Relationship between hydrogel spacer distribution and dosimetric parameters in linear-accelerator-based stereotactic body radiotherapy for prostate cancer.

PURPOSE: To explore the potential of quantitative parameters of the hydrogel spacer distribution as predictors for separating the rectum from the planning target volume (PTV) in linear-accelerator-based stereotactic body radiotherapy (SBRT) for prostate cancer. METHODS: Fifty-five patients underwent insertion of a hydrogel spacer and were divided into groups 1 and 2 of the PTV separated from and overlapping with the rectum, respectively. Prescribed doses of 36.25-45 Gy in five fractions were delivered to the PTV. The spacer cover ratio (SCR) and hydrogel-implant quality score (HIQS) were calculated. RESULTS: Dosimetric and quantitative parameters of the hydrogel spacer distribution were compared between the two groups. For PTV, D99% in group 1 (n = 29) was significantly higher than that in group 2 (n = 26), and Dmax, D0.03cc, D1cc, and D10% for the rectum were significantly lower in group 1 than in group 2. The SCR for prostate (89.5 ± 12.2%) in group 1 was significantly higher (p < 0.05) than that in group 2 (74.7 ± 10.3%). In contrast, the HIQS values did not show a significant difference between the groups. An area under the curve of 0.822 (95% confidence interval, 0.708-0.936) for the SCR was obtained with a cutoff of 93.6%, sensitivity of 62.1%, and specificity of 100%. CONCLUSIONS: The SCR seems promising to predict the separation of the rectum from the PTV in linear-accelerator-based SBRT for prostate cancer.

Surface and build-up dose comparison between Elekta 6 MV flattening filter and flattening-filter-free beams using an advanced Markus ionization chamber and a solid water-equivalent phantom.

Using a plane-parallel advanced Markus ionization chamber and a stack of water-equivalent solid phantom blocks, percentage surface and build-up doses of Elekta 6 MV flattening filter (FF) and flattening-filter-free (FFF) beams were measured as a function of the phantom depth for field sizes ranging from 2 × 2 to 10 × 10 cm2 . It was found that the dose difference between the FF and the FFF beams was relatively small. The maximum dose difference between the FF and the FFF beams was 4.4% at a depth of 1 mm for a field size of 2 × 2 cm2 . The dose difference was gradually decreased while the field size was increased up to 10 × 10 cm2 . The measured data were also compared to published Varian FF and FFF data, suggesting that the percentage surface and build-up doses as well as the percentage dose difference between FF and FFF beams by our Elekta linac were smaller than those by the Varian linac.

[Improvement in Image Quality of CBCT during Treatment by Cycle Generative Adversarial Network].

PURPOSE: Volumetric modulated arc therapy (VMAT) can acquire projection images during rotational irradiation, and cone-beam computed tomography (CBCT) images during VMAT delivery can be reconstructed. The poor quality of CBCT images prevents accurate recognition of organ position during the treatment. The purpose of this study was to improve the image quality of CBCT during the treatment by cycle generative adversarial network (CycleGAN). METHOD: Twenty patients with clinically localized prostate cancer were treated with VMAT, and projection images for intra-treatment CBCT (iCBCT) were acquired. Synthesis of PCT (SynPCT) with improved image quality by CycleGAN requires only unpaired and unaligned iCBCT and planning CT (PCT) images for training. We performed visual and quantitative evaluation to compare iCBCT, SynPCT and PCT deformable image registration (DIR) to confirm the clinical usefulness. RESULT: We demonstrated suitable CycleGAN networks and hyperparameters for SynPCT. The image quality of SynPCT improved visually and quantitatively while preserving anatomical structures of the original iCBCT. The undesirable deformation of PCT was reduced when SynPCT was used as its reference instead of iCBCT. CONCLUSION: We have performed image synthesis with preservation of organ position by CycleGAN for iCBCT and confirmed the clinical usefulness.

Radiation dose reduction with frame rate conversion in X-ray fluoroscopic imaging systems with flat panel detector: basic study and clinical retrospective analysis.

