International journal of computer assisted radiology and surgery · 2025
Left Ventricular Motion Analysis Framework for the MATRIX-VT Study.
СтатьяНазвание и аннотация: Перевод в очереди
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Janorschke Christian, Popescu Sorin S, Osburg Jonas, Lu Xinyu, Xie Jingyang, Yaman Engin, Marquetand Christoph, Blanck Oliver, Alessandrini Hannes, Schweikard Achim, Tilz Roland R
Аннотация
PURPOSE: Ultrasound (US) is commonly used to assess left ventricular motion for examination of heart function. In stereotactic arrhythmia radioablation (STAR) therapy, managing cardiorespiratory motion during radiation delivery requires representation of motion information in computed tomography (CT) coordinates. Similar to conventional US-guided navigation during surgical procedures, 3D US can provide real-time motion data of the radiation target that could be transferred to CT coordinates and then be accounted for by the radiation system. A motion analysis framework is presented that covers all necessary components to capture and analyse US motion data and transfer it to CT coordinates.
METHODS: Utilizing a robotic test set-up with a human phantom, a baseline and ground truth dataset is recorded for the development and implementation of the motion analysis framework. An optical tracking system and an additional spatial calibration phantom are used to determine necessary transformations. Methods for frame matching, calibration, registration and evaluation are implemented.
RESULTS: The hardware set-up meets all requirements, including a frame rate exceeding 20 Hz and acceptable image quality, while involving only a few components that can easily be mounted and dismantled in a clinical context.The recorded phantom dataset meets all hardware-specific requirements including a frame rate exceeding 20 Hz, an offset between CT trigger time and the closest US recording of 2-20 ms as well as acceptable US image quality. The static phantom allows for quantitative evaluation by matching structures from different US frames in CT coordinates. While each individual step of the US and CT fusion process achieves the target accuracy of less than 5 mm error, the cumulative error over all transformations exceeded this limit for extreme probe positions.
CONCLUSION: The framework is developed and tested for the MATRIX-VT study and can be utilized for patient data evaluation as well as for transferring information such as positional data of moving anatomical structures between US and CTpredictive motion management in STAR therapy. Its modular design allows for the incorporation of advanced calibration and registration methods to address probe positioning limitations, thereby enhancing overall system performance for future applications.
METHODS: Utilizing a robotic test set-up with a human phantom, a baseline and ground truth dataset is recorded for the development and implementation of the motion analysis framework. An optical tracking system and an additional spatial calibration phantom are used to determine necessary transformations. Methods for frame matching, calibration, registration and evaluation are implemented.
RESULTS: The hardware set-up meets all requirements, including a frame rate exceeding 20 Hz and acceptable image quality, while involving only a few components that can easily be mounted and dismantled in a clinical context.The recorded phantom dataset meets all hardware-specific requirements including a frame rate exceeding 20 Hz, an offset between CT trigger time and the closest US recording of 2-20 ms as well as acceptable US image quality. The static phantom allows for quantitative evaluation by matching structures from different US frames in CT coordinates. While each individual step of the US and CT fusion process achieves the target accuracy of less than 5 mm error, the cumulative error over all transformations exceeded this limit for extreme probe positions.
CONCLUSION: The framework is developed and tested for the MATRIX-VT study and can be utilized for patient data evaluation as well as for transferring information such as positional data of moving anatomical structures between US and CTpredictive motion management in STAR therapy. Its modular design allows for the incorporation of advanced calibration and registration methods to address probe positioning limitations, thereby enhancing overall system performance for future applications.