Mathematical modeling is a powerful and flexible method to investigate complex phenomena. It discloses the possibility of reproducing expensive as well as invasive experiments in a safe environment with limited costs. This makes it suitable to mimic tumor evolution and response to radiotherapy although the reliability of the results remains an issue. Complexity reduction is therefore a critical aspect in order to be able to compare model outcomes to clinical data. Among the factors affecting treatment efficacy, tumor oxygenation is known to play a key role in radiotherapy response. In this work, we aim at relating the oxygenation dynamics, predicted by a macroscale model trained on tumor volumetric data of uterine cervical cancer patients, to vascularization and blood flux indices assessed on Ultrasound Doppler images.

Comparison between model-predicted tumor oxygenation dynamics and vascular-/flow-related Doppler indices

BELFATTO, ANTONELLA;BARONI, GUIDO;CERVERI, PIETRO
2017

Abstract

Mathematical modeling is a powerful and flexible method to investigate complex phenomena. It discloses the possibility of reproducing expensive as well as invasive experiments in a safe environment with limited costs. This makes it suitable to mimic tumor evolution and response to radiotherapy although the reliability of the results remains an issue. Complexity reduction is therefore a critical aspect in order to be able to compare model outcomes to clinical data. Among the factors affecting treatment efficacy, tumor oxygenation is known to play a key role in radiotherapy response. In this work, we aim at relating the oxygenation dynamics, predicted by a macroscale model trained on tumor volumetric data of uterine cervical cancer patients, to vascularization and blood flux indices assessed on Ultrasound Doppler images.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1026771
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