Users can visualize anatomy exactly as they would on a fresh cadaver. Individual structures are reconstructed in accurate 3D, resulting in an unprecedented level of real accurate anatomy, dissectible in 3D.

The Table allows for exploration and learning of human anatomy beyond what any cadaver could offer. The Anatomage Table based education is proven to be effective. Growing publications show improved test scores, more efficient class and lab sessions, and student acceptance.

The Table allows students to interact with young and well preserved digital cadavers instead of aged and degenerated bodies. The Anatomage Table is the advanced technology available for your institution. Students, parents, alumni, or visitors will be impressed with the presence and visual impact of the Table.

There are no chemicals, no unpleasant smell, no recurring facility costs, no regulations and a higher student adoption rate over traditional cadavers. This system could set your institution as the technology leader in your community. The Anatomage Table is the only fully segmented real human 3D anatomy platform.

Anatomy is presented as a fully interactive, life-sized touch screen experience, in operatory bed form. The Anatomage Table is the foremost advanced virtual dissection technology available for your institution. Students, parents, alumni, and visitors will be impressed with the presence and visual impact of the Table.

There are no chemicals to deal with, no unpleasant smells, no recurring facility costs, no regulations and a higher student adoption rate over traditional cadavers.

This system will set your institution as the technology leader in your community. Anatomage Table offers 5 gross anatomy cases, 40 high-resolution regional anatomy cases, and more than 1, case study examples, featuring real anatomy in both patients and animal cases.

These are high-resolution and supreme quality cases that are unique to Anatomage. More than 2, anatomical structures are meticulously segmented from photographic images to deliver the most accurate real 3D anatomy.

Even individual vascular structures are meticulously traced to be accurate. These features cannot be copied overnight and we are proud to say that we are the only ones that offer such content. Students are also exposed to different anatomical variations and a large number of pathological variations.

Anatomage Table Clinical version is an FDA cleared radiology software. Compatible with any medical imaging data such as CT, MRI, it can integrate with PACS system to serve as a radiology review system for both clinical and educational purposes.

Anatomage offers the highest quality and performance volume rendering ever developed, refined over a decade, and proven to be reliable in more than 10, clinics world-wide. Hundreds of institutions have already adopted the Anatomage Table as an anatomy and physiology education tool.

There is a world-wide community for seminars, resource sharing, and new developments. Anatomage works closely with institutions developing class curriculums, lab integrations, and other teaching tools.

We collected thousands of real human cases and digitized them in the highest possible resolution and spent years painstakingly separating individual structure from each slice.

The contrast of the IR-TSE protocol is only moderately influenced by small changes of relative water content. On the other hand, the contrast of the TSE protocol is sensitive to slight changes of the proton-density ratio and even vanishes for ρ D.

i close to 1. Thus, the lack of contrast between the nuclei D. i compared with the Z. MR contrast for IR-TSE and TSE imaging in thalamic subfields. The solid and the dashed lines show the calculated contrast between the nuclei Z. i for the IR-TSE and the TSE sequences, respectively. Note the relative low dependence of the IR-TSE contrast on variations of the proton-density ratio.

The comparison of MR images with photographs and drawings of stereotactic atlases revealed that the Schaltenbrand and Wahren atlas 21 seems to be the most suitable one.

Its myelin-stained plates appear similar to the presented MR images with hypointense myelin-rich and more hyperintense myelin-poor tissues. Furthermore, the overlayable transparencies with drawn borders of the different thalamic compartments based on their cytoarchitecture notably facilitate anatomic assignment.

The remarkable Morel atlas 3 shows photographs of the variety of applied stainings only exemplarily. For image comparison and assignment, however, we rate camera lucida drawings less suitable than labeled photographs of stained sections.

Unfortunately, the atlas of Mai et al 22 presents only coronal views in high magnification with elaborate anatomic labeling but no sagittal and axial ones. Despite the high degree of differentiation, the proposed assignment of areas with specific MR imaging contrast to anatomically described tissues remains somewhat ambiguous.

One possible reason for discrepancies is the markedly different nature of the images under consideration. MR images integrate tissue properties over the applied section thickness and in-plane voxel resolution. In contrast to the presented MR images with 2- to 3-mm section thickness and 0.

