Radiological Physics and Technology最新文献_第6页

Dosimetric impact of material misassignment in linear Boltzmann transport equation-based external beam radiotherapy dose calculation. 基于线性玻尔兹曼输运方程的外束放疗剂量计算中材料错配的剂量学影响。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-08-23 DOI: 10.1007/s12194-025-00954-7

Perumal Murugan, Ravikumar Manickam, Tamilarasan Rajamanickam, Sivakumar Muthu, C Dinesan, Karthik Appunu, Abishake Murali

{"title":"Dosimetric impact of material misassignment in linear Boltzmann transport equation-based external beam radiotherapy dose calculation.","authors":"Perumal Murugan, Ravikumar Manickam, Tamilarasan Rajamanickam, Sivakumar Muthu, C Dinesan, Karthik Appunu, Abishake Murali","doi":"10.1007/s12194-025-00954-7","DOIUrl":"https://doi.org/10.1007/s12194-025-00954-7","url":null,"abstract":"This study evaluates the dosimetric impact of material and mass density misassignments in Acuros XB dose calculations using phantom simulations and clinical analysis in Eclipse TPS. The phantom study analyzed material and mass density misassignments in Acuros XB using virtual phantoms with a central insert assigned different materials and mass densities to simulate misassignment. A clinical analysis of 270 patient CT scans from three scanners assessed HU variations in sinonasal cavities, bladder, and liver. Dosimetric deviations were examined in 96 radiotherapy patients across these anatomical sites by comparing automatic and manual material assignments, with dose differences assessed using D98%, Dmean, and D2% for target volumes and misclassified structures. Material misassignment caused substantial dose differences, particularly in air-lung and cartilage-bone misassignments, with 12.1% and 2.8% deviations, respectively. Mass density misassignments led to dose variations of up to 5.5% for lung-air and 2% for bone. Combined misassignments amplified differences, reaching 18% for air-lung and 5.5% for cartilage-bone. Misassignment of non-biological materials such as biological tissues resulted in dose differences from 1 to 26.5%. Clinical analysis showed HU variations frequently led to material misassignment. Sinonasal air cavities were misclassified as lung, causing dose deviations of 11.8% for D98%, 8.6% for Dmean, and 2.6% for D2%. Bladder and liver were predominantly misclassified as muscle and cartilage, respectively, resulting in systematic dose deviations of approximately 1% and 0.5%. Accurate material assignment is critical for precise Acuros XB dose calculations. Material mischaracterization introduces significant dose differences, necessitating manual verification in cases where auto-assignment is prone to misassignment.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144973615","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

Thyroid radiation dose reduction with the use of thyroid shields during CT brain studies. CT脑研究中使用甲状腺屏蔽降低甲状腺辐射剂量。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-08-22 DOI: 10.1007/s12194-025-00953-8

Vimukthi Gunathilaka, Menaka Sampath, Nuwan Darshana Wickramasinghe, Mihiri Chami Wettasinghe

{"title":"Thyroid radiation dose reduction with the use of thyroid shields during CT brain studies.","authors":"Vimukthi Gunathilaka, Menaka Sampath, Nuwan Darshana Wickramasinghe, Mihiri Chami Wettasinghe","doi":"10.1007/s12194-025-00953-8","DOIUrl":"https://doi.org/10.1007/s12194-025-00953-8","url":null,"abstract":"Medical radiation plays a crucial role in diagnostic imaging; however, any exposure carries potential risks. The thyroid gland, due to its proximity to the imaging field, is particularly vulnerable to radiation during CT brain scans. This study aims to evaluate the effectiveness of lead thyroid shields in reducing the estimated absorbed dose to the thyroid gland during CT brain imaging. This cross-sectional study was conducted at a tertiary care hospital in Sri Lanka over a 3-month period. Adult patients referred for contrast-enhanced CT (CECT) brain scans, who underwent both non-contrast and contrast-enhanced imaging, were included. The estimated absorbed dose to the thyroid gland was calculated using a Dose i-R Electronic Personal Dosimeter. Radiation dose measurements were taken with and without a 0.5 mm lead thyroid shield by placing the dosimeter both above and behind the shield. The sample consisted of 32 patients. The mean (SD) effective radiation dose during the procedures was calculated as 2.325 (0.118) mGy using a standard conversion factor of 0.0021. Without the thyroid shield, the mean (SD) estimated absorbed dose was 0.748 (0.178) mGy, which decreased to 0.352 (0.113) mGy with the lead thyroid shield. There was a statistically significant reduction in estimated absorbed dose with the thyroid shielding. There was a significant reduction in the estimated absorbed dose to the thyroid region with the use of the lead thyroid shield in patients undergoing CT brain studies. These findings highlight the effectiveness of lead thyroid shielding in minimizing radiation exposure to the thyroid region.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144973594","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

