Nihon Hoshasen Gijutsu Gakkai zasshi最新文献_第5页

[Looking Ahead to Technological Innovation and the Future of AI]. [展望技术创新和人工智能的未来]。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-0604

Koji Uchida

引用次数: 0

[Investigation of the Optimal Parameters for Block Sequential Regularized Expectation Maximization (BSREM) Reconstruction in Bone SPECT Using a Ring-type Semiconductor SPECT/CT]. [基于环形半导体SPECT/CT的骨SPECT块顺序正则化期望最大化（BSREM）重建的最优参数研究]。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-1560

Hayato Sato, Hayato Odagiri, Nao Yamaguchi, Hiroyasu Kodama, Takashi Takeuchi, Yoshitaka Tanaka, Kentaro Takanami, Akihito Usui, Tomohiro Kaneta

{"title":"[Investigation of the Optimal Parameters for Block Sequential Regularized Expectation Maximization (BSREM) Reconstruction in Bone SPECT Using a Ring-type Semiconductor SPECT/CT].","authors":"Hayato Sato, Hayato Odagiri, Nao Yamaguchi, Hiroyasu Kodama, Takashi Takeuchi, Yoshitaka Tanaka, Kentaro Takanami, Akihito Usui, Tomohiro Kaneta","doi":"10.6009/jjrt.25-1560","DOIUrl":"https://doi.org/10.6009/jjrt.25-1560","url":null,"abstract":"Purpose: This research aims to optimize the block sequential regularized expectation maximization (BSREM) reconstruction in bone single photon emission computed tomography (SPECT) images using a ring-type SPECT/computed tomography (CT) system in terms of image quality and accuracy of quantitative evaluation.Methods: SPECT images were acquired using a ring-type SPECT/CT and from a SIM2 bone phantom containing a 99m-Tc solution. BSREM parameters were assessed with coefficient of variation (CV), recovery coefficient (RC), contrast noise ratio (CNR), standardized uptake value max (SUVmax), and its root mean square error (RMSESUVmax). Clinical images were reconstructed, and the reconstructions were evaluated as superior based on phantom results.Results: Increasing γ led to higher RC and CV, while increasing β lowered these values. CNR showed no consistent trend. In terms of quantitative evaluation, γ value 5.0, β values 0.3-0.9, and γ value 10, βvalues 0.3-0.9 resulted in lower RMSESUVmax compared to Anger type. Based on the phantom experiment, γ value 5.0, β values 0.5-0.9, and γ value 10, β values 0.7-0.9 were evaluated as superior. Clinical images under these reconstructions, determined from the phantom experiments, with γ value 5.0, β value 0.9, showed the smoothest of normal bone and the clearest separation of neighboring tumors.Conclusion: As reconstruction parameters for BSREM reconstruction in bone SPECT on a ring-type semiconductor SPECT/CT system, a γ value of 5.0 and a β value of 0.9 were considered suitable for image quality and quantitative evaluation.","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"81 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144509865","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

[6. Commissioning and Dosimetry Standards for 0.35 Tesla MRI Linac]. (6。0.35特斯拉MRI直线加速器的调试和剂量学标准[j]。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-0200

Yu Kumazaki

引用次数: 0

[Dr. Taizo Sanada]. [医生Taizo Sanada]。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-0201

Yoshinori Tanabe

引用次数: 0

["Radiology for Everyone"-Join Us in Shaping the Future!-An Invitation to the 81st Annual Meeting of the Japanese Society of Radiological Technology (JSRT) in Yokohama]. “每个人的放射学”——与我们一起共创未来！-邀请参加在横滨举行的日本放射技术学会（JSRT）第81届年会上]。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-0300

Hideyuki Iwanaga

引用次数: 0

[Comparison of the Impact of Deep Learning Techniques on Low-noise Head CT Images]. [深度学习技术对低噪声头部CT图像影响的比较]。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-1537

Takuro Tahara, Seigo Yoshida

{"title":"[Comparison of the Impact of Deep Learning Techniques on Low-noise Head CT Images].","authors":"Takuro Tahara, Seigo Yoshida","doi":"10.6009/jjrt.25-1537","DOIUrl":"10.6009/jjrt.25-1537","url":null,"abstract":"Purpose: This study aims to compare the effects of two types of deep learning (DL) techniques on brain CT values, image noise content, and contrast-to-noise ratio (CNR) between white and gray matter in low-noise head CT images, along with adaptive iterative dose reduction 3D (AIDR 3D).Methods: Twenty-one normal patients with no abnormal findings who underwent head CT for identification of acute illness were included in the study. DL techniques used were Advanced intelligent Clear-IQ Engine (AiCE, Canon Medical systems, Tochigi, Japan) and PixelShine (FUJIFILM Medical, Tokyo, Japan). We performed CT value measurements of 26 cerebrum regions, image noise measurements, and CNR calculations. We also conducted a visual assessment of image noise and white matter-gray matter contrast on a 5-point scale.Results: Image noise significantly decreased with DL techniques. CT values changed significantly with AiCE. CNR for white matter-gray matter was the highest with PixelShine (P<0.01). The visual assessment of white matter-gray matter contrast was the highest for PixelShine and the lowest for AiCE (P<0.01).Conclusion: While DL techniques reduce image noise, there are differences in CT values and visual impression, especially white matter-gray matter contrast, so care should be taken when using it.","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"81 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143775036","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

