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We compared predictive performance between dose volume histogram (DVH) parameter addition and deformable image registration (DIR) addition for gastrointestinal (GI) toxicity in cervical cancer patients. A total of 59 patients receiving brachytherapy and external beam radiotherapy were analyzed retrospectively. The accumulative dose was calculated by three methods: conventional DVH parameter addition, full DIR addition and partial DIR addition. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${D}_{2{cm}^3}$\end{document}, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${D}_{1{cm}^3}$\end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${D}_{0.1{cm}^3}$\end{document} (minimum doses to the most exposed 2 cm3, 1cm3 and 0.1 cm3 of tissue, respectively) of the rectum and sigmoid were calculated by each method. V50, V60 and V70 Gy (volume irradiated over 50, 60 and 70 Gy, respectively) were calculated in full DIR addition. The DVH parameters were compared between toxicity (≥grade1) and non-toxicity groups. The area under the curve (AUC) of the receiver operating characteristic (ROC) curves were compared to evaluate the predictive performance of each method. The differences between toxicity and non-toxicity groups in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${D}_{2{cm}^3}$\end{document} were 0.2, 5.7 and 3.1 Gy for the DVH parameter addition, full DIR addition and partial DIR addition, respectively. The AUCs of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${D}_{2{cm}^3}$\end{document} were 0.51, 0.67 and 0.57 for DVH parameter addition, full DIR addition and partial DIR addition, respectively. In full DIR addition, the difference in dose between toxicity and non-toxicity was the largest and AUC was the highest. AUCs of V50, V60 and V70 Gy were 0.51, 0.63 and 0.62, respectively, and V60 and V70 were high values close to the value of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${D}_{2{cm}^3}$\end{document} of the full DIR addition. Our results suggested that the full DIR addition may have the potential to predict toxicity more accurately than the conventional DVH parameter addition, and that it could be more effective to accumulate to all pelvic irradiation by DIR.

This study aimed to evaluate the influence of change in respiratory motion on matchline (ML) and reduction of the effect by increasing ML levels of field matching technique in passive scattering proton therapy for esophageal cancer. To evaluate the influence of respiratory motion in terms of stability, we measured relative dose around ML using a respiratory motion phantom. The relative error was -0.5% when the respiratory motion phantom worked stable, whereas there was obvious change that the relative error was -25.5% when the difference of amplitude between upper field and lower field was one side 3 mm on each cranially and caudally direction. In clinical case of the seven esophageal cancer patients simulated by the treatment planning system, assuming the difference of amplitude was 3 mm, the relative error of maximum (minimum) dose in clinical target volume around ML against the original treatment plan were 5.8±1.2% (-6.0±2.7%), 3.3±0.9% (-3.8±1.0%), and 2.4±0.5% (2.6±0.8%) on average (±SD) when ML levels were 2, 4, and 6, respectively. Increasing ML levels can reduce the influence of respiratory motion.

The purpose of this study was comparing dose‐volume histogram (DVH)‐based plan verification methods for volumetric modulated arc therapy (VMAT) pretreatment QA. We evaluated two 3D dose reconstruction systems: ArcCHECK‐3DVH system (Sun Nuclear corp.) and Varian dynalog‐based dose reconstruction (DBDR) system, developed in‐house. Fifteen prostate cancer patients (67.6 Gy/26 Fr), four head and neck cancer patient (66 Gy/33 Fr), and four esophagus cancer patients (60 Gy/30 Fr) treated with VMAT were studied. First, ArcCHECK measurement was performed on all plans; simultaneously, the Varian dynalog data sets that contained the actual delivered parameters (leaf positions, gantry angles, and cumulative MUs) were acquired from the Linac control system. Thereafter, the delivered 3D patient dose was reconstructed by 3DVH software (two different calculating modes were used: High Sensitivity (3DVH‐HS) and Normal Sensitivity (3DVH‐NS)) and in‐house DBDR system. We evaluated the differences between the TPS‐calculated dose and the reconstructed dose using 3D gamma passing rates and DVH dose index analysis. The average 3D gamma passing rates (3%/3 mm) between the TPS‐calculated dose and the reconstructed dose were 99.1 ± 0.6%, 99.7 ± 0.3%, and 100.0 ± 0.1% for 3DVH–HS, 3DVH–NS, and DBDR, respectively. For the prostate cases, the average differences between the TPS‐calculated dose and reconstructed dose in the PTV mean dose were 1.52 ± 0.50%, −0.14 ± 0.55%, and −0.03 ± 0.07% for 3DVH–HS, 3DVH–NS, and DBDR, respectively. For the head and neck and esophagus cases, the dose difference to the TPS‐calculated dose caused by an effect of heterogeneity was more apparent under the 3DVH dose reconstruction than the DBDR. Although with some residual dose reconstruction errors, these dose reconstruction methods can be clinically used as effective tools for DVH‐based QA for VMAT delivery.

