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Purpose This study aimed to develop a deep convolutional neural network (CNN)-based dose distribution conversion approach for the correction of the influence of a magnetic field for online MR-guided adaptive radiotherapy. Methods Our model is based on DenseNet and consists of two 2D input channels and one 2D output channel. These three types of data comprise dose distributions without a magnetic field (uncorrected), electron density (ED) maps, and dose distributions with a magnetic field. These data were generated as follows: both types of dose distributions were created using 15-field IMRT in the same conditions except for the presence or absence of a magnetic field with the GPU Monte Carlo dose in Monaco version 5.4; ED maps were acquired with planning CT images using a clinical CT-to-ED table at our institution. Data for 50 prostate cancer patients were used; 30 patients were allocated for training, 10 for validation, and 10 for testing using 4-fold cross-validation based on rectum gas volume. The accuracy of the model was evaluated by comparing 2D gamma-indexes against the dose distributions in each irradiation field with a magnetic field (true). Results The gamma indexes in the body for CNN-corrected uncorrected dose against the true dose were 94.95% ± 4.69% and 63.19% ± 3.63%, respectively. The gamma indexes with 2%/2-mm criteria were improved by 10% in most test cases (99.36%). Conclusions Our results suggest that the CNN-based approach can be used to correct the dose-distribution influences with a magnetic field in prostate cancer treatment.

We evaluated four-dimensional cone beam computed tomography (4D-CBCT) ventilation images (VICBCT) acquired with two different linear accelerator systems at various gantry speeds using a deformable lung phantom. The 4D-CT and 4D-CBCT scans were performed using a computed tomography (CT) scanner, an X-ray volume imaging system (Elekta XVI) mounted in Versa HD, and an On-Board Imager (OBI) system mounted in TrueBeam. Intensity-based deformable image registration (DIR) was performed between peak-exhale and peak-inhale images. VICBCT- and 4D-CT-based ventilation images (VICT) were derived by DIR using two metrics: one based on the Jacobian determinant and one on changes in the Hounsfield unit (HU). Three different DIR regularization values (λ) were used for VICBCT. Correlations between the VICBCT and VICT values were evaluated using voxel-wise Spearman’s rank correlation coefficient (r). In case of both metrics, the Jacobian-based VICBCT with a gantry speed of 0.6 deg/sec in Versa HD showed the highest correlation for all the gantry speeds (e.g., λ = 0.05 and r = 0.68). Thus, the r value of the Jacobian-based VICBCT was greater or equal to that of the HU-based VICBCT. In addition, the ventilation accuracy of VICBCT increased at low gantry speeds. Thus, the image quality of VICBCT was affected by the change in gantry speed in both the imaging systems. Additionally, DIR regularization considerably influenced VICBCT in both the imaging systems. Our results have the potential to assist in designing CBCT protocols, incorporating VICBCT imaging into the functional avoidance planning process.

Purpose Radiomics is a new technique that enables noninvasive prognostic prediction by extracting features from medical images. Homology is a concept used in many branches of algebra and topology that can quantify the contact degree. In the present study, we developed homology-based radiomic features to predict the prognosis of non-small-cell lung cancer (NSCLC) patients and then evaluated the accuracy of this prediction method. Methods Four datasets were used: two to provide training and test data and two for the selection of robust radiomic features. All the datasets were downloaded from The Cancer Imaging Archive (TCIA). In two-dimensional cases, the Betti numbers consist of two values: b0 (zero-dimensional Betti number), which is the number of isolated components, and b1 (one-dimensional Betti number), which is the number of one-dimensional or "circular" holes. For homology-based evaluation, computed tomography (CT) images must be converted to binarized images in which each pixel has two possible values: 0 or 1. All CT slices of the gross tumor volume were used for calculating the homology histogram. First, by changing the threshold of the CT value (range: -150 to 300 HU) for all its slices, we developed homology-based histograms for b0 , b1 , and b1 /b0 using binarized images. All histograms were then summed, and the summed histogram was normalized by the number of slices. 144 homology-based radiomic features were defined from the histogram. To compare the standard radiomic features, 107 radiomic features were calculated using the standard radiomics technique. To clarify the prognostic power, the relationship between the values of the homology-based radiomic features and overall survival was evaluated using LASSO Cox regression model and the Kaplan-Meier method. The retained features with nonzero coefficients calculated by the LASSO Cox regression model were used for fitting the regression model. Moreover, these features were then integrated into a radiomics signature. An individualized rad score was calculated from a linear combination of the selected features, which were weighted by their respective coefficients. Results When the patients in the training and test datasets were stratified into high-risk and low-risk groups according to the rad scores, the overall survival of the groups was significantly different. The C-index values for the homology-based features (rad score), standard features (rad score), and tumor size were 0.625, 0.603, and 0.607, respectively, for the training datasets and 0.689, 0.668, and 0.667 for the test datasets. This result showed that homology-based radiomic features had slightly higher prediction power than the standard radiomic features. Conclusions Prediction performance using homology-based radiomic features had a comparable or slightly higher prediction power than standard radiomic features. These findings suggest that homology-based radiomic features may have great potential for improving the prognostic prediction accuracy of CT-based radiomics. In this result, it is noteworthy that there are some limitations.

