144 Chapter 8 treatment, future staging templates should perhaps incorporate the level of confidence to better inform risk-based clinical decision making during MDT discussions, at least for those items that are strongly influenced by variations in diagnostic confidence. Impact of virtual training and teaching Various previous works, but also our current results described in Chapter 5 and 6 have demonstrated that the experience level of the radiologist is a crucial factor that significantly impacts diagnostic staging performance [10–13]. Dedicated training and education are therefore of vital importance to optimize diagnostic performance. Though it has been shown that face-to face training with hands-on feedback is most effective to increase radiologist’s interpretative performance [10], organizing such training programs is a costly, time- and labour intensive endeavour. Recent lockdown restrictions have furthermore hampered the organization of face-to-face educational events, but at the same time have boosted the development of online training modules. In Chapter 3 we used our newly developed iScore platform to set up a virtual hands-on training program combining individual case-based training with webinars and online expert-teaching and feedback sessions. Exploratory analyses of the outcomes of our virtual training program suggest an overall increase in diagnostic staging performance with corresponding improved interreader reproducibility and staging confidence. Especially in staging items that showed relatively poor results in our analyses in Chapter 2, like EMVI, we observed a considerable increase in staging performance of 17% when comparing results before and after completion of our virtual training program. Though in-person teaching remains crucial, additional use of web-based tools can make knowledge more easily accessible especially in more specialized fields. Our results are encouraging and suggest that dedicated virtual training programs can offer a valuable addition (or even alternative) to face-to-face training. Assessing and predicting rectal tumour response Moving from baseline staging and reporting, in Chapters 5-7 we focused on treatment response evaluation by evaluating different methods to assess and predict response of rectal tumours to CRT. Locally advanced rectal cancers (LARC) are typically treated with neoadjuvant chemoradiotherapy (CRT) to downstage the tumour and increase the chance of a complete surgical resection. Approximately one fourth of patients show such a good response that no or only few tumour cells remain after CRT [14–16]. This has contributed to a recent shift towards more organ-preserving treatments, such as “watch and wait”, for selected patients with clinical evidence of a (near-)complete response [17–23]. This shift has necessitated the need to develop methods that can accurately evaluate treatment response and identify which patients may be candidates for organ-preservation. Predicting the treatment response before the start of chemo-
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