Radiation Oncologists' Views on Adjuvant Radiotherapy for Early-Stage Breast Cancer in the Elderly: Comparisons between Japan and the United States.

PURPOSE: To understand perspective on breast cancer using a survey. MATERIALS & METHODS: Questionnaire was distributed to 304 Japanese radiation oncologists (RadOncs) (response rate: 64.1%). Result was compared with a similar US survey. RESULTS: In a scenario with an 81-year-old patient with comorbidities, while most US RadOncs chose to tell that radiation might not be necessary, 2% of Japanese chose it. In a scenario with a healthy 65-year-old breast cancer patient with lumpectomy, while most US RadOncs chose to discuss omission of radiation, 24.5% of Japanese chose it. CONCLUSIONS: Differences were observed on radiotherapy for older early-stage breast cancer.

Reducing image artifacts in sparse projection CT using conditional generative adversarial networks.

Reducing the amount of projection data in computed tomography (CT), specifically sparse-view CT, can reduce exposure dose; however, image artifacts can occur. We quantitatively evaluated the effects of conditional generative adversarial networks (CGAN) on image quality restoration for sparse-view CT using simulated sparse projection images and compared them with autoencoder (AE) and U-Net models. The AE, U-Net, and CGAN models were trained using pairs of artifacts and original images; 90% of patient cases were used for training and the remaining for evaluation. Restoration of CT values was evaluated using mean error (ME) and mean absolute error (MAE). The image quality was evaluated using structural image similarity (SSIM) and peak signal-to-noise ratio (PSNR). Image quality improved in all sparse projection data; however, slight deformation in tumor and spine regions was observed, with a dispersed projection of over 5°. Some hallucination regions were observed in the CGAN results. Image resolution decreased, and blurring occurred in AE and U-Net; therefore, large deviations in ME and MAE were observed in lung and air regions, and the SSIM and PSNR results were degraded. The CGAN model achieved accurate CT value restoration and improved SSIM and PSNR compared to AE and U-Net models.

Evaluation of motion artefact reduction depending on the artefacts' directions in head MRI using conditional generative adversarial networks.

Motion artefacts caused by the patient's body movements affect magnetic resonance imaging (MRI) accuracy. This study aimed to compare and evaluate the accuracy of motion artefacts correction using a conditional generative adversarial network (CGAN) with an autoencoder and U-net models. The training dataset consisted of motion artefacts generated through simulations. Motion artefacts occur in the phase encoding direction, which is set to either the horizontal or vertical direction of the image. To create T2-weighted axial images with simulated motion artefacts, 5500 head images were used in each direction. Of these data, 90% were used for training, while the remainder were used for the evaluation of image quality. Moreover, the validation data used in the model training consisted of 10% of the training dataset. The training data were divided into horizontal and vertical directions of motion artefact appearance, and the effect of combining this data with the training dataset was verified. The resulting corrected images were evaluated using structural image similarity (SSIM) and peak signal-to-noise ratio (PSNR), and the metrics were compared with the images without motion artefacts. The best improvements in the SSIM and PSNR were observed in the consistent condition in the direction of the occurrence of motion artefacts in the training and evaluation datasets. However, SSIM > 0.9 and PSNR > 29 dB were accomplished for the learning model with both image directions. The latter model exhibited the highest robustness for actual patient motion in head MRI images. Moreover, the image quality of the corrected image with the CGAN was the closest to that of the original image, while the improvement rates for SSIM and PSNR were approximately 26% and 7.7%, respectively. The CGAN model demonstrated a high image reproducibility, and the most significant model was the consistent condition of the learning model and the direction of the appearance of motion artefacts.

Development of deep-inspiration breath-hold system that monitors the position of the chest wall using infrared rangefinder.