Consequently, the MR images are more similar to an average of neighboring sections in anatomic atlases than to the MR imaging equivalent of 1 specific section.

This observation complicates anatomic assignment, especially if anatomy changes considerably over short distances in a direction orthogonal to the sections.

One example is the nucleus zentrolateralis intermedius. Because it is a thin layer between the larger ventral and dorsal intermediate nuclei, 1 we cannot exclude the observation that the field here assigned to Z.

i belongs to one of the latter subfields. Nevertheless, we decided to adopt the labeling of the atlas photograph with the best correspondence to the MR image. Besides the Schaltenbrand and Wahren atlas, 21 the partition of the lateral thalamus parallel to the La.

m and internal capsule appears even more conspicuous in the myelin staining in Fig 46 in the work of Hirai and Jones. For an elaborate analysis of which nuclei as defined by Hassler 1 correspond to the nomenclature of Hirai and Jones and a critical view on Hassler's very large number of subdivisions, we refer to the tables and discussions given elsewhere.

To successfully delineate the anatomic subfields in the lateral dorsal thalamus, T1-weighting is essential. Ultimately, an inversion recovery approach proved to be most suitable. The applied IR-TSE sequence, with adiabatic inversion and full ° refocussing pulses, allows us to measure only a small brain slab within legal specific absorption rate limits.

The resulting 8—10 possible sections are sufficient to cover the region of interest. To measure the planned number of sections, occasionally, we were forced by the specific absorption rate limit to increase the TR from the nominal 3 seconds up to 3. Whereas the concomitant slight increase in contrast is welcomed, the prolonging of scanning time is disadvantageous.

For IR-TSE imaging, the application of specific absorption rate—reducing techniques is possible yet untested for the presently proposed application. Unlike the specific absorption rate, CSF pulsation is a serious obstacle. Sharp and contrast-rich images can be reliably acquired in dorsal thalamic regions where the rather small flow distortions are controllable by an appropriately chosen phase-encoding direction.

However, in a manner strongly dependent on the subject, IR-TSE images around the ACPC plane can be heavily distorted by flow artifacts arising from the strong pulsatile CSF flow in the third ventricle. Often these cannot be suppressed sufficiently by the flow compensation options of the product TSE sequence.

Moreover, flow-synchronous triggering is far from simple—if not impossible—for inversion recovery—prepared MR images. Currently, CSF pulsation artifacts are the reason why only images of the dorsal aspect of the thalamus are described here.

In this regard, 3 recent studies explicitly described the delineation of thalamic nuclei at 7T. Whereas Abosch et al did not show sections located more dorsally, images presented by Deistung et al showed no indication of parcellation in the dorsal aspect of the lateral thalamus.

Also the La. m appears as a rather broad and diffuse band in the quantitative susceptibility map, notwithstanding the extremely high 0. The white matter—nulled MPRAGE images of Tourdias et al 19 explicitly indicated the nuclei ventral lateral anterior and posterior in the dorsal thalamus; however, they did not depict a structure similar to the D.

i boundary shown here. The coarser appearance of the La. m and of boundaries between the nuclei in their axial images is probably a consequence of the isotropic 1-mm 3 resolution.

All these points are not criticism. We just intended to underline the importance of determining the most suitable MR imaging approach to distinguish a particular thalamic nucleus from adjacent tissues.

Target definition is a core element in the complex process necessary for precise stereotactic implantation of brain electrodes. More precise localization of the supposed optimal target for therapeutic interventions cannot balance the impact of other sources of error such as image resolution or the mechanical accuracy of stereotactic systems.

However, it reduces the total error of the procedure and thus promotes a more comprehensive understanding of therapeutic outcomes. In that regard, 2 recent studies 29 , 30 investigated possible issues for neurosurgical targeting due to higher geometric distortions at 7T.

Without dissent, they reported relatively small distortions in the central brain regions and concluded that targeting is feasible with 7T imaging. Without question, the assumed advantage of the clear visualization of intrathalamic anatomy for DBS planning has yet to be validated.

We expect that among others, the La. m, the boundary between the nuclei D. i, the boundary between the nuclei D. e, and the dorsal aspect of the centre médian are valuable landmarks. Because the boundary between the D.

i is located only a few millimeters dorsal to the anterior margin of the nucleus ventrointermedius internus, it has the potential to promote a more accurate DBS planning in patients with tremor.