To evaluate the accuracy of electron transport in the magnetic field of Electron Gamma Shower version 5 (EGS5) by using the special Fano cavity test.To simulate electron transport in the magnetic field, the trajectory of the electron was reconstructed with a short step length to restrict fractional energy loss, and the maximum user step length (mxustep) was set at 0.01 cm or 0.001 cm. For the special Fano cavity test, three-layer slab Fano test geometry was used, and uniform and isotropic per unit mass mono-energetic electrons with 0.01, 0.1, 1.0, and 10 MeV were permitted from the central axis of geometry in 0.35 T and 1.5 T. Furthermore, the magnetic field strength was scaled based on the mass density of the material. The relative difference between the calculated dose to gap and the theoretical value was evaluated. Furthermore, the special Fano cavity test was also performed using EGSnrc with the electron-enhanced electric and magnetic field macros under the same conditions, and the results were compared with those of EGS5.Deviations in 0.35 T were within 0.3% regardless of the parameter settings. In 1.5 T, stable results within 0.3% were obtained using 0.001 cm as the mxustep, except for one at 10 MeV. Further, the accuracy of EGSnrc was within 0.2%, except for 10 MeV for a 0.2-cm gap in 1.5 T.EGS5 with the appropriate parameter settings enable electron transport in magnetic fields similar with the accuracy of EGSnrc.

The purpose of the study was to compare a 3D convolutional neural network (CNN) with the conventional machine learning method for predicting intensity-modulated radiation therapy (IMRT) dose distribution using only contours in prostate cancer. In this study, which included 95 IMRT-treated prostate cancer patients with available dose distributions and contours for planning target volume (PTVs) and organs at risk (OARs), a supervised-learning approach was used for training, where the dose for a voxel set in the dataset was defined as the label. The adaptive moment estimation algorithm was employed for optimizing a 3D U-net similar network. Eighty cases were used for the training and validation set in 5-fold cross-validation, and the remaining 15 cases were used as the test set. The predicted dose distributions were compared with the clinical dose distributions, and the model performance was evaluated by comparison with RapidPlan™. Dose–volume histogram (DVH) parameters were calculated for each contour as evaluation indexes. The mean absolute errors (MAE) with one standard deviation (1SD) between the clinical and CNN-predicted doses were 1.10% ± 0.64%, 2.50% ± 1.17%, 2.04% ± 1.40%, and 2.08% ± 1.99% for D2, D98 in PTV-1 and V65 in rectum and V65 in bladder, respectively, whereas the MAEs with 1SD between the clinical and the RapidPlan™-generated doses were 1.01% ± 0.66%, 2.15% ± 1.25%, 5.34% ± 2.13% and 3.04% ± 1.79%, respectively. Our CNN model could predict dose distributions that were superior or comparable with that generated by RapidPlan™, suggesting the potential of CNN in dose distribution prediction.

We assessed the accuracy of deformable image registration (DIR) accuracy between CT and MR images using an open-source software (Elastix, from Utrecht Medical Center) and a commercial software (Velocity AI Ver. 3.2.0 from Varian Medical Systems, Palo Alto, CA, USA) software. Five male patients’ pelvic regions were studied using publicly available CT, T1-weighted (T1w) MR, and T2-weighted (T2w) MR images. In the cost function of the Elastix, we used six DIR parameter settings with different regularization weights (Elastix0, Elastix0.01, Elastix0.1, Elastix1, Elastix10, and Elastix100). We used MR Corrected Deformable algorithm for Velocity AI. The Dice similarity coefficient (DSC) and mean distance to agreement (MDA) for the prostate, bladder, rectum and left and right femoral heads were used to evaluate DIR accuracy. Except for the bladder, most algorithms produced good DSC and MDA results for all organs. In our study, the mean DSCs for the bladder ranged from 0.75 to 0.88 (CT-T1w) and from 0.72 to 0.76 (CT-T2w). Similarly, the mean MDA ranges were 2.4 to 4.9 mm (CT-T1w), 4.6 to 5.3 mm (CT-T2w). For the Elastix, CT-T1w was outperformed CT-T2w for both DSCs and MDAs at Elastix0, Elastix0.01, and Elastix0.1. In the case of Velocity AI, no significant differences in DSC and MDA of all organs were observed. This implied that the DIR accuracy of CT and MR images might differ depending on the sequence used.

We clarified the reconstructed 3D dose difference between two different commercial software programs (Mobius3D v2.0 and PerFRACTION v1.6.4). Five prostate cancer patients treated with IMRT (74 Gy/37 Fr) were studied. Log files and cine EPID images were acquired for each fraction. 3D patient dose was reconstructed using log files (Mobius3D) or log files with EPID imaging (PerFRACTION). The treatment planning dose was re-calculated on homogeneous and heterogeneous phantoms, and log files and cine EPID images were acquired. Measured doses were compared with the reconstructed point doses in the phantom. Next, we compared dosimetric metrics (mean dose for PTV, rectum, and bladder) calculated by Mobius3D and PerFRACTION for all fractions from five patients. Dose difference at isocenter between measurement and reconstructed dose for two software programs was within 3.0% in both homogeneous and heterogeneous phantoms. Moreover, the dose difference was larger using skip arc plan than that using full arc plan, especially for PerFRACTION (e.g., dose difference at isocenter for PerFRACTION: 0.34% for full arc plan vs. -4.50% for skip arc plan in patient 1). For patients, differences in dosimetric parameters were within 1% for almost all fractions. PerFRACTION had wider range of dose difference between first fraction and the other fractions than Mobius3D (e.g., maximum difference: 0.50% for Mobius3D vs. 1.85% for PerFRACTION), possibly because EPID may detect some types of MLC positioning errors such as miscalibration errors or mechanical backlash which cannot be detected by log files, or that EPID data might include image acquisition failure and image noise.

