Brain Connectivity & Machine Learning

Multi-site tumor sampling (MSTS) improves the performance of histological detection of intratumor heterogeneity in clear cell renal cell carcinoma (CCRCC)

Guarch R, Cortes JM, Lawrie CH and Lopez JI. Multi-site tumor sampling (MSTS) improves the performance of histological detection of intratumor heterogeneity in clear cell renal cell carcinoma (CCRCC). F1000Research 5: 2020, 2016 [pdf]
Current standard-of-care tumor sampling protocols for CCRCC (and other cancers) are not efficient at detecting intratumoural heterogeneity (ITH). We have demonstrated that an alternative protocol, multi-site tumor in silico sampling (MSTS) based upon the divide and conquer (DAC) algorithm, can significantly increase the efficiency of ITH detection without extra costs. Now we test this protocol on routine hematoxylin-eosin (HE) sections in a series of 38 CCRCC cases. MSTS was found to outperform traditional sampling when detecting either high grade (p=0.0136) or granular/eosinophilic cells (p=0.0114). We therefore propose that MSTS should be used in routine clinical practice.

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