The successful transfer of the imaging protocol to patient scanning is strongly bound to an effective suppression of any head movement.

A thorough comparison of the recorded images of the subject trained to keep his head very still, on the one hand, with the images of the other 4 subjects, on the other hand, suggests that residual head motion may explain the sometimes less compelling visualization of subfields in the lateral thalamus.

Methods of mitigating these artifacts used in routine MR imaging investigations of patients with motor disorders, such as the use of sedative medications or MR imaging—compatible stereotactic head frames, are not, in our view, feasible options in a 7T context. Instead, prospective motion-correction technologies 31 that do not require a tight fixation of the head present a promising alternative.

Moreover, prospective correction of microscopic head motion has already been demonstrated to be fully compatible with 7T MR imaging.

This feasibility study demonstrates that IR-TSE-based MR imaging at 7T can reveal a high degree of anatomic detail in the dorsal thalamus. Even if none of the here-visualized subfields are currently a relevant DBS target, the more general hope for the future is that precise visualization of well-defined internal thalamic landmarks will improve the definition of target point coordinates for stereotactically guided implantation of DBS electrodes.

Jude Medical. Lars Buentjen— UNRELATED : Payment for Lectures including service on Speakers Bureaus : lectures on spinal cord stimulation St. Jude Medical and occipital nerve stimulation St.

Jude Medical , workshops on spinal cord stimulation St. Jude Medical, Boston Scientific, Medtronic. Indicates open access to non-subscribers at www.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail.

We do not capture any email address. This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking. Skip to main content. Research Article Brain. Open Access. Kanowski , J. Voges , L.

Buentjen , J. Stadler , H. Heinze and C. a From the Departments of Neurology M. b Stereotactic Neurosurgery J. c Leibniz Institute for Neurobiology Magdeburg J. d German Center for Neurodegenerative Diseases H. e nucleus dorso-oralis externus D. i nucleus dorso-oralis internus IR-TSE inversion recovery turbo-spin-echo La.

m lamella medialis Z. i nucleus zentrolateralis intermedius internus. Materials and Methods We examined 5 healthy subjects 2 men; 21—28 years of age in accordance with stipulations put forth by the local ethics committee.

Results Figure 1 shows axial MR images through the thalamus at a position of about 10 mm dorsal to the ACPC plane, with the corresponding section of the atlas of Schaltenbrand and Wahren 21 at position H. Fig 1. Fig 2. Fig 3. Fig 4. Fig 5. Fig 6.

Discussion The comparison of MR images with photographs and drawings of stereotactic atlases revealed that the Schaltenbrand and Wahren atlas 21 seems to be the most suitable one. Conclusions This feasibility study demonstrates that IR-TSE-based MR imaging at 7T can reveal a high degree of anatomic detail in the dorsal thalamus.

This work was supported by the German Research Foundation SFB , TP A2 and A Anatomy of the thalamus. In: Schaltenbrand G , Bailey P , eds. Introduction to Stereotaxis with an Atlas of the Human Brain. Vol 1.

Stuttgart, Germany : Thieme ; : — Jones EG. The Thalamus. New York : Plenum Press ; Morel A. Stereotactic Atlas of the Human Thalamus and Basal Ganglia. New York : Informa Healthcare ; Spiegelmann R , Nissim O , Daniels D , et al. Stereotactic targeting of the ventrointermediate nucleus of the thalamus by direct visualization with high-field MRI.

Stereotact Funct Neurosurg ; 84 : 19 — Yovel Y , Assaf Y. Virtual definition of neuronal tissue by cluster analysis of multi-parametric imaging virtual-dot-com imaging.

Neuroimage ; 35 : 58 — Gringel T , Schulz-Schaeffer W , Elolf E , et al. Optimized high-resolution mapping of magnetization transfer MT at 3 Tesla for direct visualization of substructures of the human thalamus in clinically feasible measurement time.

J Magn Reson Imaging ; 29 : — CrossRef PubMed. Young GS , Feng F , Shen H , et al. Susceptibility-enhanced 3-Tesla T1-weighted spoiled gradient echo of the midbrain nuclei for guidance of deep brain stimulation implantation.

