  The Circle of Willis (CoW) is an important network of arteries connecting
major circulations of the brain. Its vascular architecture is believed to
affect the risk, severity, and clinical outcome of serious neuro-vascular
diseases. However, characterizing the highly variable CoW anatomy is still a
manual and time-consuming expert task. The CoW is usually imaged by two
angiographic imaging modalities, magnetic resonance angiography (MRA) and
computed tomography angiography (CTA), but there exist limited public datasets
with annotations on CoW anatomy, especially for CTA. Therefore we organized the
TopCoW Challenge in 2023 with the release of an annotated CoW dataset. The
TopCoW dataset was the first public dataset with voxel-level annotations for
thirteen possible CoW vessel components, enabled by virtual-reality (VR)
technology. It was also the first large dataset with paired MRA and CTA from
the same patients. TopCoW challenge formalized the CoW characterization problem
as a multiclass anatomical segmentation task with an emphasis on topological
metrics. We invited submissions worldwide for the CoW segmentation task, which
attracted over 140 registered participants from four continents. The top
performing teams managed to segment many CoW components to Dice scores around
90%, but with lower scores for communicating arteries and rare variants. There
were also topological mistakes for predictions with high Dice scores.
Additional topological analysis revealed further areas for improvement in
detecting certain CoW components and matching CoW variant topology accurately.
TopCoW represented a first attempt at benchmarking the CoW anatomical
segmentation task for MRA and CTA, both morphologically and topologically.
