Evidence map›Paper›PMID 36561572›Full record

ArticleFrontiers in surgery2022

High fidelity simulation of the endoscopic transsphenoidal approach: Validation of the UpSurgeOn TNS Box.

Nicola Newall, Danyal Z Khan, John G Hanrahan, James Booker, Anouk Borg, Joseph Davids, Federico Nicolosi, Siddharth Sinha, Neil Dorward, Hani J Marcus

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07568366 (The Application of Artificial Intelligence to Patients Undergoing Endoscopic Transsphenoidal Surgery), which is not on this map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 3% 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.

NCT07568366 early_phase1not yet recruitingnot on this mapstarted 2026, after this paper: background citation

The Application of Artificial Intelligence to Patients Undergoing Endoscopic Transsphenoidal Surgery: a Single-site Prospective Feasibility and Exploratory Study (IDEAL Stage 1 and 2a)

TypeinterventionalSponsorUniversity College, LondonRan2026 to 2029Enrolled30ConditionsPituitary AdenomaArmsLive intra-op AI analysis of endoscopic video feed, with output displayed on supplementary monitor
3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
  2. Real-time visualization of endoscope-brain interactions using a transparent ventricular model.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2026
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  10. Blood Harmonisation of Endoscopic Transsphenoidal Surgical Video Frames on Phantom Models.Proceedings. IEEE International Symposium on Biomedical Imaging · 2024
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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

10 authors at 5 institutions in 2 countries.

Nicola NewallDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.
Danyal Z KhanDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.
John G HanrahanDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.
James BookerDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.
Anouk BorgDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.
Joseph DavidsDepartment of Surgery and Cancer, Imperial College London, London, United Kingdom.
Federico NicolosiSchool of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Siddharth SinhaDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.
Neil DorwardDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.
Hani J MarcusDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom.
National Hospital for Neurology and Neurosurgery · GBUniversity College London · GBImperial College London · GBUniversity of Milano-Bicocca · ITWellcome / EPSRC Centre for Interventional and Surgical Sciences · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Endoscopic endonasal transsphenoidal surgery is an established technique for the resection of sellar and suprasellar lesions. The approach is technically challenging and has a steep learning curve. Simulation is a growing training tool, allowing the acquisition of technical skills pre-clinically and potentially resulting in a shorter clinical learning curve. We sought validation of the UpSurgeOn Transsphenoidal (TNS) Box for the endoscopic endonasal transsphenoidal approach to the pituitary fossa. Methods: Novice, intermediate and expert neurosurgeons were recruited from multiple centres. Participants were asked to perform a sphenoidotomy using the TNS model. Face and content validity were evaluated using a post-task questionnaire. Construct validity was assessed through post-hoc blinded scoring of operative videos using a Modified Objective Structured Assessment of Technical Skills (mOSAT) and a Task-Specific Technical Skill scoring system. Results: Fifteen participants were recruited of which Conclusion: The TNS Box simulation model has demonstrated face, content, and construct validity as a simulator for the endoscopic endonasal transsphenoidal approach. With the steep learning curve associated with endoscopic approaches, this simulation model has the potential as a valuable training tool in neurosurgery with further improvements including advancing simulation materials, dynamic models (e.g., with blood flow) and synergy with complementary technologies (e.g., artificial intelligence and augmented reality).

Indexed as

endoscopichigh fidelitysimulationtranssphenoidal approachUpSurgeOn

Identifiers

PMID36561572
PMCPMC9764859
OpenAlexW4311646502

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.