Differences In Dose Distributions Research Articles

New technique and application of truncated CBCT processing in adaptive radiotherapy for breast cancer

ObjectiveA generative adversarial network (TCBCTNet) was proposed to generate synthetic computed tomography (sCT) from truncated low-dose cone-beam computed tomography (CBCT) and planning CT (pCT). The sCT was applied to the dose calculation of radiotherapy for patients with breast cancer. MethodsThe low-dose CBCT and pCT images of 80 female thoracic patients were used for training. The CBCT, pCT, and replanning CT (rCT) images of 20 thoracic patients and 20 patients with breast cancer were used for testing. All patients were fixed in the same posture with a vacuum pad. The CBCT images were scanned under the Fast Chest M20 protocol with a 50% reduction in projection frames compared with the standard Chest M20 protocol. Rigid registration was performed between pCT and CBCT, and deformation registration was performed between rCT and CBCT. In the training stage of the TCBCTNet, truncated CBCT images obtained from complete CBCT images by simulation were used. The input of the CBCT→CT generator was truncated CBCT and pCT, and TCBCTNet was applied to patients with breast cancer after training. The accuracy of the sCT was evaluated by anatomy and dosimetry and compared with the generative adversarial network with UNet and ResNet as the generators (named as UnetGAN, ResGAN). ResultsThe three models could improve the image quality of CBCT and reduce the scattering artifacts while preserving the anatomical geometry of CBCT. For the chest test set, TCBCTNet achieved the best mean absolute error (MAE, 21.18±3.76 HU), better than 23.06±3.90 HU in UnetGAN and 22.47±3.57 HU in ResGAN. When applied to patients with breast cancer, TCBCTNet performance decreased, and MAE was 25.34±6.09 HU. Compared with rCT, sCT by TCBCTNet showed consistent dose distribution and subtle absolute dose differences between the target and the organ at risk. The 3D gamma pass rates were 98.98%±0.64% and 99.69%±0.22% at 2 mm/2% and 3 mm/3%, respectively. Ablation experiments confirmed that pCT and content loss played important roles in TCBCTNet. ConclusionsHigh-quality sCT images could be synthesized from truncated low-dose CBCT and pCT by using the proposed TCBCTNet model. In addition, sCT could be used to accurately calculate the dose distribution for patients with breast cancer.

Interobserver Variations in Target Delineation in Intensity-Modulated Radiation Therapy for Nasopharyngeal Carcinoma and its Impact on Target Dose Coverage.

To investigate the differences between physicians in target delineation in intensity-modulated radiation therapy for nasopharyngeal carcinoma as well as their impact on target dose coverage. Ninety-nine in-hospital patients were randomly selected for retrospective analysis, and the target volumes were delineated by 2 physicians. The target volumes were integrated with the original plans, and the differential parameters, including the Dice similarity coefficient (DSC), Hausdorff distance (HD), and Jaccard similarity coefficient (JSC) were recorded. The dose-volume parameters to evaluate target dose coverage were analyzed by superimposing the same original plan to the 2 sets of images on which the target volumes were contoured by the 2 physicians. The significance of differences in target volumes and dose coverage were evaluated using statistical analysis. The target dose coverage for different sets of target volumes showed statistically significant differences, while the similarity metrics to evaluate geometric target volume differences did not. More specifically, for PGTVnx, the median DSC, JSC, and HD were 0.85, 0.74, and 11.73, respectively; for PCTV1, the median values were 0.87, 0.77, and 11.78, respectively; for PCTV2, the median values were 0.90, 0.82, and 16.12, respectively. For patients in stages T3-4, DSC, and JSC were reduced but HD was increased compared to those in stages T1-2. Dosimetric analysis indicated that, for the target volumes, significant differences between the 2 physicians were found in D95, D99, and V100 for all the target volumes (ie, PGTVnx, PCTV1, and PCTV2) across the whole group of patients, as well as in patients with disease stages T3-4 and T1-2. The target volumes delineated by the 2 physicians had a high similarity, but the maximal distances between the outer contours of the 2 sets were significantly different. In patients with advanced T stages, significant differences in dose distributions were found, stemming from the deviations of target delineation.

