OBJECTIVE: To acknowledge the challenges and limitations of image-guided neurosurgery systems, we compared the application accuracy of two different image registration methods for one commercial system. (VectorVision, BrainLab, Germany). METHODS: We used an anthropomorphic head phantom for radiosurgery and a custom built add-on to simulate surgical targets inside the brain during an image-guided neurosurgery. We used two image registration methods, fiducial registration using attachable surface markers for computed tomography (CT) and surface registration using infrared laser face scanning. After simulation, we calculated the three-dimensional (3D) distance between the predicted position of a target, and its actual position using a registered pointer and an infrared camera. Deviations were measured for both superficial fiducial markers and internal surgical targets by five different users. RESULTS: Deviations from the location of fiducial markers after each registration method were 2.15 ± 0.93 mm after CT surface marker registration and 1.25 ± 0.64 mm after infrared face scanner registration. The mean target registration errors were 2.95 ± 1.4 mm using fiducial registration and 2.90 ± 1.3 mm using surface registration. The largest deviations (6.2 mm) were found for the targets in the skull base and posterior cranial fossa. Fiducial deviations and target registration errors were statistically uncorrelated. The total application accuracy was 4.87 ± 0.97 mm after CT surface marker registration and 4.14 ± 0.64 mm after infrared face scanner registration. CONCLUSIONS: Despite others have reported differences, we did not find significant variations between both registration methods for the target registration error, although application accuracy was slightly better after surface face registration. Superficial registration errors, but not the target registration error, can be routinely evaluated in the operating room. Since both errors were uncorrelated, surgeons may neglect the achievable accuracy of the procedure. The described method is recommended to assess application accuracy in the operating room.
OBJECTIVE: To acknowledge the challenges and limitations of image-guided neurosurgery systems, we compared the application accuracy of two different image registration methods for one commercial system. (VectorVision, BrainLab, Germany). METHODS: We used an anthropomorphic head phantom for radiosurgery and a custom built add-on to simulate surgical targets inside the brain during an image-guided neurosurgery. We used two image registration methods, fiducial registration using attachable surface markers for computed tomography (CT) and surface registration using infrared laser face scanning. After simulation, we calculated the three-dimensional (3D) distance between the predicted position of a target, and its actual position using a registered pointer and an infrared camera. Deviations were measured for both superficial fiducial markers and internal surgical targets by five different users. RESULTS: Deviations from the location of fiducial markers after each registration method were 2.15 ± 0.93 mm after CT surface marker registration and 1.25 ± 0.64 mm after infrared face scanner registration. The mean target registration errors were 2.95 ± 1.4 mm using fiducial registration and 2.90 ± 1.3 mm using surface registration. The largest deviations (6.2 mm) were found for the targets in the skull base and posterior cranial fossa. Fiducial deviations and target registration errors were statistically uncorrelated. The total application accuracy was 4.87 ± 0.97 mm after CT surface marker registration and 4.14 ± 0.64 mm after infrared face scanner registration. CONCLUSIONS: Despite others have reported differences, we did not find significant variations between both registration methods for the target registration error, although application accuracy was slightly better after surface face registration. Superficial registration errors, but not the target registration error, can be routinely evaluated in the operating room. Since both errors were uncorrelated, surgeons may neglect the achievable accuracy of the procedure. The described method is recommended to assess application accuracy in the operating room.
Authors: Jaafar Basma; Dom E Mahoney; Christos Anagnostopoulos; L Madison Michael; Jeffrey M Sorenson; David G Porter; Angelo Pichierri Journal: J Neurol Surg B Skull Base Date: 2021-07-05
Authors: Ruud Schreurs; F Baan; C Klop; L Dubois; L F M Beenen; P E M H Habets; A G Becking; T J J Maal Journal: Sci Rep Date: 2021-05-17 Impact factor: 4.379
Authors: Marko Švaco; Ivan Stiperski; Domagoj Dlaka; Filip Šuligoj; Bojan Jerbić; Darko Chudy; Marina Raguž Journal: Front Neurorobot Date: 2020-10-23 Impact factor: 2.650
Authors: R Schreurs; F Baan; C Klop; L Dubois; L F M Beenen; P E M H Habets; A G Becking; T J J Maal Journal: Sci Rep Date: 2021-09-10 Impact factor: 4.379