Constructing an Individualized Middle Cerebral Artery Model Using 3D Printing and Hydrogel for Bypass Training.

The importance and complexity of cerebral bypass surgery (CBS) highlight the necessity for intense and dedicated training. Several available training models are yet to satisfy this need. In this technical note, we share the steps to construct a digital imaging and communications in medicine (DICOM)-based middle cerebral artery (MCA) model that is anatomically accurate, resembles handling properties of living tissue, and enables trainers to observe the cerebrovascular anatomy, improve and maintain microsurgical dexterity, and train in the essential steps of CBS. The internal and external molds were created from the geometry of DICOM-based MCA using Fusion 360 software (Autodesk, San Rafael, USA). They were then three-dimension (3D) printed using a polylactic acid filament. The 15% w/v solution of polyvinyl alcohol (PVA) was prepared and injected between the molds. Using five freeze-thaw cycles the solution was converted to tissue-mimicking cryo-gel. The model was then placed in a chloroform bath until the internal mold dissolved. To evaluate the accuracy of the MCA model, selected characteristics were measured and compared with the MCA mesh. The DICOM-based MCA model was produced using 3D printing that was available in the lab and the overall cost was less than $5 per model. The external mold required six and a half hours to be 3D printed, while the internal mold only required 23 minutes. Overall, the time required to 3D print the DICOM-based MCA model was just short of seven hours. The greatest statistically significant difference between the virtual MCA model and the DICOM-based MCA model was found in the length of the pre-bifurcation part of the M1 segment and the total length of the superior bifurcation trunk of M1 and superior branch of M2. The smallest statistically significant difference was found at the diameter of the inferior post-bifurcation trunk of the M1 segment and the diameter at the origin of the artery. This technical report aims to show the construction of a CBS training system involving the DICOM-based MCA model that demonstrates the shape of the vascular tree, resembles the handling/suturing properties of living tissue, and helps set up a homemade training station. We believe that our DICOM-based MCA model can serve as a valuable resource for CBS training throughout the world due to its cost-effectiveness and straightforward construction steps. Moreover, once the DICOM-based MCA model is used with our training station, it may offer an option for trainers to gain and maintain CBS skills despite limitations on time, cost, and space. This work was presented in February 2019 at the American Association of Neurological Surgeons/Congress of Neurological Surgeons (AANS/CNS) Cerebrovascular Section Annual Meeting held in Honolulu, Hawaii.