Impact of dynamic jaw width adjustment in tomotherapy on hippocampus sparing and treatment efficiency in whole-brain radiotherapy. 断层治疗中动态下颌宽度调整对全脑放疗海马保留及疗效的影响。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-08-18 DOI: 10.1007/s12194-025-00951-w

Dipesh, Supratik Sen, Sandeep Singh, Manindra Bhushan, Raj Pal Singh, Abhay Kumar Singh, Mahipal, Munish Gairola

{"title":"Impact of dynamic jaw width adjustment in tomotherapy on hippocampus sparing and treatment efficiency in whole-brain radiotherapy.","authors":"Dipesh, Supratik Sen, Sandeep Singh, Manindra Bhushan, Raj Pal Singh, Abhay Kumar Singh, Mahipal, Munish Gairola","doi":"10.1007/s12194-025-00951-w","DOIUrl":"https://doi.org/10.1007/s12194-025-00951-w","url":null,"abstract":"The aim of this study is to evaluate the impact of dynamic jaw width adjustment in tomotherapy on hippocampal sparing, target dose conformity, and treatment efficiency in hippocampal-avoidance whole-brain radiotherapy (HA-WBRT), in accordance with RTOG 0933 guidelines. A retrospective study of 60 patients treated with HA-WBRT was conducted. CT-MRI fusion facilitated accurate hippocampal delineation. Treatment plans were created using Accuray Precision TPS and delivered on the Radixact Tomotherapy system with three jaw widths (1 cm, 2.5 cm, and 5 cm), fixed pitch (0.215), and modulation factor (3.0). The prescription dose was 30 Gy in 10 fractions. Evaluation metrics included PTV coverage (D98%, V95%, D2%, Dmax), homogeneity index (HI), conformity index (CI), hippocampal and lens doses, and beam-on time (BOT). Plan verification was performed with ArcCHECK using 3%/3 mm and 3%/2 mm gamma criteria. The 1 cm jaw achieved the best PTV coverage (D98% = 29.22 Gy, V95% = 98.71%), with HI = 0.09, CI = 0.99, and superior hippocampal sparing (Dmax = 14.91 Gy, Dmin = 7.57 Gy), but had the longest BOT (1165 s). Wider jaws (2.5 cm, 5 cm) reduced BOT (480 s, 280 s) but slightly compromised conformity and increased OAR doses, all within limits. Jaw width selection in Helical Tomotherapy influences dose distribution characteristics and treatment delivery efficiency in hippocampus-sparing WBRT. A 1 cm jaw width provides superior dosimetric conformity and enhanced hippocampal sparing, albeit at the cost of increased BOT. In contrast, wider jaw widths (2.5 cm and 5 cm) improve delivery efficiency but result in modest reductions in dose precision and organ-at-risk sparing. Therefore, jaw width selection should be carefully individualized based on clinical objectives, balancing the trade-off between organ preservation and treatment efficiency.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144875870","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

Effect of posture on renal volume: evaluation using multi-posture MRI. 体位对肾容积的影响：多体位MRI评价。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-08-18 DOI: 10.1007/s12194-025-00952-9

Seiya Nakagawa, Tosiaki Miyati, Naoki Ohno, Koga Kawano, Yuki Oda, Satoshi Kobayashi

引用次数: 0

Temporal image compression in cardiac computed tomography: impact of temporal super resolution and noise reduction for assessing left ventricular function. 心脏计算机断层扫描中的时间图像压缩：时间超分辨率和降噪对评估左心室功能的影响。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-08-16 DOI: 10.1007/s12194-025-00950-x

Masatoshi Kondo, Yuzo Yamasaki, Atsushi Ueno, Ryohei Funatsu, Takashi Shirasaka, Toyoyuki Kato, Kousei Ishigami

