The mechanics of decompressive craniectomy: Personalized simulations

Abstract

Decompressive craniectomy is a traditional but controversial surgical procedure that removes part of the skull to allow an injured and swollen brain to expand outward. Recent studies suggest that mechanical strain is associated with its undesired, high failure rates. However, the precise strain fields induced by the craniectomy are unknown. Here we create a personalized craniectomy model from magnetic resonance images to quantify the strains during a decompressive craniectomy using finite element analysis. We swell selected regions of the brain and remove part of the skull to allow the brain to bulge outward and release the intracranical swelling pressure. Our simulations reveal three potential failure mechanisms associated with the procedure: axonal stretch in the center of the bulge, axonal compression at the edge of the craniectomy, and axonal shear around the opening. Strikingly, for a swelling of only 10%, axonal strain, compression, and shear reach local maxima of up to 30%, and exceed the reported functional and morphological damage thresholds of 18% and 21%. Our simulations suggest that a collateral craniectomy with the skull opening at the side of swelling is less invasive than a contralateral craniectomy with the skull opening at the opposite side: It induces less deformation, less rotation, smaller strains, and a markedly smaller midline shift. Our computational craniectomy model can help quantify brain deformation, tissue strain, axonal stretch, and shear with the goal to identify high-risk regions for brain damage on a personalized basis. While computational modeling is beyond clinical practice in neurosurgery today, simulations of neurosurgical procedures have the potential to rationalize surgical process parameters including timing, location, and size, and provide standardized guidelines for clinical decision making and neurosurgical planning.