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Imaging markers of cerebral small vessel disease provide valuable informationon brain health, but their manual assessment is time-consuming and hampered bysubstantial intra- and interrater variability. Automated rating may benefitbiomedical research, as well as clinical assessment, but diagnostic reliabilityof existing algorithms is unknown. Here, we present the results of the\textit{VAscular Lesions DetectiOn and Segmentation} (\textit{Where is VALDO?})challenge that was run as a satellite event at the international conference onMedical Image Computing and Computer Aided Intervention (MICCAI) 2021. Thischallenge aimed to promote the development of methods for automated detectionand segmentation of small and sparse imaging markers of cerebral small vesseldisease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebralmicrobleeds (Task 2) and lacunes of presumed vascular origin (Task 3) whileleveraging weak and noisy labels. Overall, 12 teams participated in thechallenge proposing solutions for one or more tasks (4 for Task 1 - EPVS, 9 forTask 2 - Microbleeds and 6 for Task 3 - Lacunes). Multi-cohort data was used inboth training and evaluation. Results showed a large variability in performanceboth across teams and across tasks, with promising results notably for Task 1 -EPVS and Task 2 - Microbleeds and not practically useful results yet for Task 3- Lacunes. It also highlighted the performance inconsistency across cases thatmay deter use at an individual level, while still proving useful at apopulation level.

Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021