OBJECTIVES: To (a) evaluate the interpolation frames of frame rate conversion (FRC) compared with fluoroscopic frames of conventional method, and (b) compare radiation dose and fluoroscopy time between various clinical examinations without and with FRC retrospectively. METHODS: This study consisted of a basic study and a clinical retrospective analysis. The radiation dosimetry, visual assessment and measurements of contrast to noise ratio were examined. Similarity between interpolation frames and fluoroscopic frames was evaluated using normalised cross-correlation values. In the clinical retrospective analysis approved by the institutional review board, we extracted 270 examinations performed without FRC (conventional group, 12.5 pulses/s) and with FRC (FRC group, 6.25 pulses/s) from 23 May to 31 December 2016. The fluoroscopy parameters and demographics of the two groups of the clinical examinations were compared. Statistical analyses were performed with Wilcoxon signed-rank test, Brunner-Munzel test and χ2 test. RESULTS: In the basic study, the only significant difference was that the radiation dose of FRC was approximately half that of the conventional method in the same fluoroscopy time (p = .031). The interpolation frames of FRC were similar to the fluoroscopic frames of the conventional method. In the clinical retrospective analysis, the only significant difference was that FRC reduced the fluoroscopy dose by 48% and the total dose by 31% compared with the conventional method (p < .001). There was no significant difference in the others. CONCLUSION: FRC significantly reduced the radiation dose without extending the fluoroscopy time and maintaining the image quality compared to the conventional method. KEY POINTS: • Although X-ray fluoroscopic techniques are widely used for various clinical purposes, X-ray fluoroscopic examinations have radiation risks. • Frame rate conversion is an image processing technique for radiation dose reduction. • Clinical retrospective analysis showed that FRC reduces radiation doses of patients.

[Evaluation of a Post-analysis Method for Cumulative Dose Distribution in Stereotactic Body Radiotherapy].

PURPOSE: The purpose of this study was to evaluate a post-analysis method for cumulative dose distribution in stereotactic body radiotherapy (SBRT) using volumetric modulated arc therapy (VMAT) . METHOD: VMAT is capable of acquiring respiratory signals derived from projection images and machine parameters based on machine logs during VMAT delivery. Dose distributions were reconstructed from the respiratory signals and machine parameters in the condition where respiratory signals were without division, divided into 4 and 10 phases. The dose distribution of each respiratory phase was calculated on the planned four-dimensional CT (4DCT). Summation of the dose distributions was carried out using deformable image registration (DIR), and cumulative dose distributions were compared with those of the corresponding plans. RESULTS AND DISCUSSION: Without division, dose differences between cumulative distribution and plan were not significant. In the condition where respiratory signals were divided, dose differences were observed over dose in cranial region and under dose in caudal region of planning target volume (PTV). Differences between 4 and 10 phases were not significant. CONCLUSION: The present method was feasible for evaluating cumulative dose distribution in VMAT-SBRT using 4DCT and DIR.

Evaluation of In Vivo Volumetric Dosimetry for Prostate Cancer Using Electronic Portal Imaging Device.

PURPOSE: Volumetric modulated arc therapy (VMAT) is capable of acquiring projection images using electronic portal imaging device (EPID). Commercial EPID-based dosimetry software, dosimetry check (DC), allows in vivo dosimetry using projection images. The purpose of this study was to evaluate in vivo dosimetry for prostate cancer using VMAT. METHOD: VMAT plans were generated for eight patients with prostate cancer using treatment planning system (TPS), and patient quality assurances (QAs) were carried out with phantom. We analyzed five plans as phantom study and five plans as patient study. Projection images were acquired during VMAT delivery. DC converted acquired images into fluence images and used a pencil beam algorithm to calculate dose distributions delivered on the CT images of the phantom and the patients. We evaluated isocenter point doses and gamma analysis in both studies and dose indexes of planning target volume (PTV), bladder and rectum in patient study. RESULTS AND DISCUSSION: Dose differences at the isocenter were less than a criterion in both studies. Pass rates of the gamma analysis were less than a criterion by two plans in the phantom study. Dose indexes of reconstructed distribution were lower than original plans and standard deviations of PTV in reconstructed distribution were larger than original plans. The errors were caused by some issues, such as the commissioning of DC, variations in patient anatomy, and patient positioning. CONCLUSION: The method was feasible to non-invasively perform in vivo dose evaluation for prostate cancer using VMAT.

