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Published on: August 4, 2020
Auto-planning in preoperative shoulder arthroplasty software reduces implant planning time and number of actions
Pierre Mahe1, Sarah Shank2,3, Arthur de Gast2,3
1Stryker, Trauma & Extremities, Upper Extremities, Brest, France.
Background:
Software-based preoperative 3D shoulder arthroplasty implant planning is traditionally done manually and can be time-consuming. Systems like Blueprint© are now using software features that suggest implant positioning and sizing. This study is a comparative evaluation of preoperative planning software, assessing user interaction efficiency by comparing the time and number of actions required to complete planning tasks with and without automated planning features.
Materials And Methods:
Real world plannings log files extracted from preoperative software were used to compare the impact of the auto-planning suggestion feature on the time taken and the number of actions to perform shoulder surgical planning. Comparative analyses were performed across the two main groups (with and without auto-planning) and three subgroups divided on surgeon's experience.
Results:
A total of 7021 preoperative plannings done by 1018 surgeons were included. The auto-planning group included 65 surgeons with 780 plannings and the Manual group included 953 surgeons with 6241 plannings.The Blueprint® new preoperative auto-planning feature-marketed under the name "BP Assist"-reduced the number of actions during the planning process by 29% compared to manual planning. For the most complex cases, auto-planning reduced the planning time by 25%. The auto-planning feature used by new users resulted in preoperative planning times that were at least as fast-and often faster-than those of high experience users who planned manually, while also requiring fewer actions to complete the planning process.
Conclusions:
The integration of an auto-planning feature into preoperative software allowed for a reduction in the number of actions and the time spent during preoperative software-based planning process. Further research is needed to determine whether auto-planning represents a meaningful advancement in shoulder arthroplasty, with potential to support surgical efficiency and clinical decision-making.
