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respiTrack: Patient-specific real-time respiratory tumor motion prediction using magnetic tracking

PURPOSE: An intraoperative real-time respiratory tumor motion prediction system with magnetic tracking technology is presented. Based on respiratory movements in different body regions, it provides patient and single/multiple tumor-specific prediction that facilitates the guiding of treatments. METH...

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Detalles Bibliográficos
Autores principales: Özbek, Yusuf, Bárdosi, Zoltán, Freysinger, Wolfgang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303076/
https://www.ncbi.nlm.nih.gov/pubmed/32347464
http://dx.doi.org/10.1007/s11548-020-02174-3
Descripción
Sumario:PURPOSE: An intraoperative real-time respiratory tumor motion prediction system with magnetic tracking technology is presented. Based on respiratory movements in different body regions, it provides patient and single/multiple tumor-specific prediction that facilitates the guiding of treatments. METHODS: A custom-built phantom patient model replicates the respiratory cycles similar to a human body, while the custom-built sensor holder concept is applied on the patient’s surface to find optimum sensor number and their best possible placement locations to use in real-time surgical navigation and motion prediction of internal tumors. Automatic marker localization applied to patient’s 4D-CT data, feature selection and Gaussian process regression algorithms enable off-line prediction in the preoperative phase to increase the accuracy of real-time prediction. RESULTS: Two evaluation methods with three different registration patterns (at fully/half inhaled and fully exhaled positions) were used quantitatively at all internal target positions in phantom: The statical method evaluates the accuracy by stopping simulated breathing and dynamic with continued breathing patterns. The overall root mean square error (RMS) for both methods was between [Formula: see text] and [Formula: see text] . The overall registration RMS error was [Formula: see text] . The best prediction errors were observed by registrations at half inhaled positions with minimum [Formula: see text] , maximum [Formula: see text] . The resulting accuracy satisfies most radiotherapy treatments or surgeries, e.g., for lung, liver, prostate and spine. CONCLUSION: The built system is proposed to predict respiratory motions of internal structures in the body while the patient is breathing freely during treatment. The custom-built sensor holders are compatible with magnetic tracking. Our presented approach reduces known technological and human limitations of commonly used methods for physicians and patients.