## 5 Conclusions and Limitations
While BayLIME scored well for its justification power, its presentation style detracted from its effectiveness, underscoring the importance of not just what is presented but how it is visually conveyed. CXPlain, preferred for its clarity, faced criticism for its lack of specificity, highlighting a key tension in the explanation method's design between comprehensive coverage and targeted, relevant information. The attributes that radiologists valued most in explanation methods were pinpointed with precision during this study. Beyond accuracy and specificity, the visual appeal and the ability to integrate seamlessly into existing diagnostic processes were highly prized. Consistency in explanation delivery and the avoidance of noisy, cluttered visualizationswere also deemed essential, as they impact the ease with which radiologists can derive meaningful insights from the presented data. Noise and visual clutter were especially highlighted as detrimental factors in the lower ratings for some post hoc explanation methods. Such elements can obscure critical details and lead to potential misinterpretations or oversight, undermining the radiologist's confidence and effectiveness in lesion detection. Furthermore, methods that failed to align with radiologists' analytical styles or did not meet their expectations for clarity and precision were marked down, indicating a clear preference for tools that are intuitive and align with professional norms and practices. Moreover, this study's findings suggest that the effectiveness of explanation methods is not solely dependent on the inherent technology or algorithm but also heavily reliant on the user experience. This includes how information is conveyed, the user interface, and the overall integration of the tool into the radiological workflow. As such, developers of these technologies need to consider these factors, adopting a user-centered design philosophy that prioritizes the needs and preferences of the end-users--in this case, the radiologists. In summary, the varied ratings of the post hoc explanation methods by radiologists in this study shed light on the multifaceted nature of tool acceptance and effectiveness in a clinical setting. For a post hoc explanation method to be valued and effectively utilized, it must offer clear, accurate, and relevant insights in a visually appealing and user-friendly format. It should minimize noise and irrelevant information to avoid confusion and must align with the radiologists' preferred modes of working and analytical methods. This comprehensive understanding of radiologist preferences and needs can significantly inform the development of future explanation methods, ensuring that they are not only technologically advanced but also practical, intuitive, and conducive to the critical work of medical diagnosis. One limitation of this study is that it focuses solely on T2 MRI images for detecting prostate cancer. The performance and preferences of explanation methods may differ when other image modalities, such as ADC and diffusion images, are used. It is crucial to investigate the effectiveness of explanation methods on these image modalities as well. However, this study only considered T2 images to keep it manageable for the radiologists and to isolate the conclusions to this specific image modality. Another limitation of this study is the small sample size. While this study was designed as a pilot study, a larger sample size would be necessary to obtain more robust conclusions. Nonetheless, this study provides valuable insights that can guide future studies with larger sample sizes and different image modalities. Future studies should consider a larger sample size and other image modalities to further investigate the effectiveness of explanation methods in radiology. Conceptualization, M.A.G., C.M.T. and M.K. ; methodology, M.A.G. and C.M.T. ; solftware, M.A.G. and C.M.T. ; validation, M.A.G., C.M.T. and M.K. ; formal analysis, M.A.G., C.M.T., M.K. and M.O. ; investigation, M.A.G., C.M.T., M.O., E.E. and M.A. ; resources, M.A.G. and C.M.T.