Bi-criteria Pareto optimization to balance irradiation time and dosimetric objectives in proton arc therapy

Objective. Proton arc therapy (PAT) is a new delivery technique that exploits the continuous rotation of the gantry to distribute the therapeutic dose over many angular windows instead of using a few static fields, as in conventional (intensity-modulated) proton therapy. Although coming along with many potential clinical and dosimetric benefits, PAT has also raised a new optimization challenge. In addition to the dosimetric goals, the beam delivery time (BDT) needs to be considered in the objective function. Considering this bi-objective formulation, the task of finding a good compromise with appropriate weighting factors can turn out to be cumbersome. Approach. We have computed Pareto-optimal plans for three disease sites: a brain, a lung, and a liver, following a method of iteratively choosing weight vectors to approximate the Pareto front with few points. Mixed-integer programming (MIP) was selected to state the bi-criteria PAT problem and to find Pareto optimal points with a suited solver. Main results. The trade-offs between plan quality and beam irradiation time (static BDT) are investigated by inspecting three plans from the Pareto front. The latter are carefully picked to demonstrate significant differences in dose distribution and delivery time depending on their location on the frontier. The results were benchmarked against IMPT and SPArc plans showing the strength of degrees of freedom coming along with MIP optimization. Significance. This paper presents for the first time the application of bi-criteria optimization to the PAT problem, which eventually permits the planners to select the best treatment strategy according to the patient conditions and clinical resources available.

Comparison of atlas-based and deep learning methods for organs at risk delineation on head-and-neck CT images using an automated treatment planning system

Background and purposeTo investigate the performance of head-and-neck (HN) organs-at-risk (OAR) automatic segmentation (AS) using four atlas-based (ABAS) and two deep learning (DL) solutions. Material and MethodsAll patients underwent iodine contrast-enhanced planning CT. Fourteen OAR were manually delineated. DL.1 and DL.2 solutions were trained with 63 mono-centric patients and > 1000 multi-centric patients, respectively. Ten and 15 patients with varied anatomies were selected for the atlas library and for testing, respectively. The evaluation was based on geometric indices (DICE coefficient and 95th percentile-Hausdorff Distance (HD95%)), time needed for manual corrections and clinical dosimetric endpoints obtained using automated treatment planning. ResultsBoth DICE and HD95% results indicated that DL algorithms generally performed better compared with ABAS algorithms for automatic segmentation of HN OAR. However, the hybrid-ABAS (ABAS.3) algorithm sometimes provided the highest agreement to the reference contours compared with the 2 DL. Compared with DL.2 and ABAS.3, DL.1 contours were the fastest to correct. For the 3 solutions, the differences in dose distributions obtained using AS contours and AS + manually corrected contours were not statistically significant. High dose differences could be observed when OAR contours were at short distances to the targets. However, this was not always interrelated. ConclusionDL methods generally showed higher delineation accuracy compared with ABAS methods for AS segmentation of HN OAR. Most ABAS contours had high conformity to the reference but were more time consuming than DL algorithms, especially when considering the computing time and the time spent on manual corrections.

Density Overrides that Best Predict Bowel Changes during Pencil Beam Scanning Proton Radiotherapy for Prostate Cancer

<h3>Purpose/Objective(s)</h3> Changes in patient anatomy during pencil beam scanning proton radiotherapy (PBSPT) can result in substantial differences in dose distribution. In patients with prostate cancer receiving elective nodal irradiation (ENI), interfraction variability in bowel position or bowel filling can highlight this uncertainty. Such changes are often managed by assessing the plan on CT dataset copies with the bowel contour overridden to other densities. The ideal Hounsfield Unit (HU) overrides remain unclear, but extremes (HU=0 water and HU=-1000 air) are often utilized. The aim of the present study is to determine the bowel density overrides that are most predictive of bowel changes during a course of PBSPT. <h3>Materials/Methods</h3> Consecutive patients, from a single institution, receiving PBSPT with ENI for intact prostate cancer were retrospectively reviewed for the period between 10/2020-12/2021. Proton radiotherapy consisted of 50.4 Gy in 28 fractions to the pelvic lymph node stations with a simultaneous integrated boost to 70 Gy in 28 fractions to the prostate. Individually contoured loops of small bowel, large bowel, and rectum were overridden to HU of 0 to -1000 in 100 HU intervals. A bowel evaluation structure, consisting of a bowel bag cropped 3 cm away from the high-risk volume, was created; its dose volume histogram was reviewed; and values for the maximum point dose (Dmax), V105%, V45Gy, V20Gy were recorded for each plan. The dosimetry of bowel override plans were compared to the patient's Quality Assurance CT (QACT) scans. The bowel override plan which most closely matched the dosimetry of each QACT for each dosimetric parameter was determined, and the prevalence of closest prediction for each override value was tabulated. <h3>Results</h3> A total of 32 QACTs from 12 patients were included. For Dmax, HU=0, HU=-100, and HU=-700 predicted most accurately with 10 (31.3%), 5 (15.6%), and 4 (12.5%) closest predictions, respectively. For V105%, HU=-700 and HU=-1000 performed best with 6 (18.8%) and 7 (21.9%), respectively. For V45, HU=0 and HU=-500 predicted best with 13 (40.6%) and 5 (15.6%), respectively. For V20, HU=0, HU=-200, and HU=-600 predicted best with 18 (56.3%), 4 (12.5%), and 3 (9.4%), respectively. Overall, HU=0, -100, -600, -700, and -1000 predicted best with 42 (32.8%), 11 (8.6%), 10 (7.8%), 12 (9.4%), and 12 (9.4%) out of the 128 total dose metrics, respectively. This created a relative bimodal distribution with peaks in the 0 to -100 and -600 to -700 ranges. The nominal plan predicted best in 13 scenarios. <h3>Conclusion</h3> Bowel density override plans remain an important tool for assessment of PBSPT robustness to bowel filling changes throughout the course of therapy as the nominal CT relatively poorly predicts QACT dosimetry. The relatively bimodal distribution of accurate predictions in this study would suggest that the most predictive overrides would be HU∼0 and HU∼-650. Future investigation into multidataset robust optimization with these overrides to improve plan robustness is planned.

