Mapping tissue heterogeneity in solid tumours using PET–MRI and machine learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Biomedical Engineering,Medicine (miscellaneous),Bioengineering,Biotechnology
Link
https://www.nature.com/articles/s41551-023-01046-w.pdf
Reference5 articles.
1. Li, Z., Seehawer, M. & Polyak, K. Untangling the web of intratumour heterogeneity. Nat. Cell Biol. 24, 1192–1201 (2022). A review article on ITH and its relevance in oncology.
2. Mannheim, J. G. et al. PET/MRI hybrid systems. Semin. Nucl. Med. 48, 332–347 (2018). A review article summarizing the advances in hybrid PET–MRI.
3. Heinzmann, K., Carter, L. M., Lewis, J. S. & Aboagye, E. O. Multiplexed imaging for diagnosis and therapy. Nat. Biomed. Eng. 1, 697–713 (2017). A review article highlighting the potential of multiplexed imaging for cancer diagnosis and therapy monitoring.
4. Siegemund, M. et al. Superior antitumoral activity of dimerized targeted single-chain TRAIL fusion proteins under retention of tumor selectivity. Cell Death Dis. 3, e295 (2012). This paper reports Db-scTRAIL therapy, which we used in our experiments.
5. Disselhorst, J. A. et al. Linking imaging to omics utilizing image-guided tissue extraction. Proc. Natl Acad. Sci. USA 115, E2980–E2987 (2018). This work performs image-guided tissue sampling to link imaging data with omics data.
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