Purpose In this study, we developed a 3D-printed deformable pelvis phantom for evaluating spatial DIR accuracy. We then evaluated the spatial DIR accuracies of various DIR settings for cervical cancer. Methods A deformable female pelvis phantom was created based on patient CT data using 3D printing. To create the deformable uterus phantom, we first 3D printed both a model of uterus and a model of the internal cavities of the vagina and uterus. We then made a mold using the 3D printed uterus phantom. Finally, urethane was poured into the mold with the model of the internal cavities in place, creating the deformable uterus phantom with a cavity into which an applicator could be inserted. To create the deformable bladder phantom, we first 3D printed models of the bladder and of the same bladder scaled down by 2 mm. We then made a mold using the larger bladder model. Finally, silicone was poured into the mold with the smaller bladder model in place to create the deformable bladder phantom with a wall thickness of 2 mm. To emulate the anatomical bladder, water was poured into the created bladder. We acquired phantom image without applicator for EBRT. Then, we inserted the applicator into the phantom to simulate BT. In this situation, we scanned the phantom again to obtain the phantom image for BT. We performed DIR using the two phantom images in two cases: Case A, with full bladder (170 ml) in both EBRT and BT images; and Case B with full bladder in the BT image and half-full bladder (100 ml) in the EBRT image. DIR was evaluated using Dice similarity coefficients (DSCs) and 31 landmarks for the uterus and 25 landmarks for the bladder. A hybrid intensity and structure DIR algorithm implemented in RayStation with four DIR settings was evaluated. Results On visual inspection, reasonable agreement in shape of the uterus between the phantom and patient CT images was observed for both EBRT and BT, although some regional disagreements in shape of the bladder and rectum were apparent. The created phantom could reproduce the actual patient's uterus deformation by the applicator. For both Case A and B, large variation was seen in landmark error among the four DIR parameters. In addition, although DSCs were comparable, moderate differences in landmark error existed between the two different DIR parameters selected from the four DIR parameters (i.e., DSC = 0.96, landmark error = 13.2 ± 5.7 mm vs. DSC = 0.97, landmark error = 9.7 ± 4.0 mm). This result suggests that landmark error evaluation might thus be more effective than DSC for evaluating DIR accuracy. Conclusions Our developed phantom enabled the evaluation of spatial DIR accuracy for the female pelvic region for the first time. Although the DSCs are high, the spatial errors can still be significant and our developed phantom facilitates their quantification. Our results showed that optimization is needed to identify suitable DIR settings. For determining suitable DIR settings, our method of evaluating spatial DIR accuracy using the 3D-printed phantom may prove helpful.

Irregular breathing can influence the outcome of 4D computed tomography imaging and cause artifacts. Visual biofeedback systems associated with a patient-specific guiding waveform are known to reduce respiratory irregularities. In Japan, abdomen and chest motion self-control devices (Abches) (representing simpler visual coaching techniques without a guiding waveform) are used instead; however, no studies have compared these two systems to date. Here, we evaluate the effectiveness of respiratory coaching in reducing respiratory irregularities by comparing two respiratory management systems. We collected data from 11 healthy volunteers. Bar and wave models were used as 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 with 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. 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. The average reduction in displacement and period RMSE compared with the wave model were 27% and 47%, respectively. For variation in both displacement and period, wave model was superior to the other techniques. Our results showed that visual biofeedback combined with a wave model could potentially provide clinical benefits in respiratory management, although all techniques were able to reduce respiratory irregularities.

The purpose of this study was to evaluate the accuracy of commercially available software, using patient DVH‐based QA metrics, by investigating the correlation between estimated 3D patient dose and magnitude of MLC misalignments. We tested 3DVH software with an ArcCHECK. Two different calculating modes of ArcCHECK Planned Dose Perturbation (ACPDP) were used: “Normal Sensitivity” and “High Sensitivity”. Ten prostate cancer patients treated with hypofractionated VMAT (67.6 Gy/26 Fr) in our hospital were studied. For the baseline plan, we induced MLC errors (−0.75,−0.5,−0.25,0.25,0.5, and 0.75 mm for each single bank). We calculated the dose differences between the ACPDP dose with error and TPS dose with error using gamma passing rates and using DVH‐based QA metrics. The correlations between dose estimation error and MLC position error varied with each structure and metric. A comparison using 1%/1 mm gamma index showed that the larger was the MLC error‐induced, the worse were the gamma passing rates. Slopes of linear fit to dose estimation error versus MLC position error for mean dose and D95 to the PTV were 1.76 and 1.40% mm−1, respectively, for “Normal Sensitivity”, and −0.53 and 0.88% mm−1, respectively, for “High Sensitivity”, showing better accuracy for “High Sensitivity” than “Normal Sensitivity”. On the other hand, the slopes for mean dose to the rectum and bladder, V35 to the rectum and bladder and V55 to the rectum and bladder, were −1.00,−0.55,−2.56,−1.25,−3.53, and 1.85% mm−1, respectively, for “Normal Sensitivity”, and −2.89,−2.39,−4.54,−3.12,−6.24, and −4.11% mm−1, respectively, for “High Sensitivity”, showing significant better accuracy for “Normal Sensitivity” than “High Sensitivity”. Our results showed that 3DVH had some residual error for both sensitivities. Furthermore, we found that “Normal Sensitivity” might have better accuracy for the DVH metric for the PTV and that “High Sensitivity” might have better accuracy for DVH metrics for the rectum and bladder. We must be willing to tolerate this residual error in clinical care. PACS number: 87.55Qr