Deep learning-based low-dose CT for adaptive radiotherapy of abdominal and pelvic tumors

The shape and position of abdominal and pelvic organs change greatly during radiotherapy, so image-guided radiation therapy (IGRT) is urgently needed. The world’s first integrated CT-linac platform, equipped with fan beam CT (FBCT), can provide a diagnostic-quality FBCT for achieve adaptive radiotherapy (ART). However, CT scans will bring the risk of excessive scanning radiation dose. Reducing the tube current of the FBCT system can reduce the scanning dose, but it will lead to serious noise and artifacts in the reconstructed images. In this study, we proposed a deep learning method, Content-Noise Cycle-Consistent Generative Adversarial Network (CNCycle-GAN), to improve the image quality and CT value accuracy of low-dose FBCT images to meet the requirements of adaptive radiotherapy. We selected 76 patients with abdominal and pelvic tumors who received radiation therapy. The patients received one low-dose CT scan and one normal-dose CT scan in IGRT mode during different fractions of radiotherapy. The normal dose CT images (NDCT) and low dose CT images (LDCT) of 70 patients were used for network training, and the remaining 6 patients were used to validate the performance of the network. The quality of low-dose CT images after network restoration (RCT) were evaluated in three aspects: image quality, automatic delineation performance and dose calculation accuracy. Taking NDCT images as a reference, RCT images reduced MAE from 34.34 ± 5.91 to 20.25 ± 4.27, PSNR increased from 34.08 ± 1.49 to 37.23 ± 2.63, and SSIM increased from 0.92 ± 0.08 to 0.94 ± 0.07. The P value is less than 0.01 of the above performance indicators indicated that the difference were statistically significant. The Dice similarity coefficients (DCS) between the automatic delineation results of organs at risk such as bladder, femoral heads, and rectum on RCT and the results of manual delineation by doctors both reached 0.98. In terms of dose calculation accuracy, compared with the automatic planning based on LDCT, the difference in dose distribution between the automatic planning based on RCT and the automatic planning based on NDCT were smaller. Therefore, based on the integrated CT-linac platform, combined with deep learning technology, it provides clinical feasibility for the realization of low-dose FBCT adaptive radiotherapy for abdominal and pelvic tumors.

Estimating the dose differences nearby the metal implant by means of artificial contouring errors via Monaco and Geant4

Metal artifacts cause errors in the exact delineation of implants and dose changes in radiotherapy. In this study, the dose distribution differences in the region of interest (ROI) were calculated by deliberately making contouring errors from the real size of model implants by using both Monaco treatment planning system (TPS) and Geant4 toolkit. In Sec. 2, the computed tomography images were acquired by placing known uniform cylindrical geometry titanium (Ti6Al4V) and cobalt (CoCrMo) alloys into water phantoms separately. The metal alloys were artificially contoured as 2 mm contracted and expanded from their real dimensions in Monaco TPS. The plans were generated with 6 MV photon beams for contouring of three different sizes, real, contracted and expanded, for each metal alloy. In addition, all configurations were simulated in Geant4 by using the photon energy spectrum data of the Elekta Synergy linear accelerator. Then, the 3D dose data obtained from ROIs near the implant in Monaco TPS and Geant4 were analyzed with in-house programs. In Sec. 3, the depth dose values of Geant4 were compatible with TPS calculations and ion chamber measurements. When the alloys were contoured to real dimensions, it was observed that the local isodose values have changed up to 15% in ROI. The mean dose values were found to be higher in contracted and lower in expanded contours. It was observed that ±2 mm error in contouring the implants changed the mean dose up to ±8%. In Sec. 4, this study emphasized that a few millimeters of error in contouring different implant materials can have a significant effect on dose distribution in a region close to the implant.

