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Integrating artificial intelligence (AI) into colorectal cancer reporting.

Konstantin Bräutigam1, Ann-Marie Baker1, Viktor H Koelzer2,3

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Artificial intelligence (AI) and deep learning (DL) are revolutionizing colorectal cancer (CRC) research. AI tools can standardize pathology reports and identify new prognostic biomarkers, improving patient outcomes.

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Area of Science:

  • Oncology
  • Digital Pathology
  • Artificial Intelligence

Background:

  • Colorectal cancer (CRC) is a leading cause of cancer mortality worldwide.
  • Histopathology is crucial for CRC diagnosis and prognosis, but reporting variability persists.
  • Artificial intelligence (AI) and deep learning (DL) offer potential solutions for standardizing CRC pathology and discovering new biomarkers.

Purpose of the Study:

  • To review recent advances in AI-assisted standardization of CRC pathology reporting.
  • To explore AI-driven identification of novel prognostic biomarkers in CRC.
  • To propose a harmonized approach for improved CRC risk assessment.

Main Methods:

  • Review of recent studies on AI and DL in CRC histopathology.
  • Analysis of AI applications for feature extraction from whole-slide images.
  • Evaluation of AI-based biomarkers for prognostic prediction in CRC.

Main Results:

  • AI tools can enhance the standardization of histopathology reporting for CRC.
  • DL models applied to pathology slides can outperform traditional prognostic indicators.
  • Novel prognostic parameters, including tumor-adipocyte interactions and immune cell patterns, are identified by AI.

Conclusions:

  • AI holds significant promise for refining CRC pathology reporting and risk stratification.
  • A combination of established pathology features and AI-derived indicators can improve patient outcomes.
  • Further standardization and harmonization of AI approaches are needed for widespread clinical adoption.