Minimally invasive registration for computer-assisted orthopedic surgery: combining tracked ultrasound and bone surface points via the P-IMLOP algorithm

A review of advances in image-guided orthopedic surgery

Orthopedic surgery remains technically demanding due to the complex anatomical structures and cumbersome surgical procedures. The introduction of image-guided orthopedic surgery (IGOS) has significantly decreased the surgical risk and improved the operation results. This review focuses on the application of recent advances in artificial intelligence (AI), deep learning (DL), augmented reality (AR) and robotics in image-guided spine surgery, joint arthroplasty, fracture reduction and bone tumor resection. For the pre-operative stage, key technologies of AI and DL based medical image segmentation, 3D visualization and surgical planning procedures are systematically reviewed. For the intra-operative stage, the development of novel image registration, surgical tool calibration and real-time navigation are reviewed. Furthermore, the combination of the surgical navigation system with AR and robotic technology is also discussed. Finally, the current issues and prospects of the IGOS system are discussed, with the goal of establishing a reference and providing guidance for surgeons, engineers, and researchers involved in the research and development of this area.

[Recent research progress of hip-preserving treatment for adolescents and adults with developmental dysplasia of the hip]

Objective

To review the imaging evaluation, treatment progress, and controversy related to developmental dysplasia of the hip (DDH) in adolescents and adults.

Methods

The domestic and abroad hot issues related to adolescents and adults with DDH in recent years, including new imaging techniques for assessing cartilage, controversies over the diagnosis and treatment of borderline DDH (BDDH), and the improvement and prospect of peracetabular osteotomy (PAO) were summarized and analyzed.

Results

DDH is one of the main factors leading to hip osteoarthritis. As the understanding of the pathological changes of DDH continues to deepen, the use of delayed gadolinium-enhanced MRI of cartilage can further evaluate the progress of osteoarthritis and predict the prognosis after hip preservation. There are still controversies about the diagnosis and treatment of BDDH. At the same time, PAO technology and concepts are still being improved.

Conclusion

Cartilage injury and bony structure determine the choice of surgical methods and postoperative prognosis of hip preservation surgery. The hip preservation of adolescent and adult DDH patients will move towards the goal of individualization and accuracy.

A hybrid feature-based patient-to-image registration method for robot-assisted long bone osteotomy

PURPOSE

The purpose of this study is to provide a simple, feasible and effective patient-to-image registration method for robot-assisted long bone osteotomy, which has rarely been systematically reported. The practical requirement is to meet the accuracy of 1 mm or even higher without bone-implanted markers.

METHODS

A hybrid feature-based registration method termed CR-RAMSICP is proposed. Point-based coarse registration (CR) is accomplished relying on the optical retro-reflective markers attached to the tracked rigid body fixed out of the bone. In surface-based fine registration, an improved iterative closest point (ICP) algorithm based on the range-adaptive matching strategy (termed RAMSICP) is presented to cope with the robust precise matching between the asymmetric patient and image point clouds, which avoids converging to a local minimum.

RESULTS

A series of registration experiments based on the isolated porcine iliums are carried out. The results illustrate that CR-RAMSICP not only significantly outperforms CR and CR-ICP in the accuracy and reproducibility, but also exhibits better robustness to the CR errors and less sensitiveness to the distribution and number of fiducial points located in the patient point cloud than CR-ICP.

CONCLUSION

The proposed registration method CR-RAMSICP can stably satisfy the desired registration accuracy without the use of bone-implanted markers like fiducial screws. Besides, the RAMSICP algorithm used in fine registration is convenient for programming because any complex metrics or models are not involved.

Fiducial-based registration with a touchable region model

PURPOSE

Image-guided surgery requires registration between an image coordinate system and an intraoperative coordinate system that is typically referenced to a tracking device. In fiducial-based registration methods, this is achieved by localizing points (fiducials) in each coordinate system. Often, both localizations are performed manually, first by picking a fiducial point in the image and then by using a hand-held tracked pointer to physically touch the corresponding fiducial on the patient. These manual procedures introduce localization error that is user-dependent and can significantly decrease registration accuracy. Thus, there is a need for a registration method that is tolerant of imprecise fiducial localization in the preoperative and intraoperative phases.

METHODS

We propose the iterative closest touchable point (ICTP) registration framework, which uses model-based localization and a touchable region model. This method consists of three stages: (1) fiducial marker localization in image space, using a fiducial marker model, (2) initial registration with paired-point registration, and (3) fine registration based on the iterative closest point method.

RESULTS

We perform phantom experiments with a fiducial marker design that is commonly used in neurosurgery. The results demonstrate that ICTP can provide accuracy improvements compared to the standard paired-point registration method that is widely used for surgical navigation and surgical robot systems, especially in cases where the surgeon introduces large localization errors.

CONCLUSIONS

The results demonstrate that the proposed method can reduce the effect of the surgeon's localization performance on the accuracy of registration, thereby producing more consistent and less user-dependent registration outcomes.