Assessment of dose perturbations for metal stent in photon and proton radiotherapy plans for hepatocellular carcinoma

BackgroundThe present study aimed to investigate the dosimetric impact of metal stent for photon and proton treatment plans in hepatocellular carcinoma.MethodsWith computed tomography data of a water-equivalent solid phantom, dose perturbation caused by a metal stent included in the photon and proton treatment of hepatocellular carcinoma was evaluated by comparing Eclipse and RayStation treatment planning system (TPS) to a Monte Carlo (MC) based dose calculator. Photon and proton plans were created with anterior–posterior/posterior-anterior (AP/PA) fields using a 6 MV beam and AP/PA fields of a wobbling beam using 150 MeV and a 10 cm ridge filter. The difference in dose distributions and dosimetric parameters were compared depending on the stent's positions (the bile duct (GB) and intestinal tract (GI)) and angles (0°, 45°, and 90°). Additionally, the dose variation in the target volume including the stent was comparatively evaluated through dose volume histogram (DVH) analysis. And the comparison of clinical cases was carried out in the same way.ResultsPercentage differences in the dosimetric parameters calculated by MC ranged from − 7.0 to 3.9% for the photon plan and − 33.7 to 4.3% for the proton plan, depending on the angle at which the GB and GI stents were placed, compared to those without the stent. The maximum difference was observed at the minimum dose (Dmin), which was observed in both photon and proton plans in the GB and GI stents deployed at a 90° incidence angle. The parameter differences were greater in the proton plan than in photon plan. The target volume showed various dose variations depending on positions and angles of stent for both beams. Compared with no-stent, the doses within the target volume containing the GI and GB stents for the photon beam were overestimated in the high-dose area at 0°, nearly equal within 1% at 45°, and underestimated at 90°. These doses to the proton beam were underestimated at all angles, and the amount of underdose to the target volume increased with an increase in the stent angle. However, the difference was significantly greater with the proton plan than the photon plan.ConclusionsDose perturbations within the target volume due to the presence of the metal stent were not observed in the TPS calculations for photon and proton beams, but MC was used to confirm that there are dose variations within the target volume. The MC results found that delivery of the treatment beam avoiding the stent was the best method to prevent target volume underdose.

Comparison of Dose Distribution around Central Vaginal Applicator Brachytherapy Treatment Calculated with Water Based TG43 &amp; Model Based TG186

Aim: The focus of this research was to look at the dosimetric effect and evaluate the dose difference between TG-186 and TG-43 plans for cervical carcinoma using central vaginal applicators, in order to help clinicians to choose right algorithm. Introduction: TG-43 protocol is for calculation of dose-rate distributions around photon-emitting brachytherapy sources. The radiation is assumed to be carried out through an infinite homogeneous water phantom in the TG-43 dose calculation approach. Thus any heterogeneities within or outside the patient are not taken into account. As a result the accuracy of dose calculations in places near to air or bone may be impacted. The recently published AAPM Radiation Therapy Committee Task Group 186 (TG-186) report has provided new guidelines for dose calculation and reporting in brachytherapy to address the shortcomings of the current TG-43U1 dose calculation methodology. Heterogeneity correction algorithms have only recently been made available to the BT community in contrary to external beam radiotherapy. Materials and Methods: A retrospective study including 15 patients with cervical cancer who had undergone postoperative brachytherapy was performed. External Beam Radiotherapy (EBRT) was performed with a total dose of 50 Gy in 25 fractions as 2 Gy/per fraction using conventional fractionation schedule.Based on TG-43 and TG-186 algorithms plans were done for 15 cervical patients on the Nucletron- oncentra planning system and treated with Ir-192 brachytherapy source. The plans were not re optimized and therefore the dwell positions and dwell times were identical between the two plans. Retrospectively the plans were recalculated using the TG-186 algorithms. For each patient DVH is used to calculate dose in 0.1cc CGy, 1cc CGy, 2cc CGy and 5cc CGy of OAR doses as well as prescription point doses. Results: D w,m, found small changes in Prescription doses and in D0.1 cc, D1 cc, D2 cc, D5 cc for rectum and bladder with all dose parameters for individual patients differing from TG-43 values by &lt; 1%. Conclusion: The dose difference between TG43 and TG186 algorithms is for most clinical cases not significant for target volumes and OARs. Cylinder applicators although TG43 algorithm overestimated the tissue dose the difference of dose distribution caused by the two algorithms was almost negligible because the difference of dose distribution was not much (less than 1%) and both were located around the applicator.

