[Financial Toxicity and"Support for Balancing Treatment and Work"in Cancer Treatment].

Oncologists who are active in the front lines of cancer treatment or academic research in Japan need to acquire basic knowledge and countermeasures regarding financial toxicity(FT). They should evaluate the risk that patients will have an impact on their prognosis and quality of life due to the financial burden associated with cancer treatment. To solve FT, they should(1)make efforts to prevent income loss(, 2)make efforts to reduce spending(, 3)mental support, and(4)provide comprehensive support. At university hospitals/cancer centers and medical research institutes, we should understand that "FT research for cancer treatment"and"Cancer research balancing treatment and employment" are cutting-edge cancer research from the patient's perspective. Long-term discussions with medical economists, policy makers, industry, patient groups, and other stakeholders is mandatory to radically reduce the FT of cancer patients while striving to increase the cure rate of cancer. It is important to develop oncologists and their groups who have knowledge of FT and can take measures to reduce FT by providing guidance to support the balance between treatment and work.

Assessment of the confidence interval in the multivariable normal tissue complication probability model for predicting radiation-induced liver disease in primary liver cancer.

We developed a confidence interval-(CI) assessing model in multivariable normal tissue complication probability (NTCP) modeling for predicting radiation-induced liver disease (RILD) in primary liver cancer patients using clinical and dosimetric data. Both the mean NTCP and difference in the mean NTCP (ΔNTCP) between two treatment plans of different radiotherapy modalities were further evaluated and their CIs were assessed. Clinical data were retrospectively reviewed in 322 patients with hepatocellular carcinoma (n = 215) and intrahepatic cholangiocarcinoma (n = 107) treated with photon therapy. Dose-volume histograms of normal liver were reduced to mean liver dose (MLD) based on the fraction size-adjusted equivalent uniform dose. The most predictive variables were used to build the model based on multivariable logistic regression analysis with bootstrapping. Internal validation was performed using the cross-validation leave-one-out method. Both the mean NTCP and the mean ΔNTCP with 95% CIs were calculated from computationally generated multivariate random sets of NTCP model parameters using variance-covariance matrix information. RILD occurred in 108/322 patients (33.5%). The NTCP model with three clinical and one dosimetric parameter (tumor type, Child-Pugh class, hepatitis infection status and MLD) was most predictive, with an area under the receiver operative characteristics curve (AUC) of 0.79 (95% CI 0.74-0.84). In eight clinical subgroups based on the three clinical parameters, both the mean NTCP and the mean ΔNTCP with 95% CIs were able to be estimated computationally. The multivariable NTCP model with the assessment of 95% CIs has potential to improve the reliability of the NTCP model-based approach to select the appropriate radiotherapy modality for each patient.

Calibrated uncertainty estimation for interpretable proton computed tomography image correction using Bayesian deep learning.

Integrated-type proton computed tomography (pCT) measures proton stopping power ratio (SPR) images for proton therapy treatment planning, but its image quality is degraded due to noise and scatter. Although several correction methods have been proposed, techniques that include estimation of uncertainty are limited. This study proposes a novel uncertainty-aware pCT image correction method using a Bayesian convolutional neural network (BCNN). A DenseNet-based BCNN was constructed to predict both a corrected SPR image and its uncertainty from a noisy SPR image. A total 432 noisy SPR images of 6 non-anthropomorphic and 3 head phantoms were collected with Monte Carlo simulations, while true noise-free images were calculated with known geometric and chemical components. Heteroscedastic loss and deep ensemble techniques were performed to estimate aleatoric and epistemic uncertainties by training 25 unique BCNN models. 200-epoch end-to-end training was performed for each model independently. Feasibility of the predicted uncertainty was demonstrated after applying two post-hoc calibrations and calculating spot-specific path length uncertainty distribution. For evaluation, accuracy of head SPR images and water-equivalent thickness (WET) corrected by the trained BCNN models was compared with a conventional method and non-Bayesian CNN model. BCNN-corrected SPR images represent noise-free images with high accuracy. Mean absolute error in test data was improved from 0.263 for uncorrected images to 0.0538 for BCNN-corrected images. Moreover, the calibrated uncertainty represents accurate confidence levels, and the BCNN-corrected calibrated WET was more accurate than non-Bayesian CNN with high statistical significance. Computation time for calculating one image and its uncertainties with 25 BCNN models is 0.7 s with a consumer grade GPU. Our model is able to predict accurate pCT images as well as two types of uncertainty. These uncertainties will be useful to identify potential cause of SPR errors and develop a spot-specific range margin criterion, toward elaboration of uncertainty-guided proton therapy.

