PURPOSE: Minimal invasion computer-assisted neurosurgical procedures with various tool insertions into the brain may carry hemorrhagic risks and neurological deficits. The goal of this study is to investigate the role of computer-based surgical trajectory planning tools in improving the potential safety of image-based stereotactic neurosurgery. METHODS: Multi-sequence MRI studies of eight patients who underwent image-guided neurosurgery were retrospectively processed to extract anatomical structures-head surface, ventricles, blood vessels, white matter fibers tractography, and fMRI data of motor, sensory, speech, and visual areas. An experienced neurosurgeon selected one target for each patient. Five neurosurgeons planned a surgical trajectory for each patient using three planning methods: (1) conventional; (2) visualization, in which scans are augmented with overlays of anatomical structures and functional areas; and (3) automatic, in which three surgical trajectories with the lowest expected risk score are automatically computed. For each surgeon, target, and method, we recorded the entry point and its surgical trajectory and computed its expected risk score and its minimum distance from the key structures. RESULTS: A total of 120 surgical trajectories were collected (5 surgeons, 8 targets, 3 methods). The surgical trajectories expected risk scores improved by 76% ([Formula: see text], two-sample student's t test); the average distance of a trajectory from nearby blood vessels increased by 1.6 mm ([Formula: see text]) from 0.6 to 2.2 mm (243%). The initial surgical trajectories were changed in 85% of the cases based on the expected risk score and the trajectory distance from blood vessels. CONCLUSIONS: Computer-based patient-specific preoperative planning of surgical trajectories that minimize the expected risk of vascular and neurological damage due to incorrect tool placement is a promising technique that yields consistent improvements.
PURPOSE: Minimal invasion computer-assisted neurosurgical procedures with various tool insertions into the brain may carry hemorrhagic risks and neurological deficits. The goal of this study is to investigate the role of computer-based surgical trajectory planning tools in improving the potential safety of image-based stereotactic neurosurgery. METHODS: Multi-sequence MRI studies of eight patients who underwent image-guided neurosurgery were retrospectively processed to extract anatomical structures-head surface, ventricles, blood vessels, white matter fibers tractography, and fMRI data of motor, sensory, speech, and visual areas. An experienced neurosurgeon selected one target for each patient. Five neurosurgeons planned a surgical trajectory for each patient using three planning methods: (1) conventional; (2) visualization, in which scans are augmented with overlays of anatomical structures and functional areas; and (3) automatic, in which three surgical trajectories with the lowest expected risk score are automatically computed. For each surgeon, target, and method, we recorded the entry point and its surgical trajectory and computed its expected risk score and its minimum distance from the key structures. RESULTS: A total of 120 surgical trajectories were collected (5 surgeons, 8 targets, 3 methods). The surgical trajectories expected risk scores improved by 76% ([Formula: see text], two-sample student's t test); the average distance of a trajectory from nearby blood vessels increased by 1.6 mm ([Formula: see text]) from 0.6 to 2.2 mm (243%). The initial surgical trajectories were changed in 85% of the cases based on the expected risk score and the trajectory distance from blood vessels. CONCLUSIONS: Computer-based patient-specific preoperative planning of surgical trajectories that minimize the expected risk of vascular and neurological damage due to incorrect tool placement is a promising technique that yields consistent improvements.
Authors: Yuan Liu; Peter E Konrad; Joseph S Neimat; Stephen B Tatter; Hong Yu; Ryan D Datteri; Bennett A Landman; Jack H Noble; Srivatsan Pallavaram; Benoit M Dawant; Pierre-François D'Haese Journal: IEEE Trans Biomed Eng Date: 2014-05-09 Impact factor: 4.538
Authors: Vejay N Vakharia; Rachel Sparks; Roman Rodionov; Sjoerd B Vos; Christian Dorfer; Jonathan Miller; Daniel Nilsson; Martin Tisdall; Stefan Wolfsberger; Andrew W McEvoy; Anna Miserocchi; Gavin P Winston; Aidan G O'Keeffe; Sebastien Ourselin; John S Duncan Journal: J Neurosurg Date: 2018-04-01 Impact factor: 5.115
Authors: Rachel Sparks; Vejay Vakharia; Roman Rodionov; Sjoerd B Vos; Beate Diehl; Tim Wehner; Anna Miserocchi; Andrew W McEvoy; John S Duncan; Sebastien Ourselin Journal: Int J Comput Assist Radiol Surg Date: 2017-06-15 Impact factor: 2.924
Authors: Rachel Sparks; Gergely Zombori; Roman Rodionov; Mark Nowell; Sjoerd B Vos; Maria A Zuluaga; Beate Diehl; Tim Wehner; Anna Miserocchi; Andrew W McEvoy; John S Duncan; Sebastien Ourselin Journal: Int J Comput Assist Radiol Surg Date: 2016-07-01 Impact factor: 2.924