Radiological Physics and Technology最新文献

Comparative evaluation of quantitative analysis using two phantom-based software programs for ¹⁸F-FDG-PET/CT. 18F-FDG-PET/CT两种基于幻影的软件定量分析的比较评价。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-10-09 DOI: 10.1007/s12194-025-00974-3

Kosuke Yamashita, Kazuki Motegi, Noriaki Miyaji, Shohei Fukai, Yasuhiro Fujiwara, Takashi Terauchi

{"title":"Comparative evaluation of quantitative analysis using two phantom-based software programs for 18F-FDG-PET/CT.","authors":"Kosuke Yamashita, Kazuki Motegi, Noriaki Miyaji, Shohei Fukai, Yasuhiro Fujiwara, Takashi Terauchi","doi":"10.1007/s12194-025-00974-3","DOIUrl":"https://doi.org/10.1007/s12194-025-00974-3","url":null,"abstract":"Variability in image quality and quantitative accuracy of Fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) has been reported across institutions and devices. The Japanese Society of Nuclear Medicine (JSNM) introduced two guidelines to facilitate image quality assurance. Recently, a fully automated software, Arimaru (PDRadiopharma Inc.), has been developed to streamline this process. However, its performance relative to conventional software has not yet been fully validated. This study aimed to compare the physical parameters calculated using Arimaru and conventional software (PETquact IE, Nihon Medi-Physics Co., Ltd.) from PET images acquired using two PET/CT systems: Discovery MI and Discovery IQ (GE Healthcare). Images of the NEMA IEC Body phantom were acquired in list mode for 1800 s and reconstructed at multiple time points (30-1800 s) to simulate different noise levels. Five physical parameters (QH,10, N10, QH,10/N10, CVBG, and SUVmax) were calculated using both the methods. The results showed that the automated method accurately positioned the region of interests (ROIs) and had a strong correlation with the conventional method across all parameters (r > 0.85, p < 0.05). However, some physical parameter values from the automated method were significantly different from those obtained using conventional software program. In conclusion, the automated software showed strong concordance with the conventional method and met JSNM guidelines. Nevertheless, systematic differences in the calculated values highlight the need to understand software-specific characteristics. The adoption of such tools may promote a broader and more consistent implementation of standardized PET imaging practices.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145259636","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

Generative AI and foundation models in medical image. 生成式AI与医学图像中的基础模型。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-10-06 DOI: 10.1007/s12194-025-00968-1

Masahiro Oda

{"title":"Generative AI and foundation models in medical image.","authors":"Masahiro Oda","doi":"10.1007/s12194-025-00968-1","DOIUrl":"https://doi.org/10.1007/s12194-025-00968-1","url":null,"abstract":"In recent years, generative AI has attracted significant public attention, and its use has been rapidly expanding across a wide range of domains. From creative tasks such as text summarization, idea generation, and source code generation, to the streamlining of medical support tasks like diagnostic report generation and summarization, AI is now deeply involved in many areas. Today's breadth of AI applications is clearly distinct from what was seen before generative AI gained widespread recognition. Representative generative AI services include DALL·E 3 (OpenAI, California, USA) and Stable Diffusion (Stability AI, London, England, UK) for image generation, ChatGPT (OpenAI, California, USA), and Gemini (Google, California, USA) for text generation. The rise of generative AI has been influenced by advances in deep learning models and the scaling up of data, models, and computational resources based on the Scaling Laws. Moreover, the emergence of foundation models, which are trained on large-scale datasets and possess general-purpose knowledge applicable to various downstream tasks, is creating a new paradigm in AI development. These shifts brought about by generative AI and foundation models also profoundly impact medical image processing, fundamentally changing the framework for AI development in healthcare. This paper provides an overview of diffusion models used in image generation AI and large language models (LLMs) used in text generation AI, and introduces their applications in medical support. This paper also discusses foundation models, which are gaining attention alongside generative AI, including their construction methods and applications in the medical field. Finally, the paper explores how to develop foundation models and high-performance AI for medical support by fully utilizing national data and computational resources.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145233696","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 the reproducibility of automatic exposure control systems in general X-ray machines using a coin-based method. 用投币法评价普通x光机自动曝光控制系统的再现性。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-10-02 DOI: 10.1007/s12194-025-00973-4