We evaluated dose–volume histogram (DVH) parameters based on deformable image registration (DIR) between brachytherapy (BT) and external beam radiotherapy (EBRT) that included a center-shielded (CS) plan. Eleven cervical cancer patients were treated with BT, and their pelvic and CS EBRT were studied. Planning CT images for EBRT and BT (except for the first BT, used as the reference image) were deformed with DIR to reference image. We used two DIR parameter settings: intensity-based and hybrid. Mean Dice similarity coefficients (DSCs) comparing EBRT with the reference for the uterus, rectum and bladder were 0.81, 0.77 and 0.83, respectively, for hybrid DIR and 0.47, 0.37 and 0.42, respectively, for intensity-based DIR (P

We evaluated an anthropomorphic head and neck phantom with tissue heterogeneity, produced using a personal 3D printer, with quality assurance (QA), specific to patients undergoing intensity-modulated radiation therapy (IMRT). Using semi-automatic segmentation, 3D models of bone, soft tissue, and an air-filled cavity were created based on computed tomography (CT) images from patients with head and neck cancer treated with IMRT. For the 3D printer settings, polylactide was used for soft tissue with 100% infill. Bone was reproduced by pouring plaster into the cavity created by the 3D printer. The average CT values for soft tissue and bone were 13.0 ± 144.3 HU and 439.5 ± 137.0 HU, respectively, for the phantom and 12.1 ± 124.5 HU and 771.5 ± 405.3 HU, respectively, for the patient. The gamma passing rate (3%/3 mm) was 96.1% for a nine-field IMRT plan. Thus, this phantom may be used instead of a standard shape phantom for patient-specific QA in IMRT.

Recently, several institutions have been developing magnetic resonance imaging (MRI)-guided radiotherapy treatment systems. In this study, we examine whether it is possible to perform radiation therapy planning (RTP) using a magnetic susceptibility map obtained using MRI. The head of a healthy volunteer was scanned using dual-energy computed tomography (CT) and MRI. A T2-star-weighted 3D gradient echo-based sequence (GRE) with images taken at four different echo times was acquired using the MRI scanner. The CT images were converted to relative electron density (rED) using a predefined ΔCT-rED conversion table. ΔCT was derived using the energy-subtraction method. The rED map was obtained from a single-linear relationship with the ΔCT-rED conversion table, whereas the magnetic susceptibility map was obtained from quantitative susceptibility mapping (QSM) via MRI. Subsequently, to obtain the relationship between the magnetic susceptibility and the rED, the rED map was rigidly aligned to the susceptibility map and resampled at the susceptibility map’s resolution. Finally, the magnetic susceptibility rED conversion table was obtained via voxel-by-voxel mapping between the two maps. No strong relationship between magnetic susceptibility and rED was obtained in the healthy volunteer’s head or in this study. The coefficient correlation between these parameters was 0.0145. Magnetic susceptibility values may be not able to convert to rED using our proposed method in healthy volunteer’s head. In contrast to the magnetic-susceptibility values obtained from the QSM algorithm, which were strongly affected by calcification and iron content, the rED or CT number was not considerably affected by such materials.

Purpose To evaluate four-dimensional computed tomography (4D-CT)-derived pulmonary ventilation by comparing with 81m Kr-gas ventilation (V RI ). We also proposed two methods to improve the functional accuracy of 4D-CT ventilation images and evaluated these methods. Methods and materials Eleven lung cancer patients with 4D-CT and V RI were analyzed. Hounsfield unit-based (V HU ) and a Jacobian-based (V Jac ) 4D-CT ventilation images were calculated. They were evaluated by voxel-by-voxel spearman's rank correlation coefficient ( r ) between 4D-CT ventilation and V RI images. After applying an averaging ventilation method and a slope calculating method, correlations were also calculated. Results 4D-CT ventilation showed the high correlation to V RI ( r =0.875 with V HU ). An averaging method brought significantly higher ( p =0.012) correlations to nuclear medicine images with V HU . The improvement was not significant ( p =0.619) with V Jac . Slope calculating method improved the correlation with V HU and slightly worsened the correlation with V Jac . Conclusions The averaging method we proposed might be useful to improve 4D-CT ventilation images. We found good agreement between 4D-CT ventilation and nuclear medicine ventilation, indicating the high physiologic accuracy of 4D-CT ventilation.

Robust feature selection in radiomic analysis is often implemented using the RIDER test-retest datasets. However, the CT Protocol between the facility and test-retest datasets are different. Therefore, we investigated possibility to select robust features using thoracic four-dimensional CT (4D-CT) scans that are available from patients receiving radiation therapy. In 4D-CT datasets of 14 lung cancer patients who underwent stereotactic body radiotherapy (SBRT) and 14 test-retest datasets of non-small cell lung cancer (NSCLC), 1170 radiomic features (shape: n = 16, statistics: n = 32, texture: n = 1122) were extracted. A concordance correlation coefficient (CCC) > 0.85 was used to select robust features. We compared the robust features in various 4D-CT group with those in test-retest. The total number of robust features was a range between 846/1170 (72%) and 970/1170 (83%) in all 4D-CT groups with three breathing phases (40%–60%); however, that was a range between 44/1170 (4%) and 476/1170 (41%) in all 4D-CT groups with 10 breathing phases. In test-retest, the total number of robust features was 967/1170 (83%); thus, the number of robust features in 4D-CT was almost equal to that in test-retest by using 40–60% breathing phases. In 4D-CT, respiratory motion is a factor that greatly affects the robustness of features, thus by using only 40–60% breathing phases, excessive dimension reduction will be able to be prevented in any 4D-CT datasets, and select robust features suitable for CT protocol of your own facility.

