Lifetime attributable risk of radiation-induced secondary cancer from proton beam therapy compared with that of intensity-modulated X-ray therapy in randomly sampled pediatric cancer patients

To investigate the amount that radiation-induced secondary cancer would be reduced by using proton beam therapy (PBT) in place of intensity-modulated X-ray therapy (IMXT) in pediatric patients, we analyzed lifetime attributable risk (LAR) as an in silico surrogate marker of the secondary cancer after these treatments. From 242 pediatric patients with cancers who were treated with PBT, 26 patients were selected by random sampling after stratification into four categories: (i) brain, head and neck, (ii) thoracic, (iii) abdominal, and (iv) whole craniospinal (WCNS) irradiation. IMXT was replanned using the same computed tomography and region of interest. Using the dose-volume histograms (DVHs) of PBT and IMXT, the LARs of Schneider et al. were calculated for the same patient. All the published dose-response models were tested for the organs at risk. Calculation of the LARs of PBT and IMXT based on the DVHs was feasible for all patients. The means +/- standard deviations of the cumulative LAR difference between PBT and IMXT for the four categories were (i) 1.02 +/- 0.52% (n = 7, P = 0.0021), (ii) 23.3 +/- 17.2% (n = 8, P = 0.0065), (iii) 16.6 +/- 19.9% (n = 8, P = 0.0497) and (iv) 50.0 +/- 21.1% (n = 3, P = 0.0274), respectively (one tailed t-test). The numbers needed to treat (NNT) were (i) 98.0, (ii) 4.3, (iii) 6.0 and (iv) 2.0 for WCNS, respectively. In pediatric patients who had undergone PBT, the LAR of PBT was significantly lower than the LAR of IMXT estimated by in silico modeling. Although a validation study is required, it is suggested that the LAR would be useful as an in silico surrogate marker of secondary cancer induced by different radiotherapy techniques

Lifetime attributable risk of radiation-induced secondary cancer from proton beam therapy compared with that of intensity-modulated X-ray therapy in randomly sampled pediatric cancer patients

To investigate the amount that radiation-induced secondary cancer would be reduced by using proton beam therapy (PBT) in place of intensity-modulated X-ray therapy (IMXT) in pediatric patients, we analyzed lifetime attributable risk (LAR) as an in silico surrogate marker of the secondary cancer after these treatments. From 242 pediatric patients with cancers who were treated with PBT, 26 patients were selected by random sampling after stratification into four categories: (i) brain, head and neck, (ii) thoracic, (iii) abdominal, and (iv) whole craniospinal (WCNS) irradiation. IMXT was replanned using the same computed tomography and region of interest. Using the dose–volume histograms (DVHs) of PBT and IMXT, the LARs of Schneider et al. were calculated for the same patient. All the published dose–response models were tested for the organs at risk. Calculation of the LARs of PBT and IMXT based on the DVHs was feasible for all patients. The means ± standard deviations of the cumulative LAR difference between PBT and IMXT for the four categories were (i) 1.02 ± 0.52% (n = 7, P = 0.0021), (ii) 23.3 ± 17.2% (n = 8, P = 0.0065), (iii) 16.6 ± 19.9% (n = 8, P = 0.0497) and (iv) 50.0 ± 21.1% (n = 3, P = 0.0274), respectively (one tailed t-test). The numbers needed to treat (NNT) were (i) 98.0, (ii) 4.3, (iii) 6.0 and (iv) 2.0 for WCNS, respectively. In pediatric patients who had undergone PBT, the LAR of PBT was significantly lower than the LAR of IMXT estimated by in silico modeling. Although a validation study is required, it is suggested that the LAR would be useful as an in silico surrogate marker of secondary cancer induced by different radiotherapy techniques

Optimization of the fractionated irradiation scheme considering physical doses to tumor and organ at risk based on dose-volume histograms