We conducted a prospective study to quantitatively evaluate the movement of the chest wall to establish the simple and reproducible deep-inspiration breath-hold (DIBH) method. The left nipple position was monitored to confirm the inspiratory state. Planning computed tomography (CT) was performed under DIBH and free-breath. We conducted radiation plans with DIBH and free-breath CT and evaluated organ at risk (OAR) and target doses according to two different plans. The relationship between positioning errors of the chest wall and patient factors was evaluated using univariate analysis and fixed-effects models. Twenty-three patients aged ≤ 60 years were enrolled during January-August 2021; 358 daily radiation treatments were evaluated. The median time of treatment room occupancy was 16 minutes (interquartile range, 14-20). The area of the planning target volume (PTV) surrounded by the 95% isodose line was more extensive in DIBH than in free breathing (71.6% vs 69.5%, P < 0.01), whereas the cardiac and left anterior descending (LAD) artery doses were lower (both P < 0.01). In the fixed-effects model analysis, the occupation time of the treatment room was correlated with positioning error. The difference between the planned and irradiated dose was the largest in the LAD branch of the coronary artery (-2.5 Gy), although the OAR dose decreased owing to positional error. The current DIBH method, wherein a single point on the chest wall is monitored to confirm that the patient is in an inspiratory state, allows radiation to be performed in a short time with a small dose error.

Multi-Institutional Study of End-to-End Dose Delivery Quality Assurance Testing for Image-Guided Brachytherapy Using a Gel Dosimeter.

PURPOSE: To quantify dose delivery errors for high-dose-rate image-guided brachytherapy (HDR-IGBT) using an independent end-to-end dose delivery quality assurance test at multiple institutions. The novelty of our study is that this is the first multi-institutional end-to-end dose delivery study in the world. MATERIALS AND METHODS: The postal audit used a polymer gel dosimeter in a cylindrical acrylic container for the afterloading system. Image acquisition using computed tomography, treatment planning, and irradiation were performed at each institution. Dose distribution comparison between the plan and gel measurement was performed. The percentage of pixels satisfying the absolute-dose gamma criterion was reviewed. RESULTS: Thirty-five institutions participated in this study. The dose uncertainty was 3.6% ± 2.3% (mean ± 1.96σ). The geometric uncertainty with a coverage factor of k = 2 was 3.5 mm. The tolerance level was set to the gamma passing rate of 95% with the agreement criterion of 5% (global)/3 mm, which was determined from the uncertainty estimation. The percentage of pixels satisfying the gamma criterion was 90.4% ± 32.2% (mean ± 1.96σ). Sixty-six percent (23/35) of the institutions passed the verification. Of the institutions that failed the verification, 75% (9/12) had incorrect inputs of the offset between the catheter tip and indexer length in treatment planning and 17% (2/12) had incorrect catheter reconstruction in treatment planning. CONCLUSIONS: The methodology should be useful for comprehensively checking the accuracy of HDR-IGBT dose delivery and credentialing clinical studies. The results of our study highlight the high risk of large source positional errors while delivering dose for HDR-IGBT in clinical practices.

A cycle generative adversarial network for improving the quality of four-dimensional cone-beam computed tomography images.

BACKGROUND: Four-dimensional cone-beam computed tomography (4D-CBCT) can visualize moving tumors, thus adaptive radiation therapy (ART) could be improved if 4D-CBCT were used. However, 4D-CBCT images suffer from severe imaging artifacts. The aim of this study is to investigate the use of synthetic 4D-CBCT (sCT) images created by a cycle generative adversarial network (CycleGAN) for ART for lung cancer. METHODS: Unpaired thoracic 4D-CBCT images and four-dimensional multislice computed tomography (4D-MSCT) images of 20 lung-cancer patients were used for training. High-quality sCT lung images generated by the CycleGAN model were tested on another 10 cases. The mean and mean absolute errors were calculated to assess changes in the computed tomography number. The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) were used to compare the sCT and original 4D-CBCT images. Moreover, a volumetric modulation arc therapy plan with a dose of 48 Gy in four fractions was recalculated using the sCT images and compared with ideal dose distributions observed in 4D-MSCT images. RESULTS: The generated sCT images had fewer artifacts, and lung tumor regions were clearly observed in the sCT images. The mean and mean absolute errors were near 0 Hounsfield units in all organ regions. The SSIM and PSNR results were significantly improved in the sCT images by approximately 51% and 18%, respectively. Moreover, the results of gamma analysis were significantly improved; the pass rate reached over 90% in the doses recalculated using the sCT images. Moreover, each organ dose index of the sCT images agreed well with those of the 4D-MSCT images and were within approximately 5%. CONCLUSIONS: The proposed CycleGAN enhances the quality of 4D-CBCT images, making them comparable to 4D-MSCT images. Thus, clinical implementation of sCT-based ART for lung cancer is feasible.