Thunyarat Chusin, Ratima Wongchai, Sararat Moonkham, Thanyawee Pengpan, Kingkarn Aphiwatthanasumet

{"title":"Evaluation of the reproducibility of automatic exposure control systems in general X-ray machines using a coin-based method.","authors":"Thunyarat Chusin, Ratima Wongchai, Sararat Moonkham, Thanyawee Pengpan, Kingkarn Aphiwatthanasumet","doi":"10.1007/s12194-025-00973-4","DOIUrl":"https://doi.org/10.1007/s12194-025-00973-4","url":null,"abstract":"Automatic exposure control (AEC) in digital radiography adjusts exposure time based on the chosen milliamperage (mA) and the patient's anatomical characteristics, ensuring the delivery of an appropriate radiation dose for optimal image quality. This study aimed to evaluate the reproducibility of AEC systems in general X-ray machines under various conditions. AEC reproducibility was assessed in two general X-ray machines: the SIEMENS Multix Top and the DRGEM GXR-40S. Both systems offer three sensitivity settings (high, medium, and low). A stack of Thai ten-baht coins, consisting of one and five layers, was used as a test object and placed directly over the AEC sensor. Ten exposures were carried out for repeated measurements. Differences in mAs values and coefficients of variation (CV) were calculated, and statistical analysis was performed using the Mann-Whitney U test. Results showed that mAs values changed in response to tube voltage, sensitivity setting, object thickness, and sensor position; however, these variations remained within acceptable limits. A higher mAs value was observed at lower tube voltages (80-81 kVp), a lower sensitivity setting (D or Slow), and a five-layer coin thickness. No significant differences were observed at higher tube voltage (100 kVp) and higher sensitivity (H or Fast; p > 0.05). In conclusion, AEC reproducibility testing showed mean mAs ranges of 0.51-3.25 with a maximum CV of 2.60% for SIEMENS, and 0.37-1.62 with a maximum CV of 3.37% for DRGEM. Both systems met international standard guidelines, with a CV below 5.00%, as recommended by AAPM Report No. 150, confirming consistent mAs values under various conditions.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145207990","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

Validity of a simple spillover correction for positron emission tomography measurements in the cerebrospinal fluid region. 脑脊液区正电子发射断层扫描测量的简单溢出校正的有效性。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-10-02 DOI: 10.1007/s12194-025-00972-5

Emi Hayashi, Shin Hibino, Mitsuhito Mase

{"title":"Validity of a simple spillover correction for positron emission tomography measurements in the cerebrospinal fluid region.","authors":"Emi Hayashi, Shin Hibino, Mitsuhito Mase","doi":"10.1007/s12194-025-00972-5","DOIUrl":"https://doi.org/10.1007/s12194-025-00972-5","url":null,"abstract":"Positron emission tomography (PET) measurements in the cerebrospinal fluid (CSF) region may be overestimated because of spillover artifacts from surrounding radioactivity. In this study, we proposed a simple spillover correction method (subtraction method) and evaluated its validity. A cylindrical phantom simulating brain ventricles was used to compare the subtraction method with the geometric transfer matrix (GTM) correction approach. And the subtraction method was applied to dynamic PET images of [18F]fluorodeoxyglucose (FDG), [18F]fluorodopa (FDOPA), and [11C]raclopride (RAC), and [15O]H2O (H2O). The effects of spillover correction on CSF measurements were assessed. Both methods effectively reduced spillover artifacts in the phantom study. In dynamic PET images, after spillover correction, time-activity curves for FDG, FDOPA, and RAC approached near-zero levels in the CSF, whereas H2O continued to show increasing activity over time. This approach effectively reduces artifacts and offers the advantages of simpler volume-of-interest settings and straightforward calculation procedures.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145207940","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

