Evidence map›Paper›PMID 31141115›Full record

Trial reportJAMA surgery2019

Comparison of Cinematic Rendering and Computed Tomography for Speed and Comprehension of Surgical Anatomy.

Moustafa Elshafei, Johannes Binder, Justus Baecker, Maximilian Brunner, Michael Uder, Georg F Weber, Robert Grützmann, Christian Krautz

Open access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JAMA surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

30 citing papers in PubMed, 74 citations in OpenAlex.

  1. Article
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  5. Review
  6. Integration of high-resolution mixed reality models into resident training.Journal of vascular surgery cases and innovative techniques · 2026
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  7. Article
  8. Review
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  10. Article
  11. Cinematic rendering ofBJUI compass · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Moustafa ElshafeiDepartment of Surgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen Nürnberg, Erlangen, Germany.
Johannes BinderDepartment of Surgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen Nürnberg, Erlangen, Germany.
Justus BaeckerDepartment of Surgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen Nürnberg, Erlangen, Germany.
Maximilian BrunnerDepartment of Surgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen Nürnberg, Erlangen, Germany.
Michael UderInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen Nürnberg, Erlangen, Germany.
Georg F WeberDepartment of Surgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen Nürnberg, Erlangen, Germany.
Robert GrützmannDepartment of Surgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen Nürnberg, Erlangen, Germany.
Christian KrautzDepartment of Surgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen Nürnberg, Erlangen, Germany.
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEUniversitätsklinikum Erlangen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Three-dimensional (3-D) volume rendering has been shown to improve visualization in general surgery. Cinematic rendering (CR), a novel 3-D visualization technology for postprocessing of computed tomographaphy (CT) images, provides photorealistic images with the potential to improve visualization of anatomic details. Objective: To determine the value of CR for the comprehension of the surgical anatomy. Design, Setting, and Participants: This preclinical, randomized, 2-sequence crossover study was conducted from February to November 1, 2018, at University Hospital of Erlangen, Germany. The 40 patient cases were evaluated by 18 resident and attending surgeons using a prepared set of CT and CR images. The patient cases were randomized to 2 assessment sequences (CR-CT and CT-CR). During each assessment period, participants answered 1 question per case that addressed crucial issues of anatomic understanding, preoperative planning, and intraoperative strategies. After a washout period of 2 weeks, case evaluations were crossed over to the respective second image modality. Main Outcomes and Measures: The primary outcome measure was the correctness of answers. Secondary outcome was the time needed to answer. Results: The mean (SD) interperiod differences for the percentage of correct answers in the CR-CT sequence (8.5% [7.0%]) differed significantly from those in the CT-CR sequence (-13.1% [6.3%]) (P < .001). The mean (SD) interperiod differences for the time spent to answer the questions in the CR-CT sequence (-18.3 [76.9] seconds) also differed significantly from those in the CT-CR sequence (52.4 [88.5] seconds) (P < .001). Subgroup analysis revealed that residents as well as attending physicians benefitted from CR visualization. Analysis of the case assessment questionnaire showed that CR added significant value to the comprehension of the surgical anatomy (overall mean [SD] score, 4.53 [0.75]). No carryover or period effects were observed. Conclusions and Relevance: The visualization with CR allowed a more correct and faster comprehension of the surgical anatomy compared with conventional CT imaging, independent of level of surgeon experience. Therefore, CR may assist general surgeons with preoperative preparation and intraoperative guidance.

Indexed as

Anatomy, RegionalComprehensionSurgical Procedures, OperativeCross-Over StudiesFollow-Up StudiesHumansImaging, Three-DimensionalRetrospective StudiesSurgery, Computer-AssistedTomography, X-Ray Computed

Identifiers

PMID31141115
PMCPMC6705138
OpenAlexW2946953768

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.