[Winston-lutz test and acquisition of flexmap using rotational irradiation].

PURPOSE: IGRT (image guided radiation therapy) is a useful technique for implementing precisely targeted radiation therapy. Quality assurance and quality control (QA/QC) medical linear accelerators with a portal imaging system (electronic portal imaging device: EPID) are the key to ensuring safe IGRT. The Winston-Lutz test (WLT) provides an evaluation of the MV isocenter, which is the intersection of radiation, collimator, and couch isocenters. A flexmap can indicate a displacement of EPID from the beam center axis as a function of gantry angles which can be removed from the images. The purpose of this study was to establish a novel method for simultaneously carrying out WLT and acquiring a flexmap using rotational irradiation. We also observed long-term changes in flexmaps over a period of five months. METHOD: We employed rotational irradiation with a rectangular field (30×30 mm). First, the displacement of EPID from the beam center axis, indicated by the ball bearing (BB) center, was evaluated using an in-house program. The location of the BB center was then modified according to WLT. Second, a second irradiation was used to acquire a flexmap. We performed this examination regularly and evaluated long-term changes in the flexmap. RESULTS AND DISCUSSION: It proved feasible to perform WLT and flexmap measurements using our proposed methods. The precision of WLT using rotational irradiation was 0.1 mm. In flexmap analysis, the maximum displacement from the mean value for each angle was 0.4 mm over five months. CONCLUSION: We have successfully established a novel method of simultaneously carrying out WLT and flexmap acquisition using rotational irradiation. Maximum displacement from the mean in each angle was 0.4 mm over five months.

[Dose reconstruction using respiratory signals and machine parameters during treatment in stereotactic body radiotherapy].

PURPOSE: Volumetric modulated arc therapy (VMAT) is a rotational intensity-modulated radiotherapy (IMRT) technique capable of acquiring projection images during treatment. The purpose of this study was to reconstruct the dose distribution from respiratory signals and machine parameters acquired during stereotactic body radiotherapy (SBRT). METHODS: The treatment plans created for VMAT-SBRT included the constraint of 1 mm/degree in multileaf collimator (MLC) for a moving phantom and three patients with lung tumors. The respiratory signals were derived from projection images acquired during VMAT delivery, while the machine parameters were derived from machine logs. The respiratory signals and machine parameters were then linked along with the gantry angle. With this data, the dose distribution of each respiratory phase was calculated on the planned four-dimensional CT (4D CT). The doses at the isocenter, the point of max dose and the centroid of the target were compared with those of the corresponding plans. RESULTS AND DISCUSSION: In the phantom study, the maximum dose difference between the plan and "in-treatment" results was -0.4% at the centroid of the target. In the patient study, the difference was -1.8 ± 0.4% at the centroid of the target. Dose differences of the evaluated points between 4 and 10 phases were not significant. CONCLUSION: The present method successfully reconstructed the dose distribution using the respiratory signals and machine parameters acquired during treatment. This is a feasible method for verifying the actual dose for a moving target.

Cone-beam computed-tomography-based delta-radiomic analysis for investigating prognostic power for esophageal squamous cell cancer patients undergoing concurrent chemoradiotherapy.

