AI-Guided EUS Tissue Acquisition Planning for Deep Anatomy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional endoscopes face challenges in navigating to deep anatomical locations within patients, maintaining stabilization, and performing accurate tissue acquisition due to limited maneuverability and variability in patient anatomy, particularly in surgically altered regions, requiring advanced surgical skills and manual planning that can be time-consuming and dependent on operator experience.
Innovation Solution
An endoscopic system utilizing artificial intelligence and machine learning to generate individualized tissue acquisition plans, guiding steerable instruments with recommended tools, operational parameters, and navigation paths, enhancing automation and reducing reliance on manual skills.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional endoscopes are used for navigation to deep anatomical locations, then the procedure can be performed with existing technology, but the maneuverability and navigation capability deteriorate due to limited degree of freedom and difficulty in altered anatomy
Solution Approach 1:
The steerable instrument is divided into multiple segments or sections that can independently articulate and bend. This segmentation allows the instrument to navigate complex anatomical pathways by adjusting the orientation of each segment, thereby improving maneuverability without requiring a complete redesign of the entire system.
Solution Approach 2:
The instrument incorporates dynamic steering mechanisms that allow real-time adjustment of the distal tip direction during insertion. This dynamic capability enables the operator to adapt the instrument's path to match the patient's specific anatomy, enhancing navigation ease while maintaining a manageable system complexity through controlled flexibility.
2Productivity
If manual planning and advanced surgical skills are used for tissue acquisition, then the procedure can be performed with conventional methods, but the time consumption and operator experience dependency increase
Solution Approach 1:
The system performs preliminary automated planning of the tissue acquisition path and parameters before the actual procedure. By pre-calculating the optimal navigation route and acquisition settings based on imaging data, the system eliminates time-consuming manual planning during the procedure, thereby improving overall efficiency without requiring excessive operator experience.
Solution Approach 2:
The system incorporates real-time feedback mechanisms that monitor instrument position and tissue characteristics during the procedure. This feedback allows for automated adjustments to the acquisition parameters, reducing the need for time-consuming manual recalibration and enabling less experienced operators to achieve consistent results, thus improving productivity while reducing time loss.
3Measurement precision
If conventional endoscopes are used for tissue acquisition, then the system remains simple, but the accuracy and precision of tissue sampling deteriorate due to limited stabilization and maneuverability
Solution Approach 1:
The automated planning system acts as an intermediary between the operator and the tissue acquisition process. It processes imaging data and instrument position information to generate precise acquisition parameters, thereby improving sampling accuracy without requiring the physical endoscope system to become overly complex. The intermediary software layer handles the computational complexity while the hardware remains relatively simple.
Solution Approach 2:
The system replaces manual mechanical adjustment and stabilization with automated computational methods. By using software-based planning and real-time image guidance, the system achieves higher tissue sampling precision without relying on complex mechanical stabilization mechanisms, thus improving accuracy while keeping device complexity manageable through substitution of mechanical complexity with computational intelligence.
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
Improves the efficiency, accuracy, and safety of tissue acquisition procedures by providing automated planning and navigation, reducing variability among operators and improving procedural outcomes.
Implementation Method 1
An echoendoscope includes at its tip an ultrasound transducer that emits ultrasound waves and converts the ultrasound echoes into detailed images of the target organ or tissue
Implementation Method 2
laser has been used in applications of tissue ablation, coagulation, vaporization, fragmentation, and lithotripsy to break down calculi
Data Source
AI summary
Systems, devices, and methods for planning endoscopic ultrasound (EUS)-guided tissue acquisition (EUS-TA) from an anatomical target are disclosed. An endoscopy system comprises a steerable elongate instrument including an EUS probe to produce ultrasound scans of the anatomical target, and a tissue acquisition device to sample tissue. A processor receives image of the anatomical target including one or more EUS images converted from the ultrasound scans, apply the images to a trained machine-learning model to generate an EUS-TA plan. The EUS-TA plan may include a recommended tissue acquisition device, and recommended values of operational parameters for manipulating the tissue acquisition device, navigating the steerable elongate instrument, or positioning the EUS probe. The EUS-TA plan can be presented to a user, or used to facilitate a robot-assisted tissue acquisition procedure.