Dose and DNA damage modelling of diffusing alpha-emitters radiation therapy using Geant4.

PURPOSE: Diffusing alpha-emitters radiation therapy (DaRT) is a brachytherapy technique using α-particles to treat solid tumours. The high linear energy transfer (LET) and short range of α-particles make them good candidates for the targeted treatment of cancer. Treatment planning of DaRT requires a good understanding of the dose from α-particles and the other particles released in the 224Ra decay chain. METHODS: The Geant4 Monte Carlo toolkit has been used to simulate a DaRT seed to better understand the dose contribution from all particles and simulate the DNA damage due to this treatment. RESULTS: Close to the seed α-particles deliver the majority of dose, however at radial distances greater than 4 mm, the contribution of ß-particles is greater. The RBE has been estimated as a function of number of double strand breaks (DSBs) and complex DSBs. A maximum seed spacing of 5.5 mm and 6.5 mm was found to deliver at least 20 Gy RBE weighted dose between the seeds for RBEDSB and RBEcDSB respectively. CONCLUSIONS: The DNA damage changes with radial distance from the seed and has been found to become less complex with distance, which is potentially easier for the cell to repair. Close to the seed α-particles contribute the majority of dose, however the contribution from other particles cannot be neglected and may influence the choice of seed spacing.

Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduced radiation doses. This is essential in the context of low-dose CT lung cancer screening where accurate volumetry and characterization of pulmonary nodules in repeated CT scanning are indispensable. MATERIALS AND METHODS: A standardized CT dataset was established using an anthropomorphic chest phantom (Lungman, Kyoto Kaguku Inc., Kyoto, Japan) containing a set of 3D-printed lung nodules including six diameters (4 to 9 mm) and three morphology classes (lobular, spiculated, smooth), with an established ground truth. Images were acquired at varying radiation doses (6.04, 3.03, 1.54, 0.77, 0.41 and 0.20 mGy) and reconstructed with combinations of reconstruction kernels (soft and hard kernel) and reconstruction algorithms (ASIR-V and DLIR at low, medium and high strength). Semi-automatic volumetry measurements and subjective image quality scores recorded by five radiologists were analyzed with multiple linear regression and mixed-effect ordinal logistic regression models. RESULTS: Volumetric errors of nodules imaged with DLIR are up to 50% lower compared to ASIR-V, especially at radiation doses below 1 mGy and when reconstructed with a hard kernel. Also, across all nodule diameters and morphologies, volumetric errors are commonly lower with DLIR. Furthermore, DLIR renders higher subjective IQ, especially at the sub-mGy doses. Radiologists were up to nine times more likely to score the highest IQ-score to these images compared to those reconstructed with ASIR-V. Lung nodules with irregular margins and small diameters also had an increased likelihood (up to five times more likely) to be ascribed the best IQ scores when reconstructed with DLIR. CONCLUSION: We observed that DLIR performs as good as or even outperforms conventionally used reconstruction algorithms in terms of volumetric accuracy and subjective IQ of nodules in an anthropomorphic chest phantom. As such, DLIR potentially allows to lower the radiation dose to participants of lung cancer screening without compromising accurate measurement and characterization of lung nodules.

[Low-dose CT reconstruction based on high-dimensional partial differential equation projection recovery].

OBJECTIVE: We propose a low-dose CT reconstruction method using partial differential equation (PDE) denoising under high-dimensional constraints. METHODS: The projection data were mapped into a high-dimensional space to construct a high-dimensional representation of the data, which were updated by moving the points in the high-dimensional space. The data were denoised using partial differential equations and the CT image was reconstructed using the FBP algorithm. RESULTS: Compared with those by FBP, PWLS-QM and TGV-WLS methods, the relative root mean square error of the Shepp-Logan image reconstructed by the proposed method were reduced by 68.87%, 50.15% and 27.36%, the structural similarity values were increased by 23.50%, 8.83% and 1.62%, and the feature similarity values were increased by 17.30%, 2.71% and 2.82%, respectively. For clinical image reconstruction, the proposed method, as compared with FBP, PWLS-QM and TGV-WLS methods, resulted in reduction of the relative root mean square error by 42.09%, 31.04% and 21.93%, increased the structural similarity values by 18.33%, 13.45% and 4.63%, and increased the feature similarity values by 3.13%, 1.46% and 1.10%, respectively. CONCLUSION: The new method can effectively reduce the streak artifacts and noises while maintaining the spatial resolution in reconstructed low-dose CT images.