Modified fast adaptive scatter kernel superposition (mfASKS) correction and its dosimetric impact on CBCT-based proton therapy dose calculation.

PURPOSE: While cone beam computed tomography (CBCT) is able to provide patient anatomical information, its image quality is severely degraded due to scatter contamination, which degrades the accuracy of CBCT-based dose distribution estimation in proton therapy. In this work, we combined two existing scatter kernel correction methods: the point-spread function (PSF)-based scatter kernel derivation method and the fast adaptive scatter kernel superposition (fASKS) model, and evaluated the impact of the modified fASKS (mfASKS) correction on the accuracy of proton dose distribution estimation. To evaluate feasibility of the mfASKS approach using accurate scatter distributions, both Monte Carlo simulations and experiments were performed for an on-board CBCT machine integrated with a proton therapy machine. METHODS: We developed a strategy to modify central intensity, constant intensity, and amplitude of the scatter kernels derived from PSFs for the fASKS model. A parameter required for the fASKS model was derived by optimizing uniformity in the mfASKS-corrected reconstructed images. Subsequently, the mfASKS model was used to remove scatter in CBCT imaging. We quantitatively compared the Hounsfield Unit (HU) and proton stopping power ratio (SPR) images for five different phantoms. To assess improvement of dose calculation accuracy, a series of proton treatment plans were produced using the CBCT images with and without the mfASKS correction. RESULTS: The accuracies of both HU and SPR intensity quantifications are improved as a result of the mfASKS correction. Mean absolute water-equivalent path length difference to the true value decreases from 10.3 to 0.934 mm for the Gammex phantom (simulation). At the same time, mfASKS is able to offer more accurate dose distributions, especially at the distal fall-off region where noticeable dose overestimation is observed in the uncorrected scenario. Mean absolute relative error of proton range in the pelvic phantom improves from 5.03% to 2.57% (experiment). CONCLUSIONS: mfASKS enables more accurate CBCT-based proton dose calculation. This technique has significant implications in image-guided radiotherapy and dose verifications in adaptive proton therapy.

Projection-domain scatter correction for cone beam computed tomography using a residual convolutional neural network.

PURPOSE: Scatter is a major factor degrading the image quality of cone beam computed tomography (CBCT). Conventional scatter correction strategies require handcrafted analytical models with ad hoc assumptions, which often leads to less accurate scatter removal. This study aims to develop an effective scatter correction method using a residual convolutional neural network (CNN). METHODS: A U-net based 25-layer CNN was constructed for CBCT scatter correction. The establishment of the model consists of three steps: model training, validation, and testing. For model training, a total of 1800 pairs of x-ray projection and the corresponding scatter-only distribution in nonanthropomorphic phantoms taken in full-fan scan were generated using Monte Carlo simulation of a CBCT scanner installed with a proton therapy system. An end-to-end CNN training was implemented with two major loss functions for 100 epochs with a mini-batch size of 10. Image rotations and flips were randomly applied to augment the training datasets during training. For validation, 200 projections of a digital head phantom were collected. The proposed CNN-based method was compared to a conventional projection-domain scatter correction method named fast adaptive scatter kernel superposition (fASKS) method using 360 projections of an anthropomorphic head phantom. Two different loss functions were applied for the same CNN to evaluate the impact of loss functions on the final results. Furthermore, the CNN model trained with full-fan projections was fine-tuned for scatter correction in half-fan scan by using transfer learning with additional 360 half-fan projection pairs of nonanthropomorphic phantoms. The tuned-CNN model for half-fan scan was compared with the fASKS method as well as the CNN-based method without the fine-tuning using additional lung phantom projections. RESULTS: The CNN-based method provides projections with significantly reduced scatter and CBCT images with more accurate Hounsfield Units (HUs) than that of the fASKS-based method. Root mean squared error of the CNN-corrected projections was improved to 0.0862 compared to 0.278 for uncorrected projections or 0.117 for the fASKS-corrected projections. The CNN-corrected reconstruction provided better HU quantification, especially in regions near the air or bone interfaces. All four image quality measures, which include mean absolute error (MAE), mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM), indicated that the CNN-corrected images were significantly better than that of the fASKS-corrected images. Moreover, the proposed transfer learning technique made it possible for the CNN model trained with full-fan projections to be applicable to remove scatters in half-fan projections after fine-tuning with only a small number of additional half-fan training datasets. SSIM value of the tuned-CNN-corrected images was 0.9993 compared to 0.9984 for the non-tuned-CNN-corrected images or 0.9990 for the fASKS-corrected images. Finally, the CNN-based method is computationally efficient - the correction time for the 360 projections only took less than 5 s in the reported experiments on a PC (4.20 GHz Intel Core-i7 CPU) with a single NVIDIA GTX 1070 GPU. CONCLUSIONS: The proposed deep learning-based method provides an effective tool for CBCT scatter correction and holds significant value for quantitative imaging and image-guided radiation therapy.