Purpose The purpose of this study was to clarify the dosimetric impact of 4-dimensional computed tomography (4D-CT)-derived, ventilation-guided functional avoidance for stereotactic body radiation therapy (SBRT) with 3-dimensional conformal radiation therapy. Methods and materials Eleven lung cancer patients with peripheral tumors no greater than 5 cm in size were studied (average planning target volume, 42.4 ± 32.5 cm3). Four-dimensional-CT ventilation imaging was performed using deformable image registration for spatial mapping of the peak-exhale 4D-CT image to the peak-inhale 4D-CT image and computation of the Jacobian-based ventilation metric. For each patient, anatomical and functional plans were created using 7 to 9 noncoplanar beams for SBRT (40-56 Gy/4-8 fractions). The anatomical plan was generated without incorporating ventilation information. In the functional plan, functional dose-volume constraints were applied in planning to spare the high-functional lung that was defined as the 90th percentile functional volume. The beam directions of the 2 plans were automatically determined by beam angle optimization. Results The percentage of volume receiving a dose of ≥5 Gy (V5), V10, V20, and mean dose to the high-functional lung were 20.5%, 15.6%, 7.8%, and 4.6 Gy, respectively, for the anatomical plan, whereas they were 12.3%, 8.2%, 4.6%, and 3.2 Gy, respectively, for the functional plan. No significant differences in minimum dose, maximum dose, and conformity index of the planning target volume and in all dosimetric parameters for normal tissues between the anatomical and functional plans were seen. Conclusions We compared anatomical and functional plans for SBRT with 3-dimensional conformal radiation therapy for the first time. Our results demonstrated that a functional plan for SBRT reduced the dose in the high-functional regions without a significant change in the total lung or planning target volume even if the radiation technique cannot modulate beam intensity. Thus, this technique can be safely used in functional planning for SBRT.

The respiratory cycle is not strictly regular, and generally varies in amplitude and period from one cycle to the next. We evaluated the characteristics of respiratory patterns acquired during respiratory gating treatment in more than 300 patients. A total 331 patients treated with respiratory-gated carbon-ion beam therapy were selected from a group of patients with thoracic and abdominal conditions. Respiratory data were acquired for a total of 3,171 fractions using an external respiratory sensing monitor and evaluated for respiratory cycle, duty cycle, magnitude of baseline drift, and intrafractional/interfractional peak inhalation/exhalation positional variation. Results for the treated anatomical sites and patient positioning were compared. Mean ± SD res piratory cycle averaged over all patients was 4.1 ± 1.3 s. Mean ± SD duty cycle averaged over all patients was 36.5 ± 7.3 %. Two types of baseline drift were seen, the first decremental and the second incremental. For respiratory peak variation, the mean intrafractional variation in peak-inhalation position relative to the amplitude in the first respiratory cycle (15.5 ± 9.3 %) was significantly larger than that in exhalation (7.5 ± 4.6 %). Interfractional variations in inhalation (17.2 ± 18.5 %) were also significantly greater than those in exhalation (9.4 ± 10.0 %). Statistically significant differences were observed between patients in the supine position and those in the prone position in mean respiratory cycle, duty cycle, and intra-/interfractional variations. We quantified the characteristics of the respiratory curve based on a large number of respiratory data obtained during treatment. These results might be useful in improving the accuracy of respiratory-gated treatment.

Deformable image registration (DIR) is fundamental technique for adaptive radiotherapy and image-guided radiotherapy. However, further improvement of DIR is still needed. We evaluated the accuracy of B-spline transformation-based DIR implemented in elastix. This registration package is largely based on the Insight Segmentation and Registration Toolkit (ITK), and several new functions were implemented to achieve high DIR accuracy. The purpose of this study was to clarify whether new functions implemented in elastix are useful for improving DIR accuracy. Thoracic 4D computed tomography images of ten patients with esophageal or lung cancer were studied. Datasets for these patients were provided by DIR-lab (dir-lab.com) and included a coordinate list of anatomical landmarks that had been manually identified. DIR between peak-inhale and peak-exhale images was performed with four types of parameter settings. The first one represents original ITK (Parameter 1). The second employs the new function of elastix (Parameter 2), and the third was created to verify whether new functions improve DIR accuracy while keeping computational time (Parameter 3). The last one partially employs a new function (Parameter 4). Registration errors for these parameter settings were calculated using the manually determined landmark pairs. 3D registration errors with standard deviation over all cases were 1.78 (1.57), 1.28 (1.10), 1.44 (1.09) and 1.36 (1.35) mm for Parameter 1, 2, 3 and 4, respectively, indicating that the new functions are useful for improving DIR accuracy, even while maintaining the computational time, and this B-spline-based DIR could be used clinically to achieve high-accuracy adaptive radiotherapy.

