Japanese Journal of Radiology最新文献

{"title":"Accuracy and reproducibility of large language model measurements of liver metastases: comparison with radiologist measurements.","authors":"Haruto Sugawara, Akiyo Takada, Shimpei Kato","doi":"10.1007/s11604-025-01884-5","DOIUrl":"https://doi.org/10.1007/s11604-025-01884-5","url":null,"abstract":"<p><strong>Purpose: </strong>To compare the accuracy and reproducibility of lesion-diameter measurements performed by three state-of-the-art LLMs with those obtained by radiologists.</p><p><strong>Materials and methods: </strong>In this retrospective study using a public database, 83 patients with solitary colorectal-cancer liver metastases were identified. From each CT series, a radiologist extracted the single axial slice showing the maximal tumor diameter and converted it to a 512 × 512-pixel PNG image (window level 50 HU, window width 400 HU) with pixel size encoded in the filename. Three LLMs-ChatGPT-o3 (OpenAI), Gemini 2.5 Pro (Google), and Claude 4 Opus (Anthropic)-were prompted to estimate the longest lesion diameter twice, ≥ 1 week apart. Two board-certified radiologists (12 years' experience each) independently measured the same single slice images and one radiologist repeated the measurements after ≥ 1 week. Agreement was assessed with intraclass correlation coefficients (ICC); 95% confidence intervals were obtained by bootstrap resampling (5 000 iterations).</p><p><strong>Results: </strong>Radiologist inter-observer agreement was excellent (ICC = 0.95, 95% CI 0.86-0.99); intra-observer agreement was 0.98 (95% CI 0.94-0.99). Gemini achieved good model-to-radiologist agreement (ICC = 0.81, 95% CI 0.68-0.89) and intra-model reproducibility (ICC = 0.78, 95% CI 0.65-0.87). GPT-o3 showed moderate agreement (ICC = 0.52) and poor reproducibility (ICC = 0.25); Claude showed poor agreement (ICC = 0.07) and reproducibility (ICC = 0.47).</p><p><strong>Conclusion: </strong>LLMs do not yet match radiologists in measuring colorectal cancer liver metastasis; however, Gemini's good agreement and reproducibility highlight the rapid progress of image interpretation capability of LLMs.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical impact of computed tomography-measured skeletal muscle status at the third cervical vertebra on definitive radiotherapy outcomes for head and neck squamous cell carcinoma.","authors":"Yuki Kasuga, Atsuto Katano, Masanari Minamitani, Shouhei Hanaoka, Shin Fujiwara, Yuki Saito, Koji Yamamura, Kenya Kobayashi, Hideomi Yamashita, Osamu Abe, Wataru Gonoi","doi":"10.1007/s11604-025-01888-1","DOIUrl":"https://doi.org/10.1007/s11604-025-01888-1","url":null,"abstract":"<p><strong>Background and purpose: </strong>Loss of skeletal muscle mass is increasingly recognized as a poor prognostic indicator in patients with cancer, including those with head and neck squamous cell carcinoma (HNSCC). Emerging evidence suggests that the muscle area measured at the third cervical vertebra (C3) on CT serves as a practical surrogate for whole-body muscle status. This study aimed to evaluate the prognostic significance of C3-level body composition parameters in patients with HNSCC undergoing definitive radiotherapy.</p><p><strong>Materials and methods: </strong>A total of 283 consecutive patients with HNSCC treated with definitive radiotherapy between 2013 and 2023 were retrospectively analyzed. Pre-treatment CT scans were used to assess six body composition metrics at the C3 level: skeletal muscle area (SMA), mean skeletal muscle density, visceral adipose tissue area, subcutaneous adipose tissue area, visceral-to-subcutaneous fat ratio, and skeletal muscle fat infiltration index. Patients were stratified into high and low groups based on sex-specific median values. Associations between each body composition metric (high vs. low) and survival outcomes were assessed using univariate and multivariate analyses.</p><p><strong>Results: </strong>The cohort included 238 males and 45 females, with a median age of 67 years. Survival analysis showed a median follow-up period of 39.3 months. The 3-year overall survival (OS) rate for the entire cohort was 81.6%, and the 3-year progression free survival rate was 60.8%. In univariate analysis, only low SMA was significantly associated with poorer OS (hazard ratio: 1.841, p = 0.027). The median SMA was 35.0 cm² for males and 23.5 cm² for females. In multivariate analysis, low SMA remained an independent predictor of reduced OS (hazard ratio: 1.851, p = 0.028), along with clinical stage and chemotherapy status.</p><p><strong>Conclusion: </strong>Among the CT-derived body composition parameters assessed at the C3 level, low SMA was the only significant independent predictor of OS in patients with HNSCC receiving definitive radiotherapy. These findings support the clinical relevance of SMA assessment as a straightforward and robust prognostic biomarker and underscore the need for further investigation into the prognostic potential of other body composition metrics.