Improving the accuracy of motion quantification using area detector computed tomography for real-time tumor-tracking irradiation in stereotactic ablative radiotherapy.

CyberKnife radiotherapy enables tumor-tracking irradiation using positional information regarding the tumor and a fiducial marker in a patient's body. This positional information acts as a surrogate of tumor motion. Therefore, deviations in these movements should be quantitatively estimated and included as an internal margin for radiation treatment planning. This study aimed to investigate variations between the positions of fiducial markers and tumor regions using 320-row area detector computed tomography and to analyze the effectiveness of our proposed method in contouring tumor regions based on the fiducial marker position. To determine the moving tumor volume, a typical single-phase image was selected, and pixel values in other phase images were accumulated. Moreover, a maximum-intensity projection image was created to clarify motion deviations in the tumor volume. To evaluate the delineation accuracy, the dice similarity coefficient and mean distance to agreement were calculated in phase-selected and breath-holding computed tomography. Moving chest phantom images were acquired using helical scanning 4-dimensional computed tomography (H-4DCT) and volumetric scanning 4-dimensional computed tomography (V-4DCT), and the delineation accuracies were compared for each scanning type. The average dice similarity coefficient and mean distance to agreement were degraded in limited-phase images, which cannot represent the hysteretic motion of a tumor. Moreover, deviations in tumor volume with unstable motion reached 71.6% in H-4DCT but only 1.6% in V-4DCT. Our proposed method with V-4DCT using area detector computed tomography can achieve accurate moving tumor delineation and can clarify positional associations between the fiducial marker and tumor under respiratory motion.

Comparison of Moderate Hypofractionated Volumetric-Modulated Arc Therapy Plans With and Without Flattening Filter for Localized Prostate Cancer.

Background/Aim The aim of this study was to compare volumetric-modulated arc therapy (VMAT) radiation plans between conventional VMAT with flattening filter (cFF-VMAT) and flattening filter-free VMAT (FFF-VMAT) for localized prostate cancer. Materials and methods Ten patients with localized prostate cancer who underwent cFF-VMAT at Yokosuka General Hospital Uwamachi, Yokosuka, Japan, from July 2020 to October 2020 were enrolled. Dose-volume histogram (DVH) parameters of the target volume, normal organs, monitor units (MU), and beam-on time (BOT) were compared between cFF-VMAT and FFF-VMAT plans. Results No significant difference was observed for DVH parameters for the target volume. No significant difference was observed in all parameters for the bladder and rectum between the cFF-VMAT and FFF-VMAT groups. The mean values of MU were 686 ± 52 and 784 ± 80 in cFF-VMAT and FFF-VMAT, respectively (p < 0.001). The mean BOT was 97.0 ± 6.6 s and 72.9 ± 1.4 s for cFF-VMAT and FFF-VMAT, respectively (p < 0.001). Conclusion DVH parameters of the target volume and normal organs were not significantly different between the cFF-VMAT and FFF-VMAT plans. In FFF-VMAT, MU was significantly higher, and the BOT was significantly shorter than those in cFF-VMAT.

Quantitative evaluation of deep convolutional neural network-based image denoising for low-dose computed tomography.