{"title":"Temporal image compression in cardiac computed tomography: impact of temporal super resolution and noise reduction for assessing left ventricular function.","authors":"Masatoshi Kondo, Yuzo Yamasaki, Atsushi Ueno, Ryohei Funatsu, Takashi Shirasaka, Toyoyuki Kato, Kousei Ishigami","doi":"10.1007/s12194-025-00950-x","DOIUrl":"https://doi.org/10.1007/s12194-025-00950-x","url":null,"abstract":"Computed tomography (CT) is valuable for assessing left ventricular (LV) function. However, it leads to increased data storage demands and energy consumption. Temporal super resolution (TSR) has the potential to reduce temporal data size while preserving accuracy. This study aimed to determine the feasibility of using TSR for temporal image compression in LV functional analysis. The study included 20 patients who underwent retrospective electrocardiogram (ECG)-gated cardiac CT, from which 20 cardiac phases per patient were acquired. TSR was applied to temporally compressed image data sets, with and without noise reduction (NR), using two NR levels: weak (30%) and strong (70%). Five data sets-including the original uncompressed data and four compressed versions-were analyzed for LV function using fully automated software. Bland-Altman plots and Pearson correlation coefficients were used to assess measurement agreement and reliability. The correlations between the uncompressed and compressed data sets for LV end-systolic volumes (ESVs), end-diastolic volumes (EDVs), and ejection fractions (EFs) were strong (all r = 1.00, 95% CI = 1.00-1.00, all Ps < 0.0001). Bland-Altman analysis showed reduced bias in LV measurements when TSR was applied without NR, while bias increased when NR was applied at both levels. The limits of agreement (LOA) were narrower for EDV but remained wider for ESV and EF. TSR without NR reduced bias but failed to narrow LOA, with EF improving or unchanged in 35% of cases. While this level of consistency is limited, the findings suggest that TSR may preserve functional accuracy under certain conditions.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144859752","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

A novel hybrid convolutional and recurrent neural network model for automatic pituitary adenoma classification using dynamic contrast-enhanced MRI. 一种新的混合卷积和循环神经网络模型用于动态增强MRI垂体腺瘤自动分类。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-08-14 DOI: 10.1007/s12194-025-00947-6

Milad Motamed, Mostafa Bastam, Seyed Mohamadreza Tabatabaie, Mohammadreza Elhaie, Daryoush Shahbazi-Gahrouei

{"title":"A novel hybrid convolutional and recurrent neural network model for automatic pituitary adenoma classification using dynamic contrast-enhanced MRI.","authors":"Milad Motamed, Mostafa Bastam, Seyed Mohamadreza Tabatabaie, Mohammadreza Elhaie, Daryoush Shahbazi-Gahrouei","doi":"10.1007/s12194-025-00947-6","DOIUrl":"https://doi.org/10.1007/s12194-025-00947-6","url":null,"abstract":"Pituitary adenomas, ranging from subtle microadenomas to mass-effect macroadenomas, pose diagnostic challenges for radiologists due to increasing scan volumes and the complexity of dynamic contrast-enhanced MRI interpretation. A hybrid CNN-LSTM model was trained and validated on a multi-center dataset of 2,163 samples from Tehran and Babolsar, Iran. Transfer learning and preprocessing techniques (e.g., Wiener filters) were utilized to improve classification performance for microadenomas (< 10 mm) and macroadenomas (> 10 mm). The model achieved 90.5% accuracy, an area under the receiver operating characteristic curve (AUROC) of 0.92, and 89.6% sensitivity (93.5% for microadenomas, 88.3% for macroadenomas), outperforming standard CNNs by 5-18% across metrics. With a processing time of 0.17 s per scan, the model demonstrated robustness to variations in imaging conditions, including scanner differences and contrast variations, excelling in real-time detection and differentiation of adenoma subtypes. This dual-path approach, the first to synergize spatial and temporal MRI features for pituitary diagnostics, offers high precision and efficiency. Supported by comparisons with existing models, it provides a scalable, reproducible tool to improve patient outcomes, with potential adaptability to broader neuroimaging challenges.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856690","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

Automatic segmentation of cone beam CT images using treatment planning CT images in patients with prostate cancer. 应用治疗计划的前列腺癌CT图像自动分割锥束CT图像。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-08-14 DOI: 10.1007/s12194-025-00946-7

Yoshiki Takayama, Noriyuki Kadoya, Takaya Yamamoto, Yuya Miyasaka, Yosuke Kusano, Tomohiro Kajikawa, Seiji Tomori, Yoshiyuki Katsuta, Shohei Tanaka, Kazuhiro Arai, Ken Takeda, Keiichi Jingu

