Comparison of algorithms for automated femur fracture reduction

Hill-based musculoskeletal model for a fracture reduction robot

BACKGROUND

The introduction of fracture reduction robot can solve the problem of large reduction forces during fracture reduction surgeries and the need to collect multiple medical images. However, because its safety has not been certified, there are few academic achievements on this type of robot. To calculate the safety factor during its operation, a musculoskeletal model needs to be established to study the constraints of muscles on the robot. The existing academic achievements of musculoskeletal modelling are mainly for application such as rehabilitation treatment and collision in car accidents.

METHODS

A musculoskeletal model applied to the fracture reduction robot is proposed in this paper. First, by comparing the characteristics of mainstream muscle models and combining the biological characteristics of the anesthetised muscles, the Hill model was selected as the muscle model for this study. Second, based on the motion composition of six spatial degrees of freedom, five basic fractural malposition situations are proposed. Then, a 170-cm tall male musculoskeletal model was built in Opensim. Based on this model, the muscle force curves of the above malposition situations are calculated. Finally, a similar musculoskeletal model was established in Adams, and the accuracy of its muscle force data was tested. The study is approved by the ethics committee of the Rehabilitation Hospital, National Research Center for Rehabilitation Technical Aids, Beijing, China.

RESULTS

The muscle force curve of Opensim and Adams model under situations of five basic malposition are compared. Most of the correlation coefficients are in the range of 0.98-0.99. The overall correlation coefficient is greater than 0.95.

CONCLUSIONS

The simulation results prove that this model can be used for the safety assessment of the fracture reduction robots. This model will be served as an environmental constraint to study the control of fracture reduction robot.

Intraoperative use of cortical step sign and diameter difference sign: Accuracy, inter-rater agreement and influence of surgical experience in subtrochanteric transverse fractures

BACKGROUND

The cortical step sign (CSS) and diameter difference sign (DDS) are radiographic tools for torsional alignment control in intramedullary nailing. They have been found to be highly relevant in objective radiographic measurements, but for intraoperative visual identification they lack sufficient evidence yet. The aim of this experimental study was to evaluate their (1) accuracy, (2) inter-rater agreement, (3) predictors of correct identification for clinically relevant maltorsion (CRM: ≥15°), and (4) positive and negative predictive values.

HYPOTHESIS

Sensitivity and specificity of CSS and DDS in visual identification of CRM are comparable to those in objective measurement.

MATERIAL AND METHODS

Six observers of three different levels of surgical experience evaluated 50 a.p. and 50 lateral views of subtrochanteric fractures of cadaveric specimens with internal/external maltorsion from 0° to 30° to assess for CSS, DDS, and CRM. (1) Sensitivity and specificity were evaluated. Percentage agreement and Cohen's Kappa were used to evaluate accuracy as agreement with measured/true values and (2) inter-rater agreement. To determine (3) significant predictors of correct identification of the CSS, DDS, and CRM, a mixed-effects logistic model was constructed, and (4) predictive values were calculated.

RESULTS

(1) Sensitivities of CSS and DDS for CRM (0.99±0.03 and 0.88±0.06) were close to those in objective measurement (1.00 and 0.90). So were specificities (0.25±0.08 and 0.47±0.17 vs. 0.32 and 0.47). Agreement percentage for CSS was high (90-94%, kappa 0.40-0.69), for DDS and CRM it was slightly lower (74-82%, kappa 0.34-0.57 and 62-76%, kappa 0.26-0.49). (2) Inter-rater agreement also showed the highest values for CSS (88-96%, kappa 0.51-0.73) with slightly lower values for DDS (74-84%, kappa 0.36-0.63) and CRM (62-84%, kappa 0.21-0.68). (3) Training level and the magnitude of maltorsion were found the most relevant predictors of a correct identification of CSS/DDS/CRM. (4) DDS showed a higher positive predictive value (73.1%), CSS a higher negative predictive value (93.5%).

DISCUSSION

We found visual identification of CSS and DDS to be almost as accurate as objective measurement in the detection of CRM. Estimation of maltorsion is not sufficiently reliable, but a negative CSS excludes a CRM with high probability. Both signs should be applied by experienced surgeons.

LEVEL OF EVIDENCE

Level III, experimental setting, non-randomised experimental trial.

Medical Robotics in Bone Fracture Reduction Surgery: A Review

Since the advantages of precise operation and effective reduction of radiation, robots have become one of the best choices for solving the defects of traditional fracture reduction surgery. This paper focuses on the application of robots in fracture reduction surgery, design of the mechanism, navigation technology, robotic control, interaction technology, and the bone-robot connection technology. Through literature review, the problems in current fracture reduction robot and its future development are discussed.