Published in Cancers (Basel), 13(20), p. 5089.
Abstract:
The use of neoadjuvant therapy (NAT) in patients with pancreatic ductal adenocarcinoma (PDAC) is increasing. Objective quantification of the histopathological response to NAT may be used to guide adjuvant treatment and compare the efficacy of neoadjuvant regimens. However, current tumor response scoring (TRS) systems suffer from interobserver variability, originating from subjective definitions, the sometimes challenging histology, and response heterogeneity throughout the tumor bed. This study investigates if artificial intelligence-based segmentation of residual tumor burden in histopathology of PDAC after NAT may offer a more objective and reproducible TRS solution.
Janssen, B.V., Theijse, R., van Roessel, S., de Ruiter, R., Berkel, A., Huiskens, J., Busch, O.R., Wilmink J.W., Kazemier, G., Valkema, P., Farina, A., Verheij, J., de Boer, O.J., Besselink, M.G. (2021), Cancers (Basel), 13(20), p. 5089.
Artificial Intelligence-Based Segmentation of Residual Tumor in Histopathology of Pancreatic Cancer ...
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