{"title":"Automatic segmentation of cone beam CT images using treatment planning CT images in patients with prostate cancer.","authors":"Yoshiki Takayama, Noriyuki Kadoya, Takaya Yamamoto, Yuya Miyasaka, Yosuke Kusano, Tomohiro Kajikawa, Seiji Tomori, Yoshiyuki Katsuta, Shohei Tanaka, Kazuhiro Arai, Ken Takeda, Keiichi Jingu","doi":"10.1007/s12194-025-00946-7","DOIUrl":"https://doi.org/10.1007/s12194-025-00946-7","url":null,"abstract":"Cone-beam computed tomography-based online adaptive radiotherapy (CBCT-based online ART) is currently used in clinical practice; however, deep learning-based segmentation of CBCT images remains challenging. Previous studies generated CBCT datasets for segmentation by adding contours outside clinical practice or synthesizing tissue contrast-enhanced diagnostic images paired with CBCT images. This study aimed to improve CBCT segmentation by matching the treatment planning CT (tpCT) image quality to CBCT images without altering the tpCT image or its contours. A deep-learning-based CBCT segmentation model was trained for the male pelvis using only the tpCT dataset. To bridge the quality gap between tpCT and routine CBCT images, an artificial pseudo-CBCT dataset was generated using Gaussian noise and Fourier domain adaptation (FDA) for 80 tpCT datasets (the hybrid FDA method). A five-fold cross-validation approach was used for model training. For comparison, atlas-based segmentation was performed with a registered tpCT dataset. The Dice similarity coefficient (DSC) assessed contour quality between the model-predicted and reference manual contours. The average DSC values for the clinical target volume, bladder, and rectum using the hybrid FDA method were 0.71 ± 0.08, 0.84 ± 0.08, and 0.78 ± 0.06, respectively. Conversely, the values for the model using plain tpCT were 0.40 ± 0.12, 0.17 ± 0.21, and 0.18 ± 0.14, and for the atlas-based model were 0.66 ± 0.13, 0.59 ± 0.16, and 0.66 ± 0.11, respectively. The segmentation model using the hybrid FDA method demonstrated significantly higher accuracy than models trained on plain tpCT datasets and those using atlas-based segmentation.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856691","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

GAN-MRI enhanced multi-organ MRI segmentation: a deep learning perspective. GAN-MRI增强多器官MRI分割：深度学习视角。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-08-08 DOI: 10.1007/s12194-025-00938-7

Arvind Channarayapatna Srinivasa, Seema S Bhat, Dikendra Baduwal, Zheng Ting Jordan Sim, Shamshekhar S Patil, Ashwin Amarapur, K N Bhanu Prakash

{"title":"GAN-MRI enhanced multi-organ MRI segmentation: a deep learning perspective.","authors":"Arvind Channarayapatna Srinivasa, Seema S Bhat, Dikendra Baduwal, Zheng Ting Jordan Sim, Shamshekhar S Patil, Ashwin Amarapur, K N Bhanu Prakash","doi":"10.1007/s12194-025-00938-7","DOIUrl":"https://doi.org/10.1007/s12194-025-00938-7","url":null,"abstract":"Clinical magnetic resonance imaging (MRI) is a high-resolution tool widely used for detailed anatomical imaging. However, prolonged scan times often lead to motion artefacts and patient discomfort. Fast acquisition techniques can reduce scan times but often produce noisy, low-contrast images, compromising segmentation accuracy essential for diagnosis and treatment planning. To address these limitations, we developed an end-to-end framework that incorporates BIDS-based data organiser and anonymizer, a GAN-based MR image enhancement model (GAN-MRI), AssemblyNet for brain region segmentation, and an attention-residual U-Net with Guided loss for abdominal and thigh segmentation. Thirty brain scans (5,400 slices) and 32 abdominal (1,920 slices) and 55 thigh scans (2,200 slices) acquired from multiple MRI scanners (GE, Siemens, Toshiba) underwent evaluation. Image quality improved significantly, with SNR and CNR for brain scans increasing from 28.44 to 42.92 (p < 0.001) and 11.88 to 18.03 (p < 0.001), respectively. Abdominal scans exhibited SNR increases from 35.30 to 50.24 (p < 0.001) and CNR from 10,290.93 to 93,767.22 (p < 0.001). Double-blind evaluations highlighted improved visualisations of anatomical structures and bias field correction. Segmentation performance improved substantially in the thigh (muscle: + 21%, IMAT: + 9%) and abdominal regions (SSAT: + 1%, DSAT: + 2%, VAT: + 12%), while brain segmentation metrics remained largely stable, reflecting the robustness of the baseline model. Proposed framework is designed to handle data from multiple anatomies with variations from different MRI scanners and centres by enhancing MRI scan and improving segmentation accuracy, diagnostic precision and treatment planning while reducing scan times and maintaining patient comfort.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144800520","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 comparison of MRI and CT protocol examination times for mechanical thrombectomy in acute ischemic stroke. 急性缺血性脑卒中机械取栓术MRI与CT检查次数的比较。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-08-07 DOI: 10.1007/s12194-025-00948-5

