{"title":"[Metal Artifact Assessment of Multiple MRI-conditional Pacing and Defibrillation Leads: A Phantom Study Comparing Different Manufacturers].","authors":"Shiro Masuda, Shuhei Ogita, Haruka Aoyagi, Tomofumi Misaka, Shigeyoshi Saito, Hajime Sagawa, Toru Shinohe","doi":"10.6009/jjrt.26-1592","DOIUrl":"10.6009/jjrt.26-1592","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to evaluate metal artifacts in cardiac magnetic resonance imaging using four pacing leads and four defibrillation leads and to clarify the effects of lead differences on image quality.</p><p><strong>Methods: </strong>Each lead was fixed in a phantom and aligned parallel to the X-, Y-, and Z-axis. Short-axis images were acquired using balanced steady-state free precession (balanced SSFP) and fast gradient echo (FGRE). Artifact area (S<sub>0</sub>) and increase rate (ΔS) were calculated. For each lead, the maximum value among the three axes was used to perform inter-lead comparisons. Visual assessment was also performed using short-axis images.</p><p><strong>Results: </strong>In the physical evaluation, both S<sub>0</sub> and ΔS tended to be greater with FGRE than with balanced SSFP for all leads. The median (range) of the maximum S<sub>0</sub> and ΔS values among the three axes for each lead were 152.02 mm<sup>2</sup> (119.17-183.49) and 5024.27% (4562.10-6956.83), respectively, for pacing leads, and 114.43 mm<sup>2</sup> (79.51-148.11) and 2073.16% (1398.30-3561.46), respectively, for defibrillation leads. In the visual assessment, metal artifacts were significantly larger in some defibrillation leads in both balanced SSFP and FGRE.</p><p><strong>Conclusion: </strong>Pacing leads showed relatively small inter-lead differences, whereas some defibrillation leads exhibited inter-lead variability, suggesting the involvement of structural factors.</p>","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"82 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148159290","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}
Junichi Taoka, Hideyuki Kato, Tetsuharu Kasahara, Kenta Tako, Takashi Iimori
{"title":"[Estimation of Air Kerma-area Product Using Real-time Dosimeter in Mobile X-ray Fluoroscopy System].","authors":"Junichi Taoka, Hideyuki Kato, Tetsuharu Kasahara, Kenta Tako, Takashi Iimori","doi":"10.6009/jjrt.26-1636","DOIUrl":"https://doi.org/10.6009/jjrt.26-1636","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to estimate the air kerma-area product of a mobile X-ray fluoroscopy system by using a real-time dosimeter in situations where an area dosimeter is not available.</p><p><strong>Methods: </strong>A real-time dosimeter was mounted on the C-arm of a mobile X-ray fluoroscopy system. Using an ionization dosimeter as a reference, we evaluated the correlation between the air kerma-area product measured by the fluoroscopy system and the readings obtained from the mounted real-time dosimeter. Tube voltage was varied from 60 to 110 kV in 10-kV increments, and phantom thickness varied from 5 to 20 cm in 5-cm increments. In addition, the irradiation field area was adjusted across five levels, ranging from 168.1 to 75.5 cm<sup>2</sup>.</p><p><strong>Results: </strong>A strong linear relationship was observed between the real-time dosimeter readings x-axis and the air kerma-area product values y-axis, expressed as the regression equation y=36.181x+0.2188. The correlation coefficient was r=0.99.</p><p><strong>Conclusion: </strong>This study suggests that the air kerma-area product can be estimated by placing a real-time dosimeter on a mobile X-ray fluoroscopy system without an area dosimeter.</p>","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"82 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148414126","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}
{"title":"[Site-specific Segmentation of Skeletal Muscles in Body CT Images via Comprehensive Muscular Consideration].","authors":"Kosuke Ashino, Naoki Kamiya, Xiangrong Zhou, Hiroki Kato, Takeshi Hara, Hiroshi Fujita","doi":"10.6009/jjrt.26-1594","DOIUrl":"10.6009/jjrt.26-1594","url":null,"abstract":"<p><strong>Purpose: </strong>The objective of this study is to achieve site-specific three-dimensional (3D) automatic segmentation of skeletal muscles in body CT images. We aimed to improve recognition accuracy of nine muscle regions: sternocleidomastoid, erector spinae, trapezius, supraspinatus, rectus abdominis, obliques, quadratus lumborum, psoas major, and iliacus. Then, we focused on utilizing all skeletal muscle areas outside the target recognition regions that were not previously used.</p><p><strong>Methods: </strong>Our method trains the 2D U-Net to learn both the target site-specific skeletal muscle region and all other skeletal muscles together. We utilized 30 cases of unenhanced body CT images and performed three-fold cross-validation.</p><p><strong>Results: </strong>The proposed method achieved an average Dice coefficient of 88.37% across nine regions, showing improvements of 25.78% and 1.86% compared to the individual learning of each region (baseline) and the simultaneous learning of erector spinae (previous method), respectively.</p><p><strong>Conclusion: </strong>Comprehensive learning of all skeletal muscle regions successfully improved the accuracy of U-Net-based 3D automatic segmentation for site-specific skeletal muscles in body CT. It leads to enhanced, precise body composition analysis for skeletal muscle regions.</p>","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"82 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146121254","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}
