Biomechanical Model for Respiratory Motion Prediction
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Solution Overview
Problem
Respiratory motion in 3D thoracic images is complex and challenging to accurately predict due to the sliding and deformation of lungs and surrounding organs during respiration, leading to imaging artifacts and increased radiation doses or treatment times in medical imaging and therapy delivery.
Innovation Solution
A patient-specific, generative biomechanical model of the respiratory system is created using 3D thoracic images, driven by a personalized thoracic pressure force field estimated from images at different respiratory phases, allowing for continuous prediction of lung position and motion across various breathing patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If respiratory motion is tracked using surrogate signals (spirometers, abdominal pressure belts, external markers), then respiratory motion can be monitored, but the signals only partially reflect the complex nature of lung deformation and cause imaging artifacts when breathing patterns change
Solution Approach 1:
The patent creates a virtual copy of the respiratory system by generating a 3D anatomical model from medical images. This digital twin replicates the patient's specific anatomy and can be deformed computationally to predict lung motion, replacing the need for external surrogate signals that only partially reflect actual lung deformation.
Solution Approach 2:
The patent replaces mechanical measurement systems (spirometers, pressure belts, external markers) with a computational biomechanical model. Instead of using physical sensors that attach to the patient's body, the system uses image-based computational mechanics to predict tissue deformation, eliminating the partial reflection problem of surrogate signals.
2Productivity
If 4D CT data is compounded using respiratory surrogate signals, then image reconstruction can be performed, but non-periodic breathing patterns cause imaging artifacts
Solution Approach 1:
The patent changes the fundamental parameter used for image reconstruction from respiratory surrogate signals to a biomechanical deformation model driven by pressure fields. This allows the system to handle non-periodic breathing patterns naturally, as the model computes deformation based on physical principles rather than assuming periodicity in the driving signal.
Solution Approach 2:
The patent replaces the signal-processing-based compounding approach with a physics-based computational mechanics approach. Instead of sorting and combining image segments based on surrogate signal amplitude or phase, the system uses a biomechanical model to continuously predict tissue position and deformation throughout the respiratory cycle.
3Reliability
If gating is used to acquire images at specific respiratory instances, then motion artifacts are reduced, but treatment or imaging time increases
Solution Approach 1:
The patent enables continuous prediction of respiratory motion throughout the entire respiratory cycle using the biomechanical model. Instead of acquiring images only at specific gated instances, the system can continuously track and compensate for motion at any point in time, allowing imaging and treatment to proceed without interruption while maintaining image quality.
Solution Approach 2:
The patent performs preliminary computation of the biomechanical model to predict future respiratory positions. By pre-computing the deformation fields and motion trajectories, the system can prepare for upcoming motion patterns, allowing real-time image reconstruction and therapy delivery without waiting for specific respiratory phases.
4Reliability
If oversampling is performed to achieve accurate respiratory phase coverage, then image quality improves, but radiation dose increases
Solution Approach 1:
The patent creates a computational model that replicates respiratory motion patterns, allowing the system to predict tissue positions without acquiring additional oversampled images. The virtual respiratory phantom generated from the biomechanical model provides the necessary phase information without exposing the patient to additional radiation.
Solution Approach 2:
The patent replaces physical oversampling (acquiring more image data) with computational modeling. Instead of collecting additional CT images at different respiratory phases to ensure complete coverage, the system uses the biomechanical model to interpolate and predict tissue positions, eliminating the need for radiation-intensive oversampling.
5Stability of the object's composition
If interpolation is used to approximate respiratory motion between phases, then continuous motion representation is achieved, but step artifacts are introduced
Solution Approach 1:
The patent replaces mathematical interpolation with physics-based computational mechanics. Instead of using algorithms that estimate intermediate positions based on discrete measurements, the system uses a biomechanical model that continuously computes tissue deformation based on pressure fields and material properties, providing smooth and physically accurate motion representation without artifacts.
Solution Approach 2:
The patent changes the approach from discrete phase sampling with interpolation to continuous computational prediction. The biomechanical model solves the deformation equations continuously in time, providing smooth transitions between respiratory phases without the discontinuities introduced by interpolation methods.
Data Source
AI summary
A method and system for prediction of respiratory motion from 3D thoracic images is disclosed. A patient-specific anatomical model of the respiratory system is generated from 3D thoracic images of a patient. The patient-specific anatomical model of the respiratory system is deformed using a biomechanical model. The biomechanical model is personalized for the patient by estimating a patient-specific thoracic pressure force field to drive the biomechanical model. Respiratory motion of the patient is predicted using the personalized biomechanical model driven by the patient-specific thoracic pressure force field.