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond resection: imaging findings of expected and complicated postoperative changes in lung cancer.","authors":"Makiko Murota, Takashi Norikane, Mariko Ishimura, Yuka Yamamoto, Riku Morita, Katsuya Mitamura, Yasukage Takami, Yuri Manabe, Mitsumasa Murao, Katashi Satoh, Naoya Yokota, Yoshihiro Nishiyama","doi":"10.1007/s11604-025-01818-1","DOIUrl":"10.1007/s11604-025-01818-1","url":null,"abstract":"<p><p>Lung cancer remains the leading cause of cancer-related mortality, with surgical resection as the primary curative treatment for early-stage non-small cell lung cancer. However, distinguishing normal postoperative changes from complications on chest radiographs and CT scans presents a significant diagnostic challenge, necessitating precise radiologic interpretation. Postoperative complications manifest across a broad spectrum of timing and severity. Early complications include persistent air leak, pneumonia, and bronchopleural fistula, while late complications include bronchial anastomotic stricture, lung herniation, and unilateral pleuroparenchymal fibroelastosis. In addition, rare but clinically significant complications, such as lobar torsion, acute exacerbation of interstitial pneumonia, and pulmonary vein stump thrombosis, warrant careful consideration due to their potential for severe morbidity. Accurate identification of expected postoperative imaging findings and complications is essential to ensuring timely diagnosis and preventing unnecessary interventions. This review synthesizes current knowledge on surgical procedures, expected postoperative imaging findings, and key complications to refine radiologists' diagnostic acumen and ultimately improve patient outcomes.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":"1590-1605"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144325743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Navigating the AI revolution: will radiology sink or soar?","authors":"Heinz-Peter Schlemmer","doi":"10.1007/s11604-025-01810-9","DOIUrl":"10.1007/s11604-025-01810-9","url":null,"abstract":"<p><p>The rapid acceleration of digital transformation and artificial intelligence (AI) is fundamentally reshaping medicine. Much like previous technological revolutions, AI-driven by advances in computer technology and software including machine learning, computer vision, and generative models-is redefining cognitive work in healthcare. Radiology, as one of the first fully digitized medical specialties, is at the forefront of this transformation. AI is automating workflows, enhancing image acquisition and interpretation, and improving diagnostic precision, which collectively boost efficiency, reduce costs, and elevate patient care. Global data networks and AI-powered platforms are enabling borderless collaboration, empowering radiologists to focus on complex decision-making and patient interaction. Despite these profound opportunities, widespread AI adoption in radiology remains limited, often confined to specific use cases, such as chest, neuro, and musculoskeletal imaging. Concerns persist regarding transparency, explainability, and the ethical use of AI systems, while unresolved questions about workload, liability, and reimbursement present additional hurdles. Psychological and cultural barriers, including fears of job displacement and diminished professional autonomy, also slow acceptance. However, history shows that disruptive innovations often encounter initial resistance. Just as the discovery of X-rays over a century ago ushered in a new era, today, digitalization and artificial intelligence will drive another paradigm shift-this time through cognitive automation. To realize AI's full potential, radiologists must maintain clinical oversight and safeguard their professional identity, viewing AI as a supportive tool rather than a threat. Embracing AI will allow radiologists to elevate their profession, enhance interdisciplinary collaboration, and help shape the future of medicine. Achieving this vision requires not only technological readiness but also early integration of AI education into medical training. Ultimately, radiology will not be replaced by AI, but by radiologists who effectively harness its capabilities.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":"1628-1633"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479635/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144760109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of publicly available artificial intelligence models for pancreatic segmentation on T1-weighted Dixon images.","authors":"Yuki Sonoda, Shota Fujisawa, Mariko Kurokawa, Wataru Gonoi, Shouhei Hanaoka, Takeharu Yoshikawa, Osamu Abe","doi":"10.1007/s11604-025-01814-5","DOIUrl":"10.1007/s11604-025-01814-5","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to compare three publicly available deep learning models (TotalSegmentator, TotalVibeSegmentator, and PanSegNet) for automated pancreatic segmentation on magnetic resonance images and to evaluate their performance against human annotations in terms of segmentation accuracy, volumetric measurement, and intrapancreatic fat fraction (IPFF) assessment.