Radiological Physics and Technology最新文献_第6页

Deep learning-based approach for acquisition time reduction in ventilation SPECT in patients after lung transplantation. 基于深度学习的方法缩短肺移植术后患者通气 SPECT 的采集时间

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2024-10-23 DOI: 10.1007/s12194-024-00853-3

Masahiro Nakashima, Ryohei Fukui, Seiichiro Sugimoto, Toshihiro Iguchi

{"title":"Deep learning-based approach for acquisition time reduction in ventilation SPECT in patients after lung transplantation.","authors":"Masahiro Nakashima, Ryohei Fukui, Seiichiro Sugimoto, Toshihiro Iguchi","doi":"10.1007/s12194-024-00853-3","DOIUrl":"10.1007/s12194-024-00853-3","url":null,"abstract":"We aimed to evaluate the image quality and diagnostic performance of chronic lung allograft dysfunction (CLAD) with lung ventilation single-photon emission computed tomography (SPECT) images acquired briefly using a convolutional neural network (CNN) in patients after lung transplantation and to explore the feasibility of short acquisition times. We retrospectively identified 93 consecutive lung-transplant recipients who underwent ventilation SPECT/computed tomography (CT). We employed a CNN to distinguish the images acquired in full time from those acquired in a short time. The image quality was evaluated using the structural similarity index (SSIM) loss and normalized mean square error (NMSE). The correlation between functional volume/morphological volume (F/M) ratios of full-time SPECT images and predicted SPECT images was evaluated. Differences in the F/M ratio were evaluated using Bland-Altman plots, and the diagnostic performance was compared using the area under the curve (AUC). The learning curve, obtained using MSE, converged within 100 epochs. The NMSE was significantly lower (P < 0.001) and the SSIM was significantly higher (P < 0.001) for the CNN-predicted SPECT images compared to the short-time SPECT images. The F/M ratio of full-time SPECT images and predicted SPECT images showed a significant correlation (r = 0.955, P < 0.0001). The Bland-Altman plot revealed a bias of -7.90% in the F/M ratio. The AUC values were 0.942 for full-time SPECT images, 0.934 for predicted SPECT images and 0.872 for short-time SPECT images. Our findings suggest that a deep-learning-based approach can significantly curtail the acquisition time of ventilation SPECT, while preserving the image quality and diagnostic accuracy for CLAD.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"47-57"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Proposal of a hybrid dosimetry method for improving work efficiency in CT dose management. 提出一种提高CT剂量管理工作效率的混合剂量学方法。

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2025-02-07 DOI: 10.1007/s12194-025-00881-7

Tomokazu Shohji, Reika Tomioka, Anna Isaka, Ami Yuzawa, Nobutaka Yanano, Ryota Tsukada, Hideki Kato

{"title":"Proposal of a hybrid dosimetry method for improving work efficiency in CT dose management.","authors":"Tomokazu Shohji, Reika Tomioka, Anna Isaka, Ami Yuzawa, Nobutaka Yanano, Ryota Tsukada, Hideki Kato","doi":"10.1007/s12194-025-00881-7","DOIUrl":"10.1007/s12194-025-00881-7","url":null,"abstract":"In recent years in JAPAN, with the reform of work styles and the expansion of radiologists' duties, there has been a demand for more work improvement. Among them, many regulations surrounding computed tomography (CT) tasks require a large amount of time and manpower. In this study, we propose a hybrid method between leakage X-ray dosimetry and CT dose index (CTDI) measurement using a CTDI phantom used for CTDI measurement and elucidate the usefulness of the hybrid method. The results of the CTDI phantom generated more scattered radiation in the CT room; therefore, the previously used thoracoabdominal phantom could be replaced with the CTDI phantom. The number of exposures can be reduced by a factor of 15, work hours by 20 min, and the number of workers by two when evaluated as an average of four facilities using the hybrid method. The hybrid method enables the determination of the reproducibility of the output X-ray dose during leakage X-ray dosimetry, thereby ensuring the reliability of periodic leakage X-ray dosimetry. The use of the proposed hybrid method is reasonable because it is effective for work improvement, such as reducing work time and the number of workers.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"258-267"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143371258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effectiveness of the air-gap method for reducing radiation dose in neonate CT examinations. 气隙法降低新生儿 CT 检查辐射剂量的有效性。

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2024-11-05 DOI: 10.1007/s12194-024-00855-1

Takanori Masuda, Yoshinori Funama, Takeshi Nakaura, Tomoyasu Sato, Takayuki Oku, Atsushi Ono, Kazuo Awai