[2. Radiopharmaceuticals for Targeted Radiotherapy]. (2。靶向放疗用放射性药物[m]。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-0501

Koki Hasegawa

引用次数: 0

[8. Commissioning of 1.5 T MR Linac "Elekta Unity"]. (8。1.5 T MR直线发电机“Elekta Unity”的调试。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-0505

Masato Tsuneda

引用次数: 0

[Evaluation of the Accuracy of Patent Fixation System Using a Bi-directional X-ray Image Matching System during Spine Stereotactic Body Radiation Therapy]. [利用双向x线图像匹配系统评估脊柱立体定向放射治疗中专利固定系统的准确性]。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-1533

Kenji Matsumoto, Takahiro Sakamoto, Masakazu Otsuka, Hiroyuki Kosaka, Hidekazu Nambu

{"title":"[Evaluation of the Accuracy of Patent Fixation System Using a Bi-directional X-ray Image Matching System during Spine Stereotactic Body Radiation Therapy].","authors":"Kenji Matsumoto, Takahiro Sakamoto, Masakazu Otsuka, Hiroyuki Kosaka, Hidekazu Nambu","doi":"10.6009/jjrt.25-1533","DOIUrl":"https://doi.org/10.6009/jjrt.25-1533","url":null,"abstract":"Purpose: To evaluate the accuracy of fixation devices during irradiation of our thoracic and lumbar vertebral stereotactic body radiation therapy (SBRT) and to suggest appropriate planning target volume margins.Methods: Nine patients (45 sessions) with spinal metastases treated with spinal SBRT were studied. A fixation system with a torso shell was used as a fixture for thoracic and lumbar spinal lesions. In the patient setup, radiographic imaging was performed using Exactrac (Brainlab, Munich, Germany), followed by cone beam computed tomography (CBCT) confirmation to ensure that the images were matched within 0.3 mm just before irradiation. Irradiation was started after the collation, and additional X-ray imaging using Exactrac was performed immediately before, during, and immediately after treatment, respectively, to evaluate the fixation accuracy during irradiation.Results: The mean ±1 standard deviation for each direction for movement during irradiation with the body shell was as follows: Lateral direction: 0.01±0.21 mm, head-tail direction: -0.01±0.18 mm, anteroposterior direction: 0.06±0.16 mm, roll: 0.02±0.19°, pitch: -0.02±0.29°, yaw: -0.03±0.23°.Conclusion: The image guided radiotherapy system using X-ray imaging with Exactrac allowed the evaluation of positioning accuracy during irradiation. The body shell fixation system was able to ensure fixation accuracy within 1 mm during irradiation. In addition, the positioning during irradiation using Exactrac is very useful in the evaluation of positioning accuracy during irradiation in SBRT of the vertebral body, where very high irradiation accuracy is required.","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"81 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144201022","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

[Usefulness of Deep Learning Reconstruction in Low-dose Lung Cancer CT Screening Protocols]. [深度学习重建在低剂量肺癌CT筛查方案中的应用]。

Nihon Hoshasen Gijutsu Gakkai zasshi Pub Date : 2025-01-01 DOI: 10.6009/jjrt.25-1485

Yuse Shono, Masaaki Fukunaga, Hiroyuki Yamamoto, Osamu Ito

{"title":"[Usefulness of Deep Learning Reconstruction in Low-dose Lung Cancer CT Screening Protocols].","authors":"Yuse Shono, Masaaki Fukunaga, Hiroyuki Yamamoto, Osamu Ito","doi":"10.6009/jjrt.25-1485","DOIUrl":"https://doi.org/10.6009/jjrt.25-1485","url":null,"abstract":"Purpose: This study aimed to evaluate the changes in physical characteristics when the image reconstruction method, radiation dose, and pitch factor (PF) were varied in low-dose lung cancer CT screening, and to determine the optimal radiation dose and PF for appropriate dose reduction and the usefulness of deep learning reconstruction (DLR).Methods: Physical characteristics were evaluated using an Aquilion PrimeSP/i Edition (Canon Medical Systems, Tochigi) X-ray CT unit in conjunction with water phantoms and a chest phantom. Image reconstruction methods included filtered back projection (FBP), iterative reconstruction (IR), and DLR. Exposure conditions were varied across four dose levels and three PF levels. Physical characteristics were quantitatively evaluated using the noise power spectrum, task transfer function (TTF), low-contrast object-specific contrast-to-noise ratio (CNRLO), and system performance function (SPF).Results: Both the IR application method and DLR improved noise characteristics compared to FBP, even at low doses, and reduced noise in the high spatial frequency domain when the PF level was lowered. DLR improved TTF at low doses and SPF at a standard deviation (SD) of 50. There was no significant difference in CNRLO by PF level.Conclusion: DLR may be useful in low-dose lung cancer CT screening, and appropriate SD settings and PF selection may contribute to image optimization.","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"81 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144251196","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