To minimize radiation risk, dose reduction is important in the diagnostic and therapeutic applications of computed tomography (CT). However, image noise degrades image quality owing to the reduced X-ray dose and a possible unacceptably reduced diagnostic performance. Deep learning approaches with convolutional neural networks (CNNs) have been proposed for natural image denoising; however, these approaches might introduce image blurring or loss of original gradients. The aim of this study was to compare the dose-dependent properties of a CNN-based denoising method for low-dose CT with those of other noise-reduction methods on unique CT noise-simulation images. To simulate a low-dose CT image, a Poisson noise distribution was introduced to normal-dose images while convoluting the CT unit-specific modulation transfer function. An abdominal CT of 100 images obtained from a public database was adopted, and simulated dose-reduction images were created from the original dose at equal 10-step dose-reduction intervals with a final dose of 1/100. These images were denoised using the denoising network structure of CNN (DnCNN) as the general CNN model and for transfer learning. To evaluate the image quality, image similarities determined by the structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) were calculated for the denoised images. Significantly better denoising, in terms of SSIM and PSNR, was achieved by the DnCNN than by other image denoising methods, especially at the ultra-low-dose levels used to generate the 10% and 5% dose-equivalent images. Moreover, the developed CNN model can eliminate noise and maintain image sharpness at these dose levels and improve SSIM by approximately 10% from that of the original method. In contrast, under small dose-reduction conditions, this model also led to excessive smoothing of the images. In quantitative evaluations, the CNN denoising method improved the low-dose CT and prevented over-smoothing by tailoring the CNN model.

The effects of rotational setup errors in total body irradiation using helical tomotherapy.

PURPOSE: Helical tomotherapy (HT) is a form of intensity-modulated radiation therapy that is employed in total body irradiation (TBI). Because TBI targets the whole body, accurate setup positioning at the edge of the treatment volume is made difficult by the whole-body rotational posture. The purpose of this study is to clarify the tolerance for rotational setup error (SE) in the vertical direction. In addition, we perform a retrospective analysis of actually irradiated dose distributions using previous patients' irradiation data. METHODS: To clarify the effects of rotational SE on the dose distribution, the planned CT images of 10 patients were rotated by 1-5° in the vertical (pitch) direction to create a pseudo-rotational SE image. Then, the effect of the magnitude of the rotational SE on the dose distribution was simulated. In addition, the irradiated dose to the patients was analyzed by obtaining recalculated dose distributions using megavoltage CT images acquired before treatment. RESULTS: The simulation results showed that the average value of the lung volume receiving at least 10 Gy did not exceed the allowable value when the SE value was ≤2°. When the rotational SE was ≤3°, it was possible to maintain the clinical target volume dose heterogeneity within ±10% of the prescribed dose, which is acceptable according to the guidelines. A retrospective analysis of previous patients' irradiation data showed their daily irradiation dose distribution. The dose to the clinical target volume was reduced by up to 3.4% as a result of the residual rotational SE. Although whole-course retrospective analyses showed a statistically significant increase in high-dose areas, the increase was only approximately 1.0%. CONCLUSIONS: Dose errors induced by rotational SEs of ≤2° were acceptable in this study.

Reducing contrast dose using virtual monoenergetic imaging for aortic CTA.

