Japanese Journal of Radiology最新文献

{"title":"Contribution of white matter microstructure to diffusion tensor image analysis along perivascular space in obstructive sleep apnea.","authors":"Toshiaki Taoka, Kunihiro Iwamoto, Seiko Miyata, Rintaro Ito, Koji Kamagata, Rei Nakamichi, Toshiki Nakane, Mami Iima, Hiroshige Fujishiro, Masashi Ikeda, Kazushige Ichikawa, Akifumi Kamiunten, Nobuyasu Ichinose, Junko Kikuta, Shigeki Aoki, Shinji Naganawa","doi":"10.1007/s11604-025-01838-x","DOIUrl":"https://doi.org/10.1007/s11604-025-01838-x","url":null,"abstract":"<p><strong>Purpose: </strong>We aimed to evaluate whether the ALPS index derived from diffusion tensor image analysis along the perivascular space (DTI-ALPS) is influenced by white matter fibres within the analysis region, particularly commissural fibres from the corpus callosum that traverse this area in psychiatric patients with suspected obstructive sleep apnea (OSA). We also investigated associations between diffusion-based parameters, sleep-related data, and neurofluid-related imaging metrics.</p><p><strong>Methods: </strong>Fifty participants with OSA underwent brain magnetic resonance imaging and polysomnography, including diffusion tensor and structural sequences. Among them, 8 participants had no psychiatric comorbidities, while the remaining 42 had various psychiatric disorders in addition to OSA. Diffusion-based parameters were obtained, and both the original and variant ALPS index were calculated. Correlation analyses were conducted with sleep-related data and neurofluid-related imaging parameters, including choroid plexus volume (CPV) and volume of white matter lesion burden (WMHV). Mediation analyses were also performed to explore the influence of white matter diffusivity on the perivascular diffusivity index.</p><p><strong>Results: </strong>The ALPS index showed weak to moderate correlations with multiple sleep-related variables. It also correlated with CPV and WMHV. Mediation analyses demonstrated that diffusivity within white matter fibres was associated with the ALPS index. Moreover, variant ALPS indices measured in the corpus callosum may reflect fluid motion in the direction of perivascular spaces.</p><p><strong>Conclusion: </strong>These findings suggest that the ALPS index is influenced by both diffusivity along perivascular spaces and white matter microstructure, particularly commissural fibres. Although it should not be regarded as a highly specific marker of perivascular space function, variant indices support partial perivascular contribution. Furthermore, associations with sleep and neurofluid-related metrics imply that white matter architecture and inter-fibre spaces may serve as plausible routes for interstitial fluid flow.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144698579","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":"Survey and profile data on particle therapy technology in Japan.","authors":"Yuya Miyasaka, Yuki Tominaga, Yushi Wakisaka, Isamu Maeshima","doi":"10.1007/s11604-025-01844-z","DOIUrl":"https://doi.org/10.1007/s11604-025-01844-z","url":null,"abstract":"<p><p>The purpose of this study is to report profile data on the technical elements of Japanese particle therapy facilities. We requested a survey on the following four technical elements; (1) facilities and systems, (2) immobilization device and treatment planning CT, (3) patient specific QA, and (4) patient positioning. Responses were received from 21 facilities. The most commonly used accelerators were synchrotrons, which were used in 17 facilities (81.0%). The lowest available energy was widely distributed between 55.6 MeV/u and 290 MeV/u, but the maximum energy was often around 240 MeV/u for proton beams and 430 MeV for carbon ion beams. Of all treatment rooms, passive irradiation accounted for 57.7% (30 rooms), layer stacking irradiation for 7.7% (4 rooms), and scanning irradiation for 32.7% (17 rooms). Shell-type immobilization devices were most commonly used in the head and neck region, and vacuum bags were most commonly used in the thoracic to caudal regions. Lateral dose profile measurement was the most commonly used patient specific QA method. The most commonly used detector was the ionization chamber or ionization chamber-type planar detector. 