NDLI: A new parameter computed with independent component analysis to predict rectal toxicity following prostate cancer radiotherapy

Content Provider	IEEE Xplore Digital Library
Author	Fargeas, A. Arango, J.D.O. Kachenoura, A. Costet, N. Albera, L. Lafond, C. Acosta, O. De Crevoisier, R.
Copyright Year	2015
Description	Author affiliation: Lab. Traitement du Signal et de l'Image, Univ. de Rennes 1, Rennes, France (Costet, N.) \|\| INSERM, Rennes, France (Fargeas, A.; Arango, J.D.O.; Kachenoura, A.; Albera, L.; Acosta, O.; De Crevoisier, R.) \|\| Authors are with Centre Eugne Marquis Dpartement de Radiothrapie, Rennes, France (Lafond, C.)
Abstract	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 ≥ 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.
Starting Page	2657
Ending Page	2660
File Size	759774
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7318938
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hemorrhaging Prostate cancer Predictive models Logistics Optimized production technology Computational modeling Principal component analysis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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