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Strategy for stochastic dose-rate induced enhanced elimination of malignant tumour without dose escalation. | LitMetric

AI Article Synopsis

  • The study investigates the effectiveness of radiation therapy for cancer treatment, focusing on balancing the elimination of prostate tumor cells while protecting normal tissues from radiation damage.
  • Using a theoretical framework based on the linear-quadratic-linear (LQL) model, researchers explored how varying the radiation dose-rate can improve tumor cell elimination without increasing the overall radiation dose.
  • The findings suggest that a fluctuating radiation dose-rate offers better protection for normal tissues compared to a constant higher dose-rate, challenging traditional models that may overestimate treatment effects on tumors.

Article Abstract

The efficacy of radiation therapy, a primary modality of cancer treatment, depends in general upon the total radiation dose administered to the tumour during the course of therapy. Nevertheless, the delivered radiation also irradiates normal tissues and dose escalation procedure often increases the elimination of normal tissue as well. In this article, we have developed theoretical frameworks under the premise of linear-quadratic-linear (LQL) model using stochastic differential equation and Jensen's inequality for exploring the possibility of attending to the two therapeutic performance objectives in contraposition-increasing the elimination of prostate tumour cells and enhancing the relative sparing of normal tissue in fractionated radiation therapy, within a prescribed limit of total radiation dose. Our study predicts that stochastic temporal modulation in radiation dose-rate appreciably enhances prostate tumour cell elimination, without needing dose escalation in radiation therapy. However, constant higher dose-rate can also enhance the elimination of tumour cells. In this context, we have shown that the sparing of normal tissue with stochastic dose-rate is considerably more than the sparing of normal tissue with the equivalent constant higher dose-rate. Further, by contrasting the stochastic dose-rate effects under LQL and linear-quadratic (LQ) models, we have also shown that the LQ model over-estimates stochastic dose-rate effect in tumour and under-estimates the stochastic dose-rate effect in normal tissue. Our study indicates the possibility of utilizing stochastic modulation of radiation dose-rate for designing enhanced radiation therapy protocol for cancer.

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Source
http://dx.doi.org/10.1093/imammb/dqv012DOI Listing

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