157 A Scientific impact Scientific impact Main aims and outcomes MRI plays a crucial role in the local staging of rectal cancer and is the main tool used to stratify patients into different risk groups used to guide treatment planning. MRI nowadays also has an important role (next to endoscopy) to evaluate the local tumour response in patients undergoing neoadjuvant (chemo)radiotherapy (CRT) and to help identify which patients may be candidates for organ-preserving treatment alternatives. To support radiologists, several image guidelines, reporting guides and staging templates are available, as well as more recently developed grading systems to aid in assessing the local tumour response after CRT. An important goal of these tools is to enhance uniformity in radiological reporting and thereby promote consistent and evidence-based patient management. However, there are several potential pitfalls. Limited data is available on the reproducibility of different grading systems and on whether they are accurate in the hands of radiologists in everyday clinical practice. An important reason for this is that it is logistically challenging and costly to set up studies to test and validate diagnostic methods on a large scale, i.e. with multiple radiologists and using data from different clinical centres. An user-friendly platform to enable large scale diagnostic validation studies where images from different clinical centres can easily be shared and evaluated by multiple readers has so far been lacking. With this thesis, we successfully developed a practical web-based tool (iScore) to enable large scale testing and validation of visual diagnostic classification and staging methods while at the same offering online feedback, training and teaching to a large platform of radiologists. Seventy-four radiologists from over fifteen different countries participated in the projects described in this thesis. The pearls and pitfalls in staging and response evaluation that were identified can help to further optimize radiological staging guides, promote effective further clinical implementation, and ultimately improve diagnostic staging and reporting quality. In Chapter 2 we found that several staging items included in structured reporting templates lacked sufficient reproducibility. Main risk variables such as T- and N- stage showed considerably better reproducibility in a dichotomized risk stratification. In Chapter 4 we have shown that such a dichotomized staging can have a significant impact on the stratification of patients into low versus high-risk subgroups thereby affecting treatment planning. In Chapter 2 we also found a significant positive correlation between diagnostic confidence and diagnostic staging accuracy, suggesting that a confidence level should perhaps be included in reporting templates, especially for variables with low reproducibility.
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