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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.

Purpose An accurate source model of a medical linear accelerator is essential for Monte Carlo (MC) dose calculations. This study aims to propose an analytical photon source model based on particle transport in parameterized accelerator structures, focusing on a more realistic determination of linac photon spectra compared to existing approaches. Methods We designed the primary and secondary photon sources based on the photons attenuated and scattered by a parameterized flattening filter. The primary photons were derived by attenuating bremsstrahlung photons based on the path length in the filter. Conversely, the secondary photons were derived from the decrement of the primary photons in the attenuation process. This design facilitates these sources to share the free parameters of the filter shape and be related to each other through the photon interaction in the filter. We introduced two other parameters of the primary photon source to describe the particle fluence in penumbral regions. All the parameters are optimized based on calculated dose curves in water using the pencil-beam-based algorithm. To verify the modeling accuracy, we compared the proposed model with the phase space data (PSD) of the Varian TrueBeam 6 and 15 MV accelerators in terms of the beam characteristics and the dose distributions. The EGS5 Monte Carlo code was used to calculate the dose distributions associated with the optimized model and reference PSD in a homogeneous water phantom and a heterogeneous lung phantom. We calculated the percentage of points passing 1D and 2D gamma analysis with 1%/1 mm criteria for the dose curves and lateral dose distributions, respectively. Results The optimized model accurately reproduced the spectral curves of the reference PSD both on- and off-axis. The depth dose and lateral dose profiles of the optimized model also showed good agreement with those of the reference PSD. The passing rates of the 1D gamma analysis with 1%/1 mm criteria between the model and PSD were 100% for 4 × 4, 10 × 10, and 20 × 20 cm2 fields at multiple depths. For the 2D dose distributions calculated in the heterogeneous lung phantom, the 2D gamma pass rate was 100% for 6 and 15 MV beams. The model optimization time was less than 4 min. Conclusion The proposed source model optimization process accurately produces photon fluence spectra from a linac using valid physical properties, without detailed knowledge of the geometry of the linac head, and with minimal optimization time.

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

A method for quantitative analysis of monosaccharides including N-acetylneuraminic acid derived from sialic acid-containing oligosaccharides and glycoproteins is presented. The analysis is based on the combination of chemical and enzymatic methods coupled with capillary electrophoretic (CE) separation and laser-induced fluorescence (LIF) detection. The present method utilizes a simplified acid hydrolysis procedure consisting of mild hydrolysis (0.1 M TFA) to release sialic acid and strong acid hydrolysis (2.0 N TFA) to produce amino and neutral sugars. Amino sugars released from strong acid hydrolysis of oligosaccharides and glycoproteins were reacetylated and derivatized with 8-aminopyrene-1,3,6-trisulfonate (APTS) along with neutral sugars in the presence of sodium cyanoborohydride to yield quantitatively the highly stable fluorescent APTS adducts. N-acetylneuraminic acid (Neu5Ac), a major component of most mammalian glycoproteins, was converted in a fast specific reaction by the action of neuraminic acid aldolase (N-acylneuraminate pyruvate-lyase EC 4.1.3.3) to N-acetylmannosamine (ManNAc) and pyruvate. ManNAc was then derivatized with APTS in the same manner as the other monosaccharides. This method was demonstrated for the quantitation of pure Neu5Ac and the species derived from mild acid hydrolysis of 6'-sialyl-N-acetyllactosamine and bovine fetuin glycan. Quantitative recovery of the N-acetylmannosamine was obtained from a known amount of Neu5Ac in a mixture of seven other monosaccharides or from the sialylated oligosaccharides occurring in glycoproteins. The sequence of procedures consists of acid hydrolysis, enzymatic conversion and APTS derivatization which produced quantitative recovery of APTS-monosaccharide adducts. The detection limits for sugars derivatized with APTS and detected by CE-LIF are 100 pmol for Neu5Ac and 50 pmol for the other sugars.

