Éditeur(s) : HAL CCSD
Résumé : International audience
Objectives: Using in silico simulations from histopathological cancer prostate specimen, the objectives were to identify the total dose corresponding to various fractionations necessary to destroy the tumor cells (50% to 99.9%) and to assess the impact of the Gleason score on those doses. © 2017 IEEE.
14th IEEE International Symposium on Biomedical Imaging, ISBI 2017
Melbourne, Australia

hal-01618934
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01618934
DOI : 10.1109/ISBI.2017.7950643

Éditeur(s) : HAL CCSD IEEE
Résumé : International audience
The main challenge in prostate cancer radiotherapy is to deliver the prescribed dose to the clinical target while minimizing the dose to the neighboring organs at risk and thus avoiding subsequent toxicity-related events. With the aim of improving toxicity prediction following prostate cancer radiotherapy, the goal of our work is to propose a new predictive variable computed with independent component analysis to predict late rectal toxicity, and to compare its performance to other models (logistic regression, normal tissue complication probability model and recent principal component analysis approach). Clinical data and dose-volume histograms were collected from 216 patients having received 3D conformal radiation for prostate cancer with at least two years of follow-up. Independent component analysis was trained to predict the risk of 3-year rectal bleeding Grade extgreater= 2. The performance of all the models was assessed by computing the area under the receiving operating characteristic curve. Clinical parameters combined with the new variable were found to be predictors of rectal bleeding. The mean area under the receiving operating curve for our proposed approach was 0:75. The AUC values for the logistic regression, the Lyman-Kutcher-Burman model and the recent principal component analysis approach were 0:62, 0:53 and 0:62, respectively. Our proposed new variable may be an useful new tool in predicting late rectal toxicity. It appears as a strong predictive variable to improve classical models
2015 37th annual international conference of the IEEE Engineering in Medicine and Biology Society
Milan, Italy

hal-01304750
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01304750