Image fusion-based low-dose CBCT enhancement method for visualizing miniscrew insertion in the infrazygomatic crest.

Digital dental technology covers oral cone-beam computed tomography (CBCT) image processing and low-dose CBCT dental applications. A low-dose CBCT image enhancement method based on image fusion is proposed to address the need for subzygomatic small screw insertion. Specifically, firstly, a sharpening correction module is proposed, where the CBCT image is sharpened to compensate for the loss of details in the underexposed/over-exposed region. Secondly, a visibility restoration module based on type II fuzzy sets is designed, and a contrast enhancement module using curve transformation is designed. In addition to this, we propose a perceptual fusion module that fuses visibility and contrast of oral CBCT images. As a result, the problems of overexposure/underexposure, low visibility, and low contrast that occur in oral CBCT images can be effectively addressed with consistent interpretability. The proposed algorithm was analyzed in comparison experiments with a variety of algorithms, as well as ablation experiments. After analysis, compared with advanced enhancement algorithms, this algorithm achieved excellent results in low-dose CBCT enhancement and effective observation of subzygomatic small screw implantation. Compared with the best performing method, the evaluation metric is 0.07-2 higher on both datasets. The project can be found at: https://github.com/sunpeipei2024/low-dose-CBCT .

A systematic review and meta-analysis of randomized controlled trials comparing low-dose versus standard-dose computed tomography-guided lung biopsy.

BACKGROUND: Despite the existence of several Randomized Controlled Trials (RCTs) investigating Low-Dose Computed Tomography (LDCT) as a guide in lung biopsies, conclusive findings remain elusive. To address this contention, we conducted a systematic review and meta-analysis to evaluate the efficacy and safety of LDCT-guided lung biopsies. METHODS: A comprehensive search across major databases identified RCTs comparing the effectiveness of LDCT-guided with Standard-Dose Computed Tomography (SDCT)-guided lung biopsies. Subsequently, we utilized a random-effects model meta-analysis to assess diagnostic accuracy, radiation dose, operation duration, and clinical complications associated with these procedures. RESULTS: Out of 292 scrutinized studies, six RCTs representing 922 patients were included in the final analysis. Results indicated the differences between the LDCT and SDCT groups were not different with statistical significance in terms of diagnostic accuracy rates (Intent-to-Treat (ITT) populations: Relative Risk (RR) 1.01, 95% Confidence interval [CI] 0.97-1.06, p = 0.61; Per-Protocol (PP) populations: RR 1.01, 95% CI 0.98-1.04, p = 0.46), incidence of pneumothorax (RR 1.00, 95% CI 0.75-1.35, p = 0.98), incidence of hemoptysis (RR 0.95, 95% CI 0.63-1.43, p = 0.80), and operation duration (minutes) (Mean Differences [MD] -0.34, 95% CI -1.67-0.99, p = 0.61). Notably, LDCT group demonstrated a lower radiation dose (mGy·cm) with statistical significance (MD -188.62, 95% CI -273.90 to -103.34, p < 0.0001). CONCLUSIONS: The use of LDCT in lung biopsy procedures demonstrated equivalent efficacy and safety to standard methods while notably reducing patient radiation exposure.

Fat quantification in dual-layer detector spectral CT: How to handle iron overload, varying tube voltage and radiation dose Indices.