Assessment of Coronary Flow Velocity Reserve in the Left Main Trunk Using Phase-contrast MR Imaging at 3T: Comparison with 15O-labeled Water Positron Emission Tomography.

PURPOSE: The aim of this study was to verify coronary flow velocity reserve (CFVR) on the left main trunk (LMT) in comparison with myocardial flow reserve (MFR) by 15O-labeled water positron emission tomography (PET) (MFR-PET) in both the healthy adults and the patients with coronary artery disease (CAD), and to evaluate the feasibility of CFVR to detect CAD. METHODS: Eighteen healthy adults and 13 patients with CAD were evaluated. CFVR in LMT was estimated by 3T magnetic resonance imaging (MRI) with phase contrast technique. MFR-PET in the LMT territory including anterior descending artery and circumflex artery was calculated as the ratio of myocardial blood flow (MBF)-PET at stress to MBF-PET at rest. RESULTS: There was a significant positive relationship between CFVR and MFR-PET (R = 0.45, P < 0.0001). Inter-observer calculations of CFVR showed good correlation (R2 = 0.93, P < 0.0001). The CFVR in patients with CAD was significantly lower than that in healthy adults (1.90 ± 0.61 vs. 2.77 ± 1.03, respectively, P = 0.01), which were similar to the results of MFR-PET (2.23 ± 0.84 vs. 3.96 ± 1.04, respectively, P < 0.0001). For the detection of patients with CAD, the area under the curve was 0.78 (P = 0.01). The sensitivity was 0.77 and specificity was 0.72 when a cut-off of 2.15 was used. CONCLUSION: CFVR by 3T was validated with MFR-PET. CFVR could detect the patients with CAD. This method is a simple and reliable index without radiation or contrast material.

An analytical dose-averaged LET calculation algorithm considering the off-axis LET enhancement by secondary protons for spot-scanning proton therapy.

