Estimation of risk associated to peripheral dose in patients undergoing radiotherapy treatment

  1. Romero Expósito, María Teresa
Dirixida por:
  1. Beatriz Sánchez Nieto Director
  2. Francisco Sánchez-Doblado Director

Universidade de defensa: Universidad de Sevilla

Fecha de defensa: 21 de xullo de 2012

Tribunal:
  1. Carles Domingo Miralles Presidente/a
  2. Antonio Leal Plaza Secretario/a
  3. Juan Vicente Rosello Ferrando Vogal
  4. Roberto Bedogni Vogal
  5. Faustino Gomez Rodriguez Vogal

Tipo: Tese

Teseo: 330374 DIALNET lock_openIdus editor

Resumo

The induction of secondary cancer as a consequence of the radiotherapy treatment is an issue of concern nowadays. This fact makes relevant to consider all the dose delivered to the patient and, thus, it is necessary to include the peripheral dose. In this work we focused on the neutron radiation generated by high energy (i.e. > 10 MV) photon radiotherapy beams given that the accurate determination of the neutron equivalent doses is still a challenging task in radiotherapy. This situation is responsible of the fact that, in the implementation of modern techniques (such as intensity modulated radiotherapy), a blind choice has to be done between low energies (i.e., 6MV) (with no neutrons but throwing away the potential benefit of better conformality) and high energies (with the subsequent secondary cancer risk associated to neutrons). The aim of this work was to develop a model for the estimation in real time of neutron equivalent doses and propose a methodology to include the effect of this neutron contamination (through the associated secondary cancer risk or probability) in the evaluation of the radiotherapy treatment success by means of an integral radiobiological approach. The neutron equivalent dose model is based on the correlation between the readings of a new digital detector, which allows a real time measurement of the neutron production inside the treatment room, and the equivalent doses inside an anthropomorphic phantom for several irradiation conditions. This correlation model has been further extended to estimate neutron equivalent dose at specific organs in patients. Using current risk model from international organisms, estimation of the secondary cancer risk due to neutrons has been performed. The methodology was applied to 1377 patients in a total of 50 different facilities. Those measurements covered 15 different combinations of linac manufacturer and nominal energy. A data base has been generated with such information. The main result is that equivalent dose and secondary cancer probability scale with the number of monitor units (MU). Thus, a procedure has been established in order to makes estimates of both magnitudes from the number of MU of any treatment. This enables a quick estimation of cancer risk during treatment planning. The selection of the best radiotherapy treatment strategy is starting to routinely involve the evaluation of dose distributions in terms of the radiobiological response of tissues through the application of tumour control and normal tissue complication probabilities functions. In this work, it is proposed that secondary cancer probability can be included as an extra complication term. Thus, a new function, termed Uncomplicated and Cancer-Free tumour Control Probability has been defined representing a biologic objective function which estimates the probability to achieve complication-free tumour control, without cancer induction. This function was applied to a selected prostate case planned with all available radiotherapy treatment strategies. The results of this analysis showed that the better sparing capabilities of modern techniques can compensate the higher neutron production of high energies by means of efficient use of MU. Thus, neutron collateral effect might not represent an \a priori" limiting factor in the selection of the strategy. However, it is mandatory to perform a complete evaluation of the plan taking into account both types of complications and a clinical judgement taking into account other factors such as illness prognosis and, consequently, life expectancy.