OBJECTIVES: Opposed to other spectral CT techniques, fat quantification in dual-layer detector CT (dlCT) has only recently been developed. The impact of concomitant iron overload and dlCT-specific protocol settings such as the dose right index (DRI), a measure of image noise and tube current, on dlCT fat quantification was unclear. Further, spectral information became newly available <120 kV. Therefore, this study's objective was to evaluate the impact of iron, changing tube voltage, and DRI on dlCT fat quantification. MATERIAL AND METHODS: Phantoms with 0 and 8mg/cm3 iron; 0 and 5mg/cm3 iodine; 0, 10, 20, 35, 50, and 100% fat and liver equivalent, respectively, were scanned with a dlCT (CT7500, Philips, the Netherlands) at 100kV/20DRI, 120kV/20DRI, 140kV/20DRI, and at 120kV/16DRI, 120kV/24DRI. Material decomposition was done for fat, liver, and iodine (A1); for fat, liver, and iron (A2); and for fat, liver, and combined reference values of iodine and iron (A3). All scans were analyzed with reference values from 120kV/20DRI. For statistics, the intraclass correlation coefficient (ICC) and Bland-Altman analyses were used. RESULTS: In phantoms with iron and iodine, results were best for A3 with a mean deviation to phantom fat of 1.3±2.6% (ICC 0.999 [95%-confidence interval 0.996-1]). The standard approach A1 yielded a deviation of -2.5±3.0% (0.998[0.994-0.999]), A2 of 6.1±4.8% (0.991[0.974-0.997]). With A3 and changing tube voltage, the maximal difference between quantified fat and the phantom ground truth occurred at 100kV with 4.6±2.1%. Differences between scans were largest between 100kV and 140kV (2.0%[-7.1-11.2]). The maximal difference of changing DRI occurred between 16 and 24 DRI with 0.4%[-2.2-3.0]. CONCLUSION: For dlCT fat quantification in the presence of iron, material decomposition with combined reference values for iodine and iron delivers the most accurate results. Tube voltage-specific calibration of reference values is advisable while the impact of the DRI on dlCT fat quantification is neglectable.

Comparison of shielding effects of over-glasses-type and regular eyewear in terms of occupational eye dose reduction.

Given the new recommendations for occupational eye lens doses, various lead glasses have been used to reduce irradiation of interventional radiologists. However, the protection afforded by lead glasses over prescription glasses (thus over-glasses-type eyewear) has not been considered in detail. We used a phantom to compare the protective effects of such eyewear and regular eyewear of 0.07 mm lead-equivalent thickness. The shielding rates behind the eyewear and on the surface of the left eye of an anthropomorphic phantom were calculated. The left eye of the phantom was irradiated at various angles and the shielding effects were evaluated. We measured the radiation dose to the left side of the phantom using RPLDs attached to the left eye and to the surface/back of the left eyewear. Over-glasses-type eyewear afforded good protection against x-rays from the left and below; the average shielding rates on the surface of the left eye ranged from 0.70-0.72. In clinical settings, scattered radiation is incident on physicians' eyes from the left and below, and through any gap in lead glasses. Over-glasses-type eyewear afforded better protection than regular eyewear of the same lead-equivalent thickness at the irradiation angles of concern in clinical settings. Although clinical evaluation is needed, we suggest over-glasses-type Pb eyewear even for physicians who do not wear prescription glasses.

Individual patient radiation dose tracking: Perceptions of radiographers in South Africa.

