ObjectiveThe purpose of this study was to give an overview of the measures used to prevent chronic radiation proctitis (CRP) and to provide an algorithm for the treatment of CRP.MethodsMedical literature databases including PubMed and Medline were screened and critically analyzed for relevance in the scope of our purpose.ResultsCRP is a relatively frequent late side effect (5–20%) and mainly dependent on the dose and volume of irradiated rectum. Radiation treatment (RT) techniques to prevent CRP are constantly improving thanks to image-guided RT and intensity-modulated RT. Also, newer techniques like protons and new devices such as rectum spacers and balloons have been developed to spare rectal structures. Biopsies do not contribute to diagnosing CRP and should be avoided because of the risk of severe rectal wall damage, such as necrosis and fistulas. There is no consensus on the optimal treatment of CRP. A variety of possibilities is available and includes topical and oral agents, hyperbaric oxygen therapy, and endoscopic interventions.ConclusionsCRP has a natural history of improving over time, even without treatment. This is important to take into account when considering these treatments: first be conservative (topical and oral agents) and be aware that invasive treatments can be very toxic.

A paradigm shift from current population based medicine to personalized and participative medicine is underway. This transition is being supported by the development of clinical decision support systems based on prediction models of treatment outcome. In radiation oncology, these models 'learn' using advanced and innovative information technologies (ideally in a distributed fashion - please watch the animation: http://youtu.be/ZDJFOxpwqEA) from all available/appropriate medical data (clinical, treatment, imaging, biological/genetic, etc.) to achieve the highest possible accuracy with respect to prediction of tumor response and normal tissue toxicity. In this position paper, we deliver an overview of the factors that are associated with outcome in radiation oncology and discuss the methodology behind the development of accurate prediction models, which is a multi-faceted process. Subsequent to initial development/validation and clinical introduction, decision support systems should be constantly re-evaluated (through quality assurance procedures) in different patient datasets in order to refine and re-optimize the models, ensuring the continuous utility of the models. In the reasonably near future, decision support systems will be fully integrated within the clinic, with data and knowledge being shared in a standardized, dynamic, and potentially global manner enabling truly personalized and participative medicine.

4DCT-scans can be used as alternative to eliminate unstable radiomics features as first step in a feature selection procedure. Feature robustness is tumour-site specific and independent of prognostic value.