Evidence map›Paper›PMID 27862866›Full record

Trial reportBJU international2017

Utility of patient-specific silicone renal models for planning and rehearsal of complex tumour resections prior to robot-assisted laparoscopic partial nephrectomy.

Friedrich-Carl von Rundstedt, Jason M Scovell, Smriti Agrawal, Jacques Zaneveld, Richard E Link

Open access · greenAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BJU international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
11.0field-weighted citation impact, top 1% 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

53 citing papers in PubMed, 130 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Friedrich-Carl von RundstedtScott Department of Urology, Baylor College of Medicine, Houston, TX, USA.
Jason M ScovellScott Department of Urology, Baylor College of Medicine, Houston, TX, USA.
Smriti AgrawalDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Jacques ZaneveldLazarus 3D LLC, Houston, TX, USA.
Richard E LinkScott Department of Urology, Baylor College of Medicine, Houston, TX, USA.
Baylor College of Medicine · USFriedrich Schiller University Jena · DE

Funding

Training Program in Translational Biology and Molecular MedicineT32GM088129 · NIGMS · BAYLOR COLLEGE OF MEDICINE · PI ROONEY, CLIONA M., VAN DEN VEYVER, IGNATIA B · 2010 to 2019
$3.0M
NIGMS NIH HHS T32 GM088129
6 · The paper itself

Abstract

objectiveTo describe our experience using patient-specific tissue-like kidney models created with advanced three-dimensional (3D)-printing technology for preoperative planning and surgical rehearsal prior to robot-assisted laparoscopic partial nephrectomy (RALPN). PATIENTS AND

methodsA feasibility study of 10 patients with solid renal masses who underwent RALPN after preoperative rehearsal using 3D-print kidney models. A single surgeon performed all surgical rehearsals and procedures. Using standard preoperative imaging and 3D reconstruction, we generated pre-surgical models using a silicone-based material. All surgical rehearsals were performed using the da Vinci

resultsWe generated patient-specific models for 10 patients with complex tumour anatomy. R.E.N.A.L. nephrometry scores were between 7 and 11, with a mean maximal tumour diameter of 40.6 mm. The mean resection times between model and patient (6:58 vs 8:22 min, P = 0.162) and tumour volumes between the computer model, excised model, and excised tumour (38.88 vs 38.50 vs 41.79 mm

conclusionsWe have developed a patient-specific pre-surgical simulation protocol for RALPN. We demonstrated construct validity and provided accurate representation of enucleation time and resected tissue volume. This simulation platform can assist in surgical decision-making, provide preoperative rehearsals, and improve surgical training.

Indexed as

Models, AnatomicPrinting, Three-DimensionalSiliconesCarcinoma, Renal CellFeasibility StudiesHumansKidneyKidney NeoplasmsLaparoscopyNephrectomyPrecision MedicineRobotic Surgical ProceduresSilicones3D printing#KCSM#KidneyCancerRALPNrobotic partial nephrectomysurgical simulation

Identifiers

PMID27862866
PMCPMC6152819
OpenAlexW2551468284

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.