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Russian journal of neurosurgery

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Cerebrovascular aneurysm clipping training models with pulsatile blood flow

https://doi.org/10.17650/1683-3295-2021-23-2-128-133

Abstract

Introduction. Neurosurgery trainees are finding it increasingly difficult to obtain operative experience as the main surgeon in aneurysm procedure. Good quality cadaver dissection opportunities are also not widely available for neurosurgery residents. Simulation is emerging as a useful training aid for neurosurgery. Surgical treatment of cerebral aneurysms requires specialized skills development and proficient use of microsurgical instruments. Furthermore, any advance in neurosurgical training methods is of potential value to both neurosurgeons and patients.

The study objective is to introduce a 3D aneurysm clipping training model to enhance skill acquisition and development.

Materials and methods. The brain model is made using a 3D printed resin mold. The mold is filled with silicone Ecoflex 00–10 and mix with Silc Pig pigment additives to replicate the color and consistency of brain tissue. Dura is made from quick drying silicone paste with grey dye. The blood vessels are made from a silicone 3D printed mold of a magnetic resonance angiography. Liquid with paprika oleoresin (E160c) dye is used to simulate blood and is pumped through the vessels to simulate pulsatile motion.

Results and conclusion. These models offer an alternative method to train residents and preoperative planning. They are affordable and easy to recreate and hence can standardize training in multiple centers. With advancing technology, 3D technology is becoming an import part of medical education.

About the Author

M.J. Encarnacion Ramirez
RUDN University
Russian Federation

Manuel de Jesus Encarnacion Ramirez

6 Miklukho-Maklaya St., Moscow 117198



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Review

For citations:


Encarnacion Ramirez M. Cerebrovascular aneurysm clipping training models with pulsatile blood flow. Russian journal of neurosurgery. 2021;23(2):128-133. https://doi.org/10.17650/1683-3295-2021-23-2-128-133

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ISSN 1683-3295 (Print)
ISSN 2587-7569 (Online)
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