Purpose: Radiotherapy of solid tumors has been performed with various fractionation regimens such as multi- and hypofractionations. However, the ability to optimize the fractionation regimen considering the physical dose distribution remains insufficient. This study aims to optimize the fractionation regimen, in which the authors propose a graphical method for selecting the optimal number of fractions (n) and dose per fraction (d) based on dose-volume histograms for tumor and normal tissues of organs around the tumor. Methods: Modified linear-quadratic models were employed to estimate the radiation effects on the tumor and an organ at risk (OAR), where the repopulation of the tumor cells and the linearity of the dose-response curve in the high dose range of the surviving fraction were considered. The minimization problem for the damage effect on the OAR was solved under the constraint that the radiation effect on the tumor is fixed by a graphical method. Here, the damage effect on the OAR was estimated based on the dose-volume histogram. Results: It was found that the optimization of fractionation scheme incorporating the dose-volume histogram is possible by employing appropriate cell surviving models. The graphical method considering the repopulation of tumor cells and a rectilinear response in the high dose range enables them to derive the optimal number of fractions and dose per fraction. For example, in the treatment of prostate cancer, the optimal fractionation was suggested to lie in the range of 8-32 fractions with a daily dose of 2.2-6.3 Gy. Conclusions: It is possible to optimize the number of fractions and dose per fraction based on the physical dose distribution (i.e., dose-volume histogram) by the graphical method considering the effects on tumor and OARs around the tumor. This method may stipulate a new guideline to optimize the fractionation regimen for physics-guided fractionation. (C) 2015 American Association of Physicists in Medicine

A Mathematical Study to Select Fractionation Regimen Based on Physical Dose Distribution and the Linear–Quadratic Model

PURPOSE:Hypofractionated irradiation is often used in precise radiotherapy instead of conventional multifractionated irradiation. We propose a novel mathematical method for selecting a hypofractionated or multifractionated irradiation regimen based on physical dose distribution adding to biologic consideration. METHODS AND MATERIALS: The linear-quadratic model was used for the radiation effects on tumor and normal tissues, especially organs at risk (OARs). On the basis of the assumption that the OAR receives a fraction of the dose intended for the tumor, the minimization problem for the damage effect on the OAR was treated under the constraint that the radiation effect on the tumor is fixed. RESULTS: For an N-time fractionated irradiation regimen, the constraint of tumor lethality was described by an N-dimensional hypersphere. The total dose of the fractionated irradiations was considered for minimizing the damage effect on the OAR under the hypersphere condition. It was found that the advantage of hypofractionated or multifractionated irradiation therapies depends on the magnitude of the ratio of α/β parameters for the OAR and tumor in the linear-quadratic model and the ratio of the dose for the OAR and tumor. CONCLUSIONS: Our mathematical method shows that multifractionated irradiation with a constant dose is better if the ratio of α/β for the OAR and tumor is less than the ratio of the dose for the OAR and tumor, whereas hypofractionated irradiation is better otherwise

A Nucleoside Anticancer Drug, 1-(3-C-Ethynyl-β-D-Ribo-Pentofuranosyl)Cytosine, Induces Depth-Dependent Enhancement of Tumor Cell Death in Spread-Out Bragg Peak (SOBP) of Proton Beam

The effect of 1-(3-C-ethynyl-β-D-ribo-pentofuranosyl)cytosine (ECyd) on proton-induced cell death was evaluated in human lung carcinoma cell line A549 and Chinese hamster fibroblast cell line V79 to enhance relative biological effectiveness (RBE) within the spread-out Bragg peak (SOBP) of proton beams. Treatment with ECyd significantly enhanced the proton-induced loss of clonogenicity and increased senescence at the center, but not at the distal edge of SOBP. The p53-binding protein 1 foci formation assay showed that ECyd decelerated the rate of DNA double-strand break (DSB) repair at the center, but not the distal region of SOBP, suggesting that the ECyd-induced enhancement of proton-induced cell death is partially associated with the inhibition of DSB repair. This study demonstrated that ECyd enhances proton-induced cell killing at all positions of SOBP, except for the distal region and minimizes the site-dependent differences in RBE within SOBP. Thus, ECyd is a unique radiosensitizer for proton therapy that may be useful because it levels the biological dose within SOBP, which improves tumor control and reduces the risk of adverse effects at the distal edge of SOBP

First experimental results of gated proton imaging using x-ray fluoroscopy to detect a fiducial marker

Increasing numbers of proton imaging research studies are being conducted for accurate proton range determination in proton therapy treatment planning. However, there is no proton imaging system that deals with motion artifacts. In this study, a gated proton imaging system was developed and the first experimental results of proton radiography were obtained for a moving object without motion artifacts. A motion management system using dual x-ray fluoroscopy for detecting a spherical gold fiducial marker was introduced and the proton beam was gated in accordance with the motion of the object. To demonstrate the performance of the gated proton imaging system, gated proton radiography images of a moving phantom were acquired experimentally, and the motion artifacts clearly were diminished. Also, the factors causing image deteriorations were evaluated focusing on the new gating system developed here, and the main factor was identified as the latency (with a maximum value of 93 ms) between the ideal gating signal according to the actual marker position and the actual gating signal. The possible deterioration due to the latency of the proton imaging system and proton beam irradiation was small owing to appropriate setting of the time structure