The effect of pediatric chest CT examinations on lens exposure: a Monte Carlo simulation study. 儿童胸部CT检查对晶状体暴露的影响：蒙特卡罗模拟研究。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-09-29 DOI: 10.1007/s12194-025-00971-6

Takanori Masuda, Yasushi Katsunuma, Masao Kiguchi, Chikako Fujioka, Takayuki Oku, Toru Ishibashi, Takayasu Yoshitake, Shuji Abe, Kazuo Awai

{"title":"The effect of pediatric chest CT examinations on lens exposure: a Monte Carlo simulation study.","authors":"Takanori Masuda, Yasushi Katsunuma, Masao Kiguchi, Chikako Fujioka, Takayuki Oku, Toru Ishibashi, Takayasu Yoshitake, Shuji Abe, Kazuo Awai","doi":"10.1007/s12194-025-00971-6","DOIUrl":"https://doi.org/10.1007/s12194-025-00971-6","url":null,"abstract":"The aim of the study was to evaluate the degree of error between Monte Carlo simulations of pediatric lens dose outside the scan range and measured values obtained with a dosimeter. Two types of computed tomography (CT) equipment and three pediatric anthropomorphic phantoms were used, each with a nanoDot optically stimulated luminescence dosimeter (nanoDot OSLD; Landauer, Inc., Glenwood, IL, USA) mounted on its left and right lenses. The scatter dose measurements obtained from the nanoDot were compared with those predicted by the particle and heavy ion transport code system, which served as a Monte Carlo simulation tool during pediatric chest CT examinations. The error rate between the mean measured dose and the simulated dose was within 1.5% for Aquilion Genesis and within 8.0% for Revolution. We evaluated the degree of error between Monte Carlo simulations of pediatric lens dose outside the scan range and measured values obtained with a dosimeter. The Monte Carlo simulations tended to underestimate the error.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145187185","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

Efficient knowledge-based planning model construction in institutions with limited cases using plan quality metrics. 基于计划质量度量的有限案例机构高效知识规划模型构建。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-09-29 DOI: 10.1007/s12194-025-00970-7

Yusuke Suzuki, Motoharu Sasaki, Yuji Nakaguchi, Takeshi Kamomae, Yuki Kanazawa, Yuki Tominaga, Soma Sawada, Yuto Yamaji, Hitoshi Ikushima

{"title":"Efficient knowledge-based planning model construction in institutions with limited cases using plan quality metrics.","authors":"Yusuke Suzuki, Motoharu Sasaki, Yuji Nakaguchi, Takeshi Kamomae, Yuki Kanazawa, Yuki Tominaga, Soma Sawada, Yuto Yamaji, Hitoshi Ikushima","doi":"10.1007/s12194-025-00970-7","DOIUrl":"https://doi.org/10.1007/s12194-025-00970-7","url":null,"abstract":"Prostate cancer volumetric modulated arc therapy (VMAT) planning often faces challenges in the construction of high-quality RapidPlan models when the number of cases is limited. In the present study, we retrospectively scored 90 VMAT plans using Plan Quality Metrics (PQM) and Adjusted PQM (APQM) and constructed 12 RapidPlan models from various combinations of cases with high and low PQM or APQM scores, each trained on 30 cases. Six representative models were selected for a detailed evaluation, including the P_H model based on the top 30 PQM cases and the AP_H model based on the top 30 APQM cases. All models were tested on ten independent cases that exhibited varying planning difficulties. The overall plan quality was assessed using PQM scores and dose-volume histogram (DVH) metrics for targets and organs at risk (OARs). The P_H model demonstrated significantly higher PQM scores than all other models (p < 0.05), with superior consistency and improved OAR sparing. Although the AP_H model performed well, the results were inconsistent. In challenging cases, the P_H model maintained a stable quality and outperformed both manual plans and APQM-based models. These findings indicated that case selection based on the actual clinical plan quality (PQM) is more effective than selection based on theoretical dose distributions (APQM) for building robust RapidPlan models, particularly when data are limited. This method is practical for small institutions and could be further improved by standardizing the PQM-based selection criteria and optimizing priority settings to enhance the generalizability and clinical utility of knowledge-based planning.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145193235","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

