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3D printed patient-specific prostate cancer models to guide nerve-sparing robot-assisted radical prostatectomy: a systematic review
- Source :
- Journal of Robotic Surgery.
- Publication Year :
- 2022
- Publisher :
- Springer Science and Business Media LLC, 2022.
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Abstract
- Precise knowledge of each patient’s index cancer and surrounding anatomy is required for nerve-sparing robot-assisted radical prostatectomy (NS-RARP). Complementary to this, 3D printing has proven its utility in improving the visualisation of complex anatomy. This is the first systematic review to critically assess the potential of 3D printed patient-specific prostate cancer models in improving visualisation and the practice of NS-RARP. A literature search of PubMed and OVID Medline databases was performed using the terms “3D Printing”, “Robot Assisted Radical Prostatectomy” and related index terms as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eight articles were included; six were identified via database searches, to which a further two articles were located via a snowballing approach. Eight papers were identified for review. There were five prospective single centre studies, one case series, one technical report and one letter to the editor. Of these articles, five publications (62.5%) reported on the utility of 3D printed models for NS-RARP planning. Two publications (25%) utilised 3D printed prostate models for simulation and training, and two publications (25%) used the models for patient engagement. Despite the nascency of the field, 3D printed models are emerging in the uro-oncological literature as a useful tool in visualising complex anatomy. This has proven useful in NS-RARP for preoperative planning, simulation and patient engagement. However, best practice guidelines, the future regulatory landscape, and health economic considerations need to be addressed before this synergy of new technologies is ready for the mainstream.
- Subjects :
- Health Informatics
Surgery
Subjects
Details
- ISSN :
- 18632491
- Database :
- OpenAIRE
- Journal :
- Journal of Robotic Surgery
- Accession number :
- edsair.doi.dedup.....277bd8cbe9f4926b9fb9c26940d1a310
- Full Text :
- https://doi.org/10.1007/s11701-022-01401-0