Evidence map›Paper›PMID 36749368›Full record

ArticleAbdominal radiology (New York)2023

Impact of 3D printed models on quantitative surgical outcomes for patients undergoing robotic-assisted radical prostatectomy: a cohort study.

Nicole Wake, Andrew B Rosenkrantz, Richard Huang, Luke A Ginocchio, James S Wysock, Samir S Taneja, William C Huang, Hersh Chandarana

Open access · greenAbstract read
In one paragraph

Article in Abdominal radiology (New York), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 29% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 3D printing in medicine: bridging imaging, education, and practice.Archives of medical sciences. Atherosclerotic diseases · 2025
    Article
  4. Article
  5. Article
  6. 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 2 countries.

Nicole WakeGE HealthCare, New York, NY, USA. nicole.wake@ge.com.ORCID http://orcid.org/0000-0002-8441-6059
Andrew B RosenkrantzDepartment of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
Richard HuangDivision of Urologic Oncology, Department of Urology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
Luke A GinocchioDepartment of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
James S WysockDivision of Urologic Oncology, Department of Urology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
Samir S TanejaDivision of Urologic Oncology, Department of Urology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
William C HuangDivision of Urologic Oncology, Department of Urology, 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.
Advanced Imaging Research (United States) · USGeneral Electric (Spain) · ES

Funding

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

Abstract

backgroundThree-dimensional (3D) printed anatomic models can facilitate presurgical planning by providing surgeons with detailed knowledge of the exact location of pertinent anatomical structures. Although 3D printed anatomic models have been shown to be useful for pre-operative planning, few studies have demonstrated how these models can influence quantitative surgical metrics.

objectiveTo prospectively assess whether patient-specific 3D printed prostate cancer models can improve quantitative surgical metrics in patients undergoing robotic-assisted radical prostatectomy (RARP).

methodsPatients with MRI-visible prostate cancer (PI-RADS V2 ≥ 3) scheduled to undergo RARP were prospectively enrolled in our IRB approved study (n = 82). Quantitative surgical metrics included the rate of positive surgical margins (PSMs), operative times, and blood loss. A qualitative Likert scale survey to assess understanding of anatomy and confidence regarding surgical approach was also implemented.

resultsThe rate of PSMs was lower for the 3D printed model group (8.11%) compared to that with imaging only (28.6%), p = 0.128. The 3D printed model group had a 9-min reduction in operating time (213 ± 42 min vs. 222 ± 47 min) and a 5 mL reduction in average blood loss (227 ± 148 mL vs. 232 ± 114 mL). Surgeon anatomical understanding and confidence improved after reviewing the 3D printed models (3.60 ± 0.74 to 4.20 ± 0.56, p = 0.62 and 3.86 ± 0.53 to 4.20 ± 0.56, p = 0.22).

conclusions3D printed prostate cancer models can positively impact quantitative patient outcomes such as PSMs, operative times, and blood loss in patients undergoing RARP.

Indexed as

Prostatic NeoplasmsRobotic Surgical ProceduresCohort StudiesHumansMagnetic Resonance ImagingMaleMargins of ExcisionPrinting, Three-DimensionalProstatectomyTreatment Outcome3D printingMagnetic resonance imagingProstate cancerRobotic-assisted radical prostatectomySurgical planning

Identifiers

PMID36749368
PMCPMC10323697
OpenAlexW4319333625

What OpenQuestion holds

Textmetadata
LicenceTDM
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.