INTRODUCTION: Medical imaging examinations that make use of ionising radiation provide valuable information towards patient management. Literature suggests that there is a significant rise in the number of patient referrals for such examinations. The concept "individual patient radiation dose tracking" (IPRDT) is introduced to optimise radiation monitoring. Many countries across the globe explored and implemented methods to enhance and promote the justification and optimisation principles essential for patient radiation safety. In South Africa (SA), however, attention to IPRDT is limited. METHODS: A qualitative research design was employed. Radiographers in the Western Cape Province of SA were purposefully sampled for participation in one-on-one, semi-structured interviews. Thematic analysis was applied to the transcribed interview data. RESULTS: This paper presents a theme developed from the radiographer cohort of ten (10) participants. The theme: the need for creating awareness and implementing legislative support structures, was developed from the data, with the following supporting subthemes: 1) stakeholder awareness and 'buy-in' 2) continuous professional development and 3) mandated practice. CONCLUSION: This study provides findings that are of value for patient radiation safety in SA by giving a voice to local stakeholders. Other countries that are conducting similar research investigations toward the integration of an IPRDT model, method, or framework, may also benefit from these findings. IMPLICATIONS FOR PRACTICE: The effective integration of IPRDT into the clinical environment requires unison amongst the relevant stakeholders and clarity on the various professionals' roles and responsibilities. The findings of this study furthermore suggest the involvement of regulatory organisations for the provision of a mandated form of practice at national and international levels.

Relationship between assistant's lens exposure and dose information during computed tomography examinations.

According to International Commission of Radiological Protection, the equivalent dose limit for the eye lens for occupational exposure is recommended to be 20 mSv yr-1, averaged over 5 years, with no single year above 50 mSv. Some studies reported the measurement of assistant's lens exposure in diagnostic computed tomography (CT) examinations, but further investigation is still required in the association between the lens dose for assistants and various dose parameters. Therefore, we measured the assistant's lens exposure using small optically stimulated luminescence dosimeters. The type of occupation, type of assistance, total scan time, total mAs, total scan length, and dose-length product (DLP) were recorded and analyzed in association with air kerma at the lens position. The assistance was classified into four types: 'assisted ventilation,' 'head holding,' 'body holding,' and 'raising patient's arm.' The air kerma of lens position was not significantly different for each assistance type (p< 0.05, Kruskal-Wallis test). Further, the lens doses for assistants correlated with DLP, but with various strengths of correlation with the assistance type and were influenced by the distance from the CT gantry. In conclusion, lens dose during assistance and DLP demonstrated the strongest correlation. 'Raising patient's arm' and 'head holding' exhibited stronger correlations, which required less table movement during the CT scan than 'assisted ventilation' and 'body holding'.

Which is a real valuable screening tool for lung cancer and measure thoracic diseases, chest radiography or low-dose computed tomography?: A review on the current status of Japan and other countries.

Chest radiography (CR) has been used as a screening tool for lung cancer and the use of low-dose computed tomography (LDCT) is not recommended in Japan. We need to reconsider whether CR really contributes to the early detection of lung cancer. In addition, we have not well discussed about other major thoracic disease detection by CR and LDCT compared with lung cancer despite of its high frequency. We review the usefulness of CR and LDCT as veridical screening tools for lung cancer and other thoracic diseases. In the case of lung cancer, many studies showed that LDCT has capability of early detection and improving outcomes compared with CR. Recent large randomized trial also supports former results. In the case of chronic obstructive pulmonary disease (COPD), LDCT contributes to early detection and leads to the implementation of smoking cessation treatments. In the case of pulmonary infections, LDCT can reveal tiny inflammatory changes that are not observed on CR, though many of these cases improve spontaneously. Therefore, LDCT screening for pulmonary infections may be less useful. CR screening is more suitable for the detection of pulmonary infections. In the case of cardiovascular disease (CVD), CR may be a better screening tool for detecting cardiomegaly, whereas LDCT may be a more useful tool for detecting vascular changes. Therefore, the current status of thoracic disease screening is that LDCT may be a better screening tool for detecting lung cancer, COPD, and vascular changes. CR may be a suitable screening tool for pulmonary infections and cardiomegaly.

Usability of sand samples in TL Radiation Dosimetry.

