Multi-Atlas Alignment for Orthopedic Implant Sizing and Overhang
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Solution Overview
Problem
The challenge in surgical joint repair procedures, such as joint arthroplasty, lies in the planning stage where trade-offs between implant size and alignment with patient anatomy are difficult to optimize, particularly in total ankle repair, leading to complications like tibial implant overhang and Antero-Posterior alignment issues.
Innovation Solution
A system provides automated alignment and sizing advice using non-linear optimization and multi-atlas alignment techniques, leveraging preoperative scans and reference atlases of other patients to recommend optimal implant size and alignment for a specific patient, without requiring cumbersome modeling and programming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated alignment and sizing relies on non-linear optimization of surgery criteria, then alignment precision is improved, but system complexity and programming requirements increase
Solution Approach 1:
The system creates virtual copies (atlases) of patient anatomy from preoperative scans and uses these digital replicas for automated measurement and alignment calculation, eliminating the need for complex physical measurement devices and manual programming while achieving high precision
Solution Approach 2:
The patent replaces traditional mechanical measurement and optimization systems with automated image processing and computer vision algorithms that analyze anatomical landmarks in scan data, substituting physical measurement tools with digital computational methods that reduce system complexity
2Measurement precision
If multiple surgery criteria are combined into a single planning quality measure, then alignment precision is improved, but modeling and programming time increases
Solution Approach 1:
The system performs preliminary processing of preoperative scan data to automatically generate anatomical atlases and identify key landmarks before the surgical planning phase, so that when multiple surgery criteria need to be combined, the foundational measurements are already available, significantly reducing the time required for modeling and programming
Solution Approach 2:
The automated image processing system performs self-service by automatically identifying anatomical landmarks, generating measurements, and creating the planning quality measure from scan data without requiring manual intervention for each measurement, thereby reducing both modeling time and programming requirements
Data Source
AI summary
An example method includes obtaining, by one or more processors, a target atlas of a particular patient on which an arthroplasty procedure is to be performed; selecting, by the one or more processors and based on a comparison of values of the target atlas and a plurality of reference atlases of other patients on which the arthroplasty procedure has been performed, at least one reference atlas of the plurality of reference atlases of the other patients; and determining, by the one or more processors and based on the selected at least one reference atlas, one or both of an implant size and an implant alignment for the particular patient.