Treating mobile tumors such as lung or liver tumors with radiation ther- apy is challenging because the motion induced by respiration has to be considered. Until recently, there was no online and non-invasive imag- ing solution to follow the tumor motion during a treatment delivery. To ensure the target coverage, security margins are used to extend the irradiated area to encompass the motion, meaning healthy tissues are also hit which can induce undesired secondary effects. In the last few years, a new hybrid device combining Magnetic Resonance Imaging with a radiotherapy treatment unit has been developed. It allows to acquire images and deliver radiotherapy treatment simultaneously. Magnetic Resonance Imaging is the ideal imaging modality for this application because it gives a good soft tissue contrast, the orientation of the images can be chosen, and the image acquisition does not irradiate the patient. In such devices, 2D fast Magnetic Resonance images are well-suited to capture the real-time motion of the tumor. To be used effectively in an adaptive radiotherapy, these MR images have to be combined with 3D X-ray images such as CT, which are necessary to compute the radia- tion dose deposition. In this thesis, we developed a method combining both image modalities to track the motion on MR images and reproduce the tracked motion on a sequence of 3DCT images in real-time using a motion model. It can be used to drive a treatment delivery in real- time, follow breathing motion and detect irregularities in the breathing pattern. ; (FSA - Sciences de l'ingénieur) -- UCL, 2021


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    Title :

    Towards real-time image-guided radiotherapy : 3D patient-specific breathing motion models driven by 2D cine-MRI



    Publication date :

    2021-01-01


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




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