{"title":"Effectiveness of the air-gap method for reducing radiation dose in neonate CT examinations.","authors":"Takanori Masuda, Yoshinori Funama, Takeshi Nakaura, Tomoyasu Sato, Takayuki Oku, Atsushi Ono, Kazuo Awai","doi":"10.1007/s12194-024-00855-1","DOIUrl":"10.1007/s12194-024-00855-1","url":null,"abstract":"The air-gap method is a technique employed to control dose distribution and radiation scattering in medical imaging. By introducing a layer of air between the radiation source and the object, this method effectively reduces the impact of scattered radiation. The purpose of this study was to investigate the suitability of the air-gap method for radiation dose reduction in pediatric patients during computed tomography (CT) examinations. Only one type of neonate phantom is used with 64 detector-row CT scanner while helical scanning the chest. The distance between the CT table and the subject was 0 mm at the conventional method and 150 mm at the air-gap method. The values of the real-time skin dosimeter on the dorsal surface of the body, and on the left and right mammary glands and image noise are measured and compared for each method. Compared with the conventional method, it was possible to reduce the exposure dose and image noise by approximately 10% and 15%, respectively, using the air-gap method (p < 0.05). The air-gap method was useful for reducing the radiation dose during pediatric CT examinations compared with the conventional method.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"293-299"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2025-02-05 DOI: 10.1007/s12194-025-00882-6

Asuka Kikuchi, Shoichi Watanuki, Hiroshi Watabe, Manabu Tashiro

{"title":"Age-related sensitivity deterioration evaluation of positron emission tomography utilizing cross-calibration factor measurement data.","authors":"Asuka Kikuchi, Shoichi Watanuki, Hiroshi Watabe, Manabu Tashiro","doi":"10.1007/s12194-025-00882-6","DOIUrl":"10.1007/s12194-025-00882-6","url":null,"abstract":"Age-related deterioration in positron emission tomography (PET) systems can be monitored using cross-calibration scans for scanner calibration. This study aimed to evaluate changes in the sensitivity of a PET system over time using routinely collected cross-calibration factor (CCF) measurement data and NEMA sensitivity measurement data acquired at our facility. We used CCF measurement data acquired over eight years, from 2016 to 2023. The count rates were calculated from raw data. The NEMA sensitivity measurements were also performed in 2017 and 2024 to compare with the sensitivities obtained from the CCF measurements. The PET images were reconstructed using the CCF data. A region of interest (ROI) was placed at the center of the PET images and count rates from the PET images were obtained. The sensitivity changes in the CCF data showed a linear decrease in sensitivity over eight years, with a mean annual reduction rate of approximately 2.0%. A comparison of the NEMA sensitivity measurements indicated a decrease in sensitivity, with a 12% reduction over eight eight years. The sensitivity was higher at the center of the axial field of view than at the edges. The ROI data also showed a linear decrease in sensitivity. This is consistent with the CCF data. Additionally, the coefficient of variation increased towards the edge of the slice. By utilizing the CCF measurement data, we obtained age-related changes in the PET system, suggesting that the PET system used in our facility may experience an annual sensitivity deterioration of approximately 2.0%.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"268-274"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11876247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143190933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dataset augmentation with multiple contrasts images in super-resolution processing of T1-weighted brain magnetic resonance images. 在 T1 加权脑磁共振图像的超分辨率处理中使用多重对比图像进行数据集扩增。

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2024-12-16 DOI: 10.1007/s12194-024-00871-1

Hajime Kageyama, Nobukiyo Yoshida, Keisuke Kondo, Hiroyuki Akai

{"title":"Dataset augmentation with multiple contrasts images in super-resolution processing of T1-weighted brain magnetic resonance images.","authors":"Hajime Kageyama, Nobukiyo Yoshida, Keisuke Kondo, Hiroyuki Akai","doi":"10.1007/s12194-024-00871-1","DOIUrl":"10.1007/s12194-024-00871-1","url":null,"abstract":"This study investigated the effectiveness of augmenting datasets for super-resolution processing of brain Magnetic Resonance Images (MRI) T1-weighted images (T1WIs) using deep learning. By incorporating images with different contrasts from the same subject, this study sought to improve network performance and assess its impact on image quality metrics, such as peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). This retrospective study included 240 patients who underwent brain MRI. Two types of datasets were created: the Pure-Dataset group comprising T1WIs and the Mixed-Dataset group comprising T1WIs, T2-weighted images, and fluid-attenuated inversion recovery images. A U-Net-based network and an Enhanced Deep Super-Resolution network (EDSR) were trained on these datasets. Objective image quality analysis was performed using PSNR and SSIM. Statistical analyses, including paired t test and Pearson's correlation coefficient, were conducted to evaluate the results. Augmenting datasets with images of different contrasts significantly improved training accuracy as the dataset size increased. PSNR values ranged 29.84-30.26 dB for U-Net trained on mixed datasets, and SSIM values ranged 0.9858-0.9868. Similarly, PSNR values ranged 32.34-32.64 dB for EDSR trained on mixed datasets, and SSIM values ranged 0.9941-0.9945. Significant differences in PSNR and SSIM were observed between models trained on pure and mixed datasets. Pearson's correlation coefficient indicated a strong positive correlation between dataset size and image quality metrics. Using diverse image data obtained from the same subject can improve the performance of deep-learning models in medical image super-resolution tasks.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"172-185"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142830376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of gravity effect on liver and spleen volumes using multiposture MRI. 多体位MRI评价重力对肝脾体积的影响。

