Evidence map›Paper›PMID 28753252›Full record

ArticleJournal of surgical oncology2017

Utility and reproducibility of 3-dimensional printed models in pre-operative planning of complex thoracic tumors.

Elizabeth George, Maria Barile, Anji Tang, Ory Wiesel, Antonio Coppolino, Andreas Giannopoulos, Steven Mentzer, Michael Jaklitsch, Andetta Hunsaker, Dimitrios Mitsouras

Abstract read
In one paragraph

Article in Journal of surgical oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Chest wall stabilization following hemi-sternectomy assisted by 3D printed model.Case reports in plastic surgery & hand surgery · 2026
    Article
  2. From Pixels to Prototypes: 3D Printing Innovations in Radiology.Journal of pharmacy & bioallied sciences · 2025
    Review
  3. Chest wall resections for sulcus superior tumors.Journal of thoracic disease · 2024
    Review
  4. Article
  5. Application of 3-dimensional printing implants for bone tumors.Clinical and experimental pediatrics · 2022
    Article
  6. Review
  7. Review
  8. 3D Printing Applications for Radiology: An Overview.The Indian journal of radiology & imaging · 2021
    Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. 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

10 authors.

Elizabeth GeorgeDivision of Thoracic Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Maria BarileDivision of Thoracic Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Anji TangDepartment of Radiology, Applied Imaging Science Lab, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Ory WieselDivision of Thoracic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Antonio CoppolinoDivision of Thoracic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Andreas GiannopoulosDepartment of Radiology, Applied Imaging Science Lab, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Steven MentzerDivision of Thoracic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Michael JaklitschDivision of Thoracic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Andetta HunsakerDivision of Thoracic Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Dimitrios MitsourasDepartment of Radiology, Applied Imaging Science Lab, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.ORCID http://orcid.org/0000-0003-4023-0823

Funding

Quantitative Coronary Hemodynamics Derived from CT AngiographyK01EB015868 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI MITSOURAS, DIMITRIOS · 2013 to 2015
$520k
NIBIB NIH HHS K01 EB015868
6 · The paper itself

Abstract

BACKGROUND AND

objectives3D-printed models are increasingly used for surgical planning. We assessed the utility, accuracy, and reproducibility of 3D printing to assist visualization of complex thoracic tumors for surgical planning.

methodsModels were created from pre-operative images for three patients using a standard radiology 3D workstation. Operating surgeons assessed model utility using the Gillespie scale (1 = inferior to 4 = superior), and accuracy compared to intraoperative findings. Model variability was assessed for one patient for whom two models were created independently. The models were compared subjectively by surgeons and quantitatively based on overlap of depicted tissues, and differences in tumor volume and proximity to tissues.

resultsModels were superior to imaging and 3D visualization for surgical planning (mean score = 3.4), particularly for determining surgical approach (score = 4) and resectability (score = 3.7). Model accuracy was good to excellent. In the two models created for one patient, tissue volumes overlapped by >86.5%, and tumor volume and area of tissues ≤1 mm to the tumor differed by <15% and <1.8 cm

conclusion3D printing assists surgical planning for complex thoracic tumors. Models can be created by radiologists using routine practice tools with sufficient accuracy and clinically negligible variability.

Indexed as

Models, AnatomicPrinting, Three-DimensionalAdenocarcinomaAdultAgedFemaleHumansImaging, Three-DimensionalMagnetic Resonance ImagingMaleReproducibility of ResultsSarcomaThoracic Neoplasms3D printingchest wall invasionmediastinal invasionsuperior sulcus tumorthoracic oncologythoracic surgery

Identifiers

PMID28753252
PMCPMC5607645

What OpenQuestion holds

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Registered trials

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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.