Automatic multi-trajectory planning solution for steerable catheters

Authors: Alberto Favaro Leonardo Cerri Davide Scorza Elena De Momi

Date: 03.03.2018


Abstract

The present work describes a novel approach to trajectory planning for minimally invasive surgery consisting of an algorithm able to provide the surgeon with multiple curvilinear paths to connect an entry area defined on the brain cortex to a specific target point in the brain. A criterion based on the minimum distance from the safety-critical brain structures (blood vessels, thalamus and ventricles) is used to rank the obtained trajectories. The solution is integrated onto the EDEN2020∗ programmable bevel-tip needle, a multi-segment probe whose steering ability derives from the offset generated on its tip, and provides a level of tolerance with respect to tracking errors arising from catheter model inaccuracies. The case of study of the work consists of a typical Deep Brain Stimulation scenario where tests have been performed in order to compare the result obtained from standard rectilinear trajectory planning against this novel curvilinear solution using the clearance from obstacles as an index of performance of the estimated solutions.

BIB_text

@Article {
title = {Automatic multi-trajectory planning solution for steerable catheters},
pages = {1-6},
abstract = {

The present work describes a novel approach to trajectory planning for minimally invasive surgery consisting of an algorithm able to provide the surgeon with multiple curvilinear paths to connect an entry area defined on the brain cortex to a specific target point in the brain. A criterion based on the minimum distance from the safety-critical brain structures (blood vessels, thalamus and ventricles) is used to rank the obtained trajectories. The solution is integrated onto the EDEN2020∗ programmable bevel-tip needle, a multi-segment probe whose steering ability derives from the offset generated on its tip, and provides a level of tolerance with respect to tracking errors arising from catheter model inaccuracies. The case of study of the work consists of a typical Deep Brain Stimulation scenario where tests have been performed in order to compare the result obtained from standard rectilinear trajectory planning against this novel curvilinear solution using the clearance from obstacles as an index of performance of the estimated solutions.


}
isbn = {978-153862512-5},
doi = {10.1109/ISMR.2018.8333284},
date = {2018-03-03},
}
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