PURPOSE: To investigate the prognostic power of cone-beam computed-tomography (CBCT)-based delta-radiomics in esophageal squamous cell cancer (ESCC) patients treated with concurrent chemoradiotherapy (CCRT). METHODS: We collected data from 26 ESCC patients treated with CCRT. CBCT images acquired at five time points (1st-5th week) per patient during CCRT were used in this study. Radiomic features were extracted from the five CBCT images on the gross tumor volumes. Then, 17 delta-radiomic feature sets derived from five types of calculations were obtained for all the cases. Leave-one-out cross-validation was applied to investigate the prognostic power of CBCT-based delta-radiomic features. Feature selection and construction of a prediction model using Coxnet were performed using training samples. Then, the test sample was classified into high or low risk in each cross-validation fold. Survival analysis for the two groups were performed to evaluate the prognostic power of the extracted CBCT-based delta-radiomic features. RESULTS: Four delta-radiomic feature sets indicated significant differences between the high- and low-risk groups (p < 0.05). The highest C-index in the 17 delta-radiomic feature sets was 0.821 (95 % confidence interval, 0.735-0.907). That feature set had p-value of the log-rank test and hazard ratio of 0.003 and 4.940 (95 % confidence interval, 1.391-17.544), respectively. CONCLUSIONS: We investigated the potential of using CBCT-based delta-radiomics for prognosis of ESCC patients treated with CCRT. It was demonstrated that delta-radiomic feature sets based on the absolute value of relative difference obtained from the early to the middle treatment stages have high prognostic power for ESCC.

Variation in Hounsfield unit calculated using dual-energy computed tomography: comparison of dual-layer, dual-source, and fast kilovoltage switching technique.

The purpose of the study is to investigate the variation in Hounsfield unit (HU) values calculated using dual-energy computed tomography (DECT) scanners. A tissue characterization phantom inserting 16 reference materials were scanned three times using DECT scanners [dual-layer CT (DLCT), dual-source CT (DSCT), and fast kilovoltage switching CT (FKSCT)] changing scanning conditions. The single-energy CT images (120 or 140 kVp), and virtual monochromatic images at 70 keV (VMI70) and 140 keV (VMI140) were reconstructed, and the HU values of each reference material were measured. The difference in HU values was larger when the phantom was scanned using the half dose with wrapping with rubber (strong beam-hardening effect) compared with the full dose without the rubber (reference condition), and the difference was larger as the electron density increased. For SECT, the difference in HU values against the reference condition measured by the DSCT (3.2 ± 5.0 HU) was significantly smaller (p < 0.05) than that using DLCT with 120 kVp (22.4 ± 23.8 HU), DLCT with 140 kVp (11.4 ± 12.8 HU), and FKSCT (13.4 ± 14.3 HU). The respective difference in HU values in the VMI70 and VMI140 measured using the DSCT (10.8 ± 17.1 and 3.5 ± 4.1 HU) and FKSCT (11.5 ± 21.8 and 5.5 ± 10.4 HU) were significantly smaller than those measured using the DLCT120 (23.1 ± 27.5 and 12.4 ± 9.4 HU) and DLCT140 (22.3 ± 28.6 and 13.1 ± 11.4 HU). The HU values and the susceptibility to beam-hardening effects varied widely depending on the DECT scanners.

Neurological prognosis prediction for cardiac arrest patients using quantitative imaging biomarkers from brain computed tomography.

PURPOSE: We aimed to predict the neurological prognosis of cardiac arrest (CA) patients using quantitative imaging biomarkers extracted from brain computed tomography images. METHODS: We retrospectively enrolled 86 CA patients (good prognosis, 32; poor prognosis, 54) who were treated at three hospitals between 2017 and 2019. We then extracted 1131 quantitative imaging biomarkers from whole-brain and local volumes of interest in the computed tomography images of the patients. The data were split into training and test sets containing 60 and 26 samples, respectively, and the training set was used to select representative quantitative imaging biomarkers for classification. In univariate analysis, the classification was evaluated using the p-value of the Brunner-Munzel test and area under the receiver operating characteristic curve (AUC) for the test set. In multivariate analysis, machine learning models reflecting nonlinear and complex relations were trained, and they were evaluated using the AUC on the test set. RESULTS: The best performance provided p = 0.009 (<0.01) and an AUC of 0.775 (95% confidence interval, 0.590-0.960) for the univariate analysis and an AUCof0.813 (95% confidence interval, 0.640-0.985) for the multivariate analysis. Overall, the gray level with the maximum gradient in the histogram of the three-dimensionally low-pass-filtered image was an important feature for prediction across the analyses. CONCLUSIONS: Quantitative imaging biomarkers can be used in neurological prognosis prediction for CA patients. Relevant biomarkers may contribute to protocolized computed tomography image acquisition to ensure proper decision support in acute care.