Akai Tsuda, Daisuke Oura, Riku Ihara

{"title":"The comparison of MRI and CT protocol examination times for mechanical thrombectomy in acute ischemic stroke.","authors":"Akai Tsuda, Daisuke Oura, Riku Ihara","doi":"10.1007/s12194-025-00948-5","DOIUrl":"https://doi.org/10.1007/s12194-025-00948-5","url":null,"abstract":"In acute ischemic stroke (AIS), where the shortest possible assessment is required to minimize time to mechanical thrombectomy (MT). With recent advancements in MRI reconstruction technology, MRI has also become valuable in the decision-making process for AIS treatment planning. In this study, we compared the examination times of our MRI protocol with those of a standard CT protocol for evaluating AIS through phantom simulations to obtain timing information directly relevant to treatment strategies, and evaluated the utility of MRI for MT. Ten radiological technologists performed scans using the same phantom for each modality. Evaluation items included time for hemorrhage detection, time for penumbra evaluation, and time for brain artery evaluation, and total examination time. The total examination time was slightly shorter with CT (696.2 ± 52.7 s) compared to MRI (701.8 ± 15.8 s), although this difference was not statistically significant (p = 0.4). For other parameters, MRI demonstrated significantly faster detection times: hemorrhage detection (CT, 80.9 ± 12.8 s; MRI, 66.3 ± 1.7 s; p = 0.0002), penumbra evaluation (CT, 696.2 ± 52.7 s; MRI, 262.1 ± 9.3 s; p = 0.0002), and brain artery evaluation (CT, 592.1 ± 32.3 s; MRI, 367.8 ± 8.3 s; p = 0.0002). The coefficient of variation (CV) was lower for MRI compared to CT, indicating less variability in examination times with MRI. This study demonstrates that MRI protocols, including perfusion imaging, can more rapidly visualize factors essential for MT decision-making and do not delay time to MT.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144800521","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

Practical signal-to-noise ratio mapping using single clinical MR images. 实用的信噪比映射使用单个临床磁共振图像。

IF 1.5

Radiological Physics and Technology Pub Date : 2025-07-30 DOI: 10.1007/s12194-025-00944-9

Shinya Kojima, Shuntaro Higuchi, Tatsuya Hayashi, Toshiya Kariyasu, Makiko Nishikawa, Hidenori Yamaguchi, Haruhiko Machida

{"title":"Practical signal-to-noise ratio mapping using single clinical MR images.","authors":"Shinya Kojima, Shuntaro Higuchi, Tatsuya Hayashi, Toshiya Kariyasu, Makiko Nishikawa, Hidenori Yamaguchi, Haruhiko Machida","doi":"10.1007/s12194-025-00944-9","DOIUrl":"https://doi.org/10.1007/s12194-025-00944-9","url":null,"abstract":"Accurate signal-to-noise ratio (SNR) measurement is essential for evaluating image quality in magnetic resonance imaging (MRI). While the subtraction-map method provides precise SNR measurements, it requires two consecutive acquisitions, limiting its clinical applicability. This study aims to develop and validate a method for practical SNR measurement using clinical MRI images. The proposed method generates an SNR map by computing a noise-only image from a single MRI image using pixel shifting and edge component removal. The accuracy of our method was compared with the subtraction-map method in three evaluations: (1) optimization of a key parameter for edge component removal, (2) analysis of spatial resolution and SNR level effects, and (3) validation using brain MRI images. The study included brain MRI from 188 patients, and SNR measurements were performed on the resulting images. Correlation coefficients and Bland-Altman analysis were used for comparisons. Parameter optimization identified an optimal threshold for separating noise and edge components. Higher spatial resolution improved accuracy, whereas lower resolution and low SNR conditions led to overestimation. In clinical MRI, the proposed method showed a strong correlation with the subtraction-map method (Spearman r = 0.96), and the highest average error rate was 8.1% in T1-weighted images. Bland-Altman analysis demonstrated good agreement across sequences and regions. This method enables practical SNR estimation from a single image, eliminating the need for repeated acquisitions. While limitations remain in low-SNR or structurally complex regions, the method shows promise as a practical tool for retrospective and routine clinical image quality assessments.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144745458","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