The effects of gender, age, and videogame experience on performance and experiences with a surgical robotic arm: an exploratory study with general public

TiRobot‑assisted versus conventional fluoroscopy-assisted percutaneous sacroiliac screw fixation for pelvic ring injuries: a meta‑analysis

BACKGROUND

The TiRobot is the only robot that has been reported in the literature for posterior pelvic injuries. We aim to compare TiRobot-assisted pelvic screw fixation with the conventional fluoroscopy-assisted percutaneous sacroiliac screw fixation.

METHODS

We conducted a meta-analysis to identify studies involving TiRobot‑assisted versus conventional percutaneous sacroiliac screw fixation for pelvic ring injuries in electronic databases, including Web of Science, Embase, PubMed, Cochrane Controlled Trials Register, Cochrane Library, Highwire, CBM, CNKI, VIP, and WanFang database, up to April 2022. The following keywords were used: "TiRobot," "robot," "robotic," "pelvic fracture," "screw fixation," "percutaneous," and "pelvic ring injury." Pooled effects of this meta-analysis were calculated using STATA SE version 15.0.

RESULTS

Compared with conventional fluoroscopy-assisted percutaneous sacroiliac screw fixation, TiRobot will result in less radiation exposure time of screw implantation (P = 0.000), less frequency of intraoperative fluoroscopy (P = 0.000), fewer guide wire attempts (P = 0.000), less intraoperative blood loss (P = 0.005), better screw accuracy (P = 0.011), better Majeed score (P = 0.031), and higher overall excellent and good rates of Majeed score (P = 0.018). However, there were no significant differences in terms of operative time (P = 0.055), fracture healing time (P = 0.365), and overall excellent and good rate of reduction accuracy (P = 0.426) between the two groups.

CONCLUSION

TiRobot-assisted fixation has less intraoperative fluoroscopy and intraoperative blood loss, superior screw accuracy, and Majeed score compared with conventional percutaneous sacroiliac screw fixation. TiRobot has no significant effect on operative time, fracture healing time, and reduction accuracy. Given the relevant possible biases in our meta-analysis, we required more adequately powered and better-designed RCT studies with long-term follow-up to reach a firmer conclusion.

Design and evaluation of an intelligent reduction robot system for the minimally invasive reduction in pelvic fractures

Introduction

Pelvic fracture is a severe high-energy injury with the highest disability and mortality of all fractures. Traditional open surgery is associated with extensive soft tissue damages and many complications. Minimally invasive surgery potentially mitigates the risks of open surgical procedures and is becoming a new standard for pelvic fracture treatment. The accurate reduction has been recognized as the cornerstone of minimally invasive surgery for pelvic fracture. At present, the closed reduction in pelvic fractures is limited by the current sub-optimal 2D intra-operative imaging (fluoroscopy) and by the high forces of soft tissue involved in the fragment manipulation, which might result in fracture malreduction. To overcome these shortcomings and facilitate pelvic fracture reduction, we developed an intelligent robot-assisted fracture reduction (RAFR) system for pelvic fracture.

Methods

The presented method is divided into three parts. The first part is the preparation of 20 pelvic fracture models. In the second part, we offer an automatic reduction algorithm of our robotic reduction system, including Intraoperative real-time 3D navigation, reduction path planning, control and fixation, and robotic-assisted fracture reduction. In the third part, image registration accuracy and fracture reduction accuracy were calculated and analyzed.

Results

All 20 pelvic fracture bone models were reduced by the RAFR system; the mean registration error E1 of the 20 models was 1.29 ± 0.57 mm. The mean reduction error E2 of the 20 models was 2.72 ± 0.82 mm. The global error analysis of registration and reduction results showed that higher errors are mainly located at the edge of the pelvis, such as the iliac wing.

Conclusion

The accuracy of image registration error and fracture reduction error in our study was excellent, which could reach the requirements of the clinical environment. Our study demonstrated the precision and effectiveness of our RAFR system and its applicability and usability in clinical practice, thus paving the way toward robot minimally invasive pelvic fracture surgeries.