This study investigated natural sand thermoluminescence (TL) response as a possible option for retrospective high-dose gamma dosimetry. The natural sand under investigation was collected from six locations with selection criteria for sampling sites covering the highest probability of exposure to unexpected radiation on the Egyptian coast. Dose-response, glow curve, chemical composition, linearity, and fading rate for different sand samples were studied. Energy Dispersive X-ray Spectroscopy (EDX) analysis revealed differences in chemical composition among the various geological sites, leading to variations in TL glow curve intensity. Sand samples collected from Ras Sedr, Taba, Suez, and Enshas showed similar TL patterns, although with different TL intensities. Beach sands of Matrouh and North Coastal with a high calcite content did not show a clear linear response to the TL technique, in the dose range of 10 Gy up to 30 kGy. The results show that most sand samples are suitable as a radiation dosimeter at accidental levels of exposure. It is proposed here that for high-dose gamma dosimetry with doses ranging from 3 to 10 kGy, a single calibration factor might be enough for TL measurements using sand samples. However, proper calibration might allow dose assessment for doses even up to 30 kGy. Most of the investigated sand samples had nearly stable fading rates after seven days of storage. The Ras Sedr sands sample was the most reliable for retrospective dose reconstruction.

Breast density prediction from low and standard dose mammograms using deep learning: effect of image resolution and model training approach on prediction quality.

Purpose. To improve breast cancer risk prediction for young women, we have developed deep learning methods to estimate mammographic density from low dose mammograms taken at approximately 1/10th of the usual dose. We investigate the quality and reliability of the density scores produced on low dose mammograms focussing on how image resolution and levels of training affect the low dose predictions.Methods. Deep learning models are developed and tested, with two feature extraction methods and an end-to-end trained method, on five different resolutions of 15,290 standard dose and simulated low dose mammograms with known labels. The models are further tested on a dataset with 296 matching standard and real low dose images allowing performance on the low dose images to be ascertained.Results. Prediction quality on standard and simulated low dose images compared to labels is similar for all equivalent model training and image resolution versions. Increasing resolution results in improved performance of both feature extraction methods for standard and simulated low dose images, while the trained models show high performance across the resolutions. For the trained models the Spearman rank correlation coefficient between predictions of standard and low dose images at low resolution is 0.951 (0.937 to 0.960) and at the highest resolution 0.956 (0.942 to 0.965). If pairs of model predictions are averaged, similarity increases.Conclusions. Deep learning mammographic density predictions on low dose mammograms are highly correlated with standard dose equivalents for feature extraction and end-to-end approaches across multiple image resolutions. Deep learning models can reliably make high quality mammographic density predictions on low dose mammograms.

Thermoluminescence dosimetry (TLD) in a 3 T magnetic resonance imaging (MRI) environment: implications for personnel exposure monitoring.

Thermoluminescent dosimeters (TLDs) serve as compact and user-friendly tools for various applications, including personal radiation dosimetry and radiation therapy. This study explores the potential of utilizing TLD-100 personal dosimetry, conventionally applied in PET/CT (positron emission tomography/computed tomography) settings, in the PET/MRI (magnetic resonance imaging) environment. The integration of MRI into conventional radiotherapy and PET systems necessitates ionizing radiation dosimetry in the presence of static magnetic fields. In this study, TLD-100 dosimeters were exposed on the surface of a water-filled cylindrical phantom containing PET-radioisotope and positioned on the patient table of a 3 T PET/MRI, where the magnetic field strength is around 0.2 T, aiming to replicate real-world scenarios experienced by personnel in PET/MRI environments. Results indicate that the modified MR-safe TLD-100 personal dosimeters exhibit no significant impact from the static magnetic field of the 3 T PET/MRI, supporting their suitability for personal dosimetry in PET/MRI settings. This study addresses a notable gap in existing literature on the effect of MRI static magnetic field on TLDs.

Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT.

