Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

Area of Science:

• Computational pathology
• Biomedical imaging analysis
• Cancer research informatics

Background:

• The National Cancer Institute (NCI) supports cancer research consortia utilizing imaging technologies.
• The Image Analysis Working Group (IAWG) was established in 2019 to promote collaboration in cancer imaging analysis.
• Increasing complexity of multiplexed imaging necessitates advanced computational methods beyond traditional techniques.

Purpose of the Study:

• To address challenges in analyzing high-dimensional, complex datasets from fixed cancer tissues.
• To foster innovation in computational methods for cancer imaging.
• To summarize hackathon efforts, resources, and identify future challenges.

Main Methods:

• A virtual hackathon was conducted by the IAWG in 2022.
• Focus areas included cell type classification, spatial data visualization, and scaling image analysis.
• Participants explored limitations of current automated tools and developed potential solutions.

Main Results:

• Significant progress was made in addressing key challenges in cancer image analysis.
• Exploration of limitations in automated analysis tools for complex datasets.
• Development of potential solutions and resources for the research community.

Conclusions:

• The hackathon highlighted the need for advanced computational approaches in cancer imaging.
• Integration of emerging technologies into diverse imaging modalities presents ongoing challenges.
• Continued development and collaboration are crucial for advancing cancer image analysis.