Multisurgeon, multisite validation of a trajectory planning algorithm for deep brain stimulation procedures.
Deep brain stimulation, which is used to treat various neurological disorders, involves implanting a permanent electrode into precise targets deep in the brain. Reaching these targets safely is difficult because surgeons have to plan trajectories that avoid critical structures and reach targets within specific angles. A number of systems have been proposed to assist surgeons in this task. These typically involve formulating constraints as cost terms, weighting them by surgical importance, and searching for optimal trajectories, in which constraints and their weights reflect local practice. Assessing the performance of such systems is challenging because of the lack of ground truth and clear consensus on an optimal approach among surgeons. Due to difficulties in coordinating inter-institution evaluation studies, these have been performed so far at the sites at which the systems are developed. Whether or not a scheme developed at one site can also be used at another is thus unknown. In this paper, we conduct a study that involves four surgeons at three institutions to determine whether or not constraints and their associated weights can be used across institutions. Through a series of experiments, we show that a single set of weights performs well for all surgeons in our group. Out of 60 trajectories, our trajectories were accepted by a majority of neurosurgeons in 95% of the cases and the average acceptance rate was 90%. This study suggests, albeit on a limited number of surgeons, that the same system can be used to provide assistance across multiple sites and surgeons.
Yuan
Y
Liu
Peter E
PE
Konrad
Joseph S
JS
Neimat
Stephen B
SB
Tatter
Hong
H
Yu
Ryan D
RD
Datteri
Bennett A
BA
Landman
Jack H
JH
Noble
Srivatsan
S
Pallavaram
Benoit M
BM
Dawant
Pierre-François
PF
D'Haese
D000465:Algorithms; D046690:Deep Brain Stimulation / Q000379:methods*; D006801:Humans; D015203:Reproducibility of Results; D066231:Surgeons; D025321:Surgery, Computer-Assisted / Q000379:methods*