Performance evaluation of a high-ratio anti-scatter grid with aluminum interspace for digital radiography image quality. 高比率铝间距防散射网格对数字射线成像质量的性能评价。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-09-26 DOI: 10.1007/s12194-025-00965-4

Tomoya Nohechi, Katsuhiro Ichikawa, Hiroki Kawashima, Daisuke Suehara

引用次数: 0

Investigation of optimal settings for deviceless respiratory synchronization in PET/CT examinations: effects of different reconstructions on image quality. PET/CT检查中无装置呼吸同步的最佳设置研究：不同重建对图像质量的影响。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-09-26 DOI: 10.1007/s12194-025-00964-5

Naoto Mori, Kunihiro Iwata, Takahiro Uno, Taku Uchibe, Atsutaka Okizaki

{"title":"Investigation of optimal settings for deviceless respiratory synchronization in PET/CT examinations: effects of different reconstructions on image quality.","authors":"Naoto Mori, Kunihiro Iwata, Takahiro Uno, Taku Uchibe, Atsutaka Okizaki","doi":"10.1007/s12194-025-00964-5","DOIUrl":"https://doi.org/10.1007/s12194-025-00964-5","url":null,"abstract":"Positron emission tomography (PET) images can be compromised by respiratory motion, leading to a decreased standardized uptake value (SUV) of the lesion and overestimation of the metabolic tumor volume (MTV). This study aimed to determine the optimal settings for auto-gating, a deviceless respiratory synchronization technique, using advanced intelligent clear-IQ engines (AiCE) and clear adaptive low-noise method (CaLM) reconstruction conditions. We performed phantom and clinical studies on 57 patients with pulmonary lesions. We acquired images at various %count settings (nongated, 30%, 50%, and 70%) using both AiCE and CaLM. In each setting, we measured the SUVmax, SUVpeak, and MTV of the lesions and calculated and compared the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) in the liver. Additionally, we visually assessed lesion blurring and image noise to confirm whether the quantitative evaluation was consistent with the visual evaluation. Considering our findings, the optimal auto-gating setting at an acquisition time of 180 s is 50% for the lower lobe in AiCE and for both the lower and middle lobes in CaLM.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151264","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

Estimation of organ and effective doses for rotational cerebral angiography using the National Cancer Institute Dosimetry System for Radiography and Fluoroscopy (NCIRF). 使用国家癌症研究所放射和透视剂量测定系统（NCIRF）估计旋转脑血管造影的器官和有效剂量。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-09-26 DOI: 10.1007/s12194-025-00969-0

Hitoshi Miyazaki, Toshioh Fujibuchi, Donghee Han, Koji Oura, Takahiro Kosoegawa, Hiroshi Hamasaki, Hideki Yoshikawa, Koichi Arimura, Toyoyuki Kato, Kousei Ishigami, Osamu Togao, Koji Yamashita