Purpose The purpose of this study was to estimate the accuracy of the dose calculation of On-Board Imager (Varian, Palo Alto, CA) cone beam computed tomography (CBCT) with deformable image registration (DIR), using the multilevel-threshold (MLT) algorithm and histogram matching (HM) algorithm in pelvic radiation therapy. Methods and Materials One pelvis phantom and 10 patients with prostate cancer treated with intensity modulated radiation therapy were studied. To minimize the effect of organ deformation and different Hounsfield unit values between planning CT (PCT) and CBCT, we modified CBCT (mCBCT) with DIR by using the MLT (mCBCT MLT ) and HM (mCBCT HM ) algorithms. To evaluate the accuracy of the dose calculation, we compared dose differences in dosimetric parameters (mean dose [D mean ], minimum dose [D min ], and maximum dose [D max ]) for planning target volume, rectum, and bladder between PCT (reference) and CBCTs or mCBCTs. Furthermore, we investigated the effect of organ deformation compared with DIR and rigid registration (RR). We determined whether dose differences between PCT and mCBCTs were significantly lower than in CBCT by using Student t test. Results For patients, the average dose differences in all dosimetric parameters of CBCT with DIR were smaller than those of CBCT with RR (eg, rectum; 0.54% for DIR vs 1.24% for RR). For the mCBCTs with DIR, the average dose differences in all dosimetric parameters were less than 1.0%. Conclusions We evaluated the accuracy of the dose calculation in CBCT, mCBCT MLT , and mCBCT HM with DIR for 10 patients. The results showed that dose differences in D mean , D min , and D max in mCBCTs were within 1%, which were significantly better than those in CBCT, especially for the rectum ( P MLT and mCBCT HM can be useful for improving the dose calculation for adaptive radiation therapy.

We evaluated the accuracy of one commercially available and three publicly available deformable image registration (DIR) algorithms for thoracic four-dimensional (4D) computed tomography (CT) images. Five patients with esophagus cancer were studied. Datasets of the five patients were provided by DIR-lab (dir-lab.com) and consisted of thoracic 4D CT images and a coordinate list of anatomical landmarks that had been manually identified. Expert landmark correspondence was used for evaluating DIR spatial accuracy. First, the manually measured displacement vector field (mDVF) was obtained from the coordinate list of anatomical landmarks. Then the automatically calculated displacement vector field (aDVF) was calculated by using the following four DIR algorithms: B-spine implemented in Velocity AI (Velocity Medical, Atlanta, GA, USA), free-form deformation (FFD), Horn–Schunk optical flow (OF) and Demons in DIRART of MATLAB software. Registration error is defined as the difference between mDVF and aDVF. The mean 3D registration errors were 2.7 ± 0.8 mm for B-spline, 3.6 ± 1.0 mm for FFD, 2.4 ± 0.9 mm for OF and 2.4 ± 1.2 mm for Demons. The results showed that reasonable accuracy was achieved in B-spline, OF and Demons, and that these algorithms have the potential to be used for 4D dose calculation, automatic image segmentation and 4D CT ventilation imaging in patients with thoracic cancer. However, for all algorithms, the accuracy might be improved by using the optimized parameter setting. Furthermore, for B-spline in Velocity AI, the 3D registration error was small with displacements of less than ∼10 mm, indicating that this software may be useful in this range of displacements.

This study aimed to evaluate the performance of the hybrid deformable image registration (DIR) method in comparison with intensity-based DIR for pelvic cone-beam computed tomography (CBCT) images, using intensity and anatomical information. Ten prostate cancer patients treated with intensity-modulated radiation therapy (IMRT) were studied. Nine or ten CBCT scans were performed for each patient. First, rigid registration was performed between the planning CT and all CBCT images using gold fiducial markers, and then DIR was performed. The Dice similarity coefficient (DSC) and center of mass (COM) displacement were used to evaluate the quantitative DIR accuracy. The average DSCs for intensity-based DIR for the prostate, rectum, bladder, and seminal vesicles were 0.84 ± 0.05, 0.75 ± 0.05, 0.69 ± 0.07 and 0.65 ± 0.11, respectively, whereas those values for hybrid DIR were 0.98 ± 0.00, 0.97 ± 0.01, 0.98 ± 0.00 and 0.94 ± 0.03, respectively (P

Purpose: A radiophotoluminescent glass rod dosimeter (RGD) has recently become commercially available. It is being increasingly used for dosimetry in radiotherapy to measure the absorbed dose including scattered low-energy photons on the body surface of a patient and for postal dosimetry audit. In this article, the dosimetric properties of the RGD, including energy dependence of the dose response, reproducibly, variation in data obtained by the RGD for each energy, and angular dependence in low-energy photons, are discussed. Methods: An RGD (GD-301, Asahi Techno Glass Corporation, Shizuoka, Japan) was irradiated with monochromatic low-energy photon beams generated by synchrotron radiation at Photon Factory, High Energy Accelerator Research Organization (KEK). The size of GD-301 was 1.5 mm in diameter and 8.5 mm in length and the active dose readout volume being 1 mm diameter and 0.6 mm depth located 0.7 mm from the end of the detector. The energy dependence of the dose response and reproducibility and variation were investigated for RGDs irradiated with a plastic holder and those irradiated without the plastic holder. Response of the RGD was obtained by not only conventional single field irradiation but also bilateral irradiation. Angular dependence of the RGD was measured in the range of 0°–90° for 13, 17, 40, and 80 keV photon beams by conventional single field irradiation. Results: The dose responses had a peak at around 40 keV. For the energy range of less than 25 keV, all dose response curves steeply decreased in comparison with the ratio of mass energy absorption coefficient of the RGD to that of air. As for the reproducibility and variation in data obtained by the RGD, the coefficient of variance increased with decrease in photon energy. Furthermore, the variation for bilateral irradiation was less than that for single field irradiation. Regarding angular dependence of the RGD, for energies of 13 and 17 keV, the response decreased with increase in the irradiation angle, and the minimum values were 93.5% and 86%, respectively. Conclusions: Our results showed the dosimetric properties of the RGD, including the energy dependence of the dose response, reproducibly, variation, and angular dependence in low-energy photons and suggest that the accuracy of the absorbed dose in low-energy photons is affected by the readout method and the distribution of radiophotoluminescence centers in the RGD.

