Cardiac Ablation Target Mapping Through Aligned Multimodal Imaging
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Solution Overview
Problem
Current invasive and non-invasive ablation techniques for cardiac arrhythmias suffer from user-dependent variability and lack of formal decision support, leading to inconsistent treatment outcomes due to manual conversion of imaging and clinical data into treatment targets without standardized protocols.
Innovation Solution
A method utilizing multi-modal imaging (electrical, anatomic, and functional) to automatically identify cardiac arrhythmia targets through a decision support module, combining imaging data to define cardiac arrhythmia targets with confidence scoring and risk profiling, enabling precise and objective treatment planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual conversion of imaging and clinical data into treatment targets is used, then treatment can be performed with current techniques, but user-dependent variability results in inconsistent treatment outcomes
Solution Approach 1:
The system enables automated processing where the computational system independently performs target identification and treatment planning by integrating multi-modal imaging data, eliminating reliance on manual clinician interpretation and reducing user-dependent variability in treatment outcomes
Solution Approach 2:
The patent replaces the manual mechanical process of data conversion and target identification with an automated computational system that integrates imaging data and algorithmically determines treatment targets, thereby improving consistency while maintaining ease of use
2Reliability
If ad hoc target selection is used, then treatment planning is flexible, but lack of formal decision support leads to inconsistent treatment outcomes
Solution Approach 1:
The system incorporates confidence scoring that provides feedback on the reliability of identified treatment targets, allowing clinicians to assess and validate automated recommendations while maintaining flexibility in final treatment decisions
Solution Approach 2:
The system performs preliminary automated analysis of multi-modal imaging data to pre-identify potential treatment targets and generate treatment plans before clinician review, reducing variability while preserving clinical judgment and flexibility
3Reliability
If invasive catheter ablation is used, then arrhythmia treatment can be performed, but significant risk to the patient is introduced
Solution Approach 1:
The system performs comprehensive pre-treatment planning by integrating multi-modal imaging data to precisely define treatment targets and predict outcomes before procedure, enabling better-informed decisions about invasive versus non-invasive approaches and reducing unnecessary patient risks
Solution Approach 2:
The computational system acts as an intermediary between diagnostic imaging and treatment delivery, providing detailed target characterization and risk assessment that guides selection of appropriate treatment modality and optimizes safety outcomes
Data Source
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AI summary
Disclosed herein are systems and methods (100) for determining one or more cardiac arrhythmia targets for ablation. A method may include identifying a number of segments on each image of a plurality of images of a patient, each segment corresponding to a different anatomical location; identifying (110) abnormalities in each image of the plurality of images, the abnormalities comprising at least one of a scar location, a non-viable tissue location, and a location where an arrythmia originates; selecting segments in which any of the abnormalities are located; aligning the plurality of images; and selecting (120) the cardiac arrhythmia target based on the segments in the aligned plurality of images in which there is an overlap of the identified abnormalities.