Integrating Retraction Modeling Into an Atlas-Based Framework for Brain Shift Prediction

Abstract

In recent work, an atlas-based statistical model for brain shift prediction, which accounts for uncertainty in the intraoperative environment, has been proposed. Previous work reported in the literature using this technique did not account for local deformation caused by surgical retraction. It is challenging to precisely localize the retractor location prior to surgery and the retractor is often moved in the course of the procedure. This paper proposes a technique that involves computing the retractor-induced brain deformation in the operating room through an active model solve and linearly superposing the solution with the precomputed deformation atlas. As a result, the new method takes advantage of the atlas-based framework’s accounting for uncertainties while also incorporating the effects of retraction with minimal intraoperative computing. This new approach was tested using simulation and phantom experiments. The results showed an improvement in average shift correction from 50% (ranging from 14 to 81%) for gravity atlas alone to 80% using the active solve retraction component (ranging from 73 to 85%). This paper presents a novel yet simple way to integrate retraction into the atlas-based brain shift computation framework.

Android application for determining surgical variables in brain-tumor resection procedures

“…As indicated in Ref. 20, when true head orientations begin to deviate by more than 5 deg outside the capture range, the performance of our nonrigid image-to-physical registration method tended to suffer. As a result, it is important that that the head orientation angle difference between Surgical Planner and the physical plan consistently falls within this range.…”

“…The brain shift computational pipeline associated with Ref. 20 creates a 20-deg conical capture range of possible head orientations from the user-prescribed predicted head orientation in order to account for variability between the preoperatively planned head orientation and actual OR head orientation. As indicated in Ref.…”

“…On a related note, having high confidence in the accuracy of the preoperatively planned variables would have a positive impact on the extent of preoperative computing time. 20 Similarly, a poorly designed planner could also negatively impact available surgeon time by being too slow and cumbersome, and consequently inhibit adoption. For example, in Ref.…”

Neurosurgery and brain shift: review of the state of the art and main contributions of robotics

“…There are two main reasons for this brain shift. First, the opening of the dura mater (a membrane that covers and protects the brain) causes large nonlinear deformations due to pressure changes and cerebrospinal fluid loss, [54] and [55]. The surgical procedures of resection, cuts or excision are the second cause [56].…”

“…However, the limitation of this approach is that the marker should be visible. Even more interesting are the approximations that make use of a mathematical-physical model of deformations to predict the displacements of all points of the brain [54] and [55]. But they require a model validation process which is often not easy to carry out due to the difficulty of measuring the actual displacements to check the generated model [56].…”