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2025-01-10 DOI: 10.1007/s12194-024-00870-2

Seiya Nakagawa, Tosiaki Miyati, Naoki Ohno, Yuki Oda, Haruka Kashiwagi, Satoshi Kobayashi

引用次数: 0

Water/fat separate reconstruction for body quantitative susceptibility mapping in MRI. 水/脂肪分离重建在MRI中用于身体定量敏感性制图。

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2025-01-06 DOI: 10.1007/s12194-024-00878-8

Hirohito Kan, Masahiro Nakashima, Takahiro Tsuchiya, Masato Yamada, Akio Hiwatashi

{"title":"Water/fat separate reconstruction for body quantitative susceptibility mapping in MRI.","authors":"Hirohito Kan, Masahiro Nakashima, Takahiro Tsuchiya, Masato Yamada, Akio Hiwatashi","doi":"10.1007/s12194-024-00878-8","DOIUrl":"10.1007/s12194-024-00878-8","url":null,"abstract":"This study aimed to investigate the cause of susceptibility underestimation in body quantitative susceptibility mapping (QSM) and propose a water/fat separate reconstruction to address this issue. A numerical simulation was conducted using conventional QSM with/without body masking. The conventional method with body masking underestimated the susceptibility across all regions, whereas the method without body masking estimated an equivalent value to the ground truth. Additional numerical simulations and human experiments were conducted to compare the water/fat separate reconstruction, which separately reconstructs water and fat susceptibility maps based on the water/fat separation, with conventional QSM with body masking. The proposed method improved susceptibility estimation specifically in only the water tissue. The results of the human experiments were consistent with those of the numerical simulations. The lack of phase information outside the body contributed to susceptibility underestimation in conventional QSM. The developed method addressed susceptibility underestimation only in water tissue in body QSM.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"320-328"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Radiomics and dosiomics approaches to estimate lung function after stereotactic body radiation therapy in patients with lung tumors. 放射组学和剂量组学方法评估肺肿瘤患者立体定向放射治疗后的肺功能。

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2025-01-14 DOI: 10.1007/s12194-024-00877-9

Yoshiro Ieko, Noriyuki Kadoya, Shohei Tanaka, Koyo Kikuchi, Takaya Yamamoto, Hisanori Ariga, Keiichi Jingu

{"title":"Radiomics and dosiomics approaches to estimate lung function after stereotactic body radiation therapy in patients with lung tumors.","authors":"Yoshiro Ieko, Noriyuki Kadoya, Shohei Tanaka, Koyo Kikuchi, Takaya Yamamoto, Hisanori Ariga, Keiichi Jingu","doi":"10.1007/s12194-024-00877-9","DOIUrl":"10.1007/s12194-024-00877-9","url":null,"abstract":"Lung function assessment is essential for determining the optimal treatment strategy for radiation therapy in patients with lung tumors. This study aimed to develop radiomics and dosiomics approaches to estimate pulmonary function test (PFT) results in post-stereotactic body radiation therapy (SBRT). Sixty-four patients with lung tumors who underwent SBRT were included. Models were created to estimate the PFT results at 0-6 months (Cohort 1) and 6-24 months (Cohort 2) after SBRT. Radiomics and dosiomics features were extracted from the computed tomography (CT) images and dose distributions, respectively. To estimate the PFT results, Models A (dose-volume histogram [DVH] + radiomics features) and B (DVH + radiomics + dosiomics features) were created. In the PFT results, the forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) were estimated using each model, and the ratio of FEV1 to FVC (FEV1/FVC) was calculated. The Pearson's correlation coefficient (Pearson r) and area under the curve (AUC) for FEV1/FVC (< 70%) were calculated. The models were evaluated by comparing them with the conventional calculation formulae (Conventional). The Pearson r (FEV1/FVC) values were 0.30, 0.64, and 0.69 for Conventional and Models A and B (Cohort 2), respectively, and the AUC (FEV1/FVC < 70%) values were 0.63, 0.80, and 0.78, respectively. This study demonstrates the possibility of estimating lung function after SBRT using radiomics and dosiomics features based on planning CT images and dose distributions.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"238-248"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning. 自我监督学习中基于乳腺组织结构的拼图任务的乳腺癌分类。

