Computer-assisted hot-spot selection for tumor budding assessment in colorectal cancer

J. Bokhorst, F. Ciompi, I. Zlobec, A. Lugli, M. Vieth, R. Kirsch, J. van der Laak and I. Nagtegaal

European Congress of Pathology 2020.

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.