Radiological Physics and Technology最新文献_第7页

Optimum delineation of skin structure for dose calculation with the linear Boltzmann transport equation algorithm in radiotherapy treatment planning. 在放射治疗规划中使用线性玻尔兹曼传输方程算法计算剂量时的皮肤结构最佳划分。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-09-09 DOI: 10.1007/s12194-024-00840-8

Keisuke Hamada, Toshioh Fujibuchi, Hiroyuki Arakawa

引用次数: 0

Single-point macromolecular proton fraction mapping using a 0.3 T permanent magnet MRI system: phantom and healthy volunteer study. 使用 0.3 T 永磁 MRI 系统进行单点大分子质子分数绘图：模型和健康志愿者研究。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-09-09 DOI: 10.1007/s12194-024-00843-5

Yasuhiro Fujiwara, Shoma Eitoku, Nobutaka Sakae, Takahisa Izumi, Hiroyuki Kumazoe, Mika Kitajima

{"title":"Single-point macromolecular proton fraction mapping using a 0.3 T permanent magnet MRI system: phantom and healthy volunteer study.","authors":"Yasuhiro Fujiwara, Shoma Eitoku, Nobutaka Sakae, Takahisa Izumi, Hiroyuki Kumazoe, Mika Kitajima","doi":"10.1007/s12194-024-00843-5","DOIUrl":"10.1007/s12194-024-00843-5","url":null,"abstract":"In a 0.3 T permanent-magnet magnetic resonance imaging (MRI) system, quantifying myelin content is challenging owing to long imaging times and low signal-to-noise ratio. macromolecular proton fraction (MPF) offers a quantitative assessment of myelin in the nervous system. We aimed to demonstrate the practical feasibility of MPF mapping in the brain using a 0.3 T MRI. Both 0.3 T and 3.0 T MRI systems were used. The MPF-mapping protocol used a standard 3D fast spoiled gradient-echo sequence based on the single-point reference method. Proton density, T1, and magnetization transfer-weighted images were obtained from a protein phantom at 0.3 T and 3.0 T to calculate MPF maps. MPF was measured in all phantom sections to assess its relationship to protein concentration. We acquired MPF maps for 16 and 8 healthy individuals at 0.3 T and 3.0 T, respectively, measuring MPF in nine brain tissues. Differences in MPF between 0.3 T and 3.0 T, and between 0.3 T and previously reported MPF at 0.5 T, were investigated. Pearson's correlation coefficient between protein concentration and MPF at 0.3 T and 3.0 T was 0.92 and 0.90, respectively. The 0.3 T MPF of brain tissue strongly correlated with 3.0 T MPF and literature values measured at 0.5 T. The absolute mean differences in MPF between 0.3 T and 0.5 T were 0.42% and 1.70% in white and gray matter, respectively. Single-point MPF mapping using 0.3 T permanent-magnet MRI can effectively assess myelin content in neural tissue.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"869-877"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298280","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

An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis. 基于放射组学的人工智能（AI）方法在乳腺癌筛查和诊断中的最新概述。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-09-16 DOI: 10.1007/s12194-024-00842-6

Reza Elahi, Mahdis Nazari

{"title":"An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis.","authors":"Reza Elahi, Mahdis Nazari","doi":"10.1007/s12194-024-00842-6","DOIUrl":"10.1007/s12194-024-00842-6","url":null,"abstract":"Current imaging methods for diagnosing breast cancer (BC) are associated with limited sensitivity and specificity and modest positive predictive power. The recent progress in image analysis using artificial intelligence (AI) has created great promise to improve BC diagnosis and subtype differentiation. In this case, novel quantitative computational methods, such as radiomics, have been developed to enhance the sensitivity and specificity of early BC diagnosis and classification. The potential of radiomics in improving the diagnostic efficacy of imaging studies has been shown in several studies. In this review article, we discuss the radiomics workflow and current handcrafted radiomics methods in the diagnosis and classification of BC based on the most recent studies on different imaging modalities, e.g., MRI, mammography, contrast-enhanced spectral mammography (CESM), ultrasound imaging, and digital breast tumosynthesis (DBT). We also discuss current challenges and potential strategies to improve the specificity and sensitivity of radiomics in breast cancer to help achieve a higher level of BC classification and diagnosis in the clinical setting. The growing field of AI incorporation with imaging information has opened a great opportunity to provide a higher level of care for BC patients.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"795-818"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298276","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 frame rate on image quality in cardiology evaluated using an indirect conversion dynamic flat-panel detector. 使用间接转换动态平板探测器评估帧频对心脏病学图像质量的影响。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-09-18 DOI: 10.1007/s12194-024-00845-3

