Purpose The field of radiology is currently underestimated by undergraduate medical students. The “Hands-on Radiology” summer school was established to improve radiology knowledge and interest among undergraduates. The purpose of this questionnaire survey was to analyze whether a radiological hands-on course is an effective tool to reach and motivate undergraduate students. Materials and methods The three-day course held in August 2022 included lectures, quizzes, and small group hands-on workshops focusing on practical work with simulators. All participants (n = 30) were asked to rate their knowledge and motivation to specialize in radiology at the beginning of the summer school (day 1) and the end (day 3). The questionnaires included multiple choice questions, 10-point scale questions and open comment questions. The second questionnaire (day 3) included additional questions regarding the program (topic choice, length, etc.). Results Out of 178 applicants, 30 students (16.8%) from 21 universities were selected to participate (50% female and 50% male students). All students completed both questionnaires. The overall rating was 9.47 on a 10-point scale. While the self-reported knowledge level increased from 6.47 (day 1) to 7.50 (day 3), almost all participants (96.7%, n = 29/30) mentioned an increased interest in the specialization of radiology after the event. Interestingly, most students (96.7%) preferred onsite teaching instead of online teaching and chose residents over board-certified radiologists as teachers. Conclusion Intensive three-day courses are valuable tools to strengthen interest in radiology and increase knowledge among medical students. Particularly, students who already have a tendency to specialize in radiology are further motivated.

PurposeAutomated lesion segmentation is increasingly used in acute ischemic stroke magnetic resonance imaging (MRI). We explored in detail the performance of apparent diffusion coefficient (ADC) thresholding for delineating baseline diffusion-weighted imaging (DWI) lesions.MethodsRetrospective, exploratory analysis of the prospective observational single-center 1000Plus study from September 2008 to June 2013 (clinicaltrials.org; NCT00715533). We built a fully automated lesion segmentation algorithm using a fixed ADC threshold (≤620 × 10–6 mm2/s) to delineate the baseline DWI lesion and analyzed its performance compared to manual assessments. Diagnostic capabilities of best possible ADC thresholds were investigated using receiver operating characteristic curves. Influential patient factors on ADC thresholding techniques’ performance were studied by conducting multiple linear regression.Results108 acute ischemic stroke patients were selected for analysis. The median Dice coefficient for the algorithm was 0.43 (IQR 0.20–0.64). Mean ADC values in the DWI lesion (β = −0.68, p < 0.001) and DWI lesion volumes (β = 0.29, p < 0.001) predicted performance. Optimal individual ADC thresholds differed between subjects with a median of ≤691 × 10−6 mm2/s (IQR ≤660–750 × 10−6 mm2/s). Mean ADC values in the DWI lesion (β = −0.96, p < 0.001) and mean ADC values in the brain parenchyma (β = 0.24, p < 0.001) were associated with the performance of individual thresholds.ConclusionThe performance of ADC thresholds for delineating acute stroke lesions varies substantially between patients. It is influenced by factors such as lesion size as well as lesion and parenchymal ADC values. Considering the inherent noisiness of ADC maps, ADC threshold-based automated delineation of very small lesions is not reliable.