One of the primary challenges in anti-cancer histology is the heterogeneity of tumors. Different areas of a single tumor can show varied histological features, making it difficult to assess the overall grade and stage. Additionally, distinguishing between reactive changes due to therapy and residual disease can be challenging. Advanced techniques like digital pathology and machine learning algorithms are being developed to address these challenges.