BACKGROUND: Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR). METHODS: Individuals were selected from the "Lifelines" cohort who had undergone low-dose chest CT. Nodules in individuals without emphysema were matched to similar-sized nodules in individuals with at least moderate emphysema. AI results for nodular findings of 30-100 mm3 and 101-300 mm3 were compared to those of HR; two expert radiologists blindly reviewed discrepancies. Sensitivity and false positives (FPs)/scan were compared for emphysema and non-emphysema groups. RESULTS: Thirty-nine participants with and 82 without emphysema were included (n = 121, aged 61 ± 8 years (mean ± standard deviation), 58/121 males (47.9%)). AI and HR detected 196 and 206 nodular findings, respectively, yielding 109 concordant nodules and 184 discrepancies, including 118 true nodules. For AI, sensitivity was 0.68 (95% confidence interval 0.57-0.77) in emphysema versus 0.71 (0.62-0.78) in non-emphysema, with FPs/scan 0.51 and 0.22, respectively (p = 0.028). For HR, sensitivity was 0.76 (0.65-0.84) and 0.80 (0.72-0.86), with FPs/scan of 0.15 and 0.27 (p = 0.230). Overall sensitivity was slightly higher for HR than for AI, but this difference disappeared after the exclusion of benign lymph nodes. FPs/scan were higher for AI in emphysema than in non-emphysema (p = 0.028), while FPs/scan for HR were higher than AI for 30-100 mm3 nodules in non-emphysema (p = 0.009). CONCLUSIONS: AI resulted in more FPs/scan in emphysema compared to non-emphysema, a difference not observed for HR. RELEVANCE STATEMENT: In the creation of a benchmark dataset to validate AI software for lung nodule detection, the inclusion of emphysema cases is important due to the additional number of FPs. KEY POINTS: • The sensitivity of nodule detection by AI was similar in emphysema and non-emphysema. • AI had more FPs/scan in emphysema compared to non-emphysema. • Sensitivity and FPs/scan by the human reader were comparable for emphysema and non-emphysema. • Emphysema and non-emphysema representation in benchmark dataset is important for validating AI.

Surface dose measurement and comparison between TLD and OSLD during modified re constructive mastectomy irradiation.

Radiotherapy (RT) is one of the major treatment modalities among surgery and chemotherapy for carcinoma breast. The surface dose study of modified reconstructive constructive Mastectomy (MRM) breast is important due to the heterogeneity in the body contour and the conventional treatment angle to save the lungs and heart from the radiation. These angular entries of radiation beam cause an unpredictable dose deposition on the body surface, which has to be monitored. Thermoluminescent dosimeter (TLD) or optically stimulated luminescent dosimeter (nano OSLD) are commonly preferable dosimeters for this purpose. The surface dose response of TLD and nano OSLD during MRM irradiation has been compared with the predicted dose from the treatment planning system (TPS). The study monitored 100 MRM patients by employing a total 500 dosimeters consisting of TLD (n = 250) and nano OSLD (n = 250), during irradiation from an Elekta Versa HD 6 MV Linear accelerator. The study observed a variance of 3.9% in the dose measurements for TLD and 3.2% for nano OSLD from the planned surface dose, with a median percentage dose of 44.02 for nano OSLD and 40.30 for TLD (p value 0.01). There was no discernible evidence of variation in dose measurements attributable to differences in field size or from patient to patient. Additionally, no variation was observed in dose measurements when comparing the placement of the dosimeter from central to off-centre positions. In comparison, a minor difference in dose measurements were noted between TLD and nano OSLD, The study's outcomes support the applicability of both TLD and nano OSLD as effective dosimeters during MRM breast irradiation for surface dose evaluation.

Influence of deep learning image reconstruction algorithm for reducing radiation dose and image noise compared to iterative reconstruction and filtered back projection for head and chest computed tomography examinations: a systematic review.

