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Publication Number
US-12605213-B2
Publication Date
2026-04-21
Expiration Date
Abstract
Systems, devices, and methods for providing a computer-assisted endoscopic procedure guidance are disclosed. A procedure planning system can generate an endoscope navigation plan for a patient scheduled for an endoscopic procedure performed by an operating physician. The system comprises a processor that can access an endoscopic procedure database, identify therefrom physicians substantially matching the experience level of the operating physician, and retrieve reference procedure data of the past procedures performed by the matching physicians. The reference procedure data can be further selected from past procedures performed on patients with similar medical information to the scheduled patient. The processor can generate an endoscope navigation plan for the scheduled patient using reference procedure data. The endoscope navigation plan can be displayed along with the live endoscopic image to guide the operating physician in performing the procedure.
Core Innovation
The invention relates to computer-assisted endoscopic procedure guidance that plans an endoscopic procedure for a scheduled patient by generating an endoscope navigation plan. The system determines or receives an experience level of the operating physician and uses this to access an endoscopic procedure database and retrieve reference procedure data associated with matching physicians. The reference procedure data correspond to past endoscopic procedures of the same type performed by a plurality of physicians on a plurality of patients, and the plan is generated by applying the reference procedure data to a trained-learning model.
During the endoscopic procedure, the system acquires real-time procedure data including an endoscopic image taken during the procedure performed on the scheduled patient. The acquired endoscopic image is correlated with a reference endoscopic image from the reference procedure data by identifying one or more anatomical landmarks to spatially align the acquired endoscopic image with the reference endoscopic image. One or more real-time navigation parameters are then generated by applying the acquired endoscopic image and the correlation to the trained-learning model.
The system analyzes one or more differences between the real-time navigation parameters and reference endoscopic navigation parameters from the endoscope navigation plan. When the real-time navigation parameters deviate from the reference endoscopic navigation parameters by a specified amount, a navigation controller provides real-time feedback and automatically adjusts the real-time navigation parameters using actuators and iterative real-time adjustment of one or more physical positioning mechanisms of one or more components of an endoscope. The system displays a navigation parameter status chart showing different visual indicators to visually represent levels of agreement between the real-time navigation parameters and the reference navigation parameters.
Claims Coverage
The provided content includes two independent claims, covering both a system for pre-operative planning and live guidance and a corresponding method for planning an endoscopic procedure with an image-guided endoscopic system. Across the independent claims, five core inventive feature areas appear: physician experience-based reference retrieval, trained-learning generation of an endoscope navigation plan, anatomical-landmark-based correlation of real-time and reference endoscopic images, learned generation and comparison of real-time navigation parameters against plan parameters, and feedback-controlled automatic adjustment with agreement visualization via a navigation parameter status chart.
Experience level-driven retrieval of reference procedure data
Determine or receive an experience level of the operating physician and access an endoscopic procedure database to retrieve reference procedure data associated with one or more matching physicians having respective experience levels substantially matching the experience level of the operating physician, wherein the endoscopic procedure database comprises procedure data of one or more past endoscopic procedures of the type performed by a plurality of physicians on a plurality of patients.
Trained-learning endoscope navigation plan generation
Generate an endoscope navigation plan for the scheduled patient by applying the reference procedure data to a trained-learning model.
Anatomical-landmark image correlation between acquired and reference images
Correlate the acquired endoscopic image with a reference endoscopic image from the reference procedure data by identifying one or more anatomical landmarks to spatially align the acquired endoscopic image with the reference endoscopic image.
Learned real-time navigation parameters from correlated endoscopic images
Generate one or more real-time navigation parameters by applying the acquired endoscopic image and the correlation to the trained-learning model and analyze one or more differences between the one or more real-time navigation parameters and at least one of the one or more reference endoscopic navigation parameters from the endoscopic navigation plan.
Feedback-control automatic iterative adjustment with status-chart agreement visualization
Automatically adjust, via a navigation controller including feedback control circuitry configured to provide real-time feedback, the one or more real-time navigation parameters when the one or more real-time navigation parameters deviate from the one or more reference endoscopic navigation parameters by a specified amount, wherein the navigation controller further comprises one or more actuators configured to provide iterative real-time adjustment, based on data from the feedback control circuitry, of one or more physical positioning mechanisms of one or more components of an endoscope until the one or more real-time navigation parameters are within the specified amount, and display, via an output unit, a navigation parameter status chart showing different visual indicators to visually represent levels of agreement between the one or more real-time navigation parameters and the one or more reference endoscopic navigation parameters.
Across the independent claims, the claim coverage centers on using the operating physician’s experience level to retrieve reference procedure data, generating a patient-specific endoscope navigation plan via a trained-learning model, correlating real-time endoscopic images to reference images using anatomical landmarks, deriving real-time navigation parameters and comparing them to plan parameters, and performing feedback-controlled iterative adjustment of endoscope physical positioning when deviation exceeds a specified amount, with a navigation parameter status chart that visualizes agreement.
Stated Advantages
Not explicitly described in patent.
Documented Applications
Not explicitly described in patent.
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