Three-dimensional computed tomographic angiography (3D-CTA) is widely used to evaluate the inner diameters of vessels and the anatomical vascular structure prior to endoscopic aortic surgery or transcatheter valve implantation. Virtual monoenergetic imaging (VMI) is a new application in dual-energy CT (DECT). We evaluated the potential for contrast dose reduction in preoperative aortic CTA using VMI. To evaluate performance in terms of image quality and vessel shape, we quantified the contrast-to-noise ratio (CNR) and the vessel diameter using a cylinder phantom we developed, and used volume rendering to assess visual quality. All VMI had improved CNR values compared with conventional 120 kVp images at an iodine content of 15 mgI/mL. In each image, a virtual mono-energy of 40 keV yielded the highest CNR value, and an iodine content of 9 mgI/mL was comparable to that of conventional images with an iodine content of 15 mgI/mL. The circularity indices (CI) of the vascular model at 15, 12, and 9 mgI/mL were similar to those of the reference condition using conventional voltages; however, CI was degraded at iodine contents of 6 and 3 mgI/mL with VMI. In the case of iodine content of 15 mgI/mL, VMI was superior, with conventional image by visual evaluation. In the cases of iodine contents of 12 and 9 mgI/mL, image quality was judged to be almost the same level when comparing 12 and 9 mgI/mL to conventional images. In the case of 6 and 3 mgI/mL, reference image using conventional technique was superior to that of VMI. We demonstrated in that decreasing contrast iodine content is possible using VMI with an energy of 40 keV for preoperative aortic 3D-CTA.

Development of a rotational set-up correction device for stereotactic head radiation therapy: A performance evaluation.

We developed a new head supporting device to provide accurate correction of rotational setup during image-guided radiation therapy (IGRT), evaluating its correction performance and the efficacy of dose distribution in stereotactic radiotherapy (SRT) using a helical tomotherapy (HT) system. The accuracy of rotational motion was measured using an electronic inclinometer; we compared device angles and measurement values from 0.0° to 3.0°. The correction accuracy was investigated based on the distance between rotational centers in the device and on megavoltage computed tomography (MVCT); the correction values were compared using distances in the range of 0.0-9.0 cm using a head phantom with a rotational error of 1.5°. For an SRT with a simultaneous integrated boost plan and a rotational error of 3.0° in yaw angle using a head phantom, and for a single-isocenter SRT for multiple brain metastases in the data of three patients, dosimetric efficacy of the HT unit was evaluated for calculated dose distributions with MVCT after rotational correction. This device can correct pitch and yaw angles within 0.3° and can be corrected to within 0.5° for each rotational angle according to the result of MVCT correction regardless of the rotational center position. In the head phantom study, the device had a beneficial impact on rotational correction; D99% for the target improved by approximately 10% with rotational correction. Using patient data with the device, the mean difference based on the treatment planning data was 0.3% for D99% and -0.1% for coverage index to the target. Our rotational setup correction device has high efficacy, and can be used for IGRT.

Patient organ doses from megavoltage computed tomography delivery with a helical tomotherapy unit using a general treatment planning system.

The purpose of this study was to quantify actual patient organ doses from megavoltage computed tomography (MVCT) using an MVCT beam model of a helical tomotherapy unit in a general treatment planning system (TPS). Dosimetric parameters (percentage depth dose, lateral beam profile, and longitudinal beam profile) of the MVCT beam were measured using Gafchromic EBT3 films (ISP Corporation, Wayne, NJ, USA) and used for beam modeling in a Pinnacle3 TPS (Philips, Amsterdam, Netherlands); this TPS is widely used with linear accelerators. The created beam model was adjusted and validated by assessing point doses in a cylindrical phantom in static and helical beam plans with fine, normal and coarse pitches. Maximum doses delivered to important organs from MVCT delivery for five clinical cases were calculated using the created beam model. The difference (average ± one standard deviation for all evaluation points) between calculated and measured doses was -0.69 ± 1.20% in the static beam plan. In the helical beam plan, the differences were 1.83 ± 2.65%, 1.35 ± 5.94% and -0.66 ± 8.48% for fine, normal and coarse pitches, respectively. The average maximum additional dose to important organs from MVCT in clinical cases was 0.82% of the prescribed dose. In conclusion, we investigated a method for quantifying patient organ dose from MVCT delivery on helical tomotherapy using an MVCT beam model in a general TPS. This technique enables estimation of the patient-specific organ dose from MVCT delivery, without the need for additional equipment.

Appropriate treatment planning method for field joint dose in total body irradiation using helical tomotherapy.