PURPOSE: To evaluate the biological effects of proton beams as part of daily clinical routine, fast and accurate calculation of dose-averaged linear energy transfer (LETd ) is required. In this study, we have developed the analytical LETd calculation method based on the pencil-beam algorithm (PBA) considering the off-axis enhancement by secondary protons. This algorithm (PBA-dLET) was then validated using Monte Carlo simulation (MCS) results. METHODS: In PBA-dLET, LET values were assigned separately for each individual dose kernel based on the PBA. For the dose kernel, we employed a triple Gaussian model which consists of the primary component (protons that undergo the multiple Coulomb scattering) and the halo component (protons that undergo inelastic, nonelastic and elastic nuclear reaction); the primary and halo components were represented by a single Gaussian and the sum of two Gaussian distributions, respectively. Although the previous analytical approaches assumed a constant LETd value for the lateral distribution of a pencil beam, the actual LETd increases away from the beam axis, because there are more scattered and therefore lower energy protons with higher stopping powers. To reflect this LETd behavior, we have assumed that the LETs of primary and halo components can take different values (LETp and LEThalo ), which vary only along the depth direction. The values of dual-LET kernels were determined such that the PBA-dLET reproduced the MCS-generated LETd distribution in both small and large fields. These values were generated at intervals of 1 mm in depth for 96 energies from 70.2 to 220 MeV and collected in the look-up table. Finally, we compared the LETd distributions and mean LETd (LETd,mean ) values of targets and organs at risk between PBA-dLET and MCS. Both homogeneous phantom and patient geometries (prostate, liver, and lung cases) were used to validate the present method. RESULTS: In the homogeneous phantom, the LETd profiles obtained by the dual-LET kernels agree well with the MCS results except for the low-dose region in the lateral penumbra, where the actual dose was below 10% of the maximum dose. In the patient geometry, the LETd profiles calculated with the developed method reproduces MCS with the similar accuracy as in the homogeneous phantom. The maximum differences in LETd,mean for each structure between the PBA-dLET and the MCS were 0.06 keV/µm in homogeneous phantoms and 0.08 keV/µm in patient geometries under all tested conditions, respectively. CONCLUSIONS: We confirmed that the dual-LET-kernel model well reproduced the MCS, not only in the homogeneous phantom but also in complex patient geometries. The accuracy of the LETd was largely improved from the single-LET-kernel model, especially at the lateral penumbra. The model is expected to be useful, especially for proper recognition of the risk of side effects when the target is next to critical organs.

Proton-induced x-ray fluorescence CT imaging.

PURPOSE: To demonstrate the feasibility of proton-induced x-ray fluorescence CT (pXFCT) imaging of gold in a small animal sized object by means of experiments and Monte Carlo (MC) simulations. METHODS: First, proton-induced gold x-ray fluorescence (pXRF) was measured as a function of gold concentration. Vials of 2.2 cm in diameter filled with 0%-5% Au solutions were irradiated with a 220 MeV proton beam and x-ray fluorescence induced by the interaction of protons, and Au was detected with a 3 × 3 mm(2) CdTe detector placed at 90° with respect to the incident proton beam at a distance of 45 cm from the vials. Second, a 7-cm diameter water phantom containing three 2.2-diameter vials with 3%-5% Au solutions was imaged with a 7-mm FWHM 220 MeV proton beam in a first generation CT scanning geometry. X-rays scattered perpendicular to the incident proton beam were acquired with the CdTe detector placed at 45 cm from the phantom positioned on a translation/rotation stage. Twenty one translational steps spaced by 3 mm at each of 36 projection angles spaced by 10° were acquired, and pXFCT images of the phantom were reconstructed with filtered back projection. A simplified geometry of the experimental data acquisition setup was modeled with the MC TOPAS code, and simulation results were compared to the experimental data. RESULTS: A linear relationship between gold pXRF and gold concentration was observed in both experimental and MC simulation data (R(2) > 0.99). All Au vials were apparent in the experimental and simulated pXFCT images. Specifically, the 3% Au vial was detectable in the experimental [contrast-to-noise ratio (CNR) = 5.8] and simulated (CNR = 11.5) pXFCT image. Due to fluorescence x-ray attenuation in the higher concentration vials, the 4% and 5% Au contrast were underestimated by 10% and 15%, respectively, in both the experimental and simulated pXFCT images. CONCLUSIONS: Proton-induced x-ray fluorescence CT imaging of 3%-5% gold solutions in a small animal sized water phantom has been demonstrated for the first time by means of experiments and MC simulations.

Intravoxel incoherent motion diffusion-weighted imaging in head and neck squamous cell carcinoma: assessment of perfusion-related parameters compared to dynamic contrast-enhanced MRI.

