Evidence map›Paper›PMID 42775048›Full record

ReviewAnnals of surgery open : perspectives of surgical history, education, and clinical approaches2026

3D Modelling for Preoperative Planning, Intraoperative Navigation, and Training in Pancreatic Surgery: A Systematic Review.

Raffaella Sguinzi, Melissa Lagger, Edouard Maillard, Lucien Widmer, Abe Fingerhut, Michel Adamina, Christian Toso, Buhler Leo

Abstract readReview
In one paragraph

Review in Annals of surgery open : perspectives of surgical history, education, and clinical approaches, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Raffaella SguinziFrom the Department of Surgery, Fribourg Cantonal Hospital, Villars-sur-Glâne, Switzerland.
Melissa LaggerFrom the Department of Surgery, Fribourg Cantonal Hospital, Villars-sur-Glâne, Switzerland.
Edouard MaillardDepartment of Medical and Surgical Specialties, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland.
Lucien WidmerDepartment of Radiology, Fribourg Cantonal Hospital, Villars-sur-Glâne, Switzerland.
Abe FingerhutDepartment of General Surgery, Ruijin Hospital Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Michel AdaminaDepartment of Medical and Surgical Specialties, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland.
Christian TosoDivision of Digestive Surgery, University Hospitals of Geneva, Genève, Switzerland.
Buhler LeoFrom the Department of Surgery, Fribourg Cantonal Hospital, Villars-sur-Glâne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To systematically review the state of the art for 3-dimensional (3D) technologies in pancreatic surgery for preoperative planning, intraoperative navigation, and surgical training. Background: Three-dimensional modeling is currently routinely used in the standard preoperative work-up for liver surgery and is also increasingly adopted in pancreatic surgery to improve anatomical understanding, surgical planning, and intraoperative guidance. Recent advances have expanded these technologies toward augmented visualization and artificial intelligence-assisted workflows. The clinical impact, level of evidence, and real-world feasibility of these approaches are still under active investigation. Methods: A systematic review was conducted according to Preferred Reporting Items for Systematic Review and Meta-Analyses 2020 guidelines and registered in PROSPERO (CRD420251085091). PubMed and CENTRAL were searched through December 2025 to prioritize clinically oriented literature on patient-specific 3D applications in pancreatic surgery. Because of marked heterogeneity in study design, interventions, and outcome definitions, results were synthesized descriptively. Results: Fifty-eight studies met inclusion criteria and were grouped into 3 domains: preoperative planning (n = 40), intraoperative navigation (n = 7), and surgical training (n = 11). In preoperative planning, 28/40 studies demonstrated superior staging, vascular mapping, and resectability assessment compared with conventional imaging. In 6/7 studies investigating intraoperative navigation, correct alignment was achieved, and a reduction in operative time and intraoperative blood loss was reported in 2/7 studies employing augmented reality-assisted navigation. In surgical training, 9/11 studies showed improved anatomical comprehension and procedural performance using 3D printing, virtual reality, and 3D imaging, associated with reduced operative time and faster learning curves. Conclusion: Three-dimensional technologies enhance anatomical visualization and support planning, navigation, and training in pancreatic surgery; however, consistent improvement in definitive perioperative or oncologic outcomes has not yet been demonstrated. Future studies should prioritize standardized outcomes, formal study-quality assessment, workflow feasibility, cost-effectiveness, and rigorous evaluation of artificial intelligence-enabled applications.

Identifiers

PMID42775048
PMCPMC13596945

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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.