Long-term geometric quality assurance of radiation focal point and cone-beam computed tomography for Gamma Knife radiosurgery system.

To investigate the geometric accuracy of the radiation focal point (RFP) and cone-beam computed tomography (CBCT) over long-term periods for the ICON Leksell Gamma Knife radiosurgery system. This phantom study utilized the ICON quality assurance tool plus, and the phantom was manually set on the patient position system before the implementation of treatment for patients. The deviation of the RFP position from the unit center point (UCP) and the positions of the four ball bearings (BBs) in the CBCT from the reference position were automatically analyzed. During 544 days, a total of 269 analyses were performed on different days. The mean ± standard deviation (SD) of the deviation between measured RFP and UCP was 0.01 ± 0.03, 0.01 ± 0.03, and -0.01 ± 0.01 mm in the X, Y, and Z directions, respectively. The deviations with offset values after the cobalt-60 source replacement (0.00 ± 0.03, -0.01 ± 0.01, and -0.01 ± 0.01 mm in the X, Y, and Z directions, respectively) were significantly (p = 0.001) smaller than those before the replacement (0.02 ± 0.03, 0.02 ± 0.01, and -0.02 ± 0.01 mm in the X, Y, and Z directions, respectively). The overall mean ± SD of four BBs was -0.03 ± 0.03, -0.01 ± 0.05, and 0.01 ± 0.03 mm in the X, Y, and Z directions, respectively. Geometric positional accuracy was ensured to be within 0.1 mm on most days over a long-term period of more than 500 days.

An Invisible Skin Marker for External Beam Radiation Therapy: Utilization of Ultraviolet Fluorescent Marker Pens.

Radiation therapy plays an important role in cancer treatment along with surgery and systemic therapy. The total dose of radiation therapy is divided into small doses, and the treatment is typically delivered once a day. The total treatment period can need several weeks or more, and it is necessary to deliver the radiation dose to the target volume within the patient precisely each time. Therefore, the reproducibility of patient positioning is essential for the precision of the dose delivery. Although radiological technologies such as image-guided radiation therapy have also recently been widely used for positioning patients, skin marking is still widely used in many facilities. Skin marking is an inexpensive and universal positioning technique in patients undergoing radiation therapy; however, it is considered a major source of psychological stress. We propose the use of fluorescent ink pens, which are invisible in standard room lighting, as skin markers for radiotherapy. The primary technique of fluorescence emission is widely employed in molecular biological experiments and for assessing cleaning protocols for infection control. This technique may reduce the stress induced by skin markings during radiotherapy.

Virtual cone-beam computed tomography simulator with human phantom library and its application to the elemental material decomposition.

PURPOSE: The purpose of this study is to develop a virtual CBCT simulator with a head and neck (HN) human phantom library and to demonstrate the feasibility of elemental material decomposition (EMD) for quantitative CBCT imaging using this virtual simulator. METHODS: The library of 36 HN human phantoms were developed by extending the ICRP 110 adult phantoms based on human age, height, and weight statistics. To create the CBCT database for the library, a virtual CBCT simulator that simulated the direct and scattered X-ray on a flat panel detector using ray-tracing and deep-learning (DL) models was used. Gaussian distributed noise was also included on the flat panel detector, which was evaluated using a real CBCT system. The usefulness of the virtual CBCT system was demonstrated through the application of the developed DL-based EMD model for case involving virtual phantom and real patient. RESULTS: The virtual simulator could generate various virtual CBCT images based on the human phantom library, and the prediction of the EMD could be successfully performed by preparing the CBCT database from the proposed virtual system, even for a real patient. The CBCT image degradation owing to the scattered X-ray and the statistical noise affected the prediction accuracy, although these effects were minimal. Furthermore, the elemental distribution using the real CBCT image was also predictable. CONCLUSIONS: This study demonstrated the potential of using computer vision for medical data preparation and analysis, which could have important implications for improving patient outcomes, especially in adaptive radiation therapy.