Neurosurgery ; 65 : — Kanowski M , Voges J , Tempelmann C. Delineation of the nucleus centre median by proton density weighted magnetic resonance imaging at 3 T. Neurosurgery ; 66 3 suppl operative : E — Bender B , Mänz C , Korn A , et al. Optimized 3D magnetization-prepared rapid acquisition of gradient echo: identification of thalamus substructures at 3T.

AJNR Am J Neuroradiol ; 32 : — Traynor CR , Barker GJ , Crum WR , et al. Segmentation of the thalamus in MRI based on T1 and T2. Neuroimage ; 56 : — Buentjen L , Kopitzki K , Schmitt FC , et al.

Direct targeting of the thalamic anteroventral nucleus for deep brain stimulation by T1-weighted magnetic resonance imaging at 3 T.

Stereotact Funct Neurosurg ; 92 : 25 — Holmes CJ , Hoge R , Collins L , et al. Enhancement of MR images using registration for signal averaging. J Comput Assist Tomogr ; 22 : — Magnotta VA , Gold S , Andreasen NC , et al.

Visualization of subthalamic nuclei with cortex attenuated inversion recovery MR imaging. Neuroimage ; 11 : — Behrens TE , Johansen-Berg H , Woolrich MW , et al. Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nat Neurosci ; 6 : — Wiegell MR , Tuch DS , Larsson HB , et al.

Automatic segmentation of thalamic nuclei from diffusion tensor magnetic resonance imaging. Neuroimage ; 19 : — Deoni SC , Josseau MJ , Rutt BK , et al.

Visualization of thalamic nuclei on high resolution, multi-averaged T1 and T2 maps acquired at 1. Hum Brain Mapp ; 25 : — Abosch A , Yacoub E , Ugurbil K , et al. An assessment of current brain targets for deep brain stimulation surgery with susceptibility-weighted imaging at 7 Tesla.

Neurosurgery ; 67 : — Deistung A , Schäfer A , Schweser F , et al. Neuroimage ; 65 : — Tourdias T , Saranathan M , Levesque IR , et al.

Visualization of intra-thalamic nuclei with optimized white-matter-nulled MPRAGE at 7T. Neuroimage ; 84 : — Sussman MS , Vidarsson L , Pauly JM , et al. A technique for rapid single-echo spin-echo T2 mapping. Magn Reson Med ; 64 : — Schaltenbrand G , Wahren W. Atlas for Stereotaxy of The Human Brain.

Stuttgart, Germany : Thieme ; Mai KM , Assheuer J , Paxinos G. Atlas of the Human Brain. Amsterdam, the Netherlands : Elsevier ; Mai KM , Paxinos G Mai KM , Forutan F , Thalamus.

In: Mai KM , Paxinos G , eds. The Human Nervous System. Amsterdam, the Netherlands : Academic Press ; : — Yagishita A , Nakano I , Oda M , et al. Location of the corticospinal tract in the internal capsule at MR imaging.

Radiology ; : — Hirai T , Jones EG. A new parcellation of the human thalamus on the basis of histochemical staining. Brain Res Brain Res Rev ; 14 : 1 — Macchi G , Jones EG.

Toward an agreement on terminology of nuclear and subnuclear divisions of the motor thalamus. J Neurosurg ; 86 : — Percheron G , François C , Talbi B , et al. The primate motor thalamus. Brain Res Brain Res Rev ; 22 : 93 — Lemaire JJ , Sakka L , Ouchchane L , et al.

Anatomy of the human thalamus based on spontaneous contrast and microscopic voxels in high-field magnetic resonance imaging. Dammann P , Kraff O , Wrede KH , et al. Evaluation of hardware-related geometrical distortion in structural MRI at 7 Tesla for image-guided applications in neurosurgery.

Acad Radiol ; 18 : — Duchin Y , Abosch A , Yacoub E , et al. Feasibility of using ultra-high field 7 T MRI for clinical surgical targeting. PLoS One ; 7 : e Maclaren J , Herbst M , Speck O , et al.

Prospective motion correction in brain imaging: a review. Magn Reson Med ; 69 : — Maclaren J , Armstrong BS , Barrows RT , et al. Measurement and correction of microscopic head motion during magnetic resonance imaging of the brain. Previous Next. Back to top. In this issue.

Clicking on a tract in the Bundle List, or 3D Brain, will highlight that tract in both panels and open up the corresponding line plot showing diffusion properties of that tract for each subject.

