Evidence map›Paper›PMID 34709482›Full record

Article3D printing in medicine2021

A workflow to generate patient-specific three-dimensional augmented reality models from medical imaging data and example applications in urologic oncology.

Nicole Wake, Andrew B Rosenkrantz, William C Huang, James S Wysock, Samir S Taneja, Daniel K Sodickson, Hersh Chandarana

Abstract read
In one paragraph

Article in 3D printing in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Dynamic CTA image guidance for targeted robotic ligation of type II aortic endoleak.Journal of vascular surgery cases and innovative techniques · 2026
    Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. [Intervention planning in modern renal surgery].Urologie (Heidelberg, Germany) · 2023
    Review
  8. Review
  9. Advanced 3D Visualization and 3D Printing in Radiology.Advances in experimental medicine and biology · 2023
    Article
  10. Article
  11. Investigating uncertainty in augmented reality enhanced renal navigation using in vitro patient-specific tissue-mimicking phantoms.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2022
    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

7 authors.

Nicole WakeDepartment of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY, 10467, USA. nwake@montefiore.org.ORCID http://orcid.org/0000-0002-8441-6059
Andrew B RosenkrantzCenter for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
William C HuangDepartment of Urology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
James S WysockDepartment of Urology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
Samir S TanejaDepartment of Urology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
Daniel K SodicksonCenter for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
Hersh ChandaranaCenter for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Christopher M Collins · 2014 to 2026
$19.3M
NIBIB NIH HHS NIH P41 EB017183NIBIB NIH HHS P41 EB017183
6 · The paper itself

Abstract

Augmented reality (AR) and virtual reality (VR) are burgeoning technologies that have the potential to greatly enhance patient care. Visualizing patient-specific three-dimensional (3D) imaging data in these enhanced virtual environments may improve surgeons' understanding of anatomy and surgical pathology, thereby allowing for improved surgical planning, superior intra-operative guidance, and ultimately improved patient care. It is important that radiologists are familiar with these technologies, especially since the number of institutions utilizing VR and AR is increasing. This article gives an overview of AR and VR and describes the workflow required to create anatomical 3D models for use in AR using the Microsoft HoloLens device. Case examples in urologic oncology (prostate cancer and renal cancer) are provided which depict how AR has been used to guide surgery at our institution.

Indexed as

Augmented realityMedical imagingSurgical planningThree-dimensionalUrologic oncology

Identifiers

PMID34709482
PMCPMC8554989

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.