Ventilation imaging can be performed using thoracic four dimensional computed tomography (4D-CT) images (max inhale phase and max exhale phase) and deformable image registration (DIR). If this method was administered in multi institution, some institution would use commercially available automatic DIR software. But, there are not many reports about commercially available automatic DIR. In this study, we evaluated the accuracy of a commercially available automatic deformable image registration (DIR) algorithm using 4D-CT images. For evaluating the accuracy of DIR, registration error was calculated by difference between manual displacement and automatic calculated displacement (DIR outputs). A B-spline DIR algorithm implemented in a Velocity AI ver. 2.7.0 software (Velocity Medial, GA, USA) was evaluated. 4D-CT images including 300 landmarks /case, throughout the lung, provided by DIR-lab (www.dir-lab.com). In this study, five patients were studied. The goal of DIR was to find a point to point correspondence between inhale image and exhale image. First, manual displacement was calculated by land mark points between max inhale phase and max exhale phase. Next, DIR outputs were calculated by a Velocity AI. After that, registration error was calculated by difference between manual displacement and DIR outputs. The mean 3D registration error (standard deviation) for the five cases was 2.70 (2.24) mm. Fewer large errors were seen, but the frequent histogram had a peak at 1.5mm of 3D error, and the frequencies decline as one moves away from the peak. The average 3D registration errors for case1 were 0.94 mm for 1.5 mm motion distance magnitude, 1.96 mm for 6.0 mm and 3.70 mm for 9.0 mm, respectively. Our result clearly shows that the accuracy of DIR in Velocity AI was within 3.0 mm. Therefore commercially available automatic DIR may be useful for image-guided radiation therapy, adaptive radiation therapy and ventilation imaging.

We evaluated dose calculation accuracy for modi- fied Cone-Beam computed tomography (CBCT) images using Multi -level-threshold algorithm, and compared it with un- modified CBCT images. Inhomogeneous pelvis phantom imag- es and three prostate cancer patient images were acquired from both planning CT (PCT) and CBCT. The Hounsfield Units (HUs) were measured for air, tissue, bone. Using in- house software, three different tissue types were differentiated in both imaging modalities. The HUs of CBCT images were replaced by the mean HUs of the same tissue type of the PCT. An intensity modulated radiation therapy (IMRT) plan was created on PCT and copied to the modified CBCT. To evaluate the dosimetric accuracy, dose distributions based on CBCT images were compared it with PCT for four datasets (one inhomogeneous phantom, three prostate cancer patients ). HU- ED calibration acquired with PCT was used in both images. In the inhomogeneous pelvis phantom, differences in dose param- eter were seen. Regarding PTV, Rectum, and Bladder, differ- ences in mean dose between PCT and CBCT were 0.4%, 0.4%, and 0.1%, respectively, whereas those between PCT and modi- fied CBCT were 0.2%, 0.1%, and 0%, respectively. In the patient study, the average dose difference of PTV, Rectum, and Bladder between PCT and CBCT were 1.0%, 0.2%, and 0.6%, respectively, compared to PCT and modified CBCT, 0.5%, 0.1%, and 0.2%, respectively. We found that the dose difference in the plans based on PCT and CBCT were de- creased after this modification. The uncertainty in patient positioning between PCT and CBCT may cause additional discrepancies in the calculated results compared to the results in the phantom study. An accurate dose calculation based on CBCT images is possible when density distributions are cor- rected. This method does not need to acquire HU-ED calibra- tion for CBCT, and may be able to remove scatter.

For geotextile-reinforced soil wall, a prediction of deformation characteristic is important for a purpose of serviceability. Usually, this prediction is carried out by FEM. analyses. On the other hand, the purposes of this report are to predict deformation characteristics of geotextile-reinforced soil wall, to estimate tension distribution of geotextiles and to estimate earth pressure against wall, based on limit equilibrium method.For convenience of analyses, the facing of the reinforced soil wall was adopted as discrete type concrete panels. It assumed the condition that the concrete panels were supported from the front side and removed the supports after filling was completed. A trial wedge method by linear sliding (method of Coulomb's earth pressure) was applied to simplify the analysis, based on an equilibrium condition for series of potential sliding surface that originated from connecting part of each panel. Internal stress and deformation behavior of reinforced soil wall were calculated.

Purpose: The purpose of this study was to evaluate the accuracy of patient DVH-based QA metrics and test the hypothesis: measurement-guided 3D dose reconstruction (MGDR) captures the induced dose error. Methods: We used 3DVH software with an ArcCHECK to estimate 3D patient dose by MGDR. Two different calculating modes of MGDR were used: “Normal Sensitivity” and “High Sensitivity”. Ten prostate cancer patients treated with hypo-fractionated VMAT (67.6 Gy/26 Fr) 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), generated by in-house software. We compared the 3D patient dose estimated by 3DVH and that calculated by the treatment planning system. We evaluated the correlation between dose estimation error and MLC position error. Results: 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 and V55 to the rectum and bladder were −1.00, −0.55, −3.53 and −1.85% mm-1, respectively, for “Normal Sensitivity” and −2.89, −2.39, −6.24 and −4.11% mm-1, respectively, for “High Sensitivity”, showing significant better accuracy for “Normal Sensitivity” than “High Sensitivity”. Conclusion: Our results showed that 3DVH had some residual error for both sensitivities, indicating the MGDR could capture a part of the induced error but not all of the induced error.Furthermore, we found that “Normal Sensitivity” might have better accuracy for the DVH metric for 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.