金沢大学医薬保健研究域保健学系, Real-time tumor tracking in external radiotherapy can be achieved by diagnostic (kV) X-ray imaging with a dynamic flat-panel detector (FPD). The purpose of this study was to address image lag in target tracking and its influence on the accuracy of tumor tracking. Fluoroscopic images were obtained using a direct type of dynamic FPD. Image lag properties were measured without test devices according to IEC 62220-1. Modulation transfer function (MTF) and profile curves were measured on the edges of a moving tungsten plate at movement rate of 10 and 20 mm/s, covering lung tumor movement of normal breathing. A lung tumor and metal sphere with blurred edge due to image lag was simulated using the results and then superimposed on breathing chest radiographs of a patient. The moving target with and without image lag was traced using a template-matching technique. In the results, the image lag for the first frame after X-ray cutoff was 2.0% and decreased to less than 0.1% in the fifth frame. In the measurement of profile curves on the edges of static and moving tungsten material plates, the effect of image lag was seen as blurred edges of the plate. The blurred edges of a moving target were indicated as reduction of MTF. However, the target could be traced within an error of ± 5 mm. The results indicated that there was no effect of image lag on target tracking in usual breathing speed in a radiotherapy situation.

We construct numerically the minimal surface in AdS spacetime surrounded by the light-like segments, which are dual to the 4, 6 and 8-point gluon scattering amplitudes in N = 4 super-Yang–Mills theory. We evaluate the area of the minimal surface in the radial cut-off regularization and compare these areas with the formula conjectured by Bern, Dixon and Smirnov (BDS), which is modified by the remainder function of cross-ratios of external momenta for n ( ⩾ 6 ) -point amplitudes. In our momentum configuration cross-ratios are constant. We calculate the difference of areas with different conformal boost parameters, which is independent of the remainder function, and find that its dependence on the boost parameter is numerically consistent with the BDS formula.

The aim of this study was to determine whether metabolic tumor volume (MTV) and total lesion glycolysis (TLG) are associated with outcomes in Stage I lung cancer patients treated with stereotactic body radiation therapy (SBRT). Thirty-eight patients underwent [18F] fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) within 60 days before SBRT at our institution between January 2001 and December 2011. The maximum standardized uptake value (SUVmax), MTV2, MTV4, MTV6, TLG40%, TLG50% and TLG60% were calculated. Prognostic factors for overall survival (OS) and local control (LC) were analyzed using Cox's proportional hazards model, and survival curves were calculated using the Kaplan–Meier method. Receiver operating characteristics (ROC) curves of PET parameters for OS and LC were calculated. The median follow-up period for survivors was 37.7 months. Three-year OS and LC rates were 56.4% and 70.5%, respectively, and 5-year OS and LC rates were 36.8% and 70.5%, respectively. In univariate analyses, tumor diameter (P = 0.019), single dose ≥10 Gy (P = 0.017), MTV2 (P = 0.030) and MTV4 (P = 0.048) were significant predictors for OS. Tumor diameter (P

Irregular breathing can influence the outcome of four-dimensional computed tomography imaging for causing artifacts. Audio-visual biofeedback systems associated with patient-specific guiding waveform are known to reduce respiratory irregularities. In Japan, abdomen and chest motion selfcontrol devices (Abches), representing simpler visual coaching techniques without guiding waveform are used instead; however, no studies have compared these two systems to date. Here, we evaluate the effectiveness of respiratory coaching to reduce respiratory irregularities by comparing two respiratory management systems. We collected data from eleven healthy volunteers. Bar and wave models were used as audio-visual biofeedback systems. Abches consisted of a respiratory indicator indicating the end of each expiration and inspiration motion. Respiratory variations were quantified as root mean squared error (RMSE) of displacement and period of breathing cycles. All coaching techniques improved respiratory variation, compared to free-breathing. Displacement RMSEs were 1.43 ± 0.84, 1.22 ± 1.13, 1.21 ± 0.86, and 0.98 ± 0.47 mm for free-breathing, Abches, bar model, and wave model, respectively. Freebreathing and wave model differed significantly (p < 0.05). Period RMSEs were 0.48 ± 0.42, 0.33 ± 0.31, 0.23 ± 0.18, and 0.17 ± 0.05 s for free-breathing, Abches, bar model, and wave model, respectively. For variation in both displacement and period, wave model was superior to free-breathing, bar model, and Abches. The average reduction in displacement and period RMSE compared with wave model were 27% and 47%, respectively. The efficacy of audio-visual biofeedback to reduce respiratory irregularity compared with Abches. Our results showed that audio-visual biofeedback combined with a wave model can potentially provide clinical benefits in respiratory management, although all techniques could reduce respiratory irregularities.

Purpose/Objectives: Substantial cervical body volume reduction (CBVR) occurs during fractionated external beam radiation therapy (EBRT) for head-and-neck cancer (HNC) and could have potential dosimetric influences. This study aims to investigate measurable clinical factors before treatment initiation correlating with CBVR during curative EBRT in HNC patients, and to determine which patients receive the great benefit from routine adaptive radiation therapy (ART). Materials/Methods: Fifty-six patients with oropharyngeal squamous cell carcinoma (OSCC) and 67 patients with hypopharyngeal squamous cell carcinoma (HSCC) had received curative EBRT between 2006 and 2013 were enrolled. For EBRT planning, computed tomography (CT) images were acquired before EBRT initiation and between two to seven weeks after the start of EBRT for replanning in each patient. A MATLAB program was used to evaluate the CBVR rate (CBVRR) between the initial and replanning CT imaging. The following factors were assessed for correlation with CBVRR: the T and N stage, induction and concurrent chemotherapy, the initial gross tumor volume (GTV), the GTV reduction rate (GTVRR) between the initial and replanning CT imaging, the initial body weight (BW) and the BW loss rate (BWLR) during the EBRT course. Results: In the OSCC group, the CBVRR ranged from 1.8 to 17.1% (median, 6.8%). In the HSCC group, the CBVRR ranged from 1.2 to 23.7% (median, 6.5%). In non-parametric univariate analysis, the N3 stage demonstrated a greater trend with the CBVRR than the N2c≥ stage in the HSCC group (p=0.023), whereas marginal inclination (p=0.096) was found in the OSCC group. The CBVRR was substantially related to the GTVRR (p=0.001) in the HSCC group.