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2025-01-06 DOI: 10.1007/s12194-024-00874-y

Keisuke Sugawara, Eichi Takaya, Ryusei Inamori, Yuma Konaka, Jumpei Sato, Yuta Shiratori, Fumihito Hario, Tomoya Kobayashi, Takuya Ueda, Yoshikazu Okamoto

{"title":"Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning.","authors":"Keisuke Sugawara, Eichi Takaya, Ryusei Inamori, Yuma Konaka, Jumpei Sato, Yuta Shiratori, Fumihito Hario, Tomoya Kobayashi, Takuya Ueda, Yoshikazu Okamoto","doi":"10.1007/s12194-024-00874-y","DOIUrl":"10.1007/s12194-024-00874-y","url":null,"abstract":"Self-supervised learning (SSL) has gained attention in the medical field as a deep learning approach utilizing unlabeled data. The Jigsaw puzzle task in SSL enables models to learn both features of images and the positional relationships within images. In breast cancer diagnosis, radiologists evaluate not only lesion-specific features but also the surrounding breast structures. However, deep learning models that adopt a diagnostic approach similar to human radiologists are still limited. This study aims to evaluate the effectiveness of the Jigsaw puzzle task in characterizing breast tissue structures for breast cancer classification on mammographic images. Using the Chinese Mammography Database (CMMD), we compared four pre-training pipelines: (1) IN-Jig, pre-trained with both the ImageNet classification task and the Jigsaw puzzle task, (2) Scratch-Jig, pre-trained only with the Jigsaw puzzle task, (3) IN, pre-trained only with the ImageNet classification task, and (4) Scratch, that is trained from random initialization without any pre-training tasks. All pipelines were fine-tuned using binary classification to distinguish between the presence or absence of breast cancer. Performance was evaluated based on the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Additionally, detailed analysis was conducted for performance across different radiological findings, breast density, and regions of interest were visualized using gradient-weighted class activation mapping (Grad-CAM). The AUC for the four models were 0.925, 0.921, 0.918, 0.909, respectively. Our results suggest the Jigsaw puzzle task is an effective pre-training method for breast cancer classification, with the potential to enhance diagnostic accuracy with limited data.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"209-218"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11876229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Peripheral dose assessment in radiation therapy using photon beams: experimental results with optically stimulated luminescence dosimeter. 光子束放射治疗的外周剂量评估：光激发发光剂量计的实验结果。

IF 1.7

Radiological Physics and Technology Pub Date : 2025-03-01 Epub Date: 2025-01-25 DOI: 10.1007/s12194-025-00883-5

Y Retna Ponmalar, Ravikumar Manickam, Henry Finlay Godson, Kadirampatti Mani Ganesh, Sathiyan Saminathan, Varatharaj Chandraraj, Arun Raman

{"title":"Peripheral dose assessment in radiation therapy using photon beams: experimental results with optically stimulated luminescence dosimeter.","authors":"Y Retna Ponmalar, Ravikumar Manickam, Henry Finlay Godson, Kadirampatti Mani Ganesh, Sathiyan Saminathan, Varatharaj Chandraraj, Arun Raman","doi":"10.1007/s12194-025-00883-5","DOIUrl":"10.1007/s12194-025-00883-5","url":null,"abstract":"The estimation of peripheral dose (PD) is vital in cancer patients with long life expectancy. Assessment of PD to radiosensitive organs is important to determine the possible risk of late effects. An attempt has been made to assess the peripheral dose using optically stimulated luminescence dosimeter (OSLD) with megavoltage photon beams as a function of field size, depth, energy, and distance from the field edge. The PD measurements were carried out at 13 locations starting from 1.5 cm to 20.8 cm from radiation field edge for three different field sizes at three different depths with 6 and 18 MV photon beams. In addition, the measurements were carried out to analyze the response in PD due to the presence of wedge. The %PD decreases gradually with an increase in distance from the radiation field edge. The %PD at surface for 10 × 10cm2 with 6MV photon beams was 6.77 ± 0.32% and 1.0 ± 0.04% at 1.5 cm and 20.8 cm away from field edge. For 20 × 20 cm2 field, %PD was found to be much higher at surface than at 5 cm depth for all distances from field edge. This study demonstrates the suitability of OSLD for PD assessment in megavoltage photon beams. The PD increases as field size increases, primarily due to greater amount of out-of-field scatter generated by larger surface area of the collimator defining the larger field size. An enhancement in PD was observed with wedge when the thick end was oriented towards the OSLDs. This study assessed PD that would be a risk factor of the normal tissue complication and secondary cancer induction.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"275-286"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143041542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0