Akira Hasegawa, Yohan Kondo

引用次数: 0

Evaluation of patient-specific quality assurance for fractionated stereotactic treatment plans with 6 and 10MV photon beams in beam-matched linacs. 评估在光束匹配直列加速器中使用6MV和10MV光子束的分层立体定向治疗计划的患者特定质量保证。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-10-04 DOI: 10.1007/s12194-024-00848-0

Mageshraja Kannan, Sathiyan Saminathan, Varatharaj Chandraraj, B Shwetha, D Gowtham Raj, K M Ganesh

{"title":"Evaluation of patient-specific quality assurance for fractionated stereotactic treatment plans with 6 and 10MV photon beams in beam-matched linacs.","authors":"Mageshraja Kannan, Sathiyan Saminathan, Varatharaj Chandraraj, B Shwetha, D Gowtham Raj, K M Ganesh","doi":"10.1007/s12194-024-00848-0","DOIUrl":"10.1007/s12194-024-00848-0","url":null,"abstract":"Beam-matched linear accelerators (LA's) require accurate and precise dosimetry for fractionated stereotactic treatment. In this study, the beam data were validated by comparing the three-beam-matched LA's measured data and the vendor reference data. Upon its validation, the accuracy of the volumetric dose delivery for eighty patient-specific fractionated stereotactic treatment plans was evaluated. Measurements of the percentage depth dose (PDD), beam profiles, output factors (OFs), absolute output, and dynamic multi-leaf collimator (MLC) transmission factors for 6 MV and 10 MV flattening filter (FF) and flattening filter-free (FFF) photon beams were obtained from three-beam-matched LA's. The patient-specific quality assurance evaluation for all eighty plans was performed using PTW Octavius 1000 SRS™ array detectors for two-dimensional (2D) fluence measurement. The following 2D gamma passing criteria were used: 1%/1 mm, 2%/1 mm, 1%/2 mm, 2%/2 mm and 3%/2 mm. In all three LA's, gamma analysis for PDD and profile were above 97% with gamma criteria of 1%/1 mm. The differences OFs, absolute output, and dynamic MLC transmission factors were less than ± 1% of base value. For all eighty cases, the median passing rates on the three LA's were above 76%, 88%, 92%, 96%, and 98% for the above-mentioned gamma criteria of the three LA's. The beam-matched LA's showed good agreement between the measured and treatment planning system (TPS) calculated values for fractionated stereotactic VMAT plans with 6 MV and 10 MV (FF and FFF) photon beams. Patients can be shifted and treated on any beam-matched linac without the need of re-planning.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"896-906"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373206","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

Parameter optimisation for image acquisition and stacking in carbon dioxide digital subtraction angiography. 二氧化碳数字减影血管造影中图像采集和叠加的参数优化。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-09-09 DOI: 10.1007/s12194-024-00841-7

