Multiple instruments motion trajectory tracking in optical surgical navigation

Accuracy of dental implant placement using different dynamic navigation and robotic systems: an in vitro study

Computer-aided implant surgery has undergone continuous development in recent years. In this study, active and passive systems of dynamic navigation were divided into active dynamic navigation system group and passive dynamic navigation system group (ADG and PDG), respectively. Active, passive and semi-active implant robots were divided into active robot group, passive robot group and semi-active robot group (ARG, PRG and SRG), respectively. Each group placed two implants (FDI tooth positions 31 and 36) in a model 12 times. The accuracy of 216 implants in 108 models were analysed. The coronal deviations of ADG, PDG, ARG, PRG and SRG were 0.85 ± 0.17 mm, 1.05 ± 0.42 mm, 0.29 ± 0.15 mm, 0.40 ± 0.16 mm and 0.33 ± 0.14 mm, respectively. The apical deviations of the five groups were 1.11 ± 0.23 mm, 1.07 ± 0.38 mm, 0.29 ± 0.15 mm, 0.50 ± 0.19 mm and 0.36 ± 0.16 mm, respectively. The axial deviations of the five groups were 1.78 ± 0.73°, 1.99 ± 1.20°, 0.61 ± 0.25°, 1.04 ± 0.37° and 0.42 ± 0.18°, respectively. The coronal, apical and axial deviations of ADG were higher than those of ARG, PRG and SRG (all P < 0.001). Similarly, the coronal, apical and axial deviations of PDG were higher than those of ARG, PRG, and SRG (all P < 0.001). Dynamic and robotic computer-aided implant surgery may show good implant accuracy in vitro. However, the accuracy and stability of implant robots are higher than those of dynamic navigation systems.

Image-guided navigation system for minimally invasive total hip arthroplasty (MITHA) using an improved position-sensing marker

PURPOSE

Minimally invasive total hip arthroplasty (MITHA) is a treatment for hip arthritis, and it causes less tissue trauma, blood loss, and recovery time. However, the limited incision makes it difficult for surgeons to perceive the instruments' location and orientation. Computer-assisted navigation systems can help improve the medical outcome of MITHA. Directly applying existing navigation systems for MITHA, however, suffers from problems of bulky fiducial marker, severe feature-loss, multiple instruments tracking confusion, and radiation exposure. To tackle these problems, we propose an image-guided navigation system for MITHA using a novel position-sensing marker.

METHODS

A position-sensing marker is proposed to serve as the fiducial marker with high-density and multi-fold ID tags. It results in less feature span and enables the use of ID for each feature, overcoming the problem of bulky fiducial markers and multiple instruments tracking confusion. And the marker can be recognized even when a large part of locating features is obscured. As for the elimination of intraoperative radiation exposure, we propose a point-based method to achieve patient-image registration based on anatomical landmarks.

RESULTS

Quantitative experiments are conducted to evaluate the feasibility of our system. The accuracy of instrument positioning is achieved at 0.33 ± 0.18 mm, and that of patient-image registration is achieved at 0.79 ± 0.15 mm. And qualitative experiments are also performed, verifying that our system can be used in compact surgical spatial volume and can address severe feature-loss and tracking confusion problems. In addition, our system does not require any intraoperative medical scans.

CONCLUSION

Experimental results indicate that our proposed system can assist surgeons without larger space occupations, radiation exposure, and extra incision, showing its potential application value in MITHA.

The accuracy and learning curves of active and passive dynamic navigation-guided dental implant surgery: An in vitro study

OBJECTIVES

Infrared dynamic navigation principles can be categorized into active and passive navigation systems based on whether the surgical instruments can emit or only reflect light, respectively. This in vitro study aimed to compare the accuracy of implant placement and the learning curves of both active and passive dynamic navigation systems using different registration methods.

METHODS

Implants (n=704) were placed in 64 sets of models and divided into active (Yizhime, DCARER, Suzhou, China) and passive (Iris-Clinic, EPED, Kaohsiung, China) dynamic navigation groups. Both marker point-based registration (M-PBR) and feature point-based registration (F-PBR) were employed by two groups mentioned above. Based on preoperative and postoperative cone-beam computed tomography imaging, the coronal, midpoint, apical, and angular deviations were analyzed from 2D and 3D views. The operation time was recorded for each group.

RESULTS

The active dynamic navigation group exhibited significantly greater accuracy than the passive dynamic navigation group for outcome variables (angular deviation, 4.13 ± 2.39° and 4.62 ± 3.32°; coronal global deviation, 1.48 ± 0.60 and 1.86 ± 1.12 mm; apical global deviation, 1.75 ± 0.81 and 2.20 ± 1.68 mm, respectively). Significant interaction effects were observed for both registration methods and four quadrants with different dynamic navigation systems. Learning curves for the two dynamic navigation groups approached each other after 12 procedures, and finally converged after 27 procedures.

CONCLUSIONS

The accuracy of active dynamic navigation system was superior to that of passive dynamic navigation system. Different combinations of dynamic navigation systems, registration methods, and implanted quadrants displayed various interactions.

CLINICAL SIGNIFICANCE

Our findings could provide guidance for surgeons in choosing an appropriate navigation system use in various implant surgeries. Furthermore, the time required by surgeons to master the technique was calculated for reference. Nevertheless, there are certain limitations to this in vitro study, and therefore further research is required.

Comparative Analysis of Optoelectronic Accuracy in the Laboratory Setting Versus Clinical Operative Environment: A Systematic Review

STUDY DESIGN

Systematic review.

