7 Tesla MRI of the ex vivo human brain at 100 micron resolution

Edlow, Brian L.; Mareyam, Azma; Horn, Andreas; Polimeni, Jon̈athan R.; Witzel, Thomas; Tisdall, M. Dylan; Augustinack, Jean C.; Stockmann, Jason P.; Diamond, Bram R.; Stevens, Allison; Tirrell, Lee S.; Folkerth, Rebecca D.; Wald, Lawrence L.; Fischl, Bruce; Kouwe, André van der

doi:10.1038/s41597-019-0254-8

Cited by 219 publications

(176 citation statements)

References 34 publications

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“…We failed to include some patients because of corrupted or missing pre-or post-operative images. A 100-μm T1 scan of an ex-vivo human brain, acquired on a 7T MRI scanner (Edlow et al, 2019) served as a background template in Figure 1. The definition of the striatum, GPe and GPi boundaries was informed by the Distal atlas (Ewert et al, 2018).…”

Section: Group-based Microelectrode Track Trajectoriesmentioning

confidence: 99%

What is the true discharge rate and pattern of the striatal projection neurons in Parkinson’s disease and Dystonia?

Valsky

Grosberg²,

Israel

et al. 2020

eLife

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Dopamine and striatal dysfunctions play a key role in the pathophysiology of Parkinson's disease (PD) and Dystonia, but our understanding of the changes in the discharge rate and pattern of striatal projection neurons (SPNs) remains limited. Here, we recorded and examined multi-unit signals from the striatum of PD and dystonic patients undergoing deep brain stimulation surgeries. Contrary to earlier human findings, we found no drastic changes in the spontaneous discharge of the well-isolated and stationary SPNs of the PD patients compared to the dystonic patients or to the normal levels of striatal activity reported in healthy animals. Moreover, cluster analysis using SPN discharge properties did not characterize two well-separated SPN subpopulations, indicating no SPN subpopulation-specific (D1 or D2 SPNs) discharge alterations in the pathological state. Our results imply that small to moderate changes in spontaneous SPN discharge related to PD and Dystonia are likely amplified by basal ganglia downstream structures.

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Section: Group-based Microelectrode Track Trajectoriesmentioning

confidence: 99%

What is the true discharge rate and pattern of the striatal projection neurons in Parkinson’s disease and Dystonia?

Valsky

Grosberg²,

Israel

et al. 2020

eLife

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“…We scanned the patient's brain using a 7 Tesla MRI scanner and 3 Tesla MRI scanner, as previously described. 19 Briefly, the 7T Siemens Magnetom MRI scan utilized a custom-built 31channel receive array coil 49 and a MEF sequence 50…”

Section: Ex Vivo Mri Acquisitionmentioning

confidence: 99%

Tractography-Pathology Correlations in Traumatic Brain Injury: A TRACK-TBI Study

Nolan

Petersen²,

Iacono

et al. 2020

Preprint

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Diffusion tractography MRI can infer changes in network connectivity in patients with traumatic brain injury (TBI), but pathological substrates of disconnected tracts have not been well-defined due to a lack of high-resolution imaging with histopathological validation. We developed an ex vivo MRI protocol to analyze tract terminations at 750 μm resolution, followed by histopathologic evaluation of white matter pathology, and applied these methods to a 60-year-old man who died 26 days after TBI. Analysis of 74 cerebral hemispheric white matter regions revealed a heterogeneous distribution of tract disruptions. Associated histopathology identified variable white matter injury with patchy deposition of amyloid precursor protein and loss of neurofilament-positive axonal processes, myelin dissolution, astrogliosis, microgliosis, and perivascular hemosiderin-laden macrophages. Multiple linear regression revealed that tract disruption strongly correlated with neurofilament loss. Ex vivo diffusion MRI can detect tract disruptions in the human brain that reflect axonal injury.

