ESTRO 2021 Abstract Book


ESTRO 2021

consider the intensive implications of such imaging approach on the patient, especially when considering the fundamental radiation protection requirements for justification and optimization. Imaging techniques using non-ionizing radiation (US, MRI) will not be discussed. Ionizing radiations are used for dosimetric planning (CT, PET/CT) purpose, patient position verification (CBCT), replanning (CBCT), and portal verification (MV imaging -EPID dosimetry). In all these cases justifiable dose to critical organs and tissues must be taken into account. The effective dose and organ dose values for CT and CBCT examinations will be discussed, considering that for the same patient, CT have a reduced repetition (are repeated in reduced number) while CBCT imaging has a higher frequency related to the growth of image guided radiotherapy. The frequency and the patient dose depends on the protocols used by the different Departments in relation to clinical application (patient positioning, replanning). Most of these imaging devices deliver an additional dose to the patient. These non-negligible doses have to be evaluated and reported. Then, the principles based on the “as low as reasonably achievable (ALARA) concept” must be considered and adapted to the planning and to the image-guided radiotherapy. The organ and effective doses provide information for justification and optimization of CT, PET/CT and CBCT procedures and these values will be compared with doses delivered by other imaging devices and in relation to dose escalation to critical organs considered for some treatments. Organ doses for different technique and analytic models related to CT, CT/PET and CBCT images have been measured. Quality controls are mandatory and exposure index of the different imaging modality must be stored into DICOM archive. On these issues the world of imaging in radiotherapy is not always able to provide exposure parameters in line with the state of the art of the standard (DICOM, IHE); a significant example is the case of CBCT. On the other hand, exposure reduction in CBCT may trigger excellent results providing new image reconstruction algorithms are developed aiming to improve image quality and therefore reduce patient exposure. A specific status of imaging is important in proton therapy and hadrontherapy where online monitoring imaging by PET is developed for clinical application. Finally, it should be remembered that the forthcoming use of MRI for treatment planning and online verification using hybrid technologies will bring the world of radiotherapy to new scenarios of optimization and justification. Abstract Text While GTV delineation can be thought of as an image segmentation problem, in which an abnormal appearing tumor mass is delineated on radiological images, the CTV is invisible. The CTV accounts for microscopic extensions of the tumor beyond the GTV that are not visible with current in-vivo imaging techniques. Thus, CTV delineation requires knowledge of the patterns of microscopic tumor progression. Mathematical models of tumor progression may quantitatively describe tumor spread and thereby support CTV definition. The talk will illustrate this for one example for each of the two types of CTV used in radiotherapy: the primary tumor CTV- T and the nodal CTV-N. CTV-T definition amounts to a margin expansion around the primary GTV-T. However, this margin expansion is often not isotropic but is influenced by anatomical barriers of tumor infiltration as well as preferred directions of tumor cell migration. A prominent example is glioma. Ventricles, dura, and falx represent anatomical barriers. In addition, tumor cells primarily spread within white matter and infiltrate grey matter to a lesser degree. The first part of the talk will present an update on the work on glioma growth models, which can be used for smart anisotropic GTV-to-CTV expansion that is consistent with neuroanatomy. The second and main part of the talk will consider nodal CTV-N definition for the example of head & neck squamous cell carcinoma (HNSCC). CTV-N definition does not amount to a margin expansion around the nodal GTV-N, the macroscopic lymph node metastases visible on imaging, and is therefore conceptually different from CTV-T definition. Instead, it consists of lymph node levels (LNLs), i.e. anatomically defined regions of the lymph drainage system that are at risk of harboring occult metastases despite negative imaging findings. We present our recent work on the development of a statistical model of lymphatic tumor progression. The model estimates the probability of microscopic involvement of LNLs given the individual patient's state of disease progression, i.e. T-stage and the location of primary tumor and macroscopic lymph node metastases. The work is based on the methodology of Hidden Markov Models. The graph of the network represents the anatomically defined lymph drainage patterns; the parameters of the network, which quantitatively describe the probabilities of tumor spread to and between lymph node levels, are learned from a dataset of lymphatic progression patterns in previously treated patients. In the existing literature, detailed reports on the metastatic involvement of individual LNLs and tumor characteristics are scarce. Therefore, we built a dataset of 287 oropharyngeal HNSCC patients treated at our institution for whom LNL involvement as well as primary tumor location, T-stage, and other risk factors were recorded. To explore and visualize the data, a graphical user interface was developed. In the future, the statistical model of lymphatic progression together with larger multi-institutional datasets may allow for further personalization of CTV definition. Symposium: Novel planning approaches for uncertanties in GTV delineation and microscopic disease around GTVs SP-0253 Modelling and quantifying microscopic tumour progression J. Unkelbach 1 , R. Ludwig 1 , B. Pouymayou 1 , J. Hoffmann 1 , P. Balermpas 1 1 University Hospital Zurich, Radiation Oncology, Zurich, Switzerland

SP-0254 Probabilistic planning for microscopic disease

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