2D X-ray radiography was the most commonly used in patient positioning. Marker matching was commonly used for the prostate and liver, bone matching for the head and neck and lungs, and tumor matching was used only sparingly. The results of this study may clarify current issues in particle therapy technology and provide data to guide further technology development.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144690309","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":"Overview of MRI findings in progressive multifocal leukoencephalopathy.","authors":"Koichiro Mori, Mariko Kurokawa, Masafumi Harada, Kazuo Nakamichi, Hideo Arai, Masaki Takao, Yasunobu Takaki, Yoshiharu Miura","doi":"10.1007/s11604-025-01837-y","DOIUrl":"https://doi.org/10.1007/s11604-025-01837-y","url":null,"abstract":"<p><p>Progressive multifocal leukoencephalopathy (PML) is a severe demyelinating disease of the central nervous system caused by JC virus (JCV) infection. PML affects patients with various underlying conditions, such as HIV/AIDS, hematological malignancies, organ transplants, autoimmune diseases, or multiple sclerosis particularly those receiving disease-modifying therapies. MRI plays a crucial role in diagnosis, demonstrating characteristic findings across multiple sequences, including T2-weighted imaging (T2WI)/fluid-attenuated inversion recovery (FLAIR), T1-weighted imaging (T1WI), diffusion-weighted imaging (DWI), and susceptibility-weighted imaging (SWI). Early stage markers first appear as a cluster of punctate high-signal areas in T2WI (the \"punctate pattern\") and later develop into a distribution of oval-shaped lesions of varying sizes, commonly referred to as the \"milky way appearance.\" Lesions typically show T2WI/FLAIR hyperintensity, T1WI hypointensity, and DWI hyperintensity. Recent findings highlight the significance of SWI hypointensity as a potential early marker. The prognosis varies significantly depending on the underlying condition and timing of diagnosis, with mortality rates ranging from 20 to 90%. Early detection, particularly in asymptomatic stages, significantly improves survival rates, emphasizing the importance of regular MRI screening in high-risk patients. Diagnostic challenges include low JCV DNA levels in cerebrospinal fluid (CSF), particularly in early stages and drug-associated cases, necessitating ultrasensitive PCR testing. This review provides an overview of PML's imaging characteristics, with particular emphasis on early diagnostic features using MRI, with a detailed understanding of PML's imaging characteristics across various stages and clinical subtypes, aiming to improve patient outcomes through early detection and intervention.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674803","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":"Impact of tailored feedback on optimization and radiation dose reduction in coronary CT angiography: a comparative survey between 2021 and 2023 in Mie prefecture.","authors":"Suguru Araki, Kakuya Kitagawa, Miyuko Fujita, Shintaro Yamaguchi, Takanori Kokawa, Florian Michallek, Masafumi Takafuji, Satoshi Nakamura, Yasutaka Ichikawa, Hajime Sakuma","doi":"10.1007/s11604-025-01835-0","DOIUrl":"https://doi.org/10.1007/s11604-025-01835-0","url":null,"abstract":"<p><strong>Purpose: </strong>Despite advances in dose-reduction strategies for coronary CT angiography (CCTA), a 2021 regional survey in Mie Prefecture revealed that the 75th percentile CT dose index volume (CTDIvol) remained 48 mGy-lower than Japan's 2020 diagnostic reference level (66 mGy), yet substantially exceeding international benchmarks (~ 25 mGy). Tailored feedback based on Society of Cardiovascular Computed Tomography (SCCT) guidelines was disseminated to each institution in 2022. This study aimed to evaluate the impact of these intervention on cardiac CT practice in Mie Prefecture in 2023.</p><p><strong>Materials and methods: </strong>Institutions with 64-row or greater multidetector CT scanners across Mie Prefecture were invited; 17 hospitals ultimately enrolled. Each site provided CCTA scan protocols and radiation dose data from 20 to 30 consecutive patients aged 20-80 years and weighing 50-70 kg. Examinations performed for coronary artery bypass graft evaluation or aortic valve assessment were excluded. Imaging parameters and radiation dose metrics were compared with a 2021 pre-feedback survey.