Total body irradiation (TBI) using helical tomotherapy (HT) has advantages over the standard linear accelerator-based approach to the conditioning regimen for hematopoietic cell transplantation. However, the radiation field has to be divided into two independent irradiation plans to deliver a homogeneous dose to the whole body. A clinical target volume near the skin increases the skin surface dose; therefore, high- or low-dose regions arise depending on the set-up position accuracy because the two radiation fields are somewhat overlapped or separated. We aimed to determine an adequate treatment planning method robust to the set-up accuracy for the field joint dose distribution using HT-TBI. We calculated treatment plans reducing target volumes at the interface between the upper and lower body irradiations and evaluated these joint dose distributions via simulation and experimental studies. Target volumes used for the optimization calculation were reduced by 0, 0.5, 1.0, 2.0, 2.5, and 3.0 cm from the boundary surface on the upper and lower sides. Combined dose distributions with set-up error simulated by modifying coordinate positions were investigated to find the optimal planning method. In the ideal set-up position, the target volume without a gap area caused field junctional doses of up to approximately 200%; therefore, target volumes reduced by 2.0-3.0 cm could suppress the maximum dose to within 150%. However, with set-up error, high-dose areas exceeding 150% and low-dose areas below 100% were found with 2.0 and 3.0 cm target volume reduction. Using the dynamic jaw (DJ) system, dose deviations caused by set-up error reached approximately 20%, which is not suitable for HT-TBI. Moreover, these dose distributions can be easily adjusted when combined with the intensity modulation technique for field boundary regions. The results of a simulation and experimental study using a film dosimetry were almost identical, which indicated that reducing the target volume at the field boundary surface by 2.5 cm produces the most appropriate target definition.

Effect of region extraction and assigned mass-density values on the accuracy of dose calculation with magnetic resonance-based volumetric arc therapy planning.

This study aimed to verify the validity of generating treatment plans for volumetric arc therapy (VMAT) for prostate cancer using magnetic resonance (MR) imaging with a dose calculation algorithm in Acuros XB (Eclipse version 13.6; Varian Medical Systems, Palo Alto, CA, USA) based on deterministically solving the linear Boltzmann transport equations. Four different classes were applied to prostate MR images: MRW (all water equivalent); MRW+B (water and bone); MRS+B (soft tissue and bone); and MRS+B+G (soft tissue, bone, and rectal gas). Each of these regions was assigned a mass density for calculating doses. The assigned mass-density values were then altered in three ways. Using initial planning and optimization parameters, MR-based VMAT plans were generated and compared with corresponding forward-calculated computed tomography-based plans for doses to the target volumes and organs at risk using dose-volume histograms and γ analyses. In the MRW plans, the mean doses for TVs were overestimated by approximately 1.3%. The MRW+B plans revealed reduced differences within 0.5%. Further segmentation (MRS+B) did not result in substantial improvement. Dose deviations affected by the changes in the mass densities assigned to soft tissue were as small as approximately 1.0%, whereas larger deviations were revealed in bone and rectal gas, especially those with > 5% error. Assignment of accurate mass-density values acquired from MR images is needed for MR-based radiation treatment planning. Multiple MR sequences should be acquired for segmentation and mass-density conversion purposes. Segmented MR-based VMAT planning is feasible with a density assignment method using Acuros XB.

Calculation Accuracy of Gross Tumor Volume at the Diaphragm Boundary Evaluated Using Respiratory-gated PET/CT.

