3D Cone Beam CT Clot Characterization
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Solution Overview
Problem
Current medical imaging technologies face challenges in accurately and quickly determining the position and composition of clots in patients, particularly in stroke cases, which is critical for timely and effective treatment.
Innovation Solution
A system and method that utilize a combination of contrasted and non-contrasted imagery to determine the location and composition of clots, employing machine learning models and image processing techniques to analyze the imagery and provide accurate clot characterization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional non-contrasted imagery is used for clot characterization, then radiation exposure and contrast agent usage are reduced, but measurement precision and reliability of clot composition determination deteriorate
Solution Approach 1:
The imaging process is segmented into two distinct phases: a non-contrasted imaging phase for initial clot location identification, and a contrasted imaging phase for detailed composition analysis. This segmentation allows the system to minimize overall contrast agent usage while ensuring accurate characterization when needed.
Solution Approach 2:
The system performs preliminary non-contrasted imaging to identify potential clot locations before administering contrast agents. This preliminary action allows the system to target contrast injection more precisely, reducing the overall amount of contrast agent and radiation exposure required for accurate diagnosis.
2Loss of time
If rapid clot characterization is achieved using streamlined imaging protocols, then treatment time is reduced, but measurement precision of clot composition may deteriorate
Solution Approach 1:
The system extracts and processes only the most diagnostically relevant features from the contrasted imagery, such as specific attenuation values and texture characteristics, rather than analyzing the entire image dataset. This extraction approach maintains high measurement precision while significantly reducing processing time.
Solution Approach 2:
The system implements automated real-time analysis of contrast uptake patterns, skipping manual review steps and rushing through the critical measurement phases. This allows rapid characterization by automatically identifying key compositional features without sacrificing accuracy.
3Measurement precision
If detailed clot composition analysis is performed using multiple imaging sequences, then measurement precision improves, but device complexity and loss of time increase
Solution Approach 1:
The imaging system is designed with multi-functionality to perform both non-contrasted and contrasted imaging sequences using the same hardware infrastructure. The unified system can adaptively select and execute different imaging protocols based on clinical needs, reducing overall device complexity while maintaining detailed analysis capabilities.
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
The system enables quick and robust clot characterization with high accuracy, facilitating better clinical decision-making during thrombectomy procedures and potentially improving patient outcomes by ensuring correct device selection and therapy implementation.
Implementation Method 1
They allow obtaining 3D (three-dimensional) imagery of the brain which can be analyzed for stroke
Implementation Method 2
3D cone beam computed tomography
Data Source
AI summary
All X-ray computerized tomography systems that are available or proposed base their reconstructions on measurements that integrate over energy. X-ray tubes produce a broad spectrum of photon energies and a great deal of information can be derived by measuring changes in the transmitted spectrum. We show that for any material, complete energy spectral information may be summarized by a few constants which are independent of energy. A technique is presented which uses simple, low-resolution, energy spectrum measurements and conventional computerized tomography techniques to calculate these constants at every point within a cross-section of an object. For comparable accuracy, patient dose is shown to be approximately the same as that produced by conventional systems. Possible uses of energy spectral information for diagnosis are presented.