Evidence map›Paper›PMID 28062895›Full record

ArticleAbdominal radiology (New York)2017

3D printed renal cancer models derived from MRI data: application in pre-surgical planning.

Nicole Wake, Temitope Rude, Stella K Kang, Michael D Stifelman, James F Borin, Daniel K Sodickson, William C Huang, Hersh Chandarana

Registry-linked trialAbstract read
In one paragraph

Article in Abdominal radiology (New York), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03606044 (Single-site Single-arm Feasibility Study of Patient-specific Interactive 3D Anatomical Models Aimed at Improving Surgery Planning Processes for Complex Renal Cancer Patients), which is not on this map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed
7.1field-weighted citation impact, top 2% 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.

NCT03606044 completednot on this mapstarted 2019, after this paper: background citation

Single-site Single-arm Feasibility Study of Patient-specific Interactive 3D Anatomical Models Aimed at Improving Surgery Planning Processes for Complex Renal Cancer Patients

TypeobservationalSponsorDr Eoin R HydeRan2019 to 2019Enrolled24ConditionsKidney Neoplasms, Surgical OncologyArms3D-models
3 · Its place in the literature

Who cites it

55 citing papers in PubMed, 131 citations in OpenAlex.

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  15. Advanced 3D Visualization and 3D Printing in Radiology.Advances in experimental medicine and biology · 2023
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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 3 institutions in 1 country.

Nicole WakeDepartment of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA. nicole.wake@nyumc.org.
Temitope RudeDivision of Urologic Oncology, Department of Urology, New York University School of Medicine, New York, NY, USA.
Stella K KangDepartment of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA.
Michael D StifelmanDepartment of Urology, Hackensack University Medical Center, Hackensack, NJ, USA.
James F BorinDivision of Urologic Oncology, Department of Urology, New York University School of Medicine, New York, NY, USA.
Daniel K SodicksonDepartment of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA.
William C HuangDivision of Urologic Oncology, Department of Urology, New York University School of Medicine, New York, NY, USA.
Hersh ChandaranaDepartment of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA.
New York University · USAdvanced Imaging Research (United States) · USHackensack University Medical Center · US

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

objectiveTo determine whether patient-specific 3D printed renal tumor models change pre-operative planning decisions made by urological surgeons in preparation for complex renal mass surgical procedures. MATERIALS AND

methodsFrom our ongoing IRB approved study on renal neoplasms, ten renal mass cases were retrospectively selected based on Nephrometry Score greater than 5 (range 6-10). A 3D post-contrast fat-suppressed gradient-echo T1-weighted sequence was used to generate 3D printed models. The cases were evaluated by three experienced urologic oncology surgeons in a randomized fashion using (1) imaging data on PACS alone and (2) 3D printed model in addition to the imaging data. A questionnaire regarding surgical approach and planning was administered. The presumed pre-operative approaches with and without the model were compared. Any change between the presumed approaches and the actual surgical intervention was recorded.

resultsThere was a change in planned approach with the 3D printed model for all ten cases with the largest impact seen regarding decisions on transperitoneal or retroperitoneal approach and clamping, with changes seen in 30%-50% of cases. Mean parenchymal volume loss for the operated kidney was 21.4%. Volume losses >20% were associated with increased ischemia times and surgeons tended to report a different approach with the use of the 3D model compared to that with imaging alone in these cases. The 3D printed models helped increase confidence regarding the chosen operative procedure in all cases.

conclusionsPre-operative physical 3D models created from MRI data may influence surgical planning for complex kidney cancer.

Indexed as

Imaging, Three-DimensionalMagnetic Resonance ImagingPatient Care PlanningPrinting, Three-DimensionalHumansImage Interpretation, Computer-AssistedKidney NeoplasmsRetrospective StudiesSurveys and Questionnaires3D printingMagnetic resonance imagingPartial nephrectomySurgical planningUrological oncology

Identifiers

PMID28062895
PMCPMC5410387
OpenAlexW2570402361

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

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.