OBJECTIVE: The present study aimed to clarify gross tumor volume (GTV) contouring accuracy at the diaphragm boundary using respiratory-gated PET/CT. METHODS: The lung/diaphragm boundary was simulated using a phantom containing 18F solution (10.6 kBq/mL). Tumors were simulated using spheres (diameter, 11-38 mm) containing 18F and located at the positions of the lungs and liver. The tumor background ratios (TBR) were 2, 4, and 8. The phantom was moved from the superior to inferior direction with a 20-mm motion displacement at 3.6 s intervals. The recovery coefficient (RC), volume RC (VRC), and standardized uptake value (SUV) threshold were calculated using stationary, non-gated (3D), and gated (4D) PET/CT. RESULTS: In lung cancer simulation, RC and VRC in 3D PET images were, respectively, underestimated and overestimated in smaller tumors, whereas both improved in 4D PET images regardless of tumor size and TBR. The optimal SUV threshold was about 30% in 4D PET images. In liver cancer simulation, RC and VRC were, respectively, underestimated and overestimated in smaller tumors, and when the TBR was lower, but both improved in 4D PET images when tumors were >17 mm and the TBR was >4. The optimal SUV threshold tended to depend on the TBR. CONCLUSIONS: The contouring accuracy of GTV was improved by considering TBR and using an optimal SUV threshold acquired from 4D PET images.

Limited Impact of Setup and Range Uncertainties, Breathing Motion, and Interplay Effects in Robustly Optimized Intensity Modulated Proton Therapy for Stage III Non-small Cell Lung Cancer.

PURPOSE: To investigate the impact of setup and range uncertainties, breathing motion, and interplay effects using scanning pencil beams in robustly optimized intensity modulated proton therapy (IMPT) for stage III non-small cell lung cancer (NSCLC). METHODS AND MATERIALS: Three-field IMPT plans were created using a minimax robust optimization technique for 10 NSCLC patients. The plans accounted for 5- or 7-mm setup errors with ±3% range uncertainties. The robustness of the IMPT nominal plans was evaluated considering (1) isotropic 5-mm setup errors with ±3% range uncertainties; (2) breathing motion; (3) interplay effects; and (4) a combination of items 1 and 2. The plans were calculated using 4-dimensional and average intensity projection computed tomography images. The target coverage (TC, volume receiving 95% of prescribed dose) and homogeneity index (D2 - D98, where D2 and D98 are the least doses received by 2% and 98% of the volume) for the internal clinical target volume, and dose indexes for lung, esophagus, heart and spinal cord were compared with that of clinical volumetric modulated arc therapy plans. RESULTS: The TC and homogeneity index for all plans were within clinical limits when considering the breathing motion and interplay effects independently. The setup and range uncertainties had a larger effect when considering their combined effect. The TC decreased to <98% (clinical threshold) in 3 of 10 patients for robust 5-mm evaluations. However, the TC remained >98% for robust 7-mm evaluations for all patients. The organ at risk dose parameters did not significantly vary between the respective robust 5-mm and robust 7-mm evaluations for the 4 error types. Compared with the volumetric modulated arc therapy plans, the IMPT plans showed better target homogeneity and mean lung and heart dose parameters reduced by about 40% and 60%, respectively. CONCLUSIONS: In robustly optimized IMPT for stage III NSCLC, the setup and range uncertainties, breathing motion, and interplay effects have limited impact on target coverage, dose homogeneity, and organ-at-risk dose parameters.

[Impact of the Infrared Monitor Signal Pattern on Accuracy of Target Imaging in 4-dimensional Cone-beam Computed Tomography].

To realize the high precision radiotherapy, localized radiation field of the moving target is very important, and visualization of a temporal location of the target can help to improve the accuracy of the target localization. However, conditions of the breathing and the patient's own motion differ from the situation of the treatment planning. Therefore, positions of the tumor are affected by these changes. In this study, we implemented a method to reconstruct target motions obtained with the 4D CBCT using the sorted projection data according to the phase and displacement of the extracorporeal infrared monitor signal, and evaluated the proposed method with a moving phantom. In this method, motion cycles and positions of the marker were sorted to reconstruct the image, and evaluated the image quality affected by changes in the cycle, phase, and positions of the marker. As a result, we realized the visualization of the moving target using the sorted projection data according to the infrared monitor signal. This method was based on the projection binning, in which the signal of the infrared monitor was surrogate of the tumor motion. Thus, further major efforts are needed to ensure the accuracy of the infrared monitor signal.