Radioanatomy, short for radiographic anatomy, is the study of anatomy through medical imaging. Its early-stage introduction into medical curricula has been recommended in the literature. As with many other medical courses, it has seen a shift toward blended learning, including assessment on learning management systems such as Moodle, one advantage being automatic or at least assisted grading. The majority of previous studies in the realm of radioanatomy report only on the usage of multiple choice questions, due to several challenges related to computer-based assessment. Nonetheless, we encourage radioanatomy teachers to include a more diverse set of question types. We consolidated the lessons learned during our experience over three academic years of carrying out summative assessments in radioanatomy courses on Moodle. Among others, we discuss technical aspects such as image optimization. Providing a lexicon for standardized answers fosters automatic grading. A student survey supports the idea of using stack visualizations for better image interpretation. We finally underline the importance of collaboration between different stakeholders to ensure a smooth assessment preparation, execution, and analysis. These findings offer valuable insights for improving e-assessment in radioanatomy and potentially other medical courses.