Analysis of Rapid arc-based Radiation Therapy on Dosimetric Parameters in Cervical Cancer Patients with and without Bone Marrow Sparing.

The standard treatment for cervical cancer is chemoradiation therapy. Pelvic radiation is associated with higher dose to bone marrow (BM) causing interrupted treatment due to haematologic toxicity with inferior outcomes. This study aims to evaluate rapid arc technique in sparing pelvic BM and dosimetric parameters for pelvis V5GY, V10GY, V20GY, V30GY, and V40GY dose. Twenty one cervical cancer patients were selected for the analysis. Planning target volume (PTV) contours, total pelvic BM and surrounding structures contours were standardised. Two rapid arc based procedures were designed for individual patient. One was done using bone marrow sparing (BMS) constraints while other was performed without BMS constraints. Data for both plans was calculated with regard to PTV, normal structures and pelvic BM. Difference in dose distribution in both groups was analysed using Wilcoxon and Friedman ANOVA test. In the presence of BM constraint a significant changes in pelvic BM dose for values of V10GY (p=0.002), V20GY (p=0.002) and V40GY (p=0.025) was observed. The coverage of PTV was found to be unaffected by adding BM constraint. The BM is radiosensitive structure so dosage is linked with haemtological toxicity. Increased dose is associated with higher grade of haematological toxicity in pelvic radiotherapy. The study suggests that adding BM constraint in plans reduced the pelvic BM dose while not affecting PTV coverage and dose to bowel, bladder and rectum. Bone marrow constraint in pelvic radiotherapy can be considered for better treatment toleration and to determine its role in decreasing haematological toxicity.

Research on new treatment mode of radiotherapy based on pseudo-medical images

Background and objectiveMulti-modal medical images with multiple feature information are beneficial for radiotherapy. A new radiotherapy treatment mode based on triangle generative adversarial network (TGAN) model was proposed to synthesize pseudo-medical images between multi-modal datasets. MethodsCBCT, MRI and CT images of 80 patients with nasopharyngeal carcinoma were selected. The TGAN model based on multi-scale discriminant network was used for data training between different image domains. The generator of the TGAN model refers to cGAN and CycleGAN, and only one generation network can establish the non-linear mapping relationship between multiple image domains. The discriminator used multi-scale discrimination network to guide the generator to synthesize pseudo-medical images that are similar to real images from both shallow and deep aspects. The accuracy of pseudo-medical images was verified in anatomy and dosimetry. ResultsIn the three synthetic directions, namely, CBCT → CT, CBCT → MRI, and MRI → CT, significant differences (p < 0.05) in the three-fold-cross validation results on PSNR and SSIM metrics between the pseudo-medical images obtained based on TGAN and the real images. In the testing stage, for TGAN, the MAE metric results in the three synthesis directions (CBCT → CT, CBCT → MRI, and MRI → CT) were presented as mean (standard deviation), which were 68.67 (5.83), 83.14 (8.48), and 79.96 (7.59), and the NMI metric results were 0.8643 (0.0253), 0.8051 (0.0268), and 0.8146 (0.0267) respectively. In terms of dose verification, the differences in dose distribution between the pseudo-CT obtained by TGAN and the real CT were minimal. The H values of the measurement results of dose uncertainty in PGTV, PGTVnd, PTV1, and PTV2 were 42.510, 43.121, 17.054, and 7.795, respectively (P < 0.05). The differences were statistically significant. The gamma pass rate (2%/2 mm) of pseudo-CT obtained by the new model was 94.94% (0.73%), and the numerical results were better than those of the three other comparison models. ConclusionsThe pseudo-medical images acquired based on TGAN were close to the real images in anatomy and dosimetry. The pseudo-medical images synthesized by the TGAN model have good application prospects in clinical adaptive radiotherapy.