Purpose: 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 self-control 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. Methods: 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. Results: 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. Free breathing 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. Free breathing and all coaching techniques differed significantly (p < 0.05). 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. Conclusion: 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.

The recent proposal on the correspondence between the ${\cal N}=4$ super Yang-Mills theory and string theory in the Penrose limit of the AdS$_5\times$S$^5$ geometry involves a few puzzles from the viewpoint of holographic principle, especially in connection with the interpretation of times. To resolve these puzzles, we propose to interpret the PP-wave strings on the basis of tunneling null geodesics connecting boundaries of the AdS geometry. Our approach predicts a direct and systematic identification of the S-matrix of Euclidean string theory in the bulk with the short-distance structure of correlation functions of super Yang-Mills theory on the AdS boundary, as an extension of the ordinary relation in supergravity-CFT correspondence. Holography requires an infinite number of contact terms for interaction vertices of string field theory and constrains their forms in a way consistent with supersymmetry., Comment: Section 3 is revised, and a note added explaining the status of our prediction

1.022-1.057, p < 0.001) and locoregional control (HR Z 1.036 per 10 cc increase, 95% CI Z 1.012-1.061, p Z 0.004), while SUVmax was not prognostic. In a multivariable model that included clinical data and metrics from both preand post-treatment PET, both pre-treatment MTV (HR Z 1.032 per 10 cc increase, 95% CI Z 1.002-1.062, p Z 0.033) and posttreatment SUVmax (HR Z 1.131 per unit increase, 95% CI Z 1.059 to 1.207, p < 0.001) were independent predictors of overall survival. Posttreatment SUVmax was the only significant predictor of locoregional control. Conclusions: Pre-treatment tumor burden (MTV) measured on PET is a strong predictor of clinical outcomes for NSCLC patients treated with chemoradiation therapy and may serve as a valuable stratification factor in clinical trials for this patient population. Acknowledgment: This project has been funded at least in part with Federal funds from the Department of Health and Human Services under Grant Number CA80098. Author Disclosure: N. Ohri: None. F. Duan: None. M. Machtay: None. J.J. Gorelick: None. B.S. Snyder: None. A. Alavi: None. B. Siegel: None. D.W. Johnson: None. J.D. Bradley: None. A.S. DeNittis: None. M. Werner-Wasik: None.

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.

Purpose: To estimate the effects of the irregular respiratory pattern during the carbon‐beam treatment of lungcancer in the four‐dimensional treatment planning, we simulated the irregular respiratory motion by the NCAT phantom and calculated the accumulated dose for respiratory gated and ungated treatment. Method and Materials: 4D NCAT phantom was used to simulate the irregular respiratory tumor motion during several cycles of respiration. The treatment planning was performed based on the first cycle of the respiration. The cycle was subdivided into 10 phases and the prescribed dose was distributed so that all points in the planning target volume (PTV) receives more than 90 percent of the total prescribed dose. The total of 52.8 GyE was delivered from four beam ports with angles selected to be 340, 70, 20, and 110 degrees. The plan was scheduled both for ungated and gated treatment. For the respiratory‐gated treatment, the gating window was set in T40%–T60% phases. The dose calculation was based on the pencil beam algorithm. The accumulated dose was evaluated and compared between gated‐ and ungated‐ results in terms of V20, D95 and dose‐volume histogram (DVH). Results: For the ungated case the dose conformation was deteriorated compared to the ideal case where the respiratory pattern was completely the same as in the treatment planning, while, for the gated treatment, the improved dose conformation was observed in terms of both D95 and V20. Conclusion: Though the 4D planning is effective to estimate internal margin, the irregular respiratory pattern may deteriorate the conformation of the accumulated dose during the whole treatment. The gating treatment, if appropriately synchronized, is effective both for the dose conformity and the reduction of the extra dose to the normal tissues or organs at risks.