Kazuya Kakuta, Koichi Chida

{"title":"Parameter optimisation for image acquisition and stacking in carbon dioxide digital subtraction angiography.","authors":"Kazuya Kakuta, Koichi Chida","doi":"10.1007/s12194-024-00841-7","DOIUrl":"10.1007/s12194-024-00841-7","url":null,"abstract":"The aim of this study was to optimise the vessel angle as well as the stack number from the profiles of carbon dioxide digital subtraction angiography (CO2-DSA) images of a water phantom containing an artificial vessel tilted at different angles which imitate arteries in the body. The artificial vessel was tilted at 0°, 15°, and 30° relative to the horizontal axis with its centre as the pivot point, and CO2-DSA images were acquired at each vessel tilt angle. The maximum opacity method was used to stack up to four images of the next frame one by one. The signal-to-noise ratio (SNR) was determined from the profile curves. The Wilcoxon rank sum test was used to evaluate whether the profile curve and SNR differed depending on the vessel tilt angle or stack number, and a p-value of less than 0.05 was considered statistically significant. Images acquired at 0° had a significantly lower SNR than images acquired at 15° (p = 0.10). When the vessel angle was 30°, the profile curves were significantly improved (p < 0.05) when two or more images were stacked over the original image. Images with a good SNR were acquired at the vessel tilt angle of 15°, and the shape of the profile curve was improved when two or more images were stacked on the original image. This study demonstrates that the quality of images acquired using CO2-DSA can be significantly improved through parameter optimisation for image acquisition and post-processing.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"862-868"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142156304","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 internal target volume definition based on velocity and time of respiratory target motion for external beam radiotherapy. 基于呼吸靶运动速度和时间的新型外照射放射治疗内靶体积定义。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-09-13 DOI: 10.1007/s12194-024-00837-3

Masashi Yamanaka, Teiji Nishio, Kohei Iwabuchi, Hironori Nagata

{"title":"A novel internal target volume definition based on velocity and time of respiratory target motion for external beam radiotherapy.","authors":"Masashi Yamanaka, Teiji Nishio, Kohei Iwabuchi, Hironori Nagata","doi":"10.1007/s12194-024-00837-3","DOIUrl":"10.1007/s12194-024-00837-3","url":null,"abstract":"This study aimed to develop a novel internal target volume (ITV) definition for respiratory motion targets, considering target motion velocity and time. The proposed ITV was evaluated in respiratory-gated radiotherapy. An ITV modified with target motion velocity and time (ITVvt) was defined as an ITV that includes a target motion based on target motion velocity and time. The target motion velocity was calculated using four-dimensional computed tomography (4DCT) images. The ITVvts were created from phantom and clinical 4DCT images. The phantom 4DCT images were acquired using a solid phantom that moved with a sinusoidal waveform (peak-to-peak amplitudes of 10 and 20 mm and cycles of 2-6 s). The clinical 4DCT images were obtained from eight lung cancer cases. In respiratory-gated radiotherapy, the ITVvt was compared with conventional ITVs for beam times of 0.5-2 s within the gating window. The conventional ITV was created by adding a uniform margin as the maximum motion within the gating window. In the phantom images, the maximum volume difference between the ITVvt and conventional ITV was -81.9%. In the clinical images, the maximum volume difference was -53.6%. Shorter respiratory cycles and longer BTs resulted in smaller ITVvt compared with the conventional ITV. Therefore, the proposed ITVvt plan could be used to reduce treatment volumes and doses to normal tissues.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"843-853"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298275","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

Development of deep learning-based novel auto-segmentation for the prostatic urethra on planning CT images for prostate cancer radiotherapy. 在前列腺癌放疗计划 CT 图像上开发基于深度学习的新型前列腺尿道自动分割技术。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-08-14 DOI: 10.1007/s12194-024-00832-8

Hisamichi Takagi, Ken Takeda, Noriyuki Kadoya, Koki Inoue, Shiki Endo, Noriyoshi Takahashi, Takaya Yamamoto, Rei Umezawa, Keiichi Jingu

