Does Powered Femoral Broaching Compromise Patient Safety in Total Hip Arthroplasty?

Background

During manual broaching (MB) in total hip arthroplasty (THA), off-axis forces delivered to the proximal femur and broach malalignment can lead to fractures and cortical perforations. Powered broaching (PB) is a novel alternative that delivers consistent impaction forces and reduces workload. This is the first large-scale study to compare intraoperative and 90-day rates of periprosthetic femur fractures (PFFs) and perforations in THA performed using MB vs PB.

Methods

Our institutional database was reviewed for all patients undergoing primary cementless direct anterior THA from 2016 to 2021. Three surgeons performing 2048 THAs (MB = 800; PB = 1248) using the same stem design were included. PFFs and perforations within 90 days of the index procedure were compared. Differences in length of surgery and demographics were assessed.

Results

Calcar fractures occurred in <1% of patients (PB [0.96%, 12/1248] vs MB [0.25%, 2/800]; P = .06). Rates of trochanteric fractures did not differ (PB = 0.32% [4/1248] vs MB = 0.38% [3/800]; P = .84). Cortical perforations occurred in 0.24% (3/1248) of the PB cohort and in 0.75% (6/800) of the MB cohort (P = .09). No revisions due to aseptic loosening or PFF occurred within 120 days of surgery.

Conclusions

Our single-center experience with powered femoral broaching in THA demonstrates PB is a safe and efficient means of performing direct anterior THA. Low rates (<1%) of PFF, perforation, and revision can be achieved. Given our positive experience with PB, all surgeon authors utilize PB nearly exclusively for elective primary direct anterior THA.

Learning intraoperative organ manipulation with context-based reinforcement learning

Purpose

Automation of sub-tasks during robotic surgery is challenging due to the high variability of the surgical scenes intra- and inter-patients. For example, the pick and place task can be executed different times during the same operation and for distinct purposes. Hence, designing automation solutions that can generalise a skill over different contexts becomes hard. All the experiments are conducted using the Pneumatic Attachable Flexible (PAF) rail, a novel surgical tool designed for robotic-assisted intraoperative organ manipulation.

Methods

We build upon previous open-source surgical Reinforcement Learning (RL) training environment to develop a new RL framework for manipulation skills, rlman. In rlman, contextual RL agents are trained to solve different aspects of the pick and place task using the PAF rail system. rlman is implemented to support both low- and high-dimensional state information to solve surgical sub-tasks in a simulation environment.

Results

We use rlman to train state of the art RL agents to solve four different surgical sub-tasks involving manipulation skills using the PAF rail. We compare the results with state-of-the-art benchmarks found in the literature. We evaluate the ability of the agent to be able to generalise over different aspects of the targeted surgical environment.

Conclusion

We have shown that the rlman framework can support the training of different RL algorithms for solving surgical sub-task, analysing the importance of context information for generalisation capabilities. We are aiming to deploy the trained policy on the real da Vinci using the dVRK and show that the generalisation of the trained policy can be transferred to the real world.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11548-022-02630-2.

Autonomous pick-and-place using the dVRK

Purpose

Robotic-assisted partial nephrectomy (RAPN) is a tissue-preserving approach to treating renal cancer, where ultrasound (US) imaging is used for intra-operative identification of tumour margins and localisation of blood vessels. With the da Vinci Surgical System (Sunnyvale, CA), the US probe is inserted through an auxiliary access port, grasped by the robotic tool and moved over the surface of the kidney. Images from US probe are displayed separately to the surgical site video within the surgical console leaving the surgeon to interpret and co-registers information which is challenging and complicates the procedural workflow.

Methods

We introduce a novel software architecture to support a hardware soft robotic rail designed to automate intra-operative US acquisition. As a preliminary step towards complete task automation, we automatically grasp the rail and position it on the tissue surface so that the surgeon is then able to manipulate manually the US probe along it.

Results

A preliminary clinical study, involving five surgeons, was carried out to evaluate the potential performance of the system. Results indicate that the proposed semi-autonomous approach reduced the time needed to complete a US scan compared to manual tele-operation.

Conclusion

Procedural automation can be an important workflow enhancement functionality in future robotic surgery systems. We have shown a preliminary study on semi-autonomous US imaging, and this could support more efficient data acquisition.

Surgical automation reduces operating time while maintaining accuracy for direct anterior total hip arthroplasty

Objective

Investigate the efficiency/accuracy of surgical automation versus manual component implantation in DA THA.

Methods

Retrospective review of 111 hips: 51 hips via automation and 60 hips via manual technique for DA THA.

Results

OR time averaged 8 min faster in the Automated group, compared to Manual group (p = 0.0009). Average femoral size was one size larger in the Automated group compared to Manual group (p = 0.007). No clinically significant differences were found between Manual and Automated groups for cup position or limb-length discrepancy. One calcar fracture occurred in the Automated group.

Conclusion

Surgical automation is efficient and accurate for DA THA.