</p><p><strong>Materials and methods: </strong>Twenty upper abdominal T1-weighted magnetic resonance series acquired using the two-point Dixon method were randomly selected. Three radiologists manually segmented the pancreas, and a ground-truth mask was constructed through a majority vote per voxel. Pancreatic segmentation was also performed using the three artificial intelligence models. Performance was evaluated using the Dice similarity coefficient (DSC), 95th-percentile Hausdorff distance, average symmetric surface distance, positive predictive value, sensitivity, Bland-Altman plots, and concordance correlation coefficient (CCC) for pancreatic volume and IPFF.</p><p><strong>Results: </strong>PanSegNet achieved the highest DSC (mean ± standard deviation, 0.883 ± 0.095) and showed no statistically significant difference from the human interobserver DSC (0.896 ± 0.068; p = 0.24). In contrast, TotalVibeSegmentator (0.731 ± 0.105) and TotalSegmentator (0.707 ± 0.142) had significantly lower DSC values compared with the human interobserver average (p < 0.001). For pancreatic volume and IPFF, PanSegNet demonstrated the best agreement with the ground truth (CCC values of 0.958 and 0.993, respectively), followed by TotalSegmentator (0.834 and 0.980) and TotalVibeSegmentator (0.720 and 0.672).</p><p><strong>Conclusion: </strong>PanSegNet demonstrated the highest segmentation accuracy and the best agreement with human measurements for both pancreatic volume and IPFF on T1-weighted Dixon images. This model appears to be the most suitable for large-scale studies requiring automated pancreatic segmentation and intrapancreatic fat evaluation.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":"1663-1669"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479682/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144325744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emergency radiology: roadmap for radiology departments.","authors":"Sonay Aydin, Bunyamin Ece, Vefa Cakmak, Burak Kocak, Mehmet Ruhi Onur","doi":"10.1007/s11604-025-01819-0","DOIUrl":"10.1007/s11604-025-01819-0","url":null,"abstract":"<p><p>Emergency radiology has evolved into a significant subspecialty over the past 2 decades, facing unique challenges including escalating imaging volumes, increasing study complexity, and heightened expectations from clinicians and patients. This review provides a comprehensive overview of the key requirements for an effective emergency radiology unit. Emergency radiologists play a crucial role in real-time decision-making by providing continuous 24/7 support, requiring expertise across various organ systems and close collaboration with emergency physicians and specialists. Beyond image interpretation, emergency radiologists are responsible for organizing staff schedules, planning equipment, determining imaging protocols, and establishing standardized reporting systems. Operational considerations in emergency radiology departments include efficient scheduling models such as circadian-based scheduling, strategic equipment organization with primary imaging modalities positioned near emergency departments, and effective imaging management through structured ordering systems and standardized protocols. Preparedness for mass casualty incidents requires a well-organized workflow process map detailing steps from patient transfer to image acquisition and interpretation, with clear task allocation and imaging pathways. Collaboration between emergency radiologists and physicians is essential, with accurate communication facilitated through various channels and structured reporting templates. Artificial intelligence has emerged as a transformative tool in emergency radiology, offering potential benefits in both interpretative domains (detecting intracranial hemorrhage, pulmonary embolism, acute ischemic stroke) and non-interpretative applications (triage systems, protocol assistance, quality control). Despite implementation challenges including clinician skepticism, financial considerations, and ethical issues, AI can enhance diagnostic accuracy and workflow optimization. Teleradiology provides solutions for staff shortages, particularly during off-hours, with hybrid models allowing radiologists to work both on-site and remotely. This review aims to guide stakeholders in establishing and maintaining efficient emergency radiology services to improve patient outcomes.