Second, the Tract Profiles from each individual subject in the Bundle Details panels are linked to their metadata. A subject of interest can be selected based on their metadata to visualize their Tract Profiles relative to the group of other subjects, or a Tract Profile of interest can be selected to compare their metadata against the group of other subjects.

Third, columns in the Metadata table are linked to mean lines in the Bundle Details plots. Clicking a column will sort the metadata table based on the data in that field, and subjects will be divided into N groups by binning the data the number of groups can be defined in a control bar.

Each bin will be assigned a color and this color will be used for the rows of the metadata table, the mean lines in the Bundle Details plot, and the individual subject lines in the plot.

Each time a new column in the metadata is selected, the mean lines are updated in the plot, and the rows are sorted and colored appropriately in the metadata table. This feature provides an efficient tool to slice a large data set across different dimensions, examine how different subject characteristics relate to diffusion measures, determine subjects that are outliers within a group, and determine how different manners of grouping produce changes across different white matter fiber tracts.

Subject z -scores are updated based on the grouping. Fourth, the spatial dimension x -axis of the Bundle Details plots is linked to the fiber tracts in the 3D brain visualization.

Manual selection brushing 64 of a range of nodes in the Bundle Details plot, enabled by toggling on the brushable tracts feature in a control bar, highlights the corresponding region of the fiber tract in the 3D brain.

This feature allows a user to link statistics, group differences, or quantitative comparisons of an individual subject back to their brain anatomy. The published website also includes a link that allows users to download the.

csv files that contain the information that is displayed, for additional computational exploration through other tools e.

The only requirement is that the user has a GitHub account and afqbrowser-publish will create the public repository, build the webpage, and launch the web server through GitHub. org database for functional MRI derivatives 65 and capitalizing on the infrastructure from other open source database projects in the field 65 , In addition to launching an AFQ-Browser instance on GitHub, the afqbrowser-publish command also commits the data to the afqvault database.

This database stores all the data and the parameters from the AFQ object including scan parameters if these were entered. Long-term preservation of the data is important and, because GitHub does not guarantee long-term storage, we suggest using another service to ensure that the data are accessible in perpetuity.

Zenodo can be used to mint a persistent digital object identifier DOI for GitHub repositories. Other solutions include institutional repositories, to which users of AFQ-Browser can upload their data. We do not intend to enforce one solution or another, and we provide users with maximal control over this process.

Reproducing results that are generated by a GUI can be problematic since figures are generated based on a series of user inputs i. To solve this problem, we record the series of interactions as a query string, and append the URL with each user input to AFQ-Browser.

By copying or bookmarking the URL, a user can save and re-open a specific state of AFQ-Browser. Hence, a discovery made through a series of operations in the GUI is recorded in the URL and can be communicated and reproduced without a lengthy description of the series of user inputs. While AFQ-Browser supports flexible exploration of the data over many dimensions, it does not implement the myriad of computations that are useful for modeling dMRI data.

Indeed, there could be many other questions to ask with these data that cannot be addressed with the functionality supported by AFQ-Browser. Jupyter Notebooks are web applications that store code, text, and figures side by side 67 and run Python and other language code through a web-browser user interface.

Binder allows users to access collections of notebooks that are stored in Github, and to execute the code in these notebooks through their browser, without having to download any software.

To integrate between AFQ-Browser and Binder, the software automatically generates a button in the AFQ-Browser website Fig.

The example notebook we include performs some data visualization and simple unsupervised learning. Visitors can then extend the code from this example to capitalize on the wealth of statistics, machine learning, and data visualization libraries in Python. Thus, even without downloading the data, AFQ-Browser enables any computation that a visitor can imagine on the shared data, and computations that annotate the data e.

AFQ-Browser is open source and distributed under the permissive BSD 3-Clause License, which allows the software to be freely used and redistributed. It is not encumbered by any pending or obtained patents that would limit its use or redistribution.

The current stable release v0. org for every change introduced to the code. The HTML version of this Article was updated shortly after publication to include a link to the peer review file.

The PDF version of the Article was correct from the time of publication. Tushar, A. flusight: interactive visualizations for infectious disease forecasts.

