Neurosurgical Microvascular Anastomosis: Systematic Review of the Existing Simulators and Proposal of a New Training Classification System.

Abstract

Background: The literature lacks a combined analysis of neurosurgical microvascular anastomosis training models. We performed a systematic literature search to provide an overview of the existing models and proposed a classification system based on the level of simulation and reproducibility of the microvascular anastomosis.

Methods: The systematic literature search followed the PRISMA guidelines. We consulted MEDLINE, Web of Knowledge, and EMBASE independently for papers about bypass training models. Every training model was analyzed according to six tasks supposed to esteem their fidelity to the real operative setting by using a scoring system from zero to two. Finally, authors classified the models into five classes, from A to E, by summing the individual scores.

Results: This study included 109 papers for analysis. Training models were grouped into synthetic tubes, ex vivo models (animal vessels, fresh human cadavers, human placentas) and in vivo simulators (live animals-rats, rabbits, pigs). By applying the proposed classification system, live animals and placentas obtained the highest scores, falling into class A (excellent simulators). Human cadavers and animal vessels (ex vivo) were categorized in class B (good simulators), followed by synthetic tubes (class C, reasonable simulators).

Conclusions: The proposed classification system helps the neurosurgeon to analyze the available training models for microvascular anastomosis critically, and to choose the most appropriate one according to the skills they need to improve.