Probabilistic conversion of neurosurgical DBS electrode coordinates into MNI space

Description: In neurosurgical literature, findings such as deep brain stimulation (DBS) electrode positions are conventionally reported in relation to the anterior and posterior commissures of the individual patient (AC/PC coordinates). However, the neuroimaging literature including neuroanatomical atlases, activation patterns, and brain connectivity maps has converged on a different population-based standard (MNI coordinates). Ideally, one could relate these two literatures by directly transforming MRIs from neurosurgical patients into MNI space. However obtaining these patient MRIs can prove difficult or impossible, especially for older studies or those with hundreds of patients. Here, we introduce a methodology for mapping an AC/PC coordinate (such as a DBS electrode position) to MNI space without the need for MRI scans from the patients themselves. We validate our approach using a cohort of DBS patients in which MRIs are available, and test whether several variations on our approach provide added benefit. We then use our approach to convert previously reported DBS electrode coordinates from eight different neurological and psychiatric diseases into MNI space. Finally, we demonstrate the value of such a conversion using the DBS target for essential tremor as an example, relating the site of the active DBS contact to different MNI atlases as well as anatomical and functional connectomes in MNI space.

Related article: http://doi.org/10.1016/j.neuroimage.2017.02.004

View ID Name Type
Field Value
Compact Identifierhttps://identifiers.org/neurovault.collection:2200
Add DateFeb. 7, 2017, 2:52 a.m.
Uploaded byandreashorn
Contributors
Related article DOI10.1016/j.neuroimage.2017.02.004
Related article authorsAndreas Horn, Andrea A. Kühn, Angela Merkl, Ludy Shih, Ron Alterman and Michael Fox
Citation guidelines

If you use the data from this collection please include the following persistent identifier in the text of your manuscript:

https://identifiers.org/neurovault.collection:2200

This will help to track the use of this data in the literature. In addition, consider also citing the paper related to this collection.