{"title":"Development of deep learning-based novel auto-segmentation for the prostatic urethra on planning CT images for prostate cancer radiotherapy.","authors":"Hisamichi Takagi, Ken Takeda, Noriyuki Kadoya, Koki Inoue, Shiki Endo, Noriyoshi Takahashi, Takaya Yamamoto, Rei Umezawa, Keiichi Jingu","doi":"10.1007/s12194-024-00832-8","DOIUrl":"10.1007/s12194-024-00832-8","url":null,"abstract":"Urinary toxicities are one of the serious complications of radiotherapy for prostate cancer, and dose-volume histogram of prostatic urethra has been associated with such toxicities in previous reports. Previous research has focused on estimating the prostatic urethra, which is difficult to delineate in CT images; however, these studies, which are limited in number, mainly focused on cases undergoing brachytherapy uses low-dose-rate sources and do not involve external beam radiation therapy (EBRT). In this study, we aimed to develop a deep learning-based method of determining the position of the prostatic urethra in patients eligible for EBRT. We used contour data from 430 patients with localized prostate cancer. In all cases, a urethral catheter was placed when planning CT to identify the prostatic urethra. We used 2D and 3D U-Net segmentation models. The input images included the bladder and prostate, while the output images focused on the prostatic urethra. The 2D model determined the prostate's position based on results from both coronal and sagittal directions. Evaluation metrics included the average distance between centerlines. The average centerline distances for the 2D and 3D models were 2.07 ± 0.87 mm and 2.05 ± 0.92 mm, respectively. Increasing the number of cases while maintaining equivalent accuracy as we did in this study suggests the potential for high generalization performance and the feasibility of using deep learning technology for estimating the position of the prostatic urethra.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"819-826"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11579160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141983522","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

Assessment of accuracy and repeatability of quantitative parameter mapping in MRI. 评估磁共振成像定量参数绘图的准确性和可重复性。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-08-28 DOI: 10.1007/s12194-024-00836-4

Yuya Hirano, Kinya Ishizaka, Hiroyuki Sugimori, Yo Taniguchi, Tomoki Amemiya, Yoshitaka Bito, Kohsuke Kudo

引用次数: 0

Joint segmentation of sternocleidomastoid and skeletal muscles in computed tomography images using a multiclass learning approach. 利用多类学习方法联合分割计算机断层扫描图像中的胸锁乳突肌和骨骼肌

IF 1.7

Radiological Physics and Technology Pub Date : 2024-12-01 Epub Date: 2024-09-06 DOI: 10.1007/s12194-024-00839-1

Kosuke Ashino, Naoki Kamiya, Xiangrong Zhou, Hiroki Kato, Takeshi Hara, Hiroshi Fujita

{"title":"Joint segmentation of sternocleidomastoid and skeletal muscles in computed tomography images using a multiclass learning approach.","authors":"Kosuke Ashino, Naoki Kamiya, Xiangrong Zhou, Hiroki Kato, Takeshi Hara, Hiroshi Fujita","doi":"10.1007/s12194-024-00839-1","DOIUrl":"10.1007/s12194-024-00839-1","url":null,"abstract":"Deep-learning-based methods can improve robustness against individual variations in computed tomography (CT) images of the sternocleidomastoid muscle, which is a challenge when using conventional methods based on probabilistic atlases are used for automatic segmentation. Thus, this study proposes a novel multiclass learning approach for the joint segmentation of the sternocleidomastoid and skeletal muscles in CT images, and it employs a two-dimensional U-Net architecture. The proposed method concurrently learns and segmented segments the sternocleidomastoid muscle and the entire skeletal musculature. Consequently, three-dimensional segmentation results are generated for both muscle groups. Experiments conducted on a dataset of 30 body CT images demonstrated segmentation accuracies of 82.94% and 92.73% for the sternocleidomastoid muscle and entire skeletal muscle compartment, respectively. These results outperformed those of conventional methods, such as the single-region learning of a target muscle and multiclass learning of specific muscle pairs. Moreover, the multiclass learning paradigm facilitated a robust segmentation performance regardless of the input image range. This highlights the method's potential for cases that present muscle atrophy or reduced muscle strength. The proposed method exhibits promising capabilities for the high-accuracy joint segmentation of the sternocleidomastoid and skeletal muscles and is effective in recognizing skeletal muscles, thus, it holds promise for integration into computer-aided diagnostic systems for comprehensive musculoskeletal analysis. These findings are expected to enhance medical image analysis techniques and their applications in clinical decision support systems.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"854-861"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11579203/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142146574","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