Evidence map›Paper›PMID 41356123›Full record

ArticleIEEE transactions on medical robotics and bionics2023

Real-Time 3-D Video Reconstruction for Guidance of Transventricular Neurosurgery.

Prasad Vagdargi, Ali Uneri, Xiaoxuan Zhang, Craig K Jones, Pengwei Wu, Runze Han, Alejandro Sisniega, Junghoon Lee, Patrick Helm, Mark Luciano and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IEEE transactions on medical robotics and bionics, 2023. 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
–field-weighted citation impact
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.

  1. Article
  2. Model-based individual life-spanning documentation in visceral surgery: a proof of concept.International journal of computer assisted radiology and surgery · 2024
    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

13 authors.

Prasad VagdargiComputer Science Department, Johns Hopkins University, Baltimore, MD 21218 USA.ORCID 0000-0002-2740-6604
Ali UneriDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218 USA.ORCID 0000-0003-3419-1805
Xiaoxuan ZhangDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218 USA.ORCID 0000-0003-0365-6833
Craig K JonesComputer Science Department, Johns Hopkins University, Baltimore, MD 21218 USA.ORCID 0000-0002-0629-3006
Pengwei WuDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218 USA.
Runze HanDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218 USA.
Alejandro SisniegaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218 USA.
Junghoon LeeDepartment of Radiation Oncology, Johns Hopkins University, Baltimore, MD 21218 USA.ORCID 0000-0002-3004-8625
Patrick HelmResearch and Development Division, Medtronic, Littleton, MA 01460 USA.
Mark LucianoDepartment of Neurosurgery, Johns Hopkins University, Baltimore, MD 21218 USA.
William S AndersonDepartment of Neurosurgery, Johns Hopkins University, Baltimore, MD 21218 USA.ORCID 0000-0003-0958-050X
Gregory D HagerComputer Science Department, Johns Hopkins University, Baltimore, MD 21218 USA.ORCID 0000-0002-6662-9763
Jeffrey H SiewerdsenDepartment of Computer Science and the Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218 USA.ORCID 0000-0001-6644-1317

Funding

Imaging, Guidance, and QA for Emerging High-Precision Neurosurgical TechniquesU01NS107133 · NINDS · JOHNS HOPKINS UNIVERSITY · PI SIEWERDSEN, JEFFREY H, UNERI, ALI · 2019 to 2023
$3.3M
NINDS NIH HHS U01 NS107133
6 · The paper itself

Abstract

Neuroendoscopic approach to deep-brain targets imparts deformation of the ventricles and adjacent parenchyma, limiting the accuracy of conventional neuronavigation. We report a method for 3D endoscopic reconstruction and registration via simultaneous localization and mapping (SLAM) for real-time guidance with or without robotic assistance. The aim is to permit augmented video overlay of structures registered from preoperative or intraoperative 3D images within and beyond the endoscopic field of view for more accurate targeting in the presence of deep-brain deformation. Phantom studies were performed to evaluate geometric accuracy and uncertainty in distinct scenarios of limited data (feature sparsity and scene occlusion), demonstrating performance over a broad range of challenges to endoscopic data. Reconstruction and registration accuracy were maintained even with up to 40% loss in feature density or 120° of the visual scene occluded. Overall, the method achieved a high degree of geometric accuracy, with target registration error of 1.02 mm and runtime supporting real-time guidance (3.45 Hz, representing a >16× speedup with SLAM approach compared to previous work). The studies establish essential quantitative performance characteristics and validation that are essential to future translation to clinical studies.

Indexed as

augmented realitycomputer visionImage-guided surgeryintraoperative imagingneurosurgerysimultaneous localization and mapping

Identifiers

PMID41356123
PMCPMC12680102

What OpenQuestion holds

Textmetadata
LicenceTDM
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.