Influence of optional measurement parameters in the Eclipse treatment planning system on the quality of the dosimetric model of the biomedical accelerator using the Acuros XB algorithm.

BackgroundTo properly configure a treatment planning system, a measurement data set is needed, which consists of the values required for its configuration. The aim is to obtain a dosimetric model of the beam that is as compatible as possible with the measured values. The set of required data can be supplemented with optional values. The aim of the study was to assess the influence of optional measurement data on the compliance of the calculations with the measurements.Materials and methodsDosimetric measurements, model configuration and dose distribution calculations were performed for the photon radiation beams generated by the VMS TrueBeam® linear accelerator. Beams were configured on an Eclipse™ v. 15.6 system using the Acuros v. 15.6 algorithm. The measured and calculated data were entered into the Alfard™ software for comparison with the calculated dose distributions. In the last stage, the absolute dose values at the designated points were also compared. The obtained data were statistically analysed with Statistica™ v. 13.3.ResultsThe work showed that the differences in the shape of the beam profile, depth dose and the dose value in points were not related to the use of optional data. Differences in dose distributions are within the tolerance. It cannot be determined under which conditions the use of optional data has a more favourable effect on the reflection of the actual dose values.ConclusionsThe use of optional data in modelling photon radiation beams does not significantly improve the compliance of the calculated and measured dose values.

Synthesis of pseudo-CT images from pelvic MRI images based on an MD-CycleGAN model for radiotherapy

Objective. A multi-discriminator-based cycle generative adversarial network (MD-CycleGAN) model is proposed to synthesize higher-quality pseudo-CT from MRI images. Approach. MRI and CT images obtained at the simulation stage with cervical cancer were selected to train the model. The generator adopted DenseNet as the main architecture. The local and global discriminators based on a convolutional neural network jointly discriminated the authenticity of the input image data. In the testing phase, the model was verified by a fourfold cross-validation method. In the prediction stage, the data were selected to evaluate the accuracy of the pseudo-CT in anatomy and dosimetry, and they were compared with the pseudo-CT synthesized by GAN with the generator based on the architectures of ResNet, sUNet, and FCN. Main results. There are significant differences (P < 0.05) in the fourfold cross-validation results on the peak signal-to-noise ratio and structural similarity index metrics between the pseudo-CT obtained based on MD-CycleGAN and the ground truth CT (CTgt). The pseudo-CT synthesized by MD-CycleGAN had closer anatomical information to the CTgt with a root mean square error of 47.83 ± 2.92 HU, a normalized mutual information value of 0.9014 ± 0.0212, and a mean absolute error value of 46.79 ± 2.76 HU. The differences in dose distribution between the pseudo-CT obtained by MD-CycleGAN and the CTgt were minimal. The mean absolute dose errors of Dosemax, Dosemin, and Dosemean based on the planning target volume were used to evaluate the dose uncertainty of the four pseudo-CT. The u-values of the Wilcoxon test were 55.407, 41.82, and 56.208, and the differences were statistically significant. The 2%/2 mm-based gamma pass rate (%) of the proposed method was 95.45 ± 1.91, and the comparison methods (ResNet_GAN, sUnet_GAN, and FCN_GAN) were 93.33 ± 1.20, 89.64 ± 1.63, and 87.31 ± 1.94, respectively. Significance. The pseudo-CT images obtained based on MD-CycleGAN have higher imaging quality and are closer to the CTgt in terms of anatomy and dosimetry than other GAN models.

Effect of Differences in Insert Materials of Cutout Block on Dose Distribution in Electron Radiotherapy: Comparison between Measurements and Monte Carlo Simulation

In electron beam radiotherapy, an irradiation field is created with a cutout block using a low melting point lead alloy. The block can be replaced with a lead plate as a shield. Dose distribution is expected to be affected by differences in the material and thickness of the shield. Thus, this study aimed to investigate the cause of differences in dose distribution by reproducing the electron beam irradiation condition via Monte Carlo simulation, comparing dose distribution when each shield is used and analyzing energy fluence distribution. Radiation interaction in the treatment device manufactured by Varian was assessed using the general-purpose simulation code, and the dose distribution in the water was calculated. Electron energy fluence and incident angle of the electron fluence incident on the water surface were analyzed, and the effect of the difference in the shield was investigated in the irradiation field limited to 3 cm or less. Regarding dose distribution, the deviation in the buildup area became larger when the lead plate was made thinner. A difference of 1.6-6.8% was observed on an average when comparing the buildup region of depth dose distributions except for 1×1 cm2 field. In electron energy fluence, the lower the lead thickness, the higher the low energy component, which affected the buildup region. The effect was greater as the electron beam energy increased. It was possible to evaluate the difference in scattered radiation between the low melting point lead alloy and the lead plate by MC simulation. Based on the study findings, the effect of scattered electrons generated from the block was strong as a factor.

