Evidence map›Paper›PMID 31605218›Full record

ReviewSurgical endoscopy2020

An overview on 3D printing for abdominal surgery.

Andrea Pietrabissa, Stefania Marconi, Erika Negrello, Valeria Mauri, Andrea Peri, Luigi Pugliese, Enrico Maria Marone, Ferdinando Auricchio

Abstract readReview
PubMed Publisher
In one paragraph

Review in Surgical endoscopy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 1 pooled it
4.6field-weighted citation impact, top 5% 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

46 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.

  1. The cutting edge of customized surgery: 3D-printed models for patient-specific interventions in otology and auricular management-a systematic review.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2022
    Pooled it
  2. Trial
  3. 3D Modelling for Preoperative Planning, Intraoperative Navigation, and Training in Pancreatic Surgery: A Systematic Review.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2026
    Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Advanced Image-Guidance and Surgical-Navigation Techniques for Real-Time Visualized Surgery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Visuospatial abilities and 3D-printed based learning.Surgical and radiologic anatomy : SRA · 2024
    Article
  17. Article
  18. Review
  19. Review
  20. 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 at 2 institutions in 1 country.

Andrea PietrabissaFondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Stefania MarconiDepartment of Civil Engineering and Architecture, University of Pavia, via Ferrata, 3, 27100, Pavia, Italy. stefania.marconi@unipv.it.ORCID 0000-0003-4608-6180
Erika NegrelloFondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Valeria MauriFondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Andrea PeriFondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Luigi PuglieseFondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Enrico Maria MaroneFondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Ferdinando AuricchioDepartment of Civil Engineering and Architecture, University of Pavia, via Ferrata, 3, 27100, Pavia, Italy.
Policlinico San Matteo Fondazione · ITUniversity of Pavia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThree-dimensional (3D) printing is a disruptive technology that is quickly spreading to many fields, including healthcare. In this context, it allows the creation of graspable, patient-specific, anatomical models generated from medical images. The ability to hold and show a physical object speeds up and facilitates the understanding of anatomical details, eases patient counseling and contributes to the education and training of students and residents. Several medical specialties are currently exploring the potential of this technology, including general surgery.

methodsIn this review, we provide an overview on the available 3D printing technologies, together with a systematic analysis of the medical literature dedicated to its application for abdominal surgery. Our experience with the first clinical laboratory for 3D printing in Italy is also reported.

resultsThere was a tenfold increase in the number of publications per year over the last decade. About 70% of these papers focused on kidney and liver models, produced primarily for pre-interventional planning, as well as for educational and training purposes. The most used printing technologies are material jetting and material extrusion. Seventy-three percent of publications reported on fewer than ten clinical cases.

conclusionThe increasing application of 3D printing in abdominal surgery reflects the dawn of a new technology, although it is still in its infancy. The potential benefit of this technology is clear, however, and it may soon lead to the development of new hospital facilities to improve surgical training, research, and patient care.

Indexed as

AbdomenPrinting, Three-DimensionalDiagnostic ImagingGeneral SurgeryHumansImage Processing, Computer-AssistedModels, AnatomicAdditive manufacturingRapid prototypingSimulation for surgeryThree-dimensional printingVirtual reconstruction

Identifiers

PMID31605218
OpenAlexW2980009295

What OpenQuestion holds

Textmetadata
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.