Automatic Registration and Error Color Maps to Improve Accuracy for Navigated Bone Tumor Surgery Using Intraoperative Cone-Beam CT

Abstract

Background: Computer-assisted surgery (CAS) can improve surgical precision in orthopaedic oncology. Accurate alignment of the patient's imaging coordinates with the anatomy, known as registration, is one of the most challenging aspects of CAS and can be associated with substantial error. Using intraoperative, on-the-table, cone-beam computed tomography (CBCT), we performed a pilot clinical study to validate a method for automatic intraoperative registration.Methods: Patients who were ‡18 years of age, had benign bone tumors, and underwent resection were prospectively enrolled. In addition to inserting a navigation tracking tool into the exposed bone adjacent to the surgical field, 2 custom plastic ULTEM tracking tools (UTTs) were attached to each patient's skin adjacent to the tumor using an adhesive. These were automatically localized within the 3-dimensional CBCT volume to be used as image landmarks for registration, and the corresponding tracker landmarks were captured using an infrared camera. The main outcomes were the fiducial registration error (FRE) and the target registration error (TRE). The navigation time was recorded.Results: Thirteen patients with benign tumors in the femur (n = 10), tibia (n = 2), and humerus (n = 1) underwent navigation-assisted resections. The mean values were 0.67 ± 0.15 mm (range, 0.47 to 0.97 mm) for FRE and 0.83 ± 0.51 mm (range, 0.42 to 2.28 mm) for TRE. Registration was successful in all cases. The mean time for CBCT imaging and tracker registration was 7.5 minutes. Conclusions:We present a novel automatic registration method for CAS exploiting intraoperative CBCT capabilities, which provided improved accuracy and reduced operative times compared with more traditional methods.Clinical Relevance: This proof-of-principle study validated a novel process for automatic registration to improve the accuracy of resecting bone tumors using a surgical navigation system.

Skull-Base Surgery—A Narrative Review on Current Approaches and Future Developments in Surgical Navigation

“…Our group has been working with an in-house navigation software package (GTx-Eyes) [ 81 ] mostly in pre-clinical settings [ 10 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 ], and in proof-of-principle clinical studies [ 66 , 86 , 93 , 94 , 95 , 96 ] with proven benefits.…”

“…The tracking is provided by a stereoscopic infrared camera (Polaris Spectra, NDI, Waterloo, Ontario). Image-to-tracker registration is obtained by paired-point matching of pre-drilled divots by means of a tracked pointer, or alternatively can be achieved through an automatic registration technique [ 93 ]. In lab studies, a small four-sphere reference tool (NDI, Waterloo, Ontario) is anchored to the skull throughout registration and simulations with a registration error of 1 mm or less that is considered acceptable for all our navigation experiments.…”

“…Our navigation technology using an intraoperative, on-the-table, cone-beam computed tomography (CBCT) has been utilized in other clinical settings. Sahovaler et al [ 93 ] published a pilot clinical study, including benign tumors in the femur, tibia and humerus and showed a mean target registration error of 0.83 ± 0.51 mm. We aim to replicate this approach in skull-base resections in the near future.…”

Evaluation of AR image tracking for AR-guided surgical applications

“…Five points were used on the skull phantom around the nasal and oral cavity areas to compute the tracking system to model rigid registration transforms. The target registration errors (TRE) were then computed with all points on the skull model for each system through the predictor detailed by West et al 8 TRE ranges on the skull model were also visualized through color-coded surface rendering using Visualization Toolkit (VTK) where threshold regions provide feedback of errors beyond fiducial points used in the registration 3 . The TRE colormap intervals were green (0 -1 mm), yellow (>1 -2 mm), orange (>2 -3 mm), and red (>3 mm).…”

“…Traditional surgical navigation helps provide precision driven planning and intervention to support complex operations. Tracking technologies such infrared (IR) optical tracking and electromagnetic (EM) tracking systems have been demonstrated to help accurately guide tracked surgical instruments and improve intraoperative decision making with submillimeter registration errors across procedures such as image-guided guided osteotomies and skull base surgery [1][2][3] . Applications integrated with these tracking systems display on computer monitors real-time information of tracked surgical instruments relative to 3D data of patient anatomy, disease, and the surgical plan.…”