Objective: We investigated the effects of partial volume and respiratory motion using a National Electrical Manufacturers Association (NEMA) phantom and proposed a simple method for correction of maximum standardized uptake value (SUVmax) for respiratory motion in early lung cancer. Methods: The maximum recovery coefficient (RC) in static mode were measured using the NEMA phantom and a dynamic moving platform. The phantom on the platform was either at rest or moving sinusoidally along the longitudinal axis of the scanner to simulate respiratory motion. We also calculated estimated RC using our approximation. Results: RC of the sphere of 28mm in diameter decreased from 0.96 to 0.80 and 0.41 with 20 and 50 mm of motion amplitude, respectively. For the sphere of 10 mm in diameter, RC was decreased from 0.40 to 0.18 and 0.08 with 20 and 50 mm of motion amplitude, respectively. Our results showed that RC decreased with increase in motion amplitude. Average percentage differences between measurement and estimation in the sphere of 37, 28, 22, 17, 13 and 10 mm were -1.8 ± 3.7, -3.1 ± 11.3, -2.8 ± 10.5, -8.1 ± 6.6, -7.0 ± 12.3 and -1.8 ± 12.2 %, respectively. This result showed that our simple correction method could estimate SUVmax with moderate accuracy. Conclusions: Our results clearly demonstrated that RC decreases with increase in motion amplitude, as expected. Our simple correction with moderate accuracy method could not precisely estimate RC. However, the estimated values agreed with the measurements. Thus, our methods could be used in clinical practice to calculate the approximate SUVmax for lung cancer patients undergoing radiotherapy showing the malignancy grading for early lung cancer.

The aim of this study was to quantify the magnitude of intrafractional lung tumor motion under free-breathing conditions with an immobilization device using four-dimensional computed tomography (4DCT). 4DCT data sets were acquired for 17 patients with lung tumors receiving carbon ion beam therapy. A single respiratory cycle was subdivided into 10 phases, and intrafractional tumor motion was calculated by identifying the gross tumor volume (GTV) center of mass (COM) in two scenarios; respiratory-ungated and -gated treatments, which were based on a whole respiratory cycle and a 30% duty cycle around peak exhalation, respectively. For the respiratory-ungated case, the mean (± standard deviation) GTV-COM dis-placements from the peak exhalation position over the 17 patients were 0.6 (± 0.8) / 0.9 (± 1.2) mm, 2.0 (± 1.4) / 0.4 (± 0.7) mm, and 0.2 (± 0.5) / 7.8 (± 6.9) mm in left/right, anterior/posterior and superior/infe-rior directions, respectively, while these were reduced for the respiratory-gated case to 0.3 (± 0.4) / 0.4 (±0.6) mm (left/right), 0.8 (± 0.7) / 0.3 (± 0.5) mm (anterior/posterior), and 0.1 (± 0.2) / 2.8 (± 2.9) mm (superior/inferior). Quantitative analysis of tumor motion with immobilization is valuable not only for par-ticle beam therapy but also for photon beam therapy.

Purpose We compared four-dimensional (4D) layer-stacking and conventional carbon ion beam distribution in the treatment of lung cancer between ungated and gated respiratory strategies using 4DCT data sets. Methods and Materials Twenty lung patients underwent 4DCT imaging under free-breathing conditions. Using planning target volumes (PTVs) at respective respiratory phases, two types of compensating bolus were designed, a full single respiratory cycle for the ungated strategy and an approximately 30% duty cycle for the exhalation-gated strategy. Beams were delivered to the PTVs for the ungated and gated strategies, PTV(ungated) and PTV(gated), respectively, which were calculated by combining the respective PTV(Tn)s by layer-stacking and conventional irradiation. Carbon ion beam dose distribution was calculated as a function of respiratory phase by applying a compensating bolus to 4DCT. Accumulated dose distributions were calculated by applying deformable registration. Results With the ungated strategy, accumulated dose distributions were satisfactorily provided to the PTV, with D95 values for layer-stacking and conventional irradiation of 94.0% and 96.2%, respectively. V20 for the lung and Dmax for the spinal cord were lower with layer-stacking than with conventional irradiation, whereas Dmax for the skin (14.1 GyE) was significantly lower (21.9 GyE). In addition, dose conformation to the GTV/PTV with layer-stacking irradiation was better with the gated than with the ungated strategy. Conclusions Gated layer-stacking irradiation allows the delivery of a carbon ion beam to a moving target without significant degradation of dose conformity or the development of hot spots.

