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High-precision radiotherapy–Do we need better pre-treatment CT imaging?

Greilich, S.; Richter, C.


Computed tomography (CT) images from fan-beam medical grade scanners are the current gold standard for treatment planning in radiation oncology: they provide geometrically correct, reliable, and quantitative measures of photon attenuation in the patient. However, this information is not fully identical with the physical quantities needed for dose calculation and optimization and additional uncertainty is introduced by inferring them from the kV images. Also, the low soft tissue contrast in CT impacts delineation accuracy. While additional Imaging modalities are advocated as complementary – sometimes alternative – techniques to CT imaging, uncertainties in image registration can even deteriorate the quality of treatment planning. Dual-energy CT – i.e. using scans from two X-ray spectra or detection in two separate energy ranges – retains the virtues of computed tomography while it opens at the same time the possibility to overcome the restrictions mentioned. It can improve the accuracy of dose calculation and delineation and enables to abandon the use of a general translation rule (“Hounsfield look-up table”) for the photon attenuation (CT numbers) - replacing it by a patient-specific determination of radiological tissue quantities. DECT-derived quantities might additionally provide opportunities in advanced image analysis methods such as radiomics, i.e. the machine-learning-based approach for the prediction of patient outcome and treatment personalization. CT-based radiomics analyses might even be able to uncover information that can so far only be derived from additional multi-modal imaging. Currently, many applications based on innovations in pre-treatment CT imaging and image analysis are investigated that could have the potential to change clinical practice in future. This presentation is intended to set the stage for the focus session which tries to look into the question, which of These applications can find its way into routine clinical application.

  • Open Access Logo Abstract in refereed journal
    Biomedical Engineering / Biomedizinische Technik 62(2017), S292-S297
    DOI: 10.1515/bmt-2017-5057