Open Source Softw. Article ADS Google Scholar. Bostock, M. D 3 : Data-Driven Documents. IEEE Trans. Article PubMed Google Scholar. Cabello, R. Sherif, T. BrainBrowser: distributed, web-based neurological data visualization. Neuroinform 8 , 89 Hähn D, Rannou N, Ahtam B et al.

Neuroimaging in the browser using the X Toolkit. FPosters 3, poster, Lancaster, J. et al. Automated analysis of fundamental features of brain structures. Neuroinformatics 9 , — Article PubMed PubMed Central Google Scholar.

Ledoux, L. Fiberweb: diffusion visualization and processing in the browser. Jones, D. Tractometry and the hunt for the missing link: a physicist perspective. Article Google Scholar. Jbabdi, S. Tractography: where do we go from here? Brain Connect. Yeatman, J. Tract profiles of white matter properties: automating fiber-tract quantification.

PLoS ONE 7 , e Article ADS PubMed PubMed Central CAS Google Scholar. Yendiki, A. Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy. Jenkinson, M. Neuroimage 62 , — Fischl, B.

Teubner-Rhodes, S. Aging-resilient associations between arcuate fasciculus microstructure and vocabulary knowledge. Article CAS Google Scholar. Johnson, R. Diffusion properties of major white matter tracts in young, typically developing children.

Neuroimage 88 , — Travis, K. Cerebellar white matter pathways are associated with reading skills in children and adolescents. Brain Mapp. Development of white matter and reading skills. USA , E—E Article ADS PubMed Google Scholar.

Wang, Y. Development of tract-specific white matter pathways during early reading development in at-risk children and typical controls. Cortex 27 , —, PubMed Central Google Scholar. Lifespan maturation and degeneration of human brain white matter. Libero, L.

Multimodal neuroimaging based classification of autism spectrum disorder using anatomical, neurochemical, and white matter correlates. Cortex 66 , 46—59 Fingher, N. Toddlers later diagnosed with autism exhibit multiple structural abnormalities in temporal corpus callosum fibers.

Cortex 97 , —, Koldewyn, K. Differences in the right inferior longitudinal fasciculus but no general disruption of white matter tracts in children with autism spectrum disorder. USA , — Article ADS PubMed CAS Google Scholar.

Sacchet, M. Structural abnormality of the corticospinal tract in major depressive disorder. Mood Anxiety Disord. Article PubMed PubMed Central CAS Google Scholar.

Characterizing white matter connectivity in major depressive disorder: automated fiber quantification and maximum density paths. IEEE Int. Imaging 11 , — PubMed PubMed Central Google Scholar. Bahrami, N. Subconcussive head impact exposure and white matter tract changes over a single season of youth football.

Radiology , — Yeh, P. Compromised neurocircuitry in chronic blast-related mild traumatic brain injury. Main, K. DTI measures identify mild and moderate TBI cases among patients with complex health problems: a receiver operating characteristic analysis of U.

Neuroimage Clin. Ogawa, S. White matter consequences of retinal receptor and ganglion cell damage. Sarica, A. The corticospinal tract profile in amyotrophic lateral sclerosis. Tractography in amyotrophic lateral sclerosis using a novel probabilistic tool: a study with tract-based reconstruction compared to voxel-based approach.

Methods , 79—87 Keller, S. Preoperative automated fibre quantification predicts postoperative seizure outcome in temporal lobe epilepsy.

Brain , 68—82 Langer, N. White matter alterations in infants at risk for developmental dyslexia. Article PubMed Central Google Scholar. Saygin, Z. Tracking the roots of reading ability: white matter volume and integrity correlate with phonological awareness in prereading and early-reading kindergarten children.

Kitzes, J. The Practice of Reproducible Research: Case Studies and Lessons from the Data-Intensive Sciences University of California Press, Oakland, Goodman, S. What does research reproducibility mean? Poline, J. Data sharing in neuroimaging research. Wandell, B. Data management to support reproducible research.

Wickham, H. Tidy Data. Goodman, A. Principles of high-dimensional data visualization in astronomy. Mallik, S. Imaging outcomes for trials of remyelination in multiple sclerosis.

Psychiatry 85 , — Roosendaal, S. Regional DTI differences in multiple sclerosis patients. Neuroimage 44 , — Article PubMed CAS Google Scholar. Vrenken, H. Altered diffusion tensor in multiple sclerosis normal-appearing brain tissue: cortical diffusion changes seem related to clinical deterioration.

