Semi-Automated Ophthalmic Photocoagulation Alignment
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Solution Overview
Problem
Current ophthalmic treatments for conditions like diabetic retinopathy and age-related macular degeneration using visible laser light are tedious and prone to inaccuracies due to patient eye movement, requiring extensive physician skill and risk of unintended damage to sensitive areas.
Innovation Solution
A semi-automated ophthalmic treatment system that includes a light source, delivery system, camera, and control electronics for registering pre-treatment images with live images, verifying alignment, and compensating for eye movement, allowing precise and efficient application of treatment patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple laser spots are applied automatically in patterns to reduce treatment time, then productivity is improved, but reliability deteriorates due to eye movement causing misalignment with target tissue
Solution Approach 1:
The system performs preliminary actions by capturing pre-treatment images to identify target tissue locations and create a treatment pattern before actual laser delivery. The pattern is pre-calculated and stored, ready for rapid automated delivery. This allows the treatment to proceed quickly while maintaining accuracy through pre-verified targeting.
Solution Approach 2:
The system implements feedback by capturing live images during treatment and comparing them with pre-treatment images to detect eye movement. When misalignment is detected, the system adjusts the treatment pattern delivery in real-time to compensate for eye movement, ensuring the laser spots remain aligned with the intended target tissue throughout the rapid automated treatment process.
2Manufacturing precision
If physicians manually position each laser beam spot to ensure precision, then manufacturing precision is improved, but loss of time increases due to the tedious and time-consuming nature of manual positioning
Solution Approach 1:
The system creates a digital copy of the treatment plan by generating a treatment pattern from pre-treatment images that maps the desired laser spot locations. This digital pattern serves as a template that guides the automated laser delivery system, replicating the precision of manual positioning without the time-consuming manual intervention. The pattern can be rapidly delivered while maintaining accuracy through the pre-planned coordination of multiple laser spots.
3Device complexity
If physicians rely on pre-treatment images to identify target tissue, then device complexity is reduced, but measurement precision deteriorates because physicians cannot track rapid eye movements (saccades) that occur during treatment
Solution Approach 1:
The system maintains continuous monitoring of the patient's eye by capturing live images throughout the treatment process. This continuous feedback allows the system to detect and compensate for eye movements including rapid saccades, ensuring that the treatment pattern remains accurately aligned with the target tissue despite ongoing eye motion during treatment delivery.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system ensures accurate and efficient delivery of treatment patterns, reducing treatment time and risk of damage by compensating for eye movement and verifying alignment, thereby improving precision and safety.
Implementation Method 1
a camera for capturing a live image of the patient's eye
Implementation Method 2
a light source for producing treatment light, a delivery system for delivering the treatment light to the patient's eye
Implementation Method 3
conditions such as diabetic retinopathy, vein occlusion and age-related macular degeneration have been treated with photocoagulation induced by visible laser light
Data Source
AI summary
An ophthalmic treatment system and method for performing therapy on target tissue in a patient's eye. A delivery system delivers treatment light to the patient's eye and a camera captures a live image of the patient's eye. Control electronics control the delivery system, register a pre-treatment image of the patient's eye to the camera's live image (where the pre-treatment image includes a treatment template that identifies target tissue within the patient's eye), and verify whether or not the delivery system is aligned to the target tissue defined by the treatment template. The control electronics control the delivery system to project the treatment light onto the patient's eye in response to both an activation of a trigger device and the verification that the delivery system is aligned. to the target tissue, as well as adjust delivery system alignment to track eye movement.