PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 10, 2026Journal of ISAKOS Joint Disorders & Orthopaedic Sports Medicine0 citationsOpen Access

Enhancing patella positioning and tracking in Total Knee Arthroplasty using Image-Based Robotic Surgery: A Comprehensive Surgical Technique

CPCarmela PizzigalloHVHannes VermueLALuca Andriollo

Key Points

  • This research aims to enhance patellar positioning and tracking during total knee arthroplasty using image-based robotic surgery.
  • Utilized image-based robotic-assisted technology for patellar resurfacing in total knee arthroplasty.
  • Outlined a detailed step-by-step approach for the surgical procedure.
  • Emphasized standardized and reproducible techniques for implantation.
  • Anticipated improvement in clinical outcomes related to anterior knee pain.
  • Potential enhancement in functional performance of active patients.

Abstract

Patellar resurfacing during total knee arthroplasty (TKA) remains a contentious topic, particularly with rising patient expectations for functional outcomes. This article highlights a novel approach utilizing image-based robotic-assisted technology (MAKO, Stryker®) to enhance patellar positioning and tracking during TKA. We outline the step-by-step approach for patellar resurfacing, that the authors anticipate could be evaluated in future studies for its potential impact on clinical outcomes like alleviating anterior knee pain and improved functional performance in active patients. This comprehensive technique facilitates precise implantation and assessment of patellar anatomy, promoting a standardized and reproducible surgical approach. Looking ahead, we advocate for enhancements in robotic software to standardize patellar measurements, ultimately aiming to refine surgical techniques and improve patient quality of life.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Pizzigallo et al. (2026) studied this question.

synapsesocial.com/papers/69af944f70916d39fea4b526https://doi.org/10.1016/j.jisako.2026.101095
Ask AI
Helpful
Bookmark
Share
View Full Paper