High-resolution phantom of a nephron for radiation nephrotoxicity evaluation in biophysical simulations

&lt;abstract&gt; &lt;p&gt;Computer simulation plays an important role in medical physics. The aim of this study was to generate an accurate model to calculate the absorbed dose at the cell level in a voxelized phantom of nephrons. In order to implement a model of kidney microdosimetry, a 3D mesh phantom of a human kidney nephron, representing a cortical nephron, was digitized to create a 3D voxelized phantom of a nephron for use in Monte Carlo simulations. The phantom was fed to GATE Monte Carlo toolkits, and simulations were performed to calculate the absorbed dose/energy from alpha and electron sources over a range of energy levels. The results were compared to the results published in literature that were derived by using a stylized phantom. The dose estimated in subunits of the voxelized and stylized phantoms showed a considerable bias (average of relative differences). The maximum difference for self-absorption was 12.5%, and up to 20% for cross-absorption. The digital phantom showed very significant differences in dose distribution among the cells in different subunits of the nephron. The results demonstrated that a small dissimilarity in the size and shape of subunits can lead to a considerable difference in the microdosimetry results. The model presented in this study offers a phantom that not only presents the realistic geometry of a nephron, which has been neglected in previous stylized models, but also one that has the capability of plotting the spatial distribution of the absorbed dose for any distribution of radiopharmaceuticals in nephron cells.&lt;/p&gt; &lt;/abstract&gt;

Difference in VMAT dose distribution for prostate cancer with/without rectal gas removal and/or adaptive replanning.

We investigated differences in the volumetric-modulated arc therapy (VMAT) dose distribution in prostate cancer patients treated by rectal gas removal and/or adaptive replanning. Cone-beam computed tomography (CBCT) scans were performed daily for 22 treatments in eight prostate cancer patients with excessive rectal gas, and the CBCT images were analyzed. Rectal gas removal was performed, and irradiation was delivered after prostate matching. We compared dose-volume histograms for the daily CBCT images before and after rectal gas removal. Plan A was the original plan on CBCT images before rectal gas removal. Plan B was a single reoptimized plan on CBCT images before rectal gas removal. Plan C was the original plan on CBCT images after rectal gas removal. Plan D was a single reoptimized plan on CBCT images after rectal gas removal. D95 of the planning target volume (PTV) minus the rectum of Plan C (94.7% ± 6.6%) was significantly higher than that of Plan A (88.5% ± 10.4%). All dosimetric parameters of Plan C were improved by rectal gas removal compared with Plan A, regardless of the initial rectal gas volume. Dosimetric parameters of PTV minus the rectum of Plan B were significantly improved compared with Plan C. Additionally, the V78 of the rectal wall of Plan B (0.2% ± 0.5%) was significantly improved compared with Plan C (3.9% ± 6.3%, p = 0.003). The dosimetric parameters of Plan D were not significantly different from Plan B. The dose distribution of prostate VMAT was improved by rectal gas removal and/or adaptive replanning. An adaptive replanning on daily CBCT images might be a better method than rectal gas removal for prostate cancer patients with excessive rectal gas.

The Dose Distribution from Iridium-192 Source on Cervical Cancer Brachytherapy by Manchester System Using Monte Carlo Simulation

One treatment for cervical cancer is to use radioactive sources that directly target the cancer cell called brachytherapy. This study is aimed to determine dose distribution at phantom pelvis using the DOSXYZnrc Monte Carlo code. The phantom was derived from a CT scan image of the DICOM-type pelvis with a size of 50 × 50 × 28.8 cm obtained from Santosa Kopo Hospital. The source used was Ir-192, which makes an asymmetrical beam with a size of 0.45 × 0.09 × 0.09 cm. Monte Carlo simulation was performed to determine the dose distribution of the Ir-192 source on cervical cancer CT images based on the Manchester system. The Monte Carlo simulation was divided into two models with distance variations on the applicator. Model A used TPS data with a distance between sources of 0.9 cm, while model B had a distance between sources of 0.5 cm. The distribution of dose resulting from the Monte Carlo simulation was analyzed and compared with TPS data. The results showed that at the range of 50 %, dose distribution in model A reaches the end of 3.9 cm. When compared to the range of 50 % dose distribution at the TPS results that reaches the point of 4 cm, it produces a deviation value of 2.5 %, which is still within the tolerance range. Model A and Model B provide different dose distribution. In model B, it reaches 3.86 cm, resulting in a deviation of 1.02 %, which is still within the tolerance range. The resulting γ-index value for the 50 % dose distribution was 2.26, while the whole area's GPR value was 94.13 %. This indicates a difference in dose distribution between the two models. Therefore, the smaller the distance between the sources, the shorter the dose distribution range with relatively more uniform dose distribution.