A simulation study on the dosimetric benefit of real-time motion compensation in spot-scanning proton therapy for prostate

For proton spot scanning, use of a real-time-image gating technique incorporating an implanted marker and dual fluoroscopy facilitates mitigation of the dose distribution deterioration caused by interplay effects. This study explored the advantages of using a real-time-image gating technique, with a focus on prostate cancer. Two patient-positioning methods using fiducial markers were compared: (i) patient positioning only before beam delivery, and (ii) patient positioning both before and during beam delivery using a real-time-gating technique. For each scenario, dose distributions were simulated using the CT images of nine prostate cancer patients. Treatment plans were generated using a single-field proton beam with 3-mm and 6-mm lateral margins. During beam delivery, the prostate was assumed to move by 5 mm in four directions that were perpendicular to the beam direction at one of three separate timings (i.e. after the completion of the first, second and third quartiles of the total delivery of spot irradiation). Using a 3-mm margin and second quartile motion timing, the averaged values for Delta D-99, Delta D-95, Delta D-5 and D5-95 were 5.1%, 3.3%, 3.6% and 9.0%, respectively, for Scenario (i) and 2.1%, 1.5%, 0.5% and 4.1%, respectively, for Scenario (ii). The margin expansion from 3 mm to 6 mm reduced the size of Delta D-99, Delta D-95, Delta D-5 and D5-95 only with Scenario (i). These results indicate that patient positioning during beam delivery is an effective way to obtain better target coverage and uniformity while reducing the target margin when the prostate moves during irradiation

Quantitative evaluation of image recognition performance of fiducial markers in real-time tumor-tracking radiation therapy

Purpose: To quantitatively evaluate and compare the image recognition performance of multiple fiducial markers available in real-time tumor-tracking radiation therapy (RTRT). Methods: Clinically available markers including sphere shape, coil shape, cylinder shape, line shape, and ball shape (folded line shape) were evaluated in liver and lung models of RTRT. Maximum thickness of the polymethyl metacrylate (PMMA) phantom that could automatically recognize the marker was determined by template-pattern matching. Image registration accuracy of the fiducial marker was determined using liver RTRT model. Lung RTRT was mimicked with an anthropomorphic chest phantom and a one-dimensional motion stage in order to simulate marker motion in heterogeneous fluoroscopic images. The success or failure of marker tracking and image registration accuracy for the lung model were evaluated in the same manner as that for the liver model. Results: All fiducial markers except for line shape and coil shape of thinner diameter were recognized by the PMMA phantom, which is assumed to have the typical thickness of an abdomen, with two-dimensional image registration accuracy of < 2 pixels. Three-dimensional calculation error with the use of real-time stereoscopic fluoroscopy in RTRT was thought to be within 1 mm. In the evaluation using the lung model, the fiducial markers were recognized stably with sufficient accuracy for clinical application. The same was true for the evaluation using the liver model. Conclusions: The image recognition performance of fiducial markers was quantified and compared. The results presented here may be useful for the selection of fiducial markers

Prediction of liver D-mean for proton beam therapy using deep learning and contour-based data augmentation

The prediction of liver D-mean with 3-dimensional radiation treatment planning (3DRTP) is time consuming in the selection of proton beam therapy (PBT), and deep learning prediction generally requires large and tumor-specific databases. We developed a simple dose prediction tool (SDP) using deep learning and a novel contour-based data augmentation (CDA) approach and assessed its usability. We trained the SDP to predict the liver D mean immediately. Five and two computed tomography (CT) data sets of actual patients with liver cancer were used for the training and validation. Data augmentation was performed by artificially embedding 199 contours of virtual clinical target volume (CTV) into CT images for each patient. The data sets of the CTVs and OARs are labeled with liver D-mean for six different treatment plans using two-dimensional calculations assuming all tissue densities as 1.0. The test of the validated model was performed using 10 unlabeled CT data sets of actual patients. Contouring only of the liver and CTV was required as input. The mean relative error (MRE), the mean percentage error (MPE) and regression coefficient between the planned and predicted D-mean was 0.1637, 6.6%, and 0.9455, respectively. The mean time required for the inference of liver D-mean of the six different treatment plans for a patient was 4.47 +/- 0.13 seconds. We conclude that the SDP is cost-effective and usable for gross estimation of liver Dmean in the clinic although the accuracy should be improved further if we need the accuracy of liver D-mean tobe compatible with 3DRTP