Background & objectives
Tumor budding (TB) is an established prognosticator for colorectal cancer. Detection of the hot-spot to score TB is based on visual inspection, hindering reproducibility of this important factor. We present an algorithm that can potentially assist pathologists in this task.
We used a previously developed algorithm for the detection of tumor buds in pan-cytokeratin stained whole slide images, calculating the number of buds for each location using a circle with 0.785mm2 surface area. From these numbers, density heatmaps were produced. The algorithm was applied to 270 slides from Bern University hospital, in which hot-spots and tumor buds were visually identified.
Heat maps were created and we located the hand-selected hotspot and noted the associated TB number. The differences and similarities between computer identified and manually selected hot-spots were visually assessed as well as via histograms. Preliminary results show that the heatmaps are helpful, as locations with the highest TB density (the top 15%) also include the hand-selected hotspots. The full results will be presented during the conference.
The presented algorithm can assist the pathologist in selecting the hot-spot with the highest tumor bud count with more ease at low magnification and can help to reduce the high interobserver variability among pathologists in scoring tumor budding.