TY - JOUR
T1 - An incremental registration method for endoscopic sinus and skull base surgery navigation
T2 - From phantom study to clinical trials
AU - Li, Wenjie
AU - Fan, Jingfan
AU - Li, Shaowen
AU - Zheng, Zhao
AU - Tian, Zhaorui
AU - Ai, Danni
AU - Song, Hong
AU - Chen, Xiaohong
AU - Yang, Jian
N1 - Publisher Copyright:
© 2022 American Association of Physicists in Medicine.
PY - 2023/1
Y1 - 2023/1
N2 - Purpose: Surface-based image-to-patient registration in current surgical navigation is mainly achieved by a 3D scanner, which has several limitations in clinical practice such as uncontrollable scanning range, complicated operation, and even high failure rate. An accurate, robust, and easy-to-perform image-to-patient registration method is urgently required. Methods: An incremental point cloud registration method was proposed for surface-based image-to-patient registration. The point cloud in image space was extracted from the computed tomography (CT) image, and a template matching method was applied to remove the redundant points. The corresponding point cloud in patient space was incrementally collected by an optically tracked pointer, while the nearest point distance (NPD) constraint was applied to ensure the uniformity of the collected points. A coarse-to-fine registration method under the constraints of coverage ratio (CR) and outliers ratio (OR) was then proposed to obtain the optimal rigid transformation from image to patient space. The proposed method was integrated in the recently developed endoscopic navigation system, and phantom study and clinical trials were conducted to evaluate the performance of the proposed method. Results: The results of the phantom study revealed that the proposed constraints greatly improved the accuracy and robustness of registration. The comparative experimental results revealed that the proposed registration method significantly outperform the scanner-based method, and achieved comparable accuracy to the fiducial-based method. In the clinical trials, the average registration duration was 1.24 ± 0.43 min, the target registration error (TRE) of 294 marker points (59 patients) was 1.25 ± 0.40 mm, and the lower 97.5% confidence limit of the success rate of positioning marker points exceeds the expected value (97.56% vs. 95.00%), revealed that the accuracy of the proposed method significantly met the clinical requirements (TRE ⩽ 2 mm, p < 0.05). Conclusions: The proposed method has both the advantages of high accuracy and convenience, which were absent in the scanner-based method and the fiducial-based method. Our findings will help improve the quality of endoscopic sinus and skull base surgery.
AB - Purpose: Surface-based image-to-patient registration in current surgical navigation is mainly achieved by a 3D scanner, which has several limitations in clinical practice such as uncontrollable scanning range, complicated operation, and even high failure rate. An accurate, robust, and easy-to-perform image-to-patient registration method is urgently required. Methods: An incremental point cloud registration method was proposed for surface-based image-to-patient registration. The point cloud in image space was extracted from the computed tomography (CT) image, and a template matching method was applied to remove the redundant points. The corresponding point cloud in patient space was incrementally collected by an optically tracked pointer, while the nearest point distance (NPD) constraint was applied to ensure the uniformity of the collected points. A coarse-to-fine registration method under the constraints of coverage ratio (CR) and outliers ratio (OR) was then proposed to obtain the optimal rigid transformation from image to patient space. The proposed method was integrated in the recently developed endoscopic navigation system, and phantom study and clinical trials were conducted to evaluate the performance of the proposed method. Results: The results of the phantom study revealed that the proposed constraints greatly improved the accuracy and robustness of registration. The comparative experimental results revealed that the proposed registration method significantly outperform the scanner-based method, and achieved comparable accuracy to the fiducial-based method. In the clinical trials, the average registration duration was 1.24 ± 0.43 min, the target registration error (TRE) of 294 marker points (59 patients) was 1.25 ± 0.40 mm, and the lower 97.5% confidence limit of the success rate of positioning marker points exceeds the expected value (97.56% vs. 95.00%), revealed that the accuracy of the proposed method significantly met the clinical requirements (TRE ⩽ 2 mm, p < 0.05). Conclusions: The proposed method has both the advantages of high accuracy and convenience, which were absent in the scanner-based method and the fiducial-based method. Our findings will help improve the quality of endoscopic sinus and skull base surgery.
KW - clinical trial
KW - endoscopic navigation system
KW - image-to-patient registration
KW - point cloud registration
UR - http://www.scopus.com/inward/record.url?scp=85137211581&partnerID=8YFLogxK
U2 - 10.1002/mp.15941
DO - 10.1002/mp.15941
M3 - Article
C2 - 35997999
AN - SCOPUS:85137211581
SN - 0094-2405
VL - 50
SP - 226
EP - 239
JO - Medical Physics
JF - Medical Physics
IS - 1
ER -