Evidence map›Paper›PMID 29589961›Full record

ReviewAnnual review of analytical chemistry (Palo Alto, Calif.)2018

3D Printed Organ Models for Surgical Applications.

Kaiyan Qiu, Ghazaleh Haghiashtiani, Michael C McAlpine

Abstract readReview
In one paragraph

Review in Annual review of analytical chemistry (Palo Alto, Calif.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. 3D-Printed Artificial Organ Models for Surgical Applications.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Article
  20. A MinireviewFrontiers in bioengineering and biotechnology · 2022
    Review
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

3 authors.

Kaiyan QiuDepartment of Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA; email: mcalpine@umn.edu.
Ghazaleh HaghiashtianiDepartment of Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA; email: mcalpine@umn.edu.
Michael C McAlpineDepartment of Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA; email: mcalpine@umn.edu.

Funding

3D Printed Nano-Bionic OrgansDP2EB020537 · NIBIB · UNIVERSITY OF MINNESOTA · PI MCALPINE, MICHAEL · 2014 to 2019
$2.7M
NIBIB NIH HHS DP2 EB020537
6 · The paper itself

Abstract

Medical errors are a major concern in clinical practice, suggesting the need for advanced surgical aids for preoperative planning and rehearsal. Conventionally, CT and MRI scans, as well as 3D visualization techniques, have been utilized as the primary tools for surgical planning. While effective, it would be useful if additional aids could be developed and utilized in particularly complex procedures involving unusual anatomical abnormalities that could benefit from tangible objects providing spatial sense, anatomical accuracy, and tactile feedback. Recent advancements in 3D printing technologies have facilitated the creation of patient-specific organ models with the purpose of providing an effective solution for preoperative planning, rehearsal, and spatiotemporal mapping. Here, we review the state-of-the-art in 3D printed, patient-specific organ models with an emphasis on 3D printing material systems, integrated functionalities, and their corresponding surgical applications and implications. Prior limitations, current progress, and future perspectives in this important area are also broadly discussed.

Indexed as

Models, AnatomicPrinting, Three-DimensionalGeneral SurgeryHumansMagnetic Resonance ImagingTomography, X-Ray Computed3D printingintegrated functionalitiesorgan modelspolymeric materialssurgical applicationstissue-mimicking materials

Identifiers

PMID29589961
PMCPMC6082023

What OpenQuestion holds

Textmetadata
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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.