Background: The most recent advances in Computed Tomography (CT) image reconstruction technology are Deep learning image reconstruction (DLIR) algorithms. Due to drawbacks in Iterative reconstruction (IR) techniques such as negative image texture and nonlinear spatial resolutions, DLIRs are gradually replacing them. However, the potential use of DLIR in Head and Chest CT has to be examined further. Hence, the purpose of the study is to review the influence of DLIR on Radiation dose (RD), Image noise (IN), and outcomes of the studies compared with IR and FBP in Head and Chest CT examinations. Methods: We performed a detailed search in PubMed, Scopus, Web of Science, Cochrane Library, and Embase to find the articles reported using DLIR for Head and Chest CT examinations between 2017 to 2023. Data were retrieved from the short-listed studies using Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Results: Out of 196 articles searched, 15 articles were included. A total of 1292 sample size was included. 14 articles were rated as high and 1 article as moderate quality. All studies compared DLIR to IR techniques. 5 studies compared DLIR with IR and FBP. The review showed that DLIR improved IQ, and reduced RD and IN for CT Head and Chest examinations. Conclusions: DLIR algorithm have demonstrated a noted enhancement in IQ with reduced IN for CT Head and Chest examinations at lower dose compared with IR and FBP. DLIR showed potential for enhancing patient care by reducing radiation risks and increasing diagnostic accuracy.

Development of shielding evaluation and management program for O-ring type linear accelerators.

The shielding parameters can vary depending on the geometrical structure of the linear accelerators (LINAC), treatment techniques, and beam energies. Recently, the introduction of O-ring type linear accelerators is increasing. The objective of this study is to evaluate the shielding parameters of new type of linac using a dedicated program developed by us named ORSE (O-ring type Radiation therapy equipment Shielding Evaluation). The shielding evaluation was conducted for a total of four treatment rooms including Elekta Unity, Varian Halcyon, and Accuray Tomotherapy. The developed program possesses the capability to calculate transmitted dose, maximum treatable patient capacity, and shielding wall thickness based on patient data. The doses were measured for five days using glass dosimeters to compare with the results of program. The IMRT factors and use factors obtained from patient data showed differences of up to 65.0% and 33.8%, respectively, compared to safety management report. The shielding evaluation conducted in each treatment room showed that the transmitted dose at every location was below 1% of the dose limit. The results of program and measurements showed a maximum difference of 0.003 mSv/week in transmitted dose. The ORSE program allows for the shielding evaluation results to the clinical environment of each institution based on patient data.

Parameter uncertainty analysis of the equivalent lung dose coefficient for the intake of radon in mines: A review.

Radon presents significant health risks due to its short-lived progeny. The evaluation of the equivalent lung dose coefficient is crucial for assessing the potential health effects of radon exposure. This review focuses on the uncertainty analysis of the parameters associated with the calculation of the equivalent lung dose coefficient attributed to radon inhalation in mines. This analysis is complex due to various factors, such as geological conditions, ventilation rates, and occupational practices. The literature review systematically examines the sources of radon and its health effects among underground miners. It also discusses the human respiratory tract model used to calculate the equivalent lung dose coefficient and the associated parameters leading to uncertainties in the calculated lung dose. Additionally, the review covers the different methodologies employed for uncertainty quantification and their implications on dose assessment. The text discusses challenges and limitations in current research practices and provides recommendations for future studies. Accurate risk assessment and effective safety measures in mining environments require understanding and mitigating parameter uncertainties.

Reply to comment on 'Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation'.

Liew and Mairani commented on our paper 'Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation' (Shiraishiet al2024aPhys. Med. Biol.69015017), which proposed a biophysical model to predict the dose-response curve of surviving cell fractions after ultra-high dose rate irradiation following conventional dose rate irradiation by considering DNA damage yields. They suggested the need to consider oxygen concentration in our prediction model and possible issues related to the data selection process used for the benchmarking test in our paper. In this reply, we discuss the limitations of both the present model and the available experimental data for determining the model's parameters. We also demonstrate that our proposed model can reproduce the experimental survival data even when using only the experimental DNA damage data measured reliably under normoxic conditions.