Artificial Intelligence to Detect Early Total Knee Replacement Implant Failure

Using Machine Learning to Detect and Predict Loosening NexGen Total Knee Replacement

The goal of this trial is to investigate whether Machine Learning (ML) can be used to detect small degrees of loosening, lucent zones, or any other changes on radiographs that might predict early failure following NexGen total knee replacement.

Researchers will identify plain AP and lateral plain film radiographs from two groups of patients. Those who has NexGen total knee replacements (TKRs) that went on to failure, and those who has well performing TKRs. Radiographs from these two groups will be labelled as 'failure' and 'well performing' and will be processed through a machine learning algorithm.

The algorithm will be successful if it is able to detect a NexGen TKR that went on to failure or went on to perform well. This will be determined by using a test set.

The population will be adults who had the recalled a NexGen Total Knee Replacement with a standard tibial tray. It will include adults only, who has the TKR at University Hospitals Southampton between 2003 and 2022.

Failure will be defined as revision of tibial or femoral components which is likely due to aspectic loosening. It will exclude washouts, exchange of poly, peri-prosthetic fractures, microbiologically confirmed infection.

Well performing TKRs will be defined as patients who have had their TKR in situ for 10 years and have reported no significant symptoms.

Study Overview

• Status: Not yet recruiting
• Conditions: Aseptic Loosening of Prosthetic Joint

• Study Type: Observational
• Enrollment (Estimated): 2105

Contacts and Locations

• Study Contact: Name: Rory Ormiston; Phone Number: 07443 432819; Email: rory.ormiston@uhs.nhs.uk

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

The population will be adults who had the recalled a NexGen Total Knee Replacement with a standard tibial tray. It will include adults only, who has the TKR at University Hospitals Southampton between 2003 and 2022.

Description

Inclusion Criteria:

• Had a NexGen TKR between 2003 and 2022.

Exclusion Criteria:

• Below 18 yrs old.
• Revision surgery for any reason other than aseptic loosening
• patients who have not had a revision but who do not have a well functioning TKR.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Failed; This group will be made up of patient who had revision TKR due to aseptic loosening within 10 years of primary arthroplasty
Well performing; This group will be made up of patients who have an asymptomatic TKR 10 years after primary arthroplasty.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Predictive accuracy of machine learning model	The predictive accuracy of a machine learning algorithm. Using common ML measured, AUROC etc.	Up to 21 years. Data starts from 2003.

Collaborators and Investigators

• Sponsor: University Hospital Southampton NHS Foundation Trust

Study record dates

Study Major Dates

• Study Start (Estimated): August 1, 2025
• Primary Completion (Estimated): December 1, 2025
• Study Completion (Estimated): December 1, 2025

Study Registration Dates

• First Submitted: November 6, 2024
• First Submitted That Met QC Criteria: December 6, 2024
• First Posted (Actual): December 9, 2024

Study Record Updates

• Last Update Posted (Actual): May 13, 2025
• Last Update Submitted That Met QC Criteria: May 12, 2025
• Last Verified: December 1, 2024

More Information

Terms related to this study

• Other Study ID Numbers: T&O0238

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No