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Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats

PURPOSE: Radiation therapy is one of the most common treatments in the fight against prostate cancer, since it is used to control the tumor (early stages), to slow its progression, and even to control pain (metastasis). Although many factors (e.g., tumor oxygenation) are known to influence treatment...

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Autores principales: Belfatto, Antonella, White, Derek A., Mason, Ralph P., Zhang, Zhang, Stojadinovic, Strahinja, Baroni, Guido, Cerveri, Pietro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association of Physicists in Medicine 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5148178/
https://www.ncbi.nlm.nih.gov/pubmed/26936712
http://dx.doi.org/10.1118/1.4941746
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author Belfatto, Antonella
White, Derek A.
Mason, Ralph P.
Zhang, Zhang
Stojadinovic, Strahinja
Baroni, Guido
Cerveri, Pietro
author_facet Belfatto, Antonella
White, Derek A.
Mason, Ralph P.
Zhang, Zhang
Stojadinovic, Strahinja
Baroni, Guido
Cerveri, Pietro
author_sort Belfatto, Antonella
collection PubMed
description PURPOSE: Radiation therapy is one of the most common treatments in the fight against prostate cancer, since it is used to control the tumor (early stages), to slow its progression, and even to control pain (metastasis). Although many factors (e.g., tumor oxygenation) are known to influence treatment efficacy, radiotherapy doses and fractionation schedules are often prescribed according to the principle “one-fits-all,” with little personalization. Therefore, the authors aim at predicting the outcome of radiation therapy a priori starting from morphologic and functional information to move a step forward in the treatment customization. METHODS: The authors propose a two-step protocol to predict the effects of radiation therapy on individual basis. First, one macroscopic mathematical model of tumor evolution was trained on tumor volume progression, measured by caliper, of eighteen Dunning R3327-AT1 bearing rats. Nine rats inhaled 100% O(2) during irradiation (oxy), while the others were allowed to breathe air. Second, a supervised learning of the weight and biases of two feedforward neural networks was performed to predict the radio-sensitivity (target) from the initial volume and oxygenation-related information (inputs) for each rat group (air and oxygen breathing). To this purpose, four MRI-based indices related to blood and tissue oxygenation were computed, namely, the variation of signal intensity [Formula: see text] in interleaved blood oxygen level dependent and tissue oxygen level dependent (IBT) sequences as well as changes in longitudinal [Formula: see text] and transverse [Formula: see text] relaxation rates. RESULTS: An inverse correlation of the radio-sensitivity parameter, assessed by the model, was found with respect the [Formula: see text] (−0.65) for the oxy group. A further subdivision according to positive and negative values of [Formula: see text] showed a larger average radio-sensitivity for the oxy rats with [Formula: see text] and a significant difference in the two distributions (p < 0.05). Finally, a leave-one-out procedure yielded a radio-sensitivity error lower than 20% in both neural networks. CONCLUSIONS: While preliminary, these specific results suggest that subjects affected by the same pathology can benefit differently from the same irradiation modalities and support the usefulness of IBT in discriminating between different responses.
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spelling pubmed-51481782016-12-19 Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats Belfatto, Antonella White, Derek A. Mason, Ralph P. Zhang, Zhang Stojadinovic, Strahinja Baroni, Guido Cerveri, Pietro Med Phys BIOLOGICAL PHYSICS AND RESPONSE PREDICTION PURPOSE: Radiation therapy is one of the most common treatments in the fight against prostate cancer, since it is used to control the tumor (early stages), to slow its progression, and even to control pain (metastasis). Although many factors (e.g., tumor oxygenation) are known to influence treatment efficacy, radiotherapy doses and fractionation schedules are often prescribed according to the principle “one-fits-all,” with little personalization. Therefore, the authors aim at predicting the outcome of radiation therapy a priori starting from morphologic and functional information to move a step forward in the treatment customization. METHODS: The authors propose a two-step protocol to predict the effects of radiation therapy on individual basis. First, one macroscopic mathematical model of tumor evolution was trained on tumor volume progression, measured by caliper, of eighteen Dunning R3327-AT1 bearing rats. Nine rats inhaled 100% O(2) during irradiation (oxy), while the others were allowed to breathe air. Second, a supervised learning of the weight and biases of two feedforward neural networks was performed to predict the radio-sensitivity (target) from the initial volume and oxygenation-related information (inputs) for each rat group (air and oxygen breathing). To this purpose, four MRI-based indices related to blood and tissue oxygenation were computed, namely, the variation of signal intensity [Formula: see text] in interleaved blood oxygen level dependent and tissue oxygen level dependent (IBT) sequences as well as changes in longitudinal [Formula: see text] and transverse [Formula: see text] relaxation rates. RESULTS: An inverse correlation of the radio-sensitivity parameter, assessed by the model, was found with respect the [Formula: see text] (−0.65) for the oxy group. A further subdivision according to positive and negative values of [Formula: see text] showed a larger average radio-sensitivity for the oxy rats with [Formula: see text] and a significant difference in the two distributions (p < 0.05). Finally, a leave-one-out procedure yielded a radio-sensitivity error lower than 20% in both neural networks. CONCLUSIONS: While preliminary, these specific results suggest that subjects affected by the same pathology can benefit differently from the same irradiation modalities and support the usefulness of IBT in discriminating between different responses. American Association of Physicists in Medicine 2016-03 2016-02-12 /pmc/articles/PMC5148178/ /pubmed/26936712 http://dx.doi.org/10.1118/1.4941746 Text en Copyright © 2016 American Association of Physicists in Medicine 0094-2405/2016/43(3)/1275/10/$30.00 All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/ ).
spellingShingle BIOLOGICAL PHYSICS AND RESPONSE PREDICTION
Belfatto, Antonella
White, Derek A.
Mason, Ralph P.
Zhang, Zhang
Stojadinovic, Strahinja
Baroni, Guido
Cerveri, Pietro
Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats
title Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats
title_full Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats
title_fullStr Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats
title_full_unstemmed Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats
title_short Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats
title_sort tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats
topic BIOLOGICAL PHYSICS AND RESPONSE PREDICTION
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5148178/
https://www.ncbi.nlm.nih.gov/pubmed/26936712
http://dx.doi.org/10.1118/1.4941746
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