PURPOSE: To investigate the correlation between perfusion-related parameters obtained with intravoxel incoherent motion (IVIM) and classical perfusion parameters obtained with dynamic contrast-enhanced (DCE) magnetic resonance imaging in patients with head and neck squamous cell carcinoma (HNSCC), and to compare direct and asymptotic fitting, the pixel-by-pixel approach, and a region of interest (ROI)-based approach respectively for IVIM parameter calculation. MATERIALS AND METHODS: Seventeen patients with HNSCC were included in this retrospective study. All magnetic resonance (MR) scanning was performed using a 3T MR unit. Acquisition of IVIM was performed using single-shot spin-echo echo-planar imaging with three orthogonal gradients with 12 b-values (0, 10, 20, 30, 50, 80, 100, 200, 400, 800, 1000, and 2000). Perfusion-related parameters of perfusion fraction 'f' and the pseudo-diffusion coefficient 'D*' were calculated from IVIM data by using least square fitting with the two fitting methods of direct and asymptotic fitting, respectively. DCE perfusion was performed in a total of 64 dynamic phases with a 3.2-s phase interval. The two-compartment exchange model was used for the quantification of tumor blood volume (TBV) and tumor blood flow (TBF). Each tumor was delineated with a polygonal ROI for the calculation of f, f∙D* performed using both the pixel-by-pixel approach and the ROI-based approach. In the pixel-by-pixel approach, after fitting each pixel to obtain f, f∙D* maps, the mean value in the delineated ROI on these maps was calculated. In the ROI-based approach, the mean value of signal intensity was calculated within the ROI for each b-value in IVIM images, and then fitting was performed using these values. Correlations between f in a total of four combinations (direct or asymptotic fitting and pixel-by-pixel or ROI-based approach) and TBV were respectively analyzed using Pearson's correlation coefficients. Correlations between f∙D* and TBF were also similarly analyzed. RESULTS: In all combinations of f and TBV, f∙D* and TBF, there was a significant correlation. In the comparison of f and TBV, a moderate correlation was observed only between f obtained by direct fitting with the pixel-by-pixel approach, whereas a good correlation was observed in the comparisons using the other three combinations. In the comparison of f∙D* and TBF, a good correlation was observed only with f∙D* obtained by asymptotic fitting with the ROI-based approach. In contrast, moderate correlations were observed in the comparisons using the other three combinations. CONCLUSION: IVIM was found to be feasible for the analysis of perfusion-related parameters in patients with HNSCC. Especially, the combination of asymptotic fitting with the ROI-based approach was better correlated with DCE perfusion.

Cost-effectiveness analysis of cochlear dose reduction by proton beam therapy for medulloblastoma in childhood.

BACKGROUND: The aim of this study is to evaluate the cost-effectiveness of proton beam therapy with cochlear dose reduction compared with conventional X-ray radiotherapy for medulloblastoma in childhood. METHODS: We developed a Markov model to describe health states of 6-year-old children with medulloblastoma after treatment with proton or X-ray radiotherapy. The risks of hearing loss were calculated on cochlear dose for each treatment. Three types of health-related quality of life (HRQOL) of EQ-5D, HUI3 and SF-6D were used for estimation of quality-adjusted life years (QALYs). The incremental cost-effectiveness ratio (ICER) for proton beam therapy compared with X-ray radiotherapy was calculated for each HRQOL. Sensitivity analyses were performed to model uncertainty in these parameters. RESULTS: The ICER for EQ-5D, HUI3 and SF-6D were $21 716/QALY, $11 773/QALY, and $20 150/QALY, respectively. One-way sensitivity analyses found that the results were sensitive to discount rate, the risk of hearing loss after proton therapy, and costs of proton irradiation. Cost-effectiveness acceptability curve analysis revealed a 99% probability of proton therapy being cost effective at a societal willingness-to-pay value. CONCLUSIONS: Proton beam therapy with cochlear dose reduction improves health outcomes at a cost that is within the acceptable cost-effectiveness range from the payer's standpoint.

Accuracy and reliability assessment of CT and MR perfusion analysis software using a digital phantom.