Injection of hydrogel spacer increased maximal intrafractional prostate motion in anterior and superior directions during volumetric modulated arc therapy-stereotactic body radiation therapy for prostate cancer.

BACKGROUND: The aim of this study was to clarify the association between intrafractional prostate shift and hydrogel spacer. METHODS: Thirty-eight patients who received definitive volumetric modulated arc therapy (VMAT)-stereotactic body radiation therapy (SBRT) for prostate cancer with prostate motion monitoring in our institution in 2018-2019 were retrospectively evaluated. In order to move the rectum away from the prostate, hydrogel spacer (SpaceOAR system, Boston Scientific, Marlborough, the United States) injection was proposed to the patients as an option in case of meeting the indication of use. We monitored intrafractional prostate motion by using a 4-dimensional (4D) transperineal ultrasound device: the Clarity 4D ultrasound system (Elekta AB). The deviation of the prostate was monitored in each direction: superior-inferior, left-right, and anterior-posterior. We also calculated the vector length. The maximum intrafractional displacement (MID) per fraction for each direction was detected and mean of MIDs was calculated per patient. The MIDs in the non-spacer group and the spacer group were compared using the unpaired t-test. RESULTS: We reviewed 33 fractions in eight patients as the spacer group and 148 fractions in 30 patients as the non-spacer group. The superior MID was 0.47 ± 0.07 (mean ± SE) mm versus 0.97 ± 0.24 mm (P = 0.014), the inferior MID was 1.07 ± 0.11 mm versus 1.03 ± 0.25 mm (P = 0.88), the left MID was 0.74 ± 0.08 mm versus 0.87 ± 0.27 mm (P = 0.55), the right MID was 0.67 ± 0.08 mm versus 0.92 ± 0.21 mm (P = 0.17), the anterior MID was 0.45 ± 0.06 mm versus 1.16 ± 0.35 mm (P = 0.0023), and the posterior MID was 1.57 ± 0.17 mm versus 1.37 ± 0.22 mm (P = 0.56) in the non-spacer group and the spacer group, respectively. The max of VL was 2.24 ± 0.19 mm versus 2.89 ± 0.62 mm (P = 0.19), respectively. CONCLUSIONS: Our findings suggest that maximum intrafractional prostate motion during VMAT-SBRT was larger in patients with hydrogel spacer injection in the superior and anterior directions. Since this difference seemed not to disturb the dosimetric advantage of the hydrogel spacer, we do not recommend routine avoidance of the hydrogel spacer use.

Training of deep cross-modality conversion models with a small data set, and their application in megavoltage CT to kilovoltage CT conversion.

PURPOSE: In recent years, deep learning-based image processing has emerged as a valuable tool for medical imaging owing to its high performance. However, the quality of deep learning-based methods heavily relies on the amount of training data; the high cost of acquiring a large data set is a limitation to their utilization in medical fields. Herein, based on deep learning, we developed a computed tomography (CT) modality conversion method requiring only a few unsupervised images. METHODS: The proposed method is based on cycle-consistency generative adversarial network (CycleGAN) with several extensions tailored for CT images, which aims at preserving the structure in the processed images and reducing the amount of training data. This method was applied to realize the conversion of megavoltage computed tomography (MVCT) to kilovoltage computed tomography (kVCT) images. Training was conducted using several data sets acquired from patients with head and neck cancer. The size of the data sets ranged from 16 slices (two patients) to 2745 slices (137 patients) for MVCT and 2824 slices (98 patients) for kVCT. RESULTS: The required size of the training data was found to be as small as a few hundred slices. By statistical and visual evaluations, the quality improvement and structure preservation of the MVCT images converted by the proposed model were investigated. As a clinical benefit, it was observed by medical doctors that the converted images enhanced the precision of contouring. CONCLUSIONS: We developed an MVCT to kVCT conversion model based on deep learning, which can be trained using only a few hundred unpaired images. The stability of the model against changes in data size was demonstrated. This study promotes the reliable use of deep learning in clinical medicine by partially answering commonly asked questions, such as "Is our data sufficient?" and "How much data should we acquire?"