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“…To graphically illustrate the electrode placement in relation to respective clinical outcome following DBS, active contacts of all patients from the two groups (upper vs. lower half in clinical improvement) were visualized, both in two-dimensional and three-dimensional space (sections S1.2 -S1.4 in the walkthrough tutorial). A 100micron T1 scan of an ex vivo human brain, acquired on a 7 Tesla MRI scanner with a scan time of 100 hours (Edlow et al, 2019) served as a background template throughout this paper and the definition of STN boundaries was informed by the DISTAL atlas (Ewert et al, 2018a).…”

Section: Lead Group Setup and Visualizationmentioning

confidence: 99%

“…Over the last decade, we aimed at minimizing this nonlinear error by introducing various concepts that ranged from multi-step linear transforms (Schönecker et al, 2009) over the introduction of multiple algorithms (Ewert et al, 2018a;Horn et al, 2019aHorn et al, , 2017aHorn et al, , 2017bHorn and Kühn, 2015) to the current multispectral default method that was recently empirically validated (Ewert et al, 2019b). Further methodological work such as the possibility to manually refine warp-fields has been published and implemented in Lead-DBS / Lead group (Edlow et al, 2019) but was not yet applied in the present work. Despite these efforts that may minimize bias introduced by warping electrodes to template space, these can likely never be overcome completely.…”

Section: Limitationsmentioning

confidence: 99%

Deep Brain Stimulation: Imaging on a group level

Treu

Strange

Oxenford

et al. 2020

Preprint

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Highlights We present a novel toolbox to carry out DBS imaging analyses on a grouplevel  Group electrodes are visualized in 2D and 3D and related to clinical regressors  A favorable target and connectivity profiles for the treatment of PD are validated Abstract Deep Brain Stimulation (DBS) is an established treatment option for movement disorders and is investigated to treat a growing number of other brain disorders. It has been shown that DBS effects are highly dependent on exact electrode placement, which is especially important when probing novel indications or stereotactic targets. Thus, considering precise electrode placement is crucial when investigating efficacy of DBS targets. To measure clinical improvement as a function of electrode placement, neuroscientific methodology and specialized software tools are needed. Such tools should have the goal to make electrode placement comparable across patients and DBS centers, and include statistical analysis options to validate and define optimal targets. Moreover, to allow for comparability across different research sites, these need to be performed within an algorithmically and anatomically standardized and openly available group space. With the publication of Lead-DBS software in 2014, an open-source tool was introduced that allowed for precise electrode reconstructions based on pre-and postoperative neuroimaging data. Here, we introduce Lead Group, implemented within the Lead-DBS environment and specifically designed to meet aforementioned demands. In the present article, we showcase the various processing streams of Lead Group in a retrospective cohort of 51 patients suffering from Parkinson's disease, who were implanted with DBS electrodes to the subthalamic nucleus (STN). Specifically, we demonstrate various ways to visualize placement of all electrodes in the group and map clinical improvement values to subcortical space. We do so by using active coordinates and volumes of tissue activated, showing converging evidence of an optimal DBS target in the dorsolateral STN. Second, we relate DBS outcome to the impact of each electrode on local structures by measuring overlap of stimulation volumes with the STN. Finally, we explore the software functions for connectomic mapping, which may be used to relate DBS outcomes to connectivity estimates with remote brain areas. We isolate a specific fiber bundlewhich structurally resembles the hyperdirect pathwaythat is associated with good clinical outcome in the cohort.The manuscript is accompanied by a walkthrough tutorial through which users are able to reproduce all main results presented in the present manuscript. All data and code needed to reproduce results are openly available.

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7 Tesla MRI of the ex vivo human brain at 100 micron resolution

Cited by 219 publications

References 34 publications

What is the true discharge rate and pattern of the striatal projection neurons in Parkinson’s disease and Dystonia?

What is the true discharge rate and pattern of the striatal projection neurons in Parkinson’s disease and Dystonia?

Tractography-Pathology Correlations in Traumatic Brain Injury: A TRACK-TBI Study

Deep Brain Stimulation: Imaging on a group level

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