PURPOSE: To design a digital phantom data set for computed tomography (CT) perfusion and perfusion-weighted imaging on the basis of the widely accepted tracer kinetic theory in which the true values of cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and tracer arrival delay are known and to evaluate the accuracy and reliability of postprocessing programs using this digital phantom. MATERIALS AND METHODS: A phantom data set was created by generating concentration-time curves reflecting true values for CBF (2.5-87.5 mL/100 g per minute), CBV (1.0-5.0 mL/100 g), MTT (3.4-24 seconds), and tracer delays (0-3.0 seconds). These curves were embedded in human brain images. The data were analyzed by using 13 algorithms each for CT and magnetic resonance (MR), including five commercial vendors and five academic programs. Accuracy was assessed by using the Pearson correlation coefficient (r) for true values. Delay-, MTT-, or CBV-dependent errors and correlations between time to maximum of residue function (Tmax) were also evaluated. RESULTS: In CT, CBV was generally well reproduced (r > 0.9 in 12 algorithms), but not CBF and MTT (r > 0.9 in seven and four algorithms, respectively). In MR, good correlation (r > 0.9) was observed in one-half of commercial programs, while all academic algorithms showed good correlations for all parameters. Most algorithms had delay-dependent errors, especially for commercial software, as well as CBV dependency for CBF or MTT calculation and MTT dependency for CBV calculation. Correlation was good in Tmax except for one algorithm. CONCLUSION: The digital phantom readily evaluated the accuracy and characteristics of the CT and MR perfusion analysis software. All commercial programs had delay-induced errors and/or insufficient correlations with true values, while academic programs for MR showed good correlations with true values. SUPPLEMENTAL MATERIAL: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12112618/-/DC1.

Biological effect of dose distortion by fiducial markers in spot-scanning proton therapy with a limited number of fields: a simulation study.

PURPOSE: In accurate proton spot-scanning therapy, continuous target tracking by fluoroscopic x ray during irradiation is beneficial not only for respiratory moving tumors of lung and liver but also for relatively stationary tumors of prostate. Implanted gold markers have been used with great effect for positioning the target volume by a fluoroscopy, especially for the cases of liver and prostate with the targets surrounded by water-equivalent tissues. However, recent studies have revealed that gold markers can cause a significant underdose in proton therapy. This paper focuses on prostate cancer and explores the possibility that multiple-field irradiation improves the underdose effect by markers on tumor-control probability (TCP). METHODS: A Monte Carlo simulation was performed to evaluate the dose distortion effect. A spherical gold marker was placed at several characteristic points in a water phantom. The markers were with two different diameters of 2 and 1.5 mm, both visible on fluoroscopy. Three beam arrangements of single-field uniform dose (SFUD) were examined: one lateral field, two opposite lateral fields, and three fields (two opposite lateral fields + anterior field). The relative biological effectiveness (RBE) was set to 1.1 and a dose of 74 Gy (RBE) was delivered to the target of a typical prostate size in 37 fractions. The ratios of TCP to that without the marker (TCP(r)) were compared with the parameters of the marker sizes, number of fields, and marker positions. To take into account the dependence of biological parameters in TCP model, α∕ß values of 1.5, 3, and 10 Gy (RBE) were considered. RESULTS: It was found that the marker of 1.5 mm diameter does not affect the TCPs with all α∕ß values when two or more fields are used. On the other hand, if the marker diameter is 2 mm, more than two irradiation fields are required to suppress the decrease in TCP from TCP(r) by less than 3%. This is especially true when multiple (two or three) markers are used for alignment of a patient. CONCLUSIONS: It is recommended that 1.5-mm markers be used to avoid the reduction of TCP as well as to spare the surrounding critical organs, as long as the markers are visible on x-ray fluoroscopy. When 2-mm markers are implanted, more than two fields should be used and the markers should not be placed close to the distal edge of any of the beams.

A parameter study of pencil beam proton dose distributions for the treatment of ocular melanoma utilizing spot scanning.

The results of Monte Carlo calculated dose distributions of proton treatment of ocular melanoma are presented. An efficient spot scanning method utilizing active energy modulation, which also minimizes the number of target spots was developed. We simulated various parameter values for the particle energy spread and the pencil beam diameter in order to determine values suitable for medical treatment. We found that a 2.5-mm-diameter proton beam with a 5% Gaussian energy spread was suitable for treatment of ocular melanoma while preserving vision for the typical case that we simulated. The energy spectra and the required proton current were also calculated and are reported. The results are intended to serve as a guideline for a new class of low-cost, compact accelerators.

