Evidence map›Paper›PMID 35851977›Full record

ArticleHuman brain mapping2022

A hierarchical anatomical framework and workflow for organizing stereotactic encephalography in epilepsy.

Bryan Zheng, Ben Hsieh, Nathaniel Rex, Peter M Lauro, Scott A Collins, Andrew S Blum, Julie L Roth, Neishay Ayub, Wael F Asaad

Open access · goldAbstract read
In one paragraph

Article in Human brain mapping, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 45% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Bryan ZhengDepartment of Neurosurgery, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.ORCID 0000-0002-7846-8389
Ben HsiehDepartment of Diagnostic Imaging, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Nathaniel RexDepartment of Diagnostic Imaging, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Peter M LauroDepartment of Neurosurgery, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Scott A CollinsDepartment of Diagnostic Imaging, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Andrew S BlumDepartment of Neurology, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Julie L RothDepartment of Neurology, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Neishay AyubDepartment of Neurology, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Wael F AsaadDepartment of Neurosurgery, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Brown University · US

Funding

Interdisciplinary Predoctoral Neuroscience Training Program in the Neuroscience Graduate Program.T32MH020068 · NIMH · BROWN UNIVERSITY · PI LIPSCOMBE, DIANE, SHEINBERG, DAVID L · 1999 to 2025
$7.6M
Brain Science Compute ClusterS10OD025181 · OD · BROWN UNIVERSITY · PI SANES, JEROME N · 2019 to 2019
$600k
NIH HHS S10 OD025181NIMH NIH HHS T32 MH020068
6 · The paper itself

Abstract

Stereotactic electroencephalography (SEEG) is an increasingly utilized method for invasive monitoring in patients with medically intractable epilepsy. Yet, the lack of standardization for labeling electrodes hinders communication among clinicians. A rational clustering of contacts based on anatomy rather than arbitrary physical leads may help clinical neurophysiologists interpret seizure networks. We identified SEEG electrodes on post-implant CTs and registered them to preoperative MRIs segmented according to an anatomical atlas. Individual contacts were automatically assigned to anatomical areas independent of lead. These contacts were then organized using a hierarchical anatomical schema for display and interpretation. Bipolar-referenced signal cross-correlations were used to compare the similarity of grouped signals within a conventional montage versus this anatomical montage. As a result, we developed a hierarchical organization for SEEG contacts using well-accepted, free software that is based solely on their post-implant anatomical location. When applied to three example SEEG cases for epilepsy, clusters of contacts that were anatomically related collapsed into standardized groups. Qualitatively, seizure events organized using this framework were better visually clustered compared to conventional schemes. Quantitatively, signals grouped by anatomical region were more similar to each other than electrode-based groups as measured by Pearson correlation. Further, we uploaded visualizations of SEEG reconstructions into the electronic medical record, rendering them durably useful given the interpretable electrode labels. In conclusion, we demonstrate a standardized, anatomically grounded approach to the organization of SEEG neuroimaging and electrophysiology data that may enable improved communication among and across surgical epilepsy teams and promote a clearer view of individual seizure networks.

Indexed as

Drug Resistant EpilepsyEpilepsyElectrodes, ImplantedElectroencephalographyHumansSeizuresStereotaxic TechniquesWorkflowepilepsyneuroanatomyneuroimagingneurophysiologySEEGseizures

Identifiers

PMID35851977
PMCPMC9582372
OpenAlexW4285797446

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.