We have developed new design algorithms for compensating boli to facilitate the implementation of four-dimensional charged-particle lung therapy in clinical applications. Four-dimensional CT (4DCT) data for eight lung cancer patients were acquired with a 16-slice CT under free breathing. Six compensating boli were developed that may be categorized into three classes: (1) boli-based on contoured gross tumor volumes (GTV) from a 4DCT data set during each respiratory phase, subsequently combined into one (GTV-4DCT bolus); (2) boli-based on contoured internal target volume (ITV) from image-processed 3DCT data only [temporal-maximum-intensity-projection (TMIP)/temporal-average-intensity-projection (TAIP)] with calculated boli (ITV-TMIP and ITV-TAIP boli); and (3) boli-based on contoured ITV utilizing image-processed 3DCT data, applied to 4DCT for design of boli for each phase, which were then combined. The carbon beam dose distribution within each bolus was calculated as a function of time and compared to plans in which respiratory-ungated/gated strategies were used. The GTV-4DCT treatment plan required a prohibitively long time for contouring the GTV manually for each respiratory phase, but it delivered more than 95% of the prescribed dose to the target volume. The TMIP and TAIP treatments, although more time-efficient, resulted in an unacceptable excess dose to normal tissues and underdosing of the target volume. The dose distribution for the ITV-4DCT bolus was similar to that for the GTV-4DCT bolus and required significantly less practitioner time. The ITV-4DCT bolus treatment plan is time-efficient and provides a high-quality dose distribution, making it a practical alternative to the GTV-4DCT bolus treatment plan.

We use the AdS/CFT prescription of Alday and Maldacena \cite{am} to analyze gluon 6-point scattering amplitudes at strong coupling in ${\cal N}=4$ SYM. By cutting and gluing we obtain AdS 6-point amplitudes that contain extra boundary conditions and come close to matching the field theory results. We interpret them as parts of the field theory amplitudes, containing only certain diagrams. We also analyze the collinear limits of 6- and 5-point amplitudes and discuss the results., 35 pages, 7 figures, latex, references added

The holographic principle in the pp-wave limit proposed in our previous works is further confirmed by studying impurity non-preserving processes which contain a fermionic BMN operator with one scalar and one fermion impurities. We show that the previously proposed duality relation between the matrix elements of the three point interaction Hamiltonian in the holographic string field theory and the OPE coefficients in super Yang-Mills theory holds to the leading order in the large $\mu$ limit. Operator mixing is required to obtain the BMN operator of definite conformal dimension which corresponds to the string state with one scalar and one fermion excitations. The mixing term plays a crucial role for our duality relation to be valid. Our results, combined with those in the previous papers, provide a positive support that our duality relation holds for the general process regardless of the kind of impurities and of whether impurities conserve or not., Comment: 44 pages, 6 figures

As a continuation of our previous works studying the holographic principle in the plane-wave limit, we discuss the 3-point correlation functions of BMN operators with bosonic excitations when impurities are not conserved. We show that our proposal for a holographic mapping between the conformal OPE coefficients of super Yang-Mills theory and the 3-point vertex of the holographic string field theory is valid to the leading order in the large $\mu$ limit. Our results provide for the first time a direct holographic relation for the 3-point correlators of BMN operators including impurity non-preserving processes., Comment: 35 pages, 5 figurs, corrected minor typos, the version to be published in Nucl. Phys. B

The issue of holographic mapping between bulk and boundary in the plane-wave limit of AdS/SYM correspondence is reexamined from the viewpoint of correlation functions. We first study the limit of large angular momentum for the so-called GKP-W relation in supergeravity approximation, connecting directly the effective action in the bulk and the generating functional of correlation functions on the boundary. The spacetime tunneling picture which has been proposed in our previous works naturally emerges. This gives not only a justification of our previous proposal, with some important refinements, on the mapping between bulk effective interaction and the CFT coefficients on the boundary in the plane-wave limit, but also implies various insights on the interpretation of holography in the plane-wave limit. Based on this result, we construct a new `holographic' string field theory. We confirm for several nontrivial examples that this gives the CFT coefficients derived by perturbation theory on the gauge-theory side. Our results are useful for understanding how apparently different duality maps proposed from different standpoints are consistent with each other and with our definite spacetime picture for the AdS holography in the plane-wave limit., Comment: corrected typos, 57 pages

There is a concern that image lag may reduce accuracy of real-time target tracking in radiotherapy. This study was performed to investigate influence of image lag on the accuracy of target tracking in radiotherapy. Fluoroscopic images were obtained using a direct type of dynamic flat-panel detector (FPD) system under conditions of target tracking during radiotherapy. The images continued to be read out after X-irradiations and cutoff, and image lag properties in the system were then determined. Subsequently, a tungsten materials plate with a precision edge was mounted on to a motor control device, which provided a constant velocity. The plate was moved into the center of the detector at movement rate of 10 and 20 mm/s, covering lung tumor movement of normal breathing, and MTF and profile curves were measured on the edges covering and uncovering the detector. A lung tumor with blurred edge due to image lag was simulated using the results and then superimposed on breathing chest radiographs of a patient. The moving target with and without image lag was traced using a template-matching technique. In the results, the target could be traced within a margin for error in external radiotherapy. The results indicated that there was no effect of image lag on target tracking in usual breathing speed in a radiotherapy situation. Further studies are required to investigate influence by the other factors, such as exposure dose, target size and shape, imaging rate, and thickness of a patient's body.

We study gluon scattering amplitudes in N=4 super Yang-Mills theory at strong coupling via the AdS/CFT correspondence. We solve numerically the discretized Euler-Lagrange equations on the square worldsheet for the minimal surface with light-like boundaries in AdS spacetime. We evaluate the area of the surface for the 4, 6 and 8-point amplitudes using worldsheet and radial cut-off regularizations. Their infrared singularities in the cut-off regularization are found to agree with the analytical results near the cusp less than 5% at 520x520 lattice points., Comment: Latex, 23 pages, 19 figures