Evidence map›Paper›PMID 31528660›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2019

Development and evaluation of a "trackerless" surgical planning and guidance system based on 3D Slicer.

Xiaochen Yang, Saramati Narasimhan, Ma Luo, Reid C Thompson, Lola B Chambless, Peter J Morone, Le He, Benoit M Dawant, Michael I Miga

Open access · greenAbstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. 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 2 institutions in 1 country.

Xiaochen YangVanderbilt University, Department of Electrical Engineering and Computer Science, Nashville, Tennessee, United States.
Saramati NarasimhanVanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.ORCID https://orcid.org/0000-0002-2965-2200
Ma LuoVanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.ORCID https://orcid.org/0000-0002-2928-0996
Reid C ThompsonVanderbilt University Medical Center, Department of Neurological Surgery, Nashville, Tennessee, United States.
Lola B ChamblessVanderbilt University Medical Center, Department of Neurological Surgery, Nashville, Tennessee, United States.
Peter J MoroneVanderbilt University Medical Center, Department of Neurological Surgery, Nashville, Tennessee, United States.
Le HeVanderbilt University Medical Center, Department of Neurological Surgery, Nashville, Tennessee, United States.
Benoit M DawantVanderbilt University, Department of Electrical Engineering and Computer Science, Nashville, Tennessee, United States.
Michael I MigaVanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.
Vanderbilt University · USVanderbilt University Medical Center · US

Funding

Multimodal Registration of the Brain's Cortical SurfaceR01NS049251 · NINDS · VANDERBILT UNIVERSITY · PI GOLBY, ALEXANDRA J, MIGA, MICHAEL IAN · 2005 to 2018
$6.7M
NINDS NIH HHS R01 NS049251
6 · The paper itself

Abstract

Conventional optical tracking systems use cameras sensitive to near-infrared (NIR) light and NIR illuminated/active-illuminating markers to localize instrumentation and the patient in the operating room (OR) physical space. This technology is widely used within the neurosurgical theater and is a staple in the standard of care for craniotomy planning. To accomplish, planning is largely conducted at the time of the procedure in the OR with the patient in a fixed head orientation. We propose a framework to achieve this in the OR without conventional tracking technology, i.e., a "trackerless" approach. Briefly, we investigate an extension of the 3D Slicer which combines surgical planning and craniotomy designation. While taking advantage of the well-developed 3D Slicer platform, we implement advanced features to aid the neurosurgeon in planning the location of the anticipated craniotomy relative to the preoperatively imaged tumor in a physical-to-virtual setup, and then subsequently aid the true physical procedure by correlating that physical-to-virtual plan with an intraoperative magnetic resonance imaging-to-physical registered field-of-view display. These steps are done such that the craniotomy can be designated without the use of a conventional optical tracking technology. To test this approach, four experienced neurosurgeons performed experiments on five different surgical cases using our 3D Slicer module as well as the conventional procedure for comparison. The results suggest that our planning system provides a simple, cost-efficient, and reliable solution for surgical planning and delivery without the use of conventional tracking technologies. We hypothesize that the combination of this craniotomy planning approach and our past developments in cortical surface registration and deformation tracking using stereo-pair data from the surgical microscope may provide a fundamental realization of an integrated trackerless surgical guidance platform.

Indexed as

3D Slicercraniotomy contourneurosurgical procedurereconstructionsurgical planningtrackerlesstracking

Identifiers

PMID31528660
PMCPMC6732664
OpenAlexW2971884498

What OpenQuestion holds

Textmetadata
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.