{"title":"[Feasibility of Effective Source-to-surface Distance Calculation Using an Electron Monte Carlo Algorithm for Electron Beams].","authors":"Shoma Okada, Reina Goto, Honomi Nishino, Shoma Hiramatsu, Kenji Matsumoto, Masakazu Otsuka, Takahiro Saika, Masahiko Okumura","doi":"10.6009/jjrt.26-1548","DOIUrl":"10.6009/jjrt.26-1548","url":null,"abstract":"<p><strong>Purpose: </strong>In radiation therapy, the absorbed dose is corrected for changes in the nominal treatment distance using the inverse square law. However, in the case of electron beams, the inverse square law using the nominal treatment distance is invalid. Therefore, an effective source-to-surface distance (SSD) should be determined. The effective SSD must be measured for all electron beam energies and applicator sizes. Here, we calculated the effective SSD using a radiotherapy planning system with an electron Monte Carlo (eMC) calculation algorithm and evaluated its usefulness.</p><p><strong>Methods: </strong>The effective SSD was calculated from the absorbed dose ratio at d<sub>max</sub> at extended SSDs under 5 gap conditions, using both eMC calculations and LINAC measurements. The consistency between calculated and measured values was evaluated based on the absorbed dose ratio at d<sub>max</sub>, effective SSD, and distance correction factor.</p><p><strong>Results: </strong>The difference in the absorbed dose ratio at d<sub>max</sub> between eMC calculations and measurements at extended SSDs was within 1.38%, and the effective SSD values agreed within 5.40 cm. Larger discrepancies in effective SSD were observed under conditions of high energy with large field sizes and low energy with small field sizes.</p><p><strong>Conclusion: </strong>The good agreement in absorbed dose ratio at d<sub>max</sub>, effective SSD, and distance correction factor between eMC calculations and measurements indicates that effective SSD calculation using eMC is feasible and can be employed for comparative verification against measured values.</p>","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"82 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146144493","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}
{"title":"[The Future of Radiological Medicine Expanding through 'Connections'].","authors":"Hidetaka Hayashi","doi":"10.6009/jjrt.26-0306","DOIUrl":"https://doi.org/10.6009/jjrt.26-0306","url":null,"abstract":"","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"82 3","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147500920","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}
{"title":"[6. Data Literacy (4): Important Things to Keep in Mind When Analyzing Data].","authors":"Ayako Yagahara","doi":"10.6009/jjrt.26-0605","DOIUrl":"https://doi.org/10.6009/jjrt.26-0605","url":null,"abstract":"","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"82 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148297624","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}
{"title":"[Diagnostic Performance of Automated Intracranial Hemorrhage Detection Software and Analysis of Volume and Hounsfield Unit Metrics in False-positive Cases].","authors":"Shunichi Ishizuka, Shun Muramatsu, Tomomi Ohmura","doi":"10.6009/jjrt.26-1628","DOIUrl":"10.6009/jjrt.26-1628","url":null,"abstract":"<p><strong>Purpose: </strong>To compare the diagnostic performance of syngo.CT Brain Hemorrhage (BH) (Siemens Healthcare, Forchheim, Germany) with physician interpretations on noncontrast head CT in patients with suspected intracranial hemorrhage (ICH), and to elucidate the volume and Hounsfield unit (HU) metrics of false-positive (FP) cases.</p><p><strong>Methods: </strong>We analyzed 509 noncontrast head CT examinations obtained for suspected ICH. Presence or absence of hemorrhage was determined by board-certified radiologists or clinicians. Among positive cases, hemorrhage subtypes were labeled as intraparenchymal hemorrhage (IPH), intraventricular hemorrhage (IVH), subdural hematoma (SDH), epidural hematoma (EDH), and subarachnoid hemorrhage (SAH). BH outputs were categorized as true positive (TP), false positive (FP), false negative (FN), or true negative (TN). For FP cases, lesion location and BH-derived quantitative indices-lesion volume and HU values (minimum, maximum, mean, and standard deviation)-were compared with TP cases.</p><p><strong>Results: </strong>BH achieved a sensitivity 100%, a specificity 82.2%, a FP rate 17.8%, and an FN rate 0%. TP cases comprised IPH 64, SAH 33, SDH 83, EDH 11, and IVH 14. FP findings were located in cerebral sulci (n=22), brain parenchyma (n=12), vessels (n=10), dura mater (n=5), and bone (n=5). All BH indices differed between FP and TP cases (p<0.01).</p><p><strong>Conclusion: </strong>BH showed favorable diagnostic performance relative to physician interpretations, and FP cases exhibited statistically significant differences from TP cases in lesion volume and HU-based metrics.</p>","PeriodicalId":74309,"journal":{"name":"Nihon Hoshasen Gijutsu Gakkai zasshi","volume":"82 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147693962","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}