Robust treatment planning of dose painting for prostate cancer based on ADC-to-Gleason score mappings - what is the potential to increase the tumor control probability?

Eric Grönlund Erik Almhagen Silvia Johansson Erik Traneus Tufve Nyholm Camilla Thellenberg Karlsson Anders Ahnesjö

Published in: Acta oncologica (Stockholm, Sweden) (2020)

TCP increases with DPBN plans optimized in a TPS were found more likely with a high precision mapping of image data into dose-responses and a high certainty of the tumor positioning. These findings motivate further development to ensure precise mappings of image data into dose-responses and to ensure a high spatial certainty of the tumor positioning when implementing DPBN clinically.

Keyphrases

prostate cancer
radical prostatectomy
deep learning
electronic health record
high resolution
magnetic resonance imaging
machine learning
data analysis
climate change
human health