Clinical impact of anisotropic analytical algorithm and Acuros XB dose calculation algorithms for intensity modulated radiation therapy in lung cancer patients

To evaluate dose differences predicted between using Anisotropic Analytical Algorithm (AAA) and Acuros XB (AXB) in patients diagnosed with locally advanced non-small cell lung cancer (NSCLC) treated with intensity modulated radiation therapy (IMRT). A phantom study was done to evaluate the dose prediction accuracy of AXB and AAA beyond low-density medium by comparing the calculated measurement results. Thirty-two advanced NSCLC patients were subjected to IMRT. The dose regimen was 60 Gy over 30 fractions. Effects on planning target volume (PTV) and organ-at-risk (OAR) were evaluated. Clinically acceptable treatment plans with AAA were re-calculated using AXB algorithms with two modes Dw and Dm at the same beam arrangements and multileaf collimator leaf settings as with AAA. Using AXB yielded better agreement with the measurements and the average dose difference for all points was about 0.5%. Conversely, using AAA showed a larger disagreement with measured values and the average difference was up to 5.9%. The maximum relative difference was between AXB_Dm and AAA for PTV dose (D98%). The percentage dose differences of plans calculated by AAA, AXB_Dw and AAA, AXB_Dm revealed that AAA overestimated the dose than AXB. Regarding OAR, results showed significant difference for lungs-PTV. AXB algorithm yields more accurate dose prediction than AAA in heterogeneous medium. Differences in dose distribution are observed when plans re-calculated with AXB indicating that AAA apparently overestimates dose, particularly the PTV dose. Thus, AXB algorithm should be used in preference to AAA for cases in which PTVs are involved with tissues of highly different densities, such as lung.

Application of Virtual Monochromatic Images Reconstructed by Dual-energy Computed Tomography in Radiotherapy Treatment Planning System

Virtual monochromatic images (VMI) that reconstructed on dual-energy computed tomography (DECT) have further application prospects in radiotherapy, and there is still a lack of clinical dose verification. In this study, GE Revolution CT scanner was used to perform conventional imaging and gemstone spectral imaging on the simulated head and body phantom. The CT images were imported to radiotherapy treatment planning system (TPS), and the same treatment plans were transplanted to compare the CT value and the dose distribution. The results show that the VMI can be imported into TPS for CT value-relative electron density conversion and dose calculation. Compared to conventional images, the VMI varies from 70 to 140 keV, has little difference in dose distribution of 6 MV photon treatment plan.

Dosimetric impact of FFF over FF beam using VMAT for brain neoplasms treated with radiotherapy

Abstract Background: This study was conducted to assess the dosimetric impact of FFF beam plans on high-grade brain neoplasms using the VMAT technique when compared with FF beam plans. Material and Methods: Thirty patients with high-grade brain neoplasms, who had received radiotherapy using VMAT technique retrospectively were selected for this study. All the patients were planned for VMAT using 6MV_FF beam and the same plan was re-optimized using 6MV_FFF beam keeping the same dose constraint. Radiotherapy dose distribution on planning target volume (PTV) and organs at risk (OAR), target conformity index (CI), Homogeneity Index (HI), Low dose volume in the patient (V5, V10, V20, and V30), and Integral dose to the whole body in both plans were compared. Results: The PTV coverage and OAR’s showed no significant differences in dose distribution between the FFF and FF beam VMAT planning. There was a reduction of the average maximum dose in the right eye, left eye, right optic nerve, and left optic nerve using FFF beams. The reduction in average low dose volume was observed in V5, V10, V20, V30, and Mean Dose. Also, a significant reduction was observed in the integral dose to the whole body using the FFF beam. Conclusions: Using FFF beams with VMAT is doable for the treatment of high-grade brain neoplasms, and the delivery mode of the FFF beam in VMAT may yield similar results to FF beam which should be confirmed in a large scale prospective clinical trial.