Metastases in mediastinal and hilar lymph nodes in patients with non-small cell lung cancer: quantitative assessment with diffusion-weighted magnetic resonance imaging and apparent diffusion coefficient.

OBJECTIVE: To evaluate diffusion-weighted magnetic resonance (DW-MR) imaging for detection of metastases in lymph nodes by using quantitative analysis. METHODS: Seventy patients with non-small cell lung cancer were examined with DW and short inversion time inversion recovery (STIR) turbo-spin-echo MR imaging. Apparent diffusion coefficient of each lung cancer and lymph node was calculated from DW-MR images. Difference of the apparent diffusion coefficient in a lung cancer and a lymph node was calculated (D1). From STIR turbo-spin-echo MR images, ratios of signal intensity in a lymph node to that in a 0.9% saline phantom was calculated (lymph node-saline ratio [LSR1]). For quantitative analysis, the threshold value for a positive test was determined on a per node basis and tested for ability to enable a correct diagnosis on a per patient basis. Results of quantitative analyses of DW- and STIR-MR images were compared on a per patient basis with McNemar testing. RESULTS: Mean D1 in the lymph node group with metastases was lower than that in the group without metastases (P < 0.001). When an D1 of 0.24 x 10(-3) mm2/s was used as the positive test threshold, sensitivity, specificity, and accuracy were 69.2%, 100%, and 94.0%, respectively, on a per patient basis. There was no significant difference (P > 0.05) between quantitative analyses of DW-MR images and STIR-MR images. CONCLUSIONS: Quantitative analysis of DW-MR images enables differentiation of lymph nodes with metastasis from those without.

A web-based remote radiation treatment planning system using the remote desktop function of a computer operating system: a preliminary report.

We developed a web-based, remote radiation treatment planning system which allowed staff at an affiliated hospital to obtain support from a fully staffed central institution. Network security was based on a firewall and a virtual private network (VPN). Client computers were installed at a cancer centre, at a university hospital and at a staff home. We remotely operated the treatment planning computer using the Remote Desktop function built in to the Windows operating system. Except for the initial setup of the VPN router, no special knowledge was needed to operate the remote radiation treatment planning system. There was a time lag that seemed to depend on the volume of data traffic on the Internet, but it did not affect smooth operation. The initial cost and running cost of the system were reasonable.

Survey of stereotactic body radiation therapy in Japan by the Japan 3-D Conformal External Beam Radiotherapy Group.

PURPOSE: To recognize the current status of stereotactic body radiotherapy (SBRT) in Japan, using a nationwide survey conducted by the Japan 3-D Conformal External Beam Radiotherapy Group. METHODS AND MATERIALS: The questionnaire was sent by mail to 117 institutions. Ninety-four institutions (80%) responded by the end of November 2005. Fifty-three institutions indicated that they have already started SBRT, and 38 institutions had been reimbursed by insurance. RESULTS: A total of 1111 patients with histologically confirmed lung cancer were treated. Among these patients, 637 had T1N0M0 and 272 had T2N0M0 lung cancer. Metastatic lung cancer was found in 702 and histologically unconfirmed lung tumor in 291 patients. Primary liver cancer was found in 207 and metastatic liver cancer in 76 patients. The most frequent schedule used for primary lung cancer was 48 Gy in 4 fractions at 22 institutions (52%), followed by 50 Gy in 5 fractions at 11 institutions (26%) and 60 Gy in 8 fractions at 4 institutions (10%). The tendency was the same for metastatic lung cancer. The average number of personnel involved in SBRT was 1.8 radiation oncologists, including 1.1 certified radiation oncologists, 2.8 technologists, 0.7 nurses, and 0.6 certified quality assurance personnel and 0.3 physicists. The most frequent amount of time for treatment planning was 61-120 min, for quality assurance was 50-60 min, and for treatment was 30 min. There were 14 (0.6% of all cases) reported Grade 5 complications: 11 cases of radiation pneumonitis, 2 cases of hemoptysis, and 1 case of radiation esophagitis. CONCLUSION: The current status of SBRT in Japan was surveyed.