Evidence map›Paper›PMID 38721022›Full record

ArticleFrontiers in surgery2024

Quantitative assessment and objective improvement of the accuracy of neurosurgical planning through digital patient-specific 3D models.

Sahin Hanalioglu, Muhammet Enes Gurses, Baylar Baylarov, Osman Tunc, Ilkay Isikay, Nergiz Ercil Cagiltay, Ilkan Tatar, Mustafa Berker

Abstract read
In one paragraph

Article in Frontiers in surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. 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

8 authors.

Sahin HanaliogluDepartment of Neurosurgery, Faculty of Medicine, Hacettepe University, Ankara, Turkey.
Muhammet Enes GursesDepartment of Neurosurgery, Faculty of Medicine, Hacettepe University, Ankara, Turkey.
Baylar BaylarovDepartment of Neurosurgery, Faculty of Medicine, Hacettepe University, Ankara, Turkey.
Osman TuncBTech Innovation, METU Technopark, Ankara, Turkey.
Ilkay IsikayDepartment of Neurosurgery, Faculty of Medicine, Hacettepe University, Ankara, Turkey.
Nergiz Ercil CagiltayDepartment of Software Engineering, Cankaya University, Ankara, Turkey.
Ilkan TatarDepartment of Anatomy, Faculty of Medicine, Hacettepe University, Ankara, Turkey.
Mustafa BerkerDepartment of Neurosurgery, Faculty of Medicine, Hacettepe University, Ankara, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Neurosurgical patient-specific 3D models have been shown to facilitate learning, enhance planning skills and improve surgical results. However, there is limited data on the objective validation of these models. Here, we aim to investigate their potential for improving the accuracy of surgical planning process of the neurosurgery residents and their usage as a surgical planning skill assessment tool. Methods: A patient-specific 3D digital model of parasagittal meningioma case was constructed. Participants were invited to plan the incision and craniotomy first after the conventional planning session with MRI, and then with 3D model. A feedback survey was performed at the end of the session. Quantitative metrics were used to assess the performance of the participants in a double-blind fashion. Results: A total of 38 neurosurgical residents and interns participated in this study. For estimated tumor projection on scalp, percent tumor coverage increased (66.4 ± 26.2%-77.2 ± 17.4%, Conclusion: This study provides evidence that patient-specific digital 3D models can be used as educational materials to objectively improve the surgical planning accuracy of neurosurgical residents and to quantitatively assess their surgical planning skills through various surgical scenarios.

Indexed as

3D modelassessmentbrain tumoreducationsimulationsurgical planning

Identifiers

PMID38721022
PMCPMC11076751

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.