{"title":"Estimation of organ and effective doses for rotational cerebral angiography using the National Cancer Institute Dosimetry System for Radiography and Fluoroscopy (NCIRF).","authors":"Hitoshi Miyazaki, Toshioh Fujibuchi, Donghee Han, Koji Oura, Takahiro Kosoegawa, Hiroshi Hamasaki, Hideki Yoshikawa, Koichi Arimura, Toyoyuki Kato, Kousei Ishigami, Osamu Togao, Koji Yamashita","doi":"10.1007/s12194-025-00969-0","DOIUrl":"https://doi.org/10.1007/s12194-025-00969-0","url":null,"abstract":"Rotational cerebral angiography requires accurate dosimetry. The National Cancer Institute Dosimetry System for Radiography and Fluoroscopy (NCIRF), a Monte Carlo-based dosimetry software, can evaluate the organ dose (OD) and effective dose (ED) with higher accuracy than the conventional Monte Carlo software (PCXMC). We estimated the OD and ED for three-dimensional digital subtraction angiography (3D-DSA) and cone beam computed tomography (CBCT) using the NCIRF, reflecting dose variations during rotational cerebral angiography. The 3D-DSA and CBCT simulation parameters were obtained by rotational imaging of a physical head phantom using the Artis Q biplane system. The air kerma area product for each projection was determined based on the ratio of the tube current-time product for each projection; the NCIRF was used with male and female voxel-type reference computational phantoms. To validate the simulation results, the lens dose of the phantom was measured using radiophotoluminescence glass dosimeters and compared to the simulated lens dose. The highest ODs were delivered to the brain: 8.8 mGy (males) and 11.6 mGy (females) in 3D-DSA and 50.0 mGy (males) and 59.4 mGy (females) in CBCT. The EDs were 0.27 mSv (males) and 0.35 mSv (females) in 3D-DSA and 1.49 mSv (males) and 1.83 mSv (females) in CBCT. Lens doses differed within 8.0% between measurements and simulations, with 45.9-65.5% overestimation in simulations that did not account for dose variability. Simulations that considered dose variability using the NCIRF more accurately estimated OD and ED in rotational cerebral angiography.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151241","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

Dose reduction in radiotherapy treatment planning CT via deep learning-based reconstruction: a single‑institution study. 基于深度学习重建的放疗治疗计划CT剂量降低：一项单机构研究。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-09-24 DOI: 10.1007/s12194-025-00967-2

Keisuke Yasui, Yuri Kasugai, Maho Morishita, Yasunori Saito, Hidetoshi Shimizu, Haruka Uezono, Naoki Hayashi

{"title":"Dose reduction in radiotherapy treatment planning CT via deep learning-based reconstruction: a single‑institution study.","authors":"Keisuke Yasui, Yuri Kasugai, Maho Morishita, Yasunori Saito, Hidetoshi Shimizu, Haruka Uezono, Naoki Hayashi","doi":"10.1007/s12194-025-00967-2","DOIUrl":"https://doi.org/10.1007/s12194-025-00967-2","url":null,"abstract":"To quantify radiation dose reduction in radiotherapy treatment-planning CT (RTCT) using a deep learning-based reconstruction (DLR; AiCE) algorithm compared with adaptive iterative dose reduction (IR; AIDR). To evaluate its potential to inform RTCT-specific diagnostic reference levels (DRLs). In this single-institution retrospective study, 4-part RTCT scans (head, head and neck, lung, and pelvis) were acquired on a large-bore CT. Scans reconstructed with IR (n = 820) and DLR (n = 854) were compared. The 75th-percentile CTDIvol and DLP (CTDIIR, DLPIR vs. CTDIDLR, DLPDLR) were determined per site. Dose reduction rates were calculated as (CTDIDLR - CTDIIR)/CTDIIR × 100% and similarly for DLP. Statistical significance was assessed by the Mann-Whitney U-test. DLR yielded CTDIvol reductions of 30.4-75.4% and DLP reductions of 23.1-73.5% across sites (p < 0.001), with the greatest reductions in head and neck RTCT (CTDIvol: 75.4%; DLP: 73.5%). Variability also narrowed. Compared with published national DRLs, DLR achieved 34.8 mGy and 18.8 mGy lower CTDIvol for head and neck versus UK-DRLs and Japanese multi-institutional data, respectively. DLR substantially lowers RTCT dose indices, providing quantitative data to guide RTCT-specific DRLs and optimize clinical workflows.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145132183","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