PURPOSE: To present a new method of evaluating the correlation between radiotherapy (RT)-induced fibrosis and the local dose delivered to non-small-cell lung cancer patients. METHODS AND MATERIALS: Treatment plans were generated using the CadPlan treatment planning system (pencil beam, no heterogeneity corrections), and RT delivery was based on these plans. Retrospective Monte-Carlo dose calculations were performed, and the Monte-Carlo distributions of dose to real tissue were calculated using the planning computed tomography (CT) images and the number of monitor units actually delivered. After registration of the follow-up CT images with the planning CT images, different grades of radiologic fibrosis were automatically segmented on the follow-up CT images. Subsequently, patient-specific fibrosis probabilities were studied as a function of the local dose and a function of time after RT completion. RESULTS: A strong patient-specific variation in the fibrosis volumes was found during the follow-up period. For both lungs, the threshold dose for which the probability of fibrosis became significant coincided with the threshold dose at which significant volumes of the lung were exposed. At later stages, only fibrosis localized in the high-dose regions persisted for both lungs. Overall, the Monte-Carlo dose distributions correlated much better with the probability of RT-induced fibrosis than did the CadPlan dose distributions. CONCLUSION: The presented method allows for an accurate, systematic, patient-specific and post-RT time-dependent numeric study of the relationship between RT-induced fibrosis and the local dose.
PURPOSE: To present a new method of evaluating the correlation between radiotherapy (RT)-induced fibrosis and the local dose delivered to non-small-cell lung cancerpatients. METHODS AND MATERIALS: Treatment plans were generated using the CadPlan treatment planning system (pencil beam, no heterogeneity corrections), and RT delivery was based on these plans. Retrospective Monte-Carlo dose calculations were performed, and the Monte-Carlo distributions of dose to real tissue were calculated using the planning computed tomography (CT) images and the number of monitor units actually delivered. After registration of the follow-up CT images with the planning CT images, different grades of radiologic fibrosis were automatically segmented on the follow-up CT images. Subsequently, patient-specific fibrosis probabilities were studied as a function of the local dose and a function of time after RT completion. RESULTS: A strong patient-specific variation in the fibrosis volumes was found during the follow-up period. For both lungs, the threshold dose for which the probability of fibrosis became significant coincided with the threshold dose at which significant volumes of the lung were exposed. At later stages, only fibrosis localized in the high-dose regions persisted for both lungs. Overall, the Monte-Carlo dose distributions correlated much better with the probability of RT-induced fibrosis than did the CadPlan dose distributions. CONCLUSION: The presented method allows for an accurate, systematic, patient-specific and post-RT time-dependent numeric study of the relationship between RT-induced fibrosis and the local dose.
Authors: David A Jaffray; Patricia E Lindsay; Kristy K Brock; Joseph O Deasy; W A Tomé Journal: Int J Radiat Oncol Biol Phys Date: 2010-03-01 Impact factor: 7.038
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Authors: Karine A Al Feghali; Qixue Charles Wu; Suneetha Devpura; Chang Liu; Ahmed I Ghanem; Ning Winston Wen; Munther Ajlouni; Michael J Simoff; Benjamin Movsas; Indrin J Chetty Journal: Clin Transl Radiat Oncol Date: 2020-02-11