Laser Surgery System Tissue Property Inference
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Solution Overview
Problem
The unpredictability of tissue response to laser energy in laser therapies makes it challenging to accurately predict outcomes, often requiring repeated treatments and impacting the precision and accuracy of interventions, leading to increased operating-room time and costs.
Innovation Solution
An automated laser-surgery system that infers tissue properties by analyzing the response to a known laser signal, allowing for the planning of a treatment path with controlled parameters such as treatment route, laser power, and duration, using interrogation features like test craters or color changes to inform subsequent treatment passes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a laser signal is directed at tissue to induce therapeutic effects, then treatment outcomes can be achieved, but the unpredictability of tissue response makes it difficult to predict outcomes and requires repeated treatments
Solution Approach 1:
The system performs preliminary actions by creating interrogation features (test craters) before the main treatment to characterize tissue properties. This preliminary characterization enables accurate prediction of subsequent treatment outcomes, eliminating the need for repeated treatments and reducing operating-room time.
Solution Approach 2:
The system implements feedback by measuring the actual response of tissue to a known laser signal, using this measured response to extract tissue properties, and then using these extracted properties to plan and execute the treatment path. This closed-loop feedback ensures predictable and reliable treatment outcomes.
2Reliability
If excess healthy tissue is impacted to ensure successful therapeutic result, then treatment success is improved, but accuracy and precision of intervention is degraded
Solution Approach 1:
The system applies local quality by using extracted tissue properties to customize the treatment path for each specific location. By planning the treatment route based on locally measured tissue characteristics, the system achieves precise ablation boundaries that spare healthy tissue while ensuring complete removal of pathological tissue.
Solution Approach 2:
The system changes parameters by adjusting laser-signal parameters (power, spot size, radiant exposure, duration of irradiance, speed) based on extracted tissue properties. This dynamic parameter adjustment enables precise control of the ablation process, achieving high precision while maintaining therapeutic success.
3Reliability
If repeated laser treatments are performed to ensure successful result, then therapeutic outcome is improved, but cost and operating-room time increase
Solution Approach 1:
The system performs preliminary tissue characterization through interrogation features before the main treatment, enabling accurate prediction of treatment outcomes in advance. This preliminary action eliminates the need for repeated treatments, improving productivity and reducing costs while maintaining high therapeutic success rates.
Solution Approach 2:
The system uses feedback from measured tissue responses to optimize the treatment plan, ensuring that a single treatment pass achieves the desired therapeutic outcome. This feedback-driven approach eliminates redundant treatments, thereby improving treatment efficiency and reducing operational costs.
4Measurement precision
If tissue properties are inferred from interrogation features, then accuracy of laser-tissue interaction prediction is improved, but device complexity increases
Solution Approach 1:
The system uses an intermediary approach by creating interrogation features (test craters) that serve as mediators between the laser signal and the tissue properties. By analyzing the characteristics of these intermediary features, the system accurately infers tissue properties without requiring direct complex measurements, thereby maintaining measurement precision while managing system complexity.
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
This approach enables more accurate prediction of laser-tissue interactions, improving the precision and efficiency of laser therapies by optimizing treatment paths and reducing the need for repeated procedures, thereby minimizing complications and costs.
Implementation Method 1
a laser signal is used to ablate tissue at the treatment site
Implementation Method 2
which indicates the manner in which the tissue responds to a laser signal
Data Source
AI summary
The present disclosure enables improved laser treatments by enabling better estimation of laser-tissue interaction to better inform the planning of a treatment path for a laser signal through a treatment region. An embodiment in accordance with the present disclosure uses a laser signal to generate a feature in the treatment region, generates a surface profile of the treatment region that includes the feature, compares that surface profile to another surface profile of the treatment region taken before the generation of the feature, and infers at least one property for at least one tissue type in the treatment region based on the comparison. In some embodiments, the feature is generated such that it includes a plurality of tissue types previously identified in the treatment region, thereby enabling inference one or more properties for each tissue type and/or locating one or more boundaries between tissue types.