Towards markerless computer assisted surgery: Application to total knee arthroplasty

FF-ViT: probe orientation regression for robot-assisted endomicroscopy tissue scanning

PURPOSE

Probe-based confocal laser endomicroscopy (pCLE) enables visualization of cellular tissue morphology during surgical procedures. To capture high-quality pCLE images during tissue scanning, it is important to maintain close contact between the probe and the tissue, while also keeping the probe perpendicular to the tissue surface. Existing robotic pCLE tissue scanning systems, which rely on macroscopic vision, struggle to accurately place the probe at the optimal position on the tissue surface. As a result, the need arises for regression of longitudinal distance and orientation via endomicroscopic vision.

METHOD

This paper introduces a novel method for automatically regressing the orientation between a pCLE probe and the tissue surface during robotic scanning, utilizing the fast Fourier vision transformer (FF-ViT) to extract local frequency representations and use them for probe orientation regression. Additionally, the FF-ViT incorporates a blur mapping attention (BMA) module to refine latent representations, which is combined with the pyramid angle regressor (PAR) to precisely estimate probe orientation.

RESULT

A first of its kind dataset for pCLE probe-tissue orientation (pCLE-PTO) has been created. The performance evaluation demonstrates that our proposed network surpasses other top regression networks in accuracy, stability, and generalizability, while maintaining low computational complexity (1.8G FLOPs) and high inference speed (90 fps).

CONCLUSION

The performance evaluation study verifies the clinical value of the proposed framework and its potential to be integrated into surgical robotic platforms for intraoperative tissue scanning.

Contactless surface registration of featureless anatomy using structured light camera: application to fibula navigation in mandible reconstruction

PURPOSE

Mandibular reconstruction using fibula free flap is a challenging surgical procedure. To assist osteotomies, computer-assisted surgery (CAS) can be used. Nevertheless, precise registration is required and often necessitates anchored markers that disturb the patient and clinical flow. This work proposes a new contactless surface-based method adapted to featureless anatomies such as fibula to achieve a fast, precise, and reproducible registration.

METHODS

Preoperatively, a CT-scan of the patient is realized and osteotomies are virtually planned. During surgery, a structured light camera digitizes the fibula. The obtained intraoperative point cloud is coarsely registered with the preoperative model using 3 points defined in the CT-scan and located on the patient's bone with a laser beam. Then, a fine registration is performed using an ICP algorithm. The registration accuracy was evaluated comparing the position of points engraved in a 3D-printed fibula with their position in the registered model and evaluating resulting osteotomies. Accuracy and execution time were compared to a conventional stylus-based registration method. The work was validated in vivo.

RESULTS

The experiment performed on a 3D-printed model showed that execution time is equivalent to surface-based registration using a stylus, with a better accuracy (mean TRE of 0.9 mm vs 1.3 mm using stylus) and guarantee good osteotomies. The preliminary in vivo study proved the feasibility of the method.

CONCLUSION

The proposed contactless surface-based registration method using structured light camera gave promising results in terms of accuracy and execution speed and should be useful to implement CAS for mandibular reconstruction.

Reliability and agreement of Azure Kinect and Kinect v2 depth sensors in the shoulder joint range of motion estimation

BACKGROUND

Depth sensor-based motion analysis systems are of interest to researchers with low cost, fast analysis capabilities, and portability; thus, their reliability is a matter of interest. Our study examined the agreement and reliability in estimating the basic shoulder movements of Azure Kinect, Microsoft's state-of-the-art depth sensor, and its predecessor, Kinect v2, by comparing them with the gold standard marker-based motion analysis system.

METHODS

In our study, the shoulder joint ranges of motion of 20 healthy individuals were analyzed during dominant-side flexion, abduction, and rotation movements. The reliability and agreement between methods were evaluated using the intraclass correlation coefficient (ICC) and the Bland-Altman method.