Imaging 23 , — Sbardella, E. DTI measurements in multiple sclerosis: evaluation of brain damage and clinical implications. Mezer, A. Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging. Dick, F. In vivo functional and myeloarchitectonic mapping of human primary auditory areas.

Weiskopf, N. Advances in MRI-based computational neuroanatomy: from morphometry to in-vivo histology. Lutti, A. Using high-resolution quantitative mapping of R1 as an index of cortical myelination. Neuroimage 93 , — Stüber, C. Myelin and iron concentration in the human brain: a quantitative study of MRI contrast.

Neuroimage 93 , 95— Li, J. A meta-analysis of diffusion tensor imaging studies in amyotrophic lateral sclerosis. a Department of Radiology. b Department of Otorhinolaryngology Nagoya University Graduate School of Medicine Nagoya, Japan.

References 1. Visualization of human inner ear anatomy with high-resolution MR imaging at 7T: initial clinical assessment. AJNR Am J Neuroradiol Aug Shibata T , Matsumoto S , Agishi T , et al.

Visualization of Reissner membrane and the spiral ganglion in human fetal cochlea by micro-computed tomography. Am J Otolaryngol ; 30 : — CrossRef PubMed.

Silver RD , Djalilian HR , Levine SC , et al. High-resolution magnetic resonance imaging of human cochlea. Laryngoscope ; : — Naganawa S , Yamazaki M , Kawai H , et al.

Visualization of endolymphatic hydrops in Ménière's disease with single-dose intravenous gadolinium-based contrast media using heavily T 2 -weighted 3D-FLAIR. Magn Reson Med Sci ; 9 : — Previous Next. Back to top. In this issue. American Journal of Neuroradiology Vol.

Table of Contents Index by author Complete Issue PDF. m and internal capsule appears even more conspicuous in the myelin staining in Fig 46 in the work of Hirai and Jones.

For an elaborate analysis of which nuclei as defined by Hassler 1 correspond to the nomenclature of Hirai and Jones and a critical view on Hassler's very large number of subdivisions, we refer to the tables and discussions given elsewhere. To successfully delineate the anatomic subfields in the lateral dorsal thalamus, T1-weighting is essential.

Ultimately, an inversion recovery approach proved to be most suitable. The applied IR-TSE sequence, with adiabatic inversion and full ° refocussing pulses, allows us to measure only a small brain slab within legal specific absorption rate limits.

The resulting 8—10 possible sections are sufficient to cover the region of interest. To measure the planned number of sections, occasionally, we were forced by the specific absorption rate limit to increase the TR from the nominal 3 seconds up to 3.

Whereas the concomitant slight increase in contrast is welcomed, the prolonging of scanning time is disadvantageous.

For IR-TSE imaging, the application of specific absorption rate—reducing techniques is possible yet untested for the presently proposed application. Unlike the specific absorption rate, CSF pulsation is a serious obstacle. Sharp and contrast-rich images can be reliably acquired in dorsal thalamic regions where the rather small flow distortions are controllable by an appropriately chosen phase-encoding direction.

However, in a manner strongly dependent on the subject, IR-TSE images around the ACPC plane can be heavily distorted by flow artifacts arising from the strong pulsatile CSF flow in the third ventricle. Often these cannot be suppressed sufficiently by the flow compensation options of the product TSE sequence.

Moreover, flow-synchronous triggering is far from simple—if not impossible—for inversion recovery—prepared MR images.

Currently, CSF pulsation artifacts are the reason why only images of the dorsal aspect of the thalamus are described here. In this regard, 3 recent studies explicitly described the delineation of thalamic nuclei at 7T. Whereas Abosch et al did not show sections located more dorsally, images presented by Deistung et al showed no indication of parcellation in the dorsal aspect of the lateral thalamus.

Also the La. m appears as a rather broad and diffuse band in the quantitative susceptibility map, notwithstanding the extremely high 0. The white matter—nulled MPRAGE images of Tourdias et al 19 explicitly indicated the nuclei ventral lateral anterior and posterior in the dorsal thalamus; however, they did not depict a structure similar to the D.

i boundary shown here. The coarser appearance of the La. m and of boundaries between the nuclei in their axial images is probably a consequence of the isotropic 1-mm 3 resolution.

