Mapping tissue heterogeneity in solid tumours using PET

Jun 03, 2023

Nature Biomedical Engineering (2023)Cite this article

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Demultiplexing PET–MRI data of solid tumours using machine learning allows the spatial characterization of intratumour tissue heterogeneity in mice and humans. Predicted maps of tissue subtypes within the tumour could aid in conducting image-guided biopsies and provide valuable insights linking the outcome of cancer therapies with phenotypic heterogeneity.

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This is a summary of: Katiyar, P. et al. Quantification of intratumoural heterogeneity in mice and patients via machine-learning models trained on PET–MRI data. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-023-01047-9 (2023).

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Mapping tissue heterogeneity in solid tumours using PET–MRI and machine learning. Nat. Biomed. Eng (2023). https://doi.org/10.1038/s41551-023-01046-w

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Published: 05 June 2023

DOI: https://doi.org/10.1038/s41551-023-01046-w

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