RESULTS

Compared to the gold standard method, the old- and new-generation Kinect showed similar performance in terms of reliability in the estimation of flexion (ICC = 0.86 vs. 0.82) and abduction (ICC = 0.78 vs. 0.79) movements, respectively. In contrast, the new-generation sensor showed higher reliability than its predecessor in internal (ICC = 0.49 vs. 0.75) and external rotation (ICC = 0.38 vs. 0.67) movement.

CONCLUSION

Compared to its predecessor, Kinect Azure has higher reliability in analyzing movements in a lower range and variability, thanks to its state-of-the-art hardware. However, the sensor should also be tested on multiaxial movements, such as combing hair, drinking water, and reaching back, which are the tasks that simulate extremity movements in daily life.

Validation of an MRI Technique for the 6-DOF Knee Kinematics Measurement

Background: For total knee arthroplasty (TKA), the optimal rotational position of the femoral component is felt to be critically important. The current knee joint kinematics measurement technology is unable to identify the exact rotation axis of the knee joint, the main reasons being low measurement accuracy and insufficient three-dimensional data (2D-3D image matching technology). In order to improve the effect of TKA surgery, we proposed a knee joint kinematics measurement method, based on the MRI technology, and verified its measurement accuracy. We then employed this method to identify the personalized optimal rotation axis of the knee joint for TKA patients. Purposes: The purpose of the study was 1) to propose a method for measuring knee joint kinematics and verify its accuracy and 2) to propose a method for determining the optimal rotation axis of knee joint for TKA surgery, based on accurate kinematic measurement results. Materials and Methods: The experiment was divided into two parts: in vitro and in vivo. The purpose of the in vitro experiment was to verify the measurement accuracy of our method. We fixed two aquarium stones (approximately 10 cm * 10 cm * 10 cm in size, close to the size of the distal femur and proximal tibia) firmly on the fixed and moving arms of the goniometer/vernier caliper with glue and immersed the aquarium stones in the water to capture MRI images. The MRI images were then processed with MATLAB software, and the relative motion of the two aquarium stones was measured. The measurement accuracy of our method was verified via the scale reading of the moving arm on the goniometer/vernier caliper. In vivo, 36 healthy elderly participants (22 females, 14 males) were recruited from the local community; our method was then employed to measure the relative motion of the tibia and femur and to observe the rollback and screw home motion of the medial/lateral condyle of the femur, which was identified as specific kinematic features of the knee joint. Results: In vitro, all measurements were accurate to <1 mm and <1°. In vivo, all knee measurements showed rollback motion (the rollback distance of the medial femoral condyle was 18.1 ± 3.7 mm and that of the lateral condyle was 31.1 ± 7.3 mm) and screw home motion. Conclusion: In the application scenario of knee joint kinematics measurement, our method has an accuracy of <1° of rotation angle and <1 mm of translation for all reference points, and it can be employed to identify the most stable axis of the knee joint. Significance: Using our method to accumulate data on the knee rotation axis of more subjects to establish an average rotation axis of a given population may help in knee prosthesis design and reduce the patient dissatisfaction rate. Individually measuring the patient's rotation axis before TKA surgery and adjusting the prosthesis installation in TKA may further reduce the patient dissatisfaction rate, and automatic computer measurement may be realized in the future, but it is still time-consuming for now.

Revision Total Knee Arthroplasty Using Robotic Arm Technology

Total knee arthroplasty (TKA) is a highly successful operation for the treatment of end-stage osteoarthritis of the knee. Increasing use of computer-assisted and robotic-assisted total joint arthroplasty has been shown to improve component position, with short-term studies demonstrating improved survivability in unicompartmental knee arthroplasty. Robotic-assisted technology has been shown to be helpful in revising unicompartmental knee arthroplasty to TKA, as well as hip fusion to total hip arthroplasty, but few have described revision of a primary TKA. This case report describes the use of robotic-assisted technology in revision TKA. Robotic assistance during revision TKA may improve component alignment and increase prosthesis longevity. Future research is needed to investigate the effects on survivorship and cost.