 64 diffusion directions. Both deterministic and probabilistic tracking methods were run and compared, with LGN as the seed mask and V1 as the target mask. Though DTI provides relatively poor spatial resolution, and accurate delineation of OR may be challenging due to its low fiber density, tractography has been shown to be advantageous both in research and clinically. Tract based spatial statistics (TBSS) revealed areas of significantly reduced white matter integrity within the OR in patients with albinism compared to controls. Pairwise comparisons revealed a significant reduction in LGN to V1 connectivity in albinism compared to controls. Comparing both tracking algorithms revealed common findings, strengthening the reliability of the technique.

This manuscript describes deterministic and probabilistic algorithms for white matter (WM) reconstruction, used to examine differences in optic radiation (OR) connectivity between albinism and controls. Although probabilistic tractography follows the true course of nerve fibers more closely, deterministic tractography was run to compare the reliability and reproducibility of both techniques.

Misurare la connettività nella Primaria via visiva in albinismo umano per mezzo del tensore di diffusione Imaging e Trattografia

In albinism, the number of ipsilaterally projecting retinal ganglion cells (RGCs) is significantly reduced. The retina and optic chiasm have been proposed ...

Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation

The purpose of this study is to show the methodology for the examination of the white matter connections of the supplementary motor area (SMA) complex (pre-SMA and SMA proper) using a combination of fiber dissection techniques on cadaveric specimens and magnetic resonance (MR) tractography. The protocol will also describe the procedure for a white matter dissection of a human brain, diffusion tensor tractography imaging, and three-dimensional documentation. The fiber dissections on human brains and the 3D documentation were performed at the University of Minnesota, Microsurgery and Neuroanatomy Laboratory, Department of Neurosurgery. Five postmortem human brain specimens and two whole heads were prepared in accordance with Klingler's method. Brain hemispheres were dissected step by step from lateral to medial and medial to lateral under an operating microscope, and 3D images were captured at every stage. All dissection results were supported by diffusion tensor imaging. Investigations on the connections in line with Meynert's fiber tract classification, including association fibers (short, superior longitudinal fasciculus I and frontal aslant tracts), projection fibers (corticospinal, claustrocortical, cingulum, and frontostriatal tracts), and commissural fibers (callosal fibers) were also conducted.

The purpose of this study is to show each step of the fiber dissection technique on human cadaveric brains, the 3D documentation of these dissections, and the diffusion tensor imaging of the anatomically dissected fiber pathways.

Connessioni a fibre della zona motori aggiuntiva Revisited: Metodologia della discizione a fibre, DTI e documentazione tridimensionale

The purpose of this study is to show the methodology for the examination of the white matter connections of the supplementary motor area (SMA) complex ...

Diffusion Tensor Magnetic Resonance Imaging in Chronic Spinal Cord Compression

Chronic spinal cord compression is the most common cause of spinal cord impairment in patients with nontraumatic spinal cord damage. Conventional magnetic resonance imaging (MRI) plays an important role in both confirming the diagnosis and evaluating the degree of compression. However, the anatomical detail provided by conventional MRI is not sufficient to accurately estimate neuronal damage and/or assess the possibility of neuronal recovery in chronic spinal cord compression patients. In contrast, diffusion tensor imaging (DTI) can provide quantitative results according to the detection of water molecule diffusion in tissues. In the present study, we develop a methodological framework to illustrate the application of DTI in chronic spinal cord compression disease. DTI fractional anisotropy (FA), apparent diffusion coefficients (ADCs), and eigenvector values are useful for visualizing microstructural pathological changes in the spinal cord. Decreased FA and increases in ADCs and eigenvector values were observed in chronic spinal cord compression patients compared to healthy controls. DTI could help surgeons understand spinal cord injury severity and provide important information regarding prognosis and neural functional recovery. In conclusion, this protocol provides a sensitive, detailed, and noninvasive tool to evaluate spinal cord compression.

Here, we present a protocol for the application of diffusion tensor imaging parameters to evaluate spinal cord compression.

Imaging a risonanza magnetica con Tensor di diffusione nella compressione del midollo spinale cronico

Chronic spinal cord compression is the most common cause of spinal cord impairment in patients with nontraumatic spinal cord damage. Conventional magnetic ...

Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is the most common type of acquired brain injury. Since patients with traumatic brain injury show a tremendous variability and heterogeneity (age, gender, type of trauma, other possible pathologies, etc.), animal models play a key role in unraveling factors that are limitations in clinical research. They provide a standardized and controlled setting to investigate the biological mechanisms of injury and repair following TBI. However, not all animal models mimic the diffuse and subtle nature of mTBI effectively. For example, the commonly used controlled cortical impact (CCI) and lateral fluid percussion injury (LFPI) models make use of a craniotomy to expose the brain and induce widespread focal trauma, which are not commonly seen in mTBI. Therefore, these experimental models are not valid to mimic mTBI. Thus, an appropriate model should be used to investigate mTBI. The Marmarou weight drop model for rats induces similar microstructural alterations and cognitive impairments as seen in patients who sustain mild trauma; therefore, this model was selected for this protocol. Conventional computed tomography and magnetic resonance imaging (MRI) scans commonly show no damage following a mild injury, because mTBI induces often only subtle and diffuse injuries. With diffusion weighted MRI, it is possible to investigate microstructural properties of brain tissue, which can provide more insight into the microscopic alterations following mild trauma. Therefore, the goal of this study is to obtain quantitative information of a selected region-of-interest (i.e., hippocampus) to follow up disease progression after obtaining a mild and diffuse brain injury.

The overall goal of this procedure is to obtain quantitative microstructural information of the hippocampus in a rat with mild traumatic brain injury. This is done using an advanced diffusion-weighted magnetic resonance imaging protocol and region-of-interest based analysis of parametric diffusion maps.

Advanced Diffusion Imaging nell'ippocampo di ratti con lievi lesioni cerebrali traumatiche

Mild traumatic brain injury (mTBI) is the most common type of acquired brain injury. Since patients with traumatic brain injury show a tremendous ...

Using Diffusion Tensor Imaging in Traumatic Brain Injury

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212;University of Southern California
Traditional brain imaging techniques using MRI are very good at visualizing the gross structures of the brain. A structural brain image made with MRI provides high contrast of the borders between gray and white matter, and information about the size and shape of brain structures. However, these images do not detail the underlying structure and integrity of white matter networks in the brain, which consist of axon bundles that interconnect local and distant brain regions.
Diffusion MRI uses pulse sequences that are sensitive to the diffusion of water molecules. By measuring the direction of diffusion, it is possible to make inferences about the structure of white matter networks in the brain. Water molecules within an axon are constrained in their movements by the cell membrane; instead of randomly moving in every direction with equal probability (isotropic movement), they are more likely to move in certain directions, in parallel with the axon (anisotropic movement; Figure 1). Therefore, measures of diffusion anisotropy are thought to reflect properties of the white matter such as fiber density, axon thickness, and degree of myelination. One common measure is fractional anisotropy (FA). FA values range from 0, which represents completely isotropic movement, to 1, reflecting maximum anisotropy.
<img alt="Figure 1" src="/files/ftp_upload/10276/10276fig1.jpg" /> 
Figure 1: Diffusion anisotropy. When the direction of diffusion is unconstrained and random, movement is measured in all directions equally. This is isotropic diffusion (A). When water molecules are contained within the axon of a neuron, diffusion is anisotropic, tending to occur more frequently along the direction of the axon (B). <a href="http://jove.unicartagenaproxy.elogim.com/files/ftp_upload/10276/10276fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
In this experiment we will use diffusion tensor imaging (DTI) to measure white matter integrity in traumatic brain injury (TBI). TBI occurs when an external force injures the brain, such as a blow to the head or a sudden movement like the kind that might occur in a car accident. This type of brain injury from mechanical forces is associated with diffuse axonal injury-damage to white matter throughout the brain. Because it is an injury affecting white matter integrity, standard neuroimaging techniques may not reveal the damage. However, measures of diffusion are especially sensitive to these anatomical changes. Following a study by Kraus et al.1, we compare a group of healthy controls to a group of people with TBI and use diffusion imaging to measure the effect of TBI on cerebral white matter. Furthermore, we will test the relationship between white matter integrity and cognitive function using an attention task.2 This study uses a region of interest (ROI) approach focusing on three white matter tracts: the splenium of the corpus callosum, the anterior corona radiata, and the superior longitudinal fasciculus (Figure 2).
<img alt="Figure 2" src="/files/ftp_upload/10276/10276fig2.jpg" /> 
Figure 2: Regions of interest. The three ROIs, defined from the ICBM DTI-81 atlas, are shown here in horizontal slices through the brain. In green is the splenium of the corpus callosum. The splenium is the most posterior part of the corpus callosum. In blue is the anterior corona radiata. The superior longitudinal fasciculus is shown in red. <a href="http://jove.unicartagenaproxy.elogim.com/files/ftp_upload/10276/10276fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Diffusion Tensor Imaging in Traumatic Brain Injury

Utilizzo dell'imaging con tensore di diffusione nelle lesioni cerebrali traumatiche

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212;University of Southern California
Traditional brain imaging techniques using MRI are ...

DTI della via visiva - White Matter Tracts e lesioni cerebrali

Riepilogo

Esplora Altri Video

Dissezione di Human Elements corpo vitreo per l'analisi proteomica

L'applicazione di permanente legatura dell'arteria cerebrale media nel mouse