Patient setup error and day-to-day esophageal motion error analyzed by cone-beam computed tomography in radiation therapy.

UNLABELLED: Little has been reported on the errors of setup and daily organ motion that occur during radiation therapy (RT) for esophageal cancer. The purpose of this paper was to determine the margins of esophageal motion during RT. METHODS AND MATERIALS: The shift of the esophagus was analyzed in 20 consecutive patients treated with RT for esophageal cancer from November 2007. CT images for RT planning were used as the primary image series. Computed tomography (CT) images were acquired using an Elekta Synergy System, equipped with a kilovoltage-based cone-beam CT (CBCT) unit. The subsequent CBCT image series used for daily RT setup were compared with the primary image series to analyze esophageal motion. CBCT was performed before treatment sessions a total of 10 times in each patient twice a week. The outer esophageal wall was contoured on the CBCT images of all 200 sets. RESULTS: In the 200 sets of CBCT images, the mean (absolute) +/- standard deviation (SD) of setup errors were 2 +/- 2 mm (max, 8 mm) in the lateral direction, 4 +/- 3 mm (max, 11 mm) in the longitudinal direction, and 4 +/- 3 mm (max, 13 mm) in the vertical direction. Additionally, the mean +/- SD values of daily esophageal motion comparing the CBCT with RT planning CT were 5 +/- 3 mm (max, 15 mm) in the lateral direction and 5 +/- 3 mm (max, 15 mm) in the vertical direction. CONCLUSIONS: Our data support the use of target margins (between the clinical target volume and planning target volume) of 9 mm for day-to-day esophageal motion and 8 mm for patient setup in all directions, respectively.

Acceptable fetal dose using flattening filter-free volumetric arc therapy (FFF VMAT) in postoperative chemoradiotherapy of tongue cancer during pregnancy.

Optimizing irradiation protocols for pregnant women is challenging, because there are few cases and a dearth of fetal dosimetry data. We cared for a 36-year-old pregnant woman with tongue cancer. Prior to treatment, we compared three intensity-modulated radiation therapy (IMRT) techniques, including helical tomotherapy, volumetric arc therapy (VMAT), and flattening-filter free VMAT (FFF-VMAT) using treatment planning software. FFF-VMAT achieved the minimum fetal exposure and was selected as the optimal modality. We prescribed 66 Gy to the involved nodes, 60 Gy to the tumor bed and ipsilateral neck, and 54 Gy to the contralateral neck over 33 fractions. To confirm the out-of-field exposure per fraction, surface doses and the rectal dose were measured during FFF-VMAT delivery. Postoperative chemoradiotherapy was delivered using IMRT and a cisplatin regimen. Without any shielding, the total fetal dose was 0.03 Gy, within the limits established by the ICRP. A healthy girl was born vaginally at 37 weeks' gestation.

Visual enhancement of Cone-beam CT by use of CycleGAN.

PURPOSE: Cone-beam computed tomography (CBCT) offers advantages over conventional fan-beam CT in that it requires a shorter time and less exposure to obtain images. However, CBCT images suffer from low soft-tissue contrast, noise, and artifacts compared to conventional fan-beam CT images. Therefore, it is essential to improve the image quality of CBCT. METHODS: In this paper, we propose a synthetic approach to translate CBCT images with deep neural networks. Our method requires only unpaired and unaligned CBCT images and planning fan-beam CT (PlanCT) images for training. The CBCT images and PlanCT images may be obtained from other patients as long as they are acquired with the same scanner settings. Once trained, three-dimensionally reconstructed CBCT images can be directly translated into high-quality PlanCT-like images. RESULTS: We demonstrate the effectiveness of our method with images obtained from 20 prostate patients, and provide a statistical and visual comparison. The image quality of the translated images shows substantial improvement in voxel values, spatial uniformity, and artifact suppression compared to those of the original CBCT. The anatomical structures of the original CBCT images were also well preserved in the translated images. CONCLUSIONS: Our method produces visually PlanCT-like images from CBCT images while preserving anatomical structures.