Optimized path planning for soft tissue resection via laser vaporization

Automating neurosurgical tumor resection surgery: Volumetric laser ablation of cadaveric porcine brain with integrated surface mapping

“…Characterization of the laser‐tissue interaction between these various pathologic and non‐pathologic tissue types (as performed in previous publications) will be essential to provide the ablation and coagulation inputs necessary to estimate the amount of tissue removed or cauterized with each cut and plan a cutting path. Once various tissues and tumor types are characterized, real‐time sensor feedback can then be used to create a controller that is capable of predicting ablation efficiency prior to each cut, as has been shown in simulation . With a predictive controller, the laser output can be optimized such that the variation in ablation can be reduced to within the accuracy benchmark set by the human neurosurgeon.…”

“…The user visually inspects the incision to determine if the correct depth was achieved, repeating if necessary. Toward improving control over cut depth during laser ablation, automated optimization of laser parameters, and cut paths for superficial ablations has been demonstrated using genetic algorithms to determine the appropriate cut speed, power, and distance between rasterized line cuts to achieve a desired depth of cut over a large area on the surface of the surgical site . Such an approach would require a computer‐guided laser ablation system capable of accurately executing the prescribed cuts, such as the Acublade, CAST system, or the device presented herein.…”

Robotic Laser Orientation Planning with a 3D Data-driven Method

“…As it is difficult to model the laser-tissue interaction due to the heterogeneity of tissue material and the complex physical mechanism, prior works have examined applying a data-driven method to model the physics [11], [8], [12], [13], [10]. The laser beam profile can be usually modelled by a Gaussian function [14], [15]. The tissue of removal should follow the similar pattern since the depth-of-cut is related to the strength of energy delivered to the target.…”

“…The tissue of removal should follow the similar pattern since the depth-of-cut is related to the strength of energy delivered to the target. Therefore, the Gaussian-based model has been widely used to describe the laser-tissue relation, and the parameters of the Gaussian function can be learned through the 3D cavity data collected by highresolution scanners such as confocal microscopy [12], [13] and computed tomography (CT) [15].…”

“…The method of learning laser-tissue physics by Gaussian function fitting has also been applied in various robotic laser applications, such as tissue depth control [11], surgical simulation [8], [12] and generating a cutting path for volumetric resection [15]. However, these studies have not discussed the problem of orientation planning with various laser angles and the application controlling the ablated profiles for robotic laser surgery, which inspires the proposed work.…”