Our aim was to investigate the feasibility of a three-dimensional (3D) -printed head-and-neck (HN) immobilization device by comparing its positional accuracy and dosimetric properties with those of a conventional immobilization device (CID). We prepared a 3D-printed immobilization device (3DID) consisting of a mask and headrest with acrylonitrile-butadiene-styrene resin developed from the computed tomography data obtained by imaging a HN phantom. For comparison, a CID comprising a thermoplastic mask and headrest was prepared using the same HN phantom. We measured the setup error using the ExacTrac X-ray image system. Furthermore, using the ionization chamber and the water-equivalent phantom, we measured the changes in the dose due to the difference in the immobilization device material from the photon of 4 MV and 6 MV. The positional accuracy of the two devices were almost similar in each direction except in the vertical, lateral, and pitch directions (t-test, p

In the present study we developed a method for quantifying regional cerebral blood flow (rCBF) using 99mTc-ECD SPECT based on a 3-compartment model. The dynamic SPECT scanning and sequential sampling of arterial blood were performed on 12 subjects with cerebrovascular diseases and etc. We defined brain fractionation index (BFI) as a parameter of rCBF, which was obtained from a single SPECT data and arterial input. The relationship between the values of BFI and rCBF obtained by the 133Xe inhalation method was analyzed by approximation with exponential function. In this method, rCBF was calculated from the values of BFI using the inverse function of the exponential function as a regression curve. The method was applied seven other patients with cerebrovascular diseases and the values of rCBF were compared with those obtained by the 133Xe inhalation method. We observed a good correlation (r = 0.854), and the inclination was approximately 1. This method can be applied to not only large field SPECT cameras but also conventional SPECT cameras.

The purpose of the study is to develop a simple and less invasive method for quantifying regional cerebral blood flow (rCBF) at pre- and post Diamox test using split-dose 99mTc-ECD and SPECT. By employing a microsphere model, integral of input function was calculated by the one-point venous sampling method previously reported. The study was performed on 5 subjects with cerebrovascular diseases. A split dose of 99mTc-ECD was injected pre- and post Diamox injection, and rCBF was measured by two SPECT scans and single venous samples, respectively. Mean CBF obtained by the present method was 0.47 +/- 0.07 ml/g/min at the control state, and 0.63 +/- 0.12 ml/g/min loaded with Diamox (mean % increase; 35%), showing good agreement with those obtained by the 133Xe-inhalation method. Since the present method does not require arterial blood sampling, dynamic data acquisition and dose corrections, it is simple, less invasive and useful in clinical SPECT studies.

The purpose of the study is to develop a simple and less invasive method for quantifying regional cerebral blood flow (rCBF) using 99mTc-ECD and SPECT. By employing a microsphere model, a new method to measure rCBF was developed, which required a single arterial or venous sample instead of continuous withdrawal of arterial blood. Using a regression line, the integral of input function of arterial blood from 0 to 30 min was inferred by activity of arterial blood sampled at time t; A(t), by activity multiplied by its octanol extraction rate; AN(t), by activity of venous blood at time t; V(t), and by activity multiplied by its octanol extraction rate; VN(t). The optimum sampling time of arterial or venous blood was examined when mean % error for inference became minimum. Consequently, minimum error of AN(6 min) was 5.5%, A(3 min) was 8.9%, VN(6 min) was 5.9%, and V(20 min) was 10.0%. Quantitative measurement of rCBF using the value of VN(6 min) was performed on other 6 subjects with dementia etc. To validate the method, 133Xe inhalation SPECT studies were also performed on the same subjects. We found a good agreement between them (r = 0.851). The presented one-point sampling methods were simple and less invasive for quantifying rCBF.