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":"1606-1617"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479673/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144333133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the need for preoperative short hookwire placement for small pulmonary lesions.","authors":"Noriyuki Umakoshi, Toshihiro Iguchi, Hiroyuki Ujike, Toshiharu Mitsuhashi, Yusuke Matsui, Koji Tomita, Soichiro Okamoto, Kazuaki Munetomo, Seiichiro Sugimoto, Shinichi Toyooka, Takao Hiraki","doi":"10.1007/s11604-025-01807-4","DOIUrl":"10.1007/s11604-025-01807-4","url":null,"abstract":"<p><strong>Purpose: </strong>Although preoperative marking is often required to accurately locate the targets for video-assisted thoracic surgery, target lesions can be identified intraoperatively without marking in some cases; however, the frequency and characteristics of these lesions remain unclear. Therefore, we aimed to retrospectively evaluate the need for a short hookwire for preoperative localization of small pulmonary lesions.</p><p><strong>Materials and methods: </strong>Computed tomography (CT)-guided short hookwire placement was performed for 176 lesions (mean diameter, 7.9 ± 3.5 mm) in 171 sessions prior to video-assisted thoracoscopic surgery. Placement was performed if one or more of the following CT findings were present: lesions (1) ≤ 10 mm in diameter; (2) ≥ 5 mm from the pleural surface, and (3) predominantly consisting of ground-glass opacity. The need for a hookwire for intraoperative lesion detection was retrospectively assessed based on surgical records. Factors associated with the absence of a hookwire for lesion detection were determined using univariate and multivariate analyses.</p><p><strong>Results: </strong>Placement was successful in all cases; however, the hookwire was dislodged at the time of surgery in four lesions (2%). Among the remaining 172 lesions, thoracoscopic resection was performed using a hookwire as a landmark in 101 lesions (58.7%), whereas 71 lesions (41.3%) were detectable without a hookwire. Previous ipsilateral lung resection significantly increased the odds of not needing a hook wire (OR 4.24; P = 0.005). Larger target lesions (mean, 8.4 vs. 7.1 mm) and those located further from the pleura (mean, 13.3 vs. 8.0 mm) were associated with an increased need for hook wires. Multivariate analysis revealed that experienced surgeons required more hookwires compared to trainees (P = 0.029). Solid nodules did not require hookwires (P = 0.032).</p><p><strong>Conclusion: </strong>Shallow solid lesions in patients with a history of ipsilateral lung resection may not require hookwire placement during resection, even if they are small.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":"1696-1704"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479618/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144173741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current perspectives and emerging trends in iodine-125 seed implantation: a comprehensive bibliometric analysis.","authors":"Zhao Liu, Qinghua Zhang, Xiancun Hou, Wei Shen, Yuan Zhu, Hui Zhu, Zhiyong Li","doi":"10.1007/s11604-025-01805-6","DOIUrl":"10.1007/s11604-025-01805-6","url":null,"abstract":"<p><strong>Purpose: </strong>Iodine-125 (125-I) seed implantation is a widely used brachytherapy technique for treating various solid tumors. This study aims to provide a bibliometric analysis of the research trends, key contributors, and emerging hotspots in this field.</p><p><strong>Materials and methods: </strong>A comprehensive search was conducted using the Web of Science Core Collection, covering publications from January, 1960 to August 20, 2024. Bibliometric analysis was performed with VOSviewer, CiteSpace, and the R package \"bibliometrix\" to examine trends in publications, countries, institutions, journals, authors, and keywords.</p><p><strong>Results: </strong>The analysis included 2212 publications, showing a steady increase in research output, with USA, China, and Japan leading in publication volume. The University of California System and Keio University were the most productive institutions. Brachytherapy and the International Journal of Radiation Oncology, Biology, and Physics emerged as the most influential journals in this field. Yorozu Atsunori and Wang Junjie were identified as key authors. Keyword co-occurrence analysis highlighted \"cancer,\" \"brachytherapy,\" and \"radiotherapy\" as core themes. Keyword burst analysis revealed evolving research hotspots, such as \"hepatocellular carcinoma,\" \"efficacy,\" \"safety,\" and \"transarterial chemoembolization,\" emphasizing concerns about long-term outcomes, safety, and treatment strategies for 125-I implantation therapy across multiple cancers.