Algorithm-based optimization for knee arthroplasty procedures

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Solution Overview

Problem

Existing arthroplasty surgical procedures often require manual modifications to surgical plans based on intraoperative patient data, lacking efficient methods for optimizing implant placement and alignment during surgeries like total knee arthroplasty and total hip arthroplasty.

Innovation Solution

A computer-assisted surgical system utilizing pre-operative data, surgical tools, and machine learning models to generate patient-specific kinetic and kinematic response values, providing real-time visualization and optimization of implant placement through interactive user interfaces and equation sets.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual modifications to surgical plans are performed based on intraoperative patient data, then surgical flexibility and adaptability are improved, but surgical time and procedural complexity increase

Engineering Contradiction:

Improvesurgical flexibilityVSAvoidsurgical time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary calculations and generates optimized surgical plans before surgery using pre-operative patient data. During surgery, the pre-computed plans can be quickly adjusted by selecting different parameter sets, eliminating the need for time-consuming manual modifications while maintaining surgical flexibility.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates digital copies of patient anatomy and surgical plans that can be manipulated and optimized during surgery without affecting the actual surgical procedure. Multiple virtual surgical plans can be generated and compared, allowing surgeons to select the best option without time loss.

Inventive Principle:

Principle #26Copying

2Manufacturing precision

If traditional surgical planning methods are used without algorithm-based optimization, then procedural simplicity is maintained, but implant placement accuracy and patient-specific optimization deteriorate

Engineering Contradiction:

Improveimplant placement accuracyVSAvoidsystem complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system replaces manual surgical planning and measurement methods with automated computer-based algorithms. The computer system processes patient data, performs kinetic and kinematic simulations, and generates optimized surgical plans, substituting manual mechanical measurement and calculation methods with automated computational processes.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system automatically processes patient-specific anatomical data and generates optimized surgical plans without requiring extensive manual intervention. The algorithms self-adjust parameters based on patient-specific constraints and surgical requirements, reducing the need for complex manual adjustments by surgeons.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If extensive manual adjustments are made during surgery to optimize implant placement, then patient-specific customization is improved, but surgical efficiency and productivity decrease

Engineering Contradiction:

Improvepatient-specific customizationVSAvoidsurgical efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

Patient-specific surgical plans are computed in advance using pre-operative data, allowing extensive customization to be completed before surgery. During the procedure, surgeons can quickly review and adjust pre-computed parameters without time-consuming calculations, maintaining both patient-specific customization and surgical efficiency.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system provides real-time feedback during surgery by comparing actual surgical parameters with optimized target values. This allows surgeons to make quick, informed adjustments to achieve patient-specific optimization without extensive manual trial and error, improving both customization and efficiency.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250255672A1Algorithm-based optimization for knee arthroplasty procedures

Publication Date: 2025.08.14 SMITH & NEPHEW INC

AI summary

A method for optimizing a knee arthroplasty surgical procedure includes receiving pre-operative data comprising (i) anatomical measurements of the patient, (ii) soft tissue measurements of the patient's anatomy, and (iii) implant parameters identifying an implant to be used in the knee arthroplasty surgical procedure. An equation set is selected from a plurality of pre-generated equation sets based on the pre-operative data. During the knee arthroplasty surgical procedure, patient-specific kinetic and kinematic response values are generated and displayed using an optimization process. The optimization process includes collecting intraoperative data from one or more surgical tools of a computer-assisted surgical system, and using the intraoperative data and the pre-operative data to solve the equation set, thereby yielding the patient-specific kinetic and kinematic response values. A visualization is then provided of the patient-specific kinetic and kinematic response values on the displays.