OBJECTIVES

The optoelectronic camera source and data interpolation process serve as the foundation for navigational integrity in robotic-assisted surgical platforms. The current systematic review serves to provide a basis for the numerical disparity observed when comparing the intrinsic accuracy of optoelectronic cameras versus accuracy in the laboratory setting and clinical operative environments.

METHODS

Review of the PubMed and Cochrane Library research databases was performed. The exhaustive literature compilation obtained was then vetted to reduce redundancies and categorized into topics of intrinsic accuracy, registration accuracy, musculoskeletal kinematic platforms, and clinical operative platforms.

RESULTS

A total of 465 references were vetted and 137 comprise the basis for the current analysis. Regardless of application, the common denominators affecting overall optoelectronic accuracy are intrinsic accuracy, registration accuracy, and application accuracy. Intrinsic accuracy equaled or was less than 0.1 mm translation and 0.1 degrees rotation per fiducial. Controlled laboratory platforms reported 0.1 to 0.5 mm translation and 0.1 to 1.0 degrees rotation per array. Accuracy in robotic-assisted spinal surgery reported 1.5 to 6.0 mm translation and 1.5 to 5.0 degrees rotation when comparing planned to final implant position.

CONCLUSIONS

Navigational integrity and maintenance of fidelity of optoelectronic data is the cornerstone of robotic-assisted spinal surgery. Transitioning from controlled laboratory to clinical operative environments requires an increased number of steps in the optoelectronic kinematic chain and error potential. Diligence in planning, fiducial positioning, system registration and intra-operative workflow have the potential to improve accuracy and decrease disparity between planned and final implant position.

Accuracy of Robotic-Assisted Spinal Surgery-Comparison to TJR Robotics, da Vinci Robotics, and Optoelectronic Laboratory Robotics

BACKGROUND

The optoelectronic camera source and data interpolation serve as the foundation for navigational integrity in the robotic-assisted surgical platform. The objective of the current systematic review serves to provide a basis for the numerical disparity that exists when comparing the intrinsic accuracy of optoelectronic cameras: accuracy observed in the laboratory setting versus accuracy in the clinical operative environment. It is postulated that there exists a greater number of connections in the optoelectronic kinematic chain when analyzing the clinical operative environment to the laboratory setting. This increase in data interpolation, coupled with intraoperative workflow challenges, reduces the degree of accuracy based on surgical application and to that observed in controlled musculoskeletal kinematic laboratory investigations.

METHODS

Review of the PubMed and Cochrane Library research databases was performed. The exhaustive literature compilation obtained was then vetted to reduce redundancies and categorized into topics of intrinsic optoelectronic accuracy, registration accuracy, musculoskeletal kinematic platforms, and clinical operative platforms.

RESULTS

A total of 147 references make up the basis for the current analysis. Regardless of application, the common denominators affecting overall optoelectronic accuracy are intrinsic accuracy, registration accuracy, and application accuracy. Intrinsic accuracy of optoelectronic tracking equaled or was less than 0.1 mm of translation and 0.1° of rotation per fiducial. Controlled laboratory platforms reported 0.1 to 0.5 mm of translation and 0.1°-1.0° of rotation per array. There is a huge falloff in clinical applications: accuracy in robotic-assisted spinal surgery reported 1.5 to 6.0 mm of translation and 1.5° to 5.0° of rotation when comparing planned to final implant position. Total Joint Robotics and da Vinci urologic robotics computed accuracy, as predicted, lies between these two extremes-1.02 mm for da Vinci and 2 mm for MAKO.

CONCLUSIONS

Navigational integrity and maintenance of fidelity of optoelectronic data is the cornerstone of robotic-assisted spinal surgery. Transitioning from controlled laboratory to clinical operative environments requires an increased number of steps in the optoelectronic kinematic chain and error potential. Diligence in planning, fiducial positioning, system registration, and intraoperative workflow have the potential to improve accuracy and decrease disparity between planned and final implant position. The key determining factors limiting navigation resolution accuracy are highlighted by this Cochrane research analysis.

Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping

BACKGROUND AND OBJECTIVES

Surgical procedures such as laparoscopic and robotic surgeries are popular since they are invasive in nature and use miniaturized surgical instruments for small incisions. Tracking of the instruments (graspers, needle drivers) and field of view from the stereoscopic camera during surgery could further help the surgeons to remain focussed and reduce the probability of committing any mistakes. Tracking is usually preferred in computerized video surveillance, traffic monitoring, military surveillance system, and vehicle navigation. Despite the numerous efforts over the last few years, object tracking still remains an open research problem, mainly due to motion blur, image noise, lack of image texture, and occlusion. Most of the existing object tracking methods are time-consuming and less accurate when the input video contains high volume of information and more number of instruments.

METHODS

This paper presents a variational framework to track the motion of moving objects in surgery videos. The key contributions are as follows: (1) A denoising method using stochastic resonance in maximal overlap discrete wavelet transform is proposed and (2) a robust energy functional based on Bhattacharyya coefficient to match the target region in the first frame of the input sequence with the subsequent frames using a similarity metric is developed. A modified affine transformation-based registration is used to estimate the motion of the features following an active contour-based segmentation method to converge the contour resulted from the registration process.

RESULTS AND CONCLUSION

The proposed method has been implemented on publicly available databases; the results are found satisfactory. Overlap index (OI) is used to evaluate the tracking performance, and the maximum OI is found to be 76% and 88% on private data and public data sequences.