Estimating organ dose with optimized peak dose index in cone-beam CT scans.

PURPOSE: Organ dose evaluation is important for optimizing cone beam computed tomography (CBCT) scan protocols. However, an evaluation method for various CBCT scanners is yet to be established. In this study, we developed scanner-independent conversion coefficients to estimate organ doses using appropriate peak dose (f(0)) indices. METHODS: This study included various scanners (angiography scanners and linear accelerators) and protocols for the head and body (thorax, abdomen, and pelvis) scan regions. f(0) was measured at five conventional positions (center position (f(0)c) and four peripheral positions (f(0)p) at 90° intervals) in the CT dose index (CTDI) phantom. To identify appropriate measurement positions for organ dose estimation, various f(0) indices were considered. Organ doses were measured by using optically stimulated luminescence dosimeters positioned in an anthropomorphic phantom. Thereafter, the conversion coefficients were calculated from each obtained f(0) value and organ or tissue dose using a linear fit for all scanners, and the coefficient of variation (CV) of the conversion coefficients was calculated for each organ or tissue. The f(0) index with the minimum CV value was proposed as the appropriate index. RESULTS: The appropriate f(0) index was determined as f(0)c for the body region and a maximum of four f(0)p values for the head region. Using the proposed conversion coefficients based on the appropriate f(0) index, the organ/tissue doses were well estimated with a mean error of 14.2% across all scanners and scan regions. CONCLUSIONS: The proposed scanner-independent coefficients are useful for organ dose evaluation using CBCT scanners.

Impact of Dose Perturbations Around Brachytherapy Seeds in External-Beam Radiotherapy Planning: A Fundamental and Clinical Validation Using Treatment Planning System-Based Monte Carlo Simulations.

Background This study evaluates dose perturbations caused by nonradioactive seeds in clinical cases by employing treatment planning system-based Monte Carlo (TPS-MC) simulation. Methodology We investigated dose perturbation using a water-equivalent phantom and 20 clinical cases of prostate cancer (10 cases with seeds and 10 cases without seeds) treated at Fujita Health University Hospital, Japan. First, dose calculations for a simple geometry were performed using the RayStation MC algorithm for a water-equivalent phantom with and without a seed. TPS-independent Monte Carlo (full-MC) simulations and film measurements were conducted to verify the accuracy of TPS-MC simulation. Subsequently, dose calculations using TPS-MC were performed on CT images of clinical cases of prostate cancer with and without seeds, and the dose distributions were compared. Results In clinical cases, dose calculations using MC simulations revealed hotspots around the seeds. However, the size of the hotspot was not correlated with the number of seeds. The maximum difference in dose perturbation between TPS-MC simulations and film measurements was 3.9%, whereas that between TPS-MC simulations and full-MC simulations was 3.7%. The dose error of TPS-MC was negligible for multiple beams or rotational irradiation. Conclusions Hotspots were observed in dose calculations using TPS-MC performed on CT images of clinical cases with seeds. The dose calculation accuracy around the seeds using TPS-MC simulations was comparable to that of film measurements and full-MC simulations, with differences within 3.9%. Although the clinical impact of hotspots occurring around the seeds is minimal, utilizing MC simulations on TPSs can be beneficial to verify their presence.

Validation of deep learning-based CT image reconstruction for treatment planning.

Deep learning-based CT image reconstruction (DLR) is a state-of-the-art method for obtaining CT images. This study aimed to evaluate the usefulness of DLR in radiotherapy. Data were acquired using a large-bore CT system and an electron density phantom for radiotherapy. We compared the CT values, image noise, and CT value-to-electron density conversion table of DLR and hybrid iterative reconstruction (H-IR) for various doses. Further, we evaluated three DLR reconstruction strength patterns (Mild, Standard, and Strong). The variations of CT values of DLR and H-IR were large at low doses, and the difference in average CT values was insignificant with less than 10 HU at doses of 100 mAs and above. DLR showed less change in CT values and smaller image noise relative to H-IR. The noise-reduction effect was particularly large in the low-dose region. The difference in image noise between DLR Mild and Standard/Strong was large, suggesting the usefulness of reconstruction intensities higher than Mild. DLR showed stable CT values and low image noise for various materials, even at low doses; particularly for Standard or Strong, the reduction in image noise was significant. These findings indicate the usefulness of DLR in treatment planning using large-bore CT systems.

Simple quality assurance based on filtered back projection for geometrical/irradiation accuracy in single-isocenter multiple-target stereotactic radiotherapy.

In single-isocenter multiple-target stereotactic radiotherapy (SIMT-SRT), it is difficult to evaluate both the geometrical accuracy and absorbed dose measurement when irradiating off-isocenter targets. This study aimed to develop a simple quality assurance (QA) method to evaluate off-isocenter irradiation position accuracy in SIMT-SRT and compare its feasibility with that of a commercial device. First, we created two types of inserts and metallic balls with a diameter of 5 mm to be inserted into a commercially available phantom (SIMT phantom). Second, we developed a dedicated analysis software using Python for the Winston-Lutz test (WLT). Third, an image processing software, including the filtered back-projection algorithm, was developed to analyze the images obtained using an electronic portal imaging device (EPID). Fourth, the feasibility of our method was evaluated by comparing it with the results of WLT using two commercially available phantoms: WL-QA and MultiMet-WL cubes. Notably, 92% of the results in one-dimensional deviations were within 0.26 mm (EPID pixel width). The correlation coefficients were 0.52, 0.92, and 0.96 in the left-right, superior-inferior, and anterior-posterior directions, respectively. In the WLT, a maximum two-dimensional deviation of 0.70 mm was detected in our method, while the deviation in the other method was within 0.5 mm. The advantage of our method is that it can evaluate the geometrical accuracy at any gantry angle during dynamic rotation irradiation using a filtered back-projection algorithm, even if the target is located off the isocenter. Our method can perform WLT at arbitrary positions and is suitable for the QA of dynamic rotation irradiation using an EPID.

Spatial distribution of 137Cs concentrations in mushrooms (Boletus hiratsukae) and their relationship with soil exchangeable cation contents.

The activity concentrations of radiocesium (137Cs) in wild mushrooms are reported to vary according to species, genus or ecological types. In addition, the concentration fluctuates among the same species collected within the same area. Therefore, we investigated whether the 137Cs concentration of wild mushrooms would be (1) spatially biased, or (2) influenced by the 137Cs or exchangeable potassium concentrations in the soils below. We set two survey plots 300 m apart in a Himalayan cedar forest in Tsukuba, Japan, where ca. 30 kBq/m2 of 137Cs was deposited after the Fukushima Nuclear Power Plant accident. From these plots, we collected fruit-bodies (fungal structures for spore production) of co-occurring Boletus hiratsukae, a mycorrhizal species, as well as from the soil below. The mean 137Cs concentrations in the fruit-bodies were significantly different between the two plots, but no difference was observed in the soil 137Cs concentration between the plots. Significant spatial autocorrelation was observed in the 137Cs concentration in the organic layer for both sites, but no significant spatial autocorrelation was observed in the 137Cs of fruit-bodies. Therefore, the variation in the 137Cs concentrations of co-occurred B. hiratsukae was not explained by spatial bias or radioactivity in the below soil. In contrast, the exchangeable potassium concentration in the soil was negatively correlated with the 137Cs in the fruit-bodies. Our results suggest that the 137Cs absorption of wild mushrooms would be suppressed by the competitive effect of exchangeable potassium in the surrounding soils.