Heart Tissue Surface Contour Radiosurgical Planning
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Solution Overview
Problem
Current radiosurgical planning tools face difficulties in efficiently creating treatment plans for arrhythmia lesions on the heart due to the complex geometry of the heart, making it challenging to visualize and draw appropriate treatment patterns on conventional planar CT scans.
Innovation Solution
A system generates a three-dimensional model of the heart's tissue surface, allowing physicians to designate lesion patterns, which are then projected back onto CT scans, enabling the creation of a radiosurgical plan with defined trajectories and dosage clouds to effectively treat arrhythmias.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional planar CT scan interfaces are used for arrhythmia treatment planning, then the existing radiosurgical planning tools can be utilized, but it becomes surprisingly difficult to efficiently establish an arrhythmia treatment plan due to the complex geometry of the heart
Solution Approach 1:
The patent transitions from two-dimensional planar CT scan interfaces to a three-dimensional surface model of the heart. The system generates a 3D model representing the tissue surface, allowing physicians to draw lesion patterns in three dimensions. This dimensional upgrade enables intuitive visualization and drawing of treatment patterns that conform to the heart's complex geometry, resolving the difficulty of operating with conventional 2D tools.
2Manufacturing precision
If treatment patterns are drawn on each planar slice of the heart, then coverage of the entire heart surface can be attempted, but the process becomes inefficient and difficult due to the need to evaluate multiple CT scans and draw lines/circles at each slice
Solution Approach 1:
Instead of processing multiple 2D slices sequentially, the system creates a unified 3D surface model where the entire heart surface is represented in a single coherent structure. Physicians can draw lesion patterns directly on this 3D model, and the system automatically calculates the corresponding treatment parameters. This eliminates the time-consuming process of evaluating and drawing on each individual slice while maintaining precise lesion placement.
Solution Approach 2:
The system generates a virtual 3D surface model that copies and represents the actual heart geometry from CT scan data. This digital model serves as a workspace where treatment patterns can be designed and visualized before being translated back to the treatment planning system. The copying approach allows efficient manipulation of treatment patterns without repeatedly processing the original multi-slice CT data.
3Measurement precision
If a three-dimensional model of the tissue surface is generated and lesion patterns are drawn on it, then precise visualization and calculation of lesion patterns is enabled, but the device complexity increases
Solution Approach 1:
The system introduces a 3D surface model as an intermediary between the CT scan data and the treatment planning process. This intermediate representation simplifies the visualization and calculation of lesion patterns by providing an intuitive geometric model that naturally captures the heart's surface geometry. The intermediary model serves as a bridge that translates complex multi-slice CT data into a form that is easier to work with while preserving measurement precision.
Data Source
AI summary
A system that generates a three-dimensional model of a tissue surface, for example the inner surface of the heart from two-dimensional image data slices. On this surface, one or more pattern lines are drawn, e.g., by a physician using a user interface, to designate desired lesion(s) on the surface. From the pattern lines, a three-dimensional volume for a lesion can be determined using known constraints. Advantageously, the series of boundaries generated by the three-dimensional volume may be projected back onto the individual CT scans, which then may be transferred to a standard radiosurgical planning tool. A dose cloud may also be projected on the model to aid in evaluating a plan.