Evidence map›Paper›PMID 42130682›Full record

Article3D printing and additive manufacturing2026

Advancing Precision Surgery: The Role of 3D Printing in Liver Surgery.

Tao Lan, Yihe Dai, Pingping Hu, Jiang Han, Yun Jin

Abstract read
In one paragraph

Article in 3D printing and additive manufacturing, 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

5 authors.

Tao LanDepartment of Hepatobiliary Surgery, The First People's Hospital of Yunnan Province, Kunming, China.ORCID https://orcid.org/0009-0004-4112-1148
Yihe DaiThe Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.
Pingping HuThe Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.
Jiang HanThe Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.
Yun JinThe Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of precision surgical procedures is rapidly transforming the treatment methods in complex surgical fields such as liver surgery. 3D printing technology, as a crucial support, has not only redefined surgical planning and execution but also improved medical education and patient communication. This article discusses the application of 3D printing in liver surgery, including surgical planning, intraoperative navigation, education and training, and 3D bioprinting technologies. 3D-printed models, with their ability to accurately display the spatial relationship between tumors and surrounding structures, provide a foundation for surgeons to devise precise surgical plans. This allows surgeons to develop more accurate surgical strategies preoperatively, reducing surgical risks and preserving more healthy liver tissue. Furthermore, this article discusses the challenges faced by 3D printing technology, such as cost and technical limitations, as well as the difficulties in clinical application, and provides a future outlook. Through a review of literature and case studies, this article highlights the significant role of 3D printing technology in enhancing surgical precision, reducing risks, and promoting patient recovery. With technological advancements, the prospects for the application of 3D printing in precision surgical procedures are broad, especially in the field of liver surgery, offering patients safer and more effective diagnostic and therapeutic options.

Indexed as

3D printingeducationhepatic surgeryorgan models

Identifiers

PMID42130682
PMCPMC13133466

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.