Evidence map›Paper›PMID 37160583›Full record

ArticleInternational journal of computer assisted radiology and surgery2023

Twin-S: a digital twin for skull base surgery.

Hongchao Shu, Ruixing Liang, Zhaoshuo Li, Anna Goodridge, Xiangyu Zhang, Hao Ding, Nimesh Nagururu, Manish Sahu, Francis X Creighton, Russell H Taylor and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–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

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Perception-first digital twin for augmented reality microsurgery.International journal of computer assisted radiology and surgery · 2026
    Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. A multimodal digital twin for autonomous micro-drilling in scientific exploration.International journal of computer assisted radiology and surgery · 2025
    Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Article
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  17. Article
  18. ENTRI: Enhanced Navigational Toolkit for Robotic Interventions.IEEE transactions on medical robotics and bionics · 2024
    Article
  19. Article
  20. Review
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

12 authors.

Hongchao Shu *Johns Hopkins University, Baltimore, MD, USA. hshu4@jhu.edu.
Ruixing Liang *Johns Hopkins University, Baltimore, MD, USA.
Zhaoshuo Li *Johns Hopkins University, Baltimore, MD, USA.
Anna GoodridgeJohns Hopkins University, Baltimore, MD, USA.
Xiangyu ZhangJohns Hopkins University, Baltimore, MD, USA.
Hao DingJohns Hopkins University, Baltimore, MD, USA.
Nimesh NagururuJohns Hopkins Medicine, Baltimore, MD, USA.
Manish SahuJohns Hopkins University, Baltimore, MD, USA.
Francis X CreightonJohns Hopkins Medicine, Baltimore, MD, USA.
Russell H TaylorJohns Hopkins University, Baltimore, MD, USA.
Adnan MunawarJohns Hopkins University, Baltimore, MD, USA.
Mathias UnberathJohns Hopkins University, Baltimore, MD, USA.

Funding

Cooperative Control Robotics and Computer Vision: Development of Semi-Autonomous Temporal Bone and Skull Base SurgeryK08DC019708 · NIDCD · JOHNS HOPKINS UNIVERSITY · PI CREIGHTON, FRANCIS XAVIER · 2021 to 2025
$959k
NIDCD NIH HHS K08 DC019708NIDCD NIH HHS NIDCD K08 Grant DC019708
6 · The paper itself

Abstract

purposeDigital twins are virtual replicas of real-world objects and processes, and they have potential applications in the field of surgical procedures, such as enhancing situational awareness. We introduce Twin-S, a digital twin framework designed specifically for skull base surgeries.

methodsTwin-S is a novel framework that combines high-precision optical tracking and real-time simulation, making it possible to integrate it into image-guided interventions. To guarantee accurate representation, Twin-S employs calibration routines to ensure that the virtual model precisely reflects all real-world processes. Twin-S models and tracks key elements of skull base surgery, including surgical tools, patient anatomy, and surgical cameras. Importantly, Twin-S mirrors real-world drilling and updates the virtual model at frame rate of 28.

resultsOur evaluation of Twin-S demonstrates its accuracy, with an average error of 1.39 mm during the drilling process. Our study also highlights the benefits of Twin-S, such as its ability to provide augmented surgical views derived from the continuously updated virtual model, thus offering additional situational awareness to the surgeon.

conclusionWe present Twin-S, a digital twin environment for skull base surgery. Twin-S captures the real-world surgical progresses and updates the virtual model in real time through the use of modern tracking technologies. Future research that integrates vision-based techniques could further increase the accuracy of Twin-S.

Indexed as

Surgery, Computer-AssistedComputer SimulationHumansImaging, Three-DimensionalNeurosurgical ProceduresSkull BaseComputer visionHuman–computer interactionImage-guided interventionIntervention planning and simulation

Identifiers

PMID37160583
PMCPMC11110948

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Registered trials

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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.