</p><p><strong>Conclusion: </strong>This bibliometric analysis underscores that research on 125-I seed implantation is primarily focused on optimizing dosimetry, improving implantation techniques, and addressing long-term outcomes and safety. The findings emphasize the need for standardized treatment protocols to ensure consistent and effective clinical practice.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":"1705-1715"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479601/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144208553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prognostic value of whole-body diffusion-weighted imaging with background body signal suppression in CRPC patients undergoing Ra-223 therapy: an exploratory analysis.","authors":"Yumiko Kono, Keita Utsunomiya, Satoaki Nakamura, Yasuhiro Ueno, Kaoru Maruyama, Junichi Ikeda, Kenta Takayasu, Nae Takizawa, Hisanori Taniguchi, Masaaki Yanishi, Hidefumi Kinoshita, Noboru Tanigawa","doi":"10.1007/s11604-025-01817-2","DOIUrl":"10.1007/s11604-025-01817-2","url":null,"abstract":"<p><strong>Objectives: </strong>The aim of this study was to evaluate the utility of diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) in monitoring the response to Ra-223 therapy in patients with castration-resistant prostate cancer (CRPC) and bone metastasis.</p><p><strong>Materials and methods: </strong>This retrospective study included 15 patients with CRPC and bone metastases. DWIBS scans were performed at baseline and after three cycles of Ra-223 therapy. Quantitative analysis of tumor total diffusion volume (tDV) categorized patients as stable disease (DWIBS-SD), partial response (DWIBS-PR), or progressive disease (DWIBS-PD). Kaplan-Meier analysis and log-rank tests were used to assess the correlation between DWIBS findings and survival.</p><p><strong>Results: </strong>Of the 15 patients (median age 72 years ± 7.3), 7 (47%) were classified as DWIBS-SD, 3 (20%) as DWIBS-PR, and 5 (33%) as DWIBS-PD. DWIBS-PD group had significantly shorter survival than the DWIBS-non-PD group (P = 0.004). Despite no significant differences in age, alkaline phosphatase, prostate-specific antigen or bone metastasis volume, DWIBS-PD group had a significantly higher proportion of patients with Eastern Cooperative Oncology Group performance status score of 2 before the treatment compared to DWIBS-non-PD group (P = 0.039).</p><p><strong>Conclusion: </strong>DWIBS is a valuable tool for monitoring treatment response and predicting outcome in patients with CRPC undergoing Ra-223 therapy. Early intervention or treatment modification is recommended for patients with DWIBS-PD.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":"1688-1695"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479555/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144316933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning reconstruction for improved image quality of ultra-high-resolution brain CT angiography: application in moyamoya disease.","authors":"Yongping Ma, Satoshi Nakajima, Yasutaka Fushimi, Takeshi Funaki, Sayo Otani, Miyuki Takiya, Akira Matsuda, Satoshi Kozawa, Yasuhiro Fukushima, Sachi Okuchi, Akihiko Sakata, Takayuki Yamamoto, Ryo Sakamoto, Hideo Chihara, Yohei Mineharu, Yoshiki Arakawa, Yuji Nakamoto","doi":"10.1007/s11604-025-01806-5","DOIUrl":"10.1007/s11604-025-01806-5","url":null,"abstract":"<p><strong>Purpose: </strong>To investigate vessel delineation and image quality of ultra-high-resolution (UHR) CT angiography (CTA) reconstructed using deep learning reconstruction (DLR) optimised for brain CTA (DLR-brain) in moyamoya disease (MMD), compared with DLR optimised for body CT (DLR-body) and hybrid iterative reconstruction (Hybrid-IR).</p><p><strong>Materials and methods: </strong>This retrospective study included 50 patients with suspected or diagnosed MMD who underwent UHR brain CTA. All images were reconstructed using DLR-brain, DLR-body, and Hybrid-IR. Quantitative analysis focussed on moyamoya perforator vessels in the basal ganglia and periventricular anastomosis. For these small vessels, edge sharpness, peak CT number, vessel contrast, full width at half maximum (FWHM), and image noise were measured and compared. Qualitative analysis was performed by visual assessment to compare vessel delineation and image quality.</p><p><strong>Results: </strong>DLR-brain significantly improved edge sharpness, peak CT number, vessel contrast, and FWHM, and significantly reduced image noise compared with DLR-body and Hybrid-IR (P < 0.05). DLR-brain significantly outperformed the other algorithms in the visual assessment (P < 0.001).</p><p><strong>Conclusion: </strong>DLR-brain provided superior visualisation of small intracranial vessels compared with DLR-body and Hybrid-IR in UHR brain CTA.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":"1634-1642"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144173806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}