All these points are not criticism. We just intended to underline the importance of determining the most suitable MR imaging approach to distinguish a particular thalamic nucleus from adjacent tissues.

Target definition is a core element in the complex process necessary for precise stereotactic implantation of brain electrodes. More precise localization of the supposed optimal target for therapeutic interventions cannot balance the impact of other sources of error such as image resolution or the mechanical accuracy of stereotactic systems.

However, it reduces the total error of the procedure and thus promotes a more comprehensive understanding of therapeutic outcomes. In that regard, 2 recent studies 29 , 30 investigated possible issues for neurosurgical targeting due to higher geometric distortions at 7T. Without dissent, they reported relatively small distortions in the central brain regions and concluded that targeting is feasible with 7T imaging.

Without question, the assumed advantage of the clear visualization of intrathalamic anatomy for DBS planning has yet to be validated. We expect that among others, the La. m, the boundary between the nuclei D. i, the boundary between the nuclei D.

e, and the dorsal aspect of the centre médian are valuable landmarks. Because the boundary between the D. i is located only a few millimeters dorsal to the anterior margin of the nucleus ventrointermedius internus, it has the potential to promote a more accurate DBS planning in patients with tremor.

The successful transfer of the imaging protocol to patient scanning is strongly bound to an effective suppression of any head movement. A thorough comparison of the recorded images of the subject trained to keep his head very still, on the one hand, with the images of the other 4 subjects, on the other hand, suggests that residual head motion may explain the sometimes less compelling visualization of subfields in the lateral thalamus.

Methods of mitigating these artifacts used in routine MR imaging investigations of patients with motor disorders, such as the use of sedative medications or MR imaging—compatible stereotactic head frames, are not, in our view, feasible options in a 7T context.

Instead, prospective motion-correction technologies 31 that do not require a tight fixation of the head present a promising alternative. Moreover, prospective correction of microscopic head motion has already been demonstrated to be fully compatible with 7T MR imaging.

This feasibility study demonstrates that IR-TSE-based MR imaging at 7T can reveal a high degree of anatomic detail in the dorsal thalamus.

Even if none of the here-visualized subfields are currently a relevant DBS target, the more general hope for the future is that precise visualization of well-defined internal thalamic landmarks will improve the definition of target point coordinates for stereotactically guided implantation of DBS electrodes.

Jude Medical. Lars Buentjen— UNRELATED : Payment for Lectures including service on Speakers Bureaus : lectures on spinal cord stimulation St. Jude Medical and occipital nerve stimulation St. Jude Medical , workshops on spinal cord stimulation St. Jude Medical, Boston Scientific, Medtronic. Indicates open access to non-subscribers at www.

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Skip to main content. Research Article Brain. Open Access. Kanowski , J. Voges , L. Buentjen , J. Stadler , H. Heinze and C. a From the Departments of Neurology M. b Stereotactic Neurosurgery J. c Leibniz Institute for Neurobiology Magdeburg J.

d German Center for Neurodegenerative Diseases H. e nucleus dorso-oralis externus D. i nucleus dorso-oralis internus IR-TSE inversion recovery turbo-spin-echo La. m lamella medialis Z. i nucleus zentrolateralis intermedius internus.

Materials and Methods We examined 5 healthy subjects 2 men; 21—28 years of age in accordance with stipulations put forth by the local ethics committee.

Results Figure 1 shows axial MR images through the thalamus at a position of about 10 mm dorsal to the ACPC plane, with the corresponding section of the atlas of Schaltenbrand and Wahren 21 at position H. Fig 1. Fig 2. Fig 3. Fig 4. Fig 5. Fig 6. Discussion The comparison of MR images with photographs and drawings of stereotactic atlases revealed that the Schaltenbrand and Wahren atlas 21 seems to be the most suitable one.

Conclusions This feasibility study demonstrates that IR-TSE-based MR imaging at 7T can reveal a high degree of anatomic detail in the dorsal thalamus. This work was supported by the German Research Foundation SFB , TP A2 and A Anatomy of the thalamus. In: Schaltenbrand G , Bailey P , eds.

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Optimized high-resolution mapping of magnetization transfer MT at 3 Tesla for direct visualization of substructures of the human thalamus in clinically feasible measurement time.

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