Challenge

The greatest challenge for radiation therapy (RT) is to reach the highest probability of cure with the least morbidity. Over the last decades, remarkable progresses have been made thanks to modern advances in computer and imaging technologies. Modern radiotherapy has evolved from non-site-specific techniques using bony anatomy and hand-drawn blocking toward a highly conformal dose distribution tailored to nearly every kind of target volume, with 3D conformal radiation therapy and intensity-modulated radiation therapy (IMRT). Therefore in theory, the cancer cells can be much better targeted with sufficient radiation doses, while simultaneously sparing surrounding healthy tissues. However in practice, some difficulties remain to identify correctly and completely all the cancer cells. A second strategy to improve treatments is through evidence based medicine: learning by doing. Evaluations of different treatment strategies with large numbers of patients lead to new protocols with statistically better performances, e.g. higher doses in certain areas. To support both strategies, new technologies will be developed in the proposed project. The focus will be on the diagnostic and treatment planning phases, in combination with post-treatment evaluations, for patient and for evidence based medicine. That should result in better patient outcome.

Yet despite all this technological and clinical innovation, experience shows that in many cases it is still not possible to provide information about functional heterogeneity of the tumour and to sufficiently control local tumour growth. To address this shortcoming, radiation oncologists and medical physicists want to characterize the tumour in terms of morphology, movement and molecular profile, and also before, during and after a treatment.

Morphology: conventional imaging techniques (computed tomography (CT), magnetic resonance imaging (MRI) or ultrasound (US)) currently enable radiation oncologists to delineate a gross tumour volume (GTV), which is the visible part of the tumour on these images. Microscopic tumour extensions and migrant cells subpopulations are not observable currently, since their sizes are below resolution limit of modern 3D imaging. That means assumptions (based on clinical and pathological experience) need to be made about the clinical target volume (CTV), which is the anatomical information required by clinicians to plan an external radiotherapy treatment. Some new technologies, such as advanced positron emission tomography (PET)/CT and single photon emission computed tomography (SPECT), have the potential to depict tumour extensions, which do not cause anatomical changes, like microscopic metastases in normal sized lymph nodes. This leads to a more accurate definition of the CTV. The expectation is that these technologies can in a not-too-distant future provide clinically usable high-resolution solutions. “SUMMER” project will significantly ease the use of these imaging methods for RT applications.

Movement: most tumours are subject to spatial changes during RT treatment. Displacements and deformations of the target may occur between treatment delivery fractions (inter-fractional changes) or during beam delivery (intra-fractional changes). To date, clinicians have taken into account this question by extending the CTV with appropriate safety margins resulting in the planning target volume (PTV). Again, these margins are based on clinical experience and often include some healthy tissue within the high dose volume. 4D-PET/CT images will be used in “SUMMER” to assess intra-fractional motion. That would already improve quality of patient outcome, since the PTV definition will be improved – e.g. with respiratory movements in tumours of the chest and upper abdomen like lung cancer. Inter-fractional motion (due to filling of bladder or bowel in prostate cancer cases) will also be addressed by non-rigid registration solutions for CT/MRI.

Molecular profile: recently, biologic variables based on differences between tumour metabolism, tumour antigens, and normal tissues have been incorporated into the treatment process. These properties may be characterized more appropriately by functional and molecular imaging using new tracers in PET and SPECT imaging and by specialized MRI scans (magnetic resonance spectroscopy (MRS), diffusion weighted MRI (DMRI), functional MRI (fMRI), etc.). However, the challenge is how to include this information in radiotherapy planning and beam delivery. That means introducing a biological target volume that discriminates tumoural sub-volumes of different radio-sensitivity. In parallel, it also means being able to identify the setting needed for delivering the corresponding inhomogeneous dose distributions.