</p><p><strong>Results: </strong>Data from 487 patients (median age: 71 years, 62% male) were analyzed. Of the 16 institutions participating in both surveys, 88% (14/16) modified protocols. Prospective ECG-triggered scanning increased (47-68%), retrospective scanning decreased (46-18%), and adoption of low tube potential rose (33-67%). The 75th percentile CTDIvol decreased from 48 to 31 mGy. No increase in adverse events or image quality deterioration was observed; rather, image quality exhibited an upward trend.</p><p><strong>Conclusion: </strong>Tailored regional feedback substantially improved CCTA radiation practices in Mie Prefecture, achieving significant dose reductions without compromising image quality or requiring equipment upgrades. These findings may inform protocol optimization efforts nationwide.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144667683","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":"Deep learning-based automatic detection of pancreatic ductal adenocarcinoma ≤ 2 cm with high-resolution computed tomography: impact of the combination of tumor mass detection and indirect indicator evaluation.","authors":"Mizuki Ozawa, Miyuki Sone, Susumu Hijioka, Hidenobu Hara, Yusuke Wakatsuki, Toshihiro Ishihara, Chihiro Hattori, Ryo Hirano, Shintaro Ambo, Minoru Esaki, Masahiko Kusumoto, Yoshiyuki Matsui","doi":"10.1007/s11604-025-01836-z","DOIUrl":"https://doi.org/10.1007/s11604-025-01836-z","url":null,"abstract":"<p><strong>Purpose: </strong>Detecting small pancreatic ductal adenocarcinomas (PDAC) is challenging owing to their difficulty in being identified as distinct tumor masses. This study assesses the diagnostic performance of a three-dimensional convolutional neural network for the automatic detection of small PDAC using both automatic tumor mass detection and indirect indicator evaluation.</p><p><strong>Materials and methods: </strong>High-resolution contrast-enhanced computed tomography (CT) scans from 181 patients diagnosed with PDAC (diameter ≤ 2 cm) between January 2018 and December 2023 were analyzed. The D/P ratio, which is the cross-sectional area of the MPD to that of the pancreatic parenchyma, was identified as an indirect indicator. A total of 204 patient data sets including 104 normal controls were analyzed for automatic tumor mass detection and D/P ratio evaluation. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were evaluated to detect tumor mass. The sensitivity of PDAC detection was compared with that of the software and radiologists, and tumor localization accuracy was validated against endoscopic ultrasonography (EUS) findings.</p><p><strong>Results: </strong>The sensitivity, specificity, PPV, and NPV for tumor mass detection were 77.0%, 76.0%, 75.5%, and 77.5%, respectively; for D/P ratio detection, 87.0%, 94.2%, 93.5%, and 88.3%, respectively; and for combined tumor mass and D/P ratio detections, 96.0%, 70.2%, 75.6%, and 94.8%, respectively. No significant difference was observed between the software's sensitivity and that of the radiologist's report (software, 96.0%; radiologist, 96.0%; p = 1). The concordance rate between software findings and EUS was 96.0%.</p><p><strong>Conclusions: </strong>Combining indirect indicator evaluation with tumor mass detection may improve small PDAC detection accuracy.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659255","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":"Deep learning for appendicitis: development of a three-dimensional localization model on CT.","authors":"Taku Takaishi, Tatsuya Kawai, Yoshimasa Kokubo, Takumi Fujinaga, Yoshinao Ojio, Tatsuhito Yamamoto, Kana Hayashi, Yusei Owatari, Hirotaka Ito, Akio Hiwatashi","doi":"10.1007/s11604-025-01834-1","DOIUrl":"https://doi.org/10.1007/s11604-025-01834-1","url":null,"abstract":"<p><strong>Purpose: </strong>To develop and evaluate a deep learning model for detecting appendicitis on abdominal CT.</p><p><strong>Materials and methods: </strong>This retrospective single-center study included 567 CTs of appendicitis patients (330 males, age range 20-96) obtained between 2011 and 2020, randomly split into training (n = 517) and validation (n = 50) sets. The validation set was supplemented with 50 control CTs performed for acute abdomen. For a test dataset, 100 appendicitis CTs and 100 control CTs were consecutively collected from a separate period after 2021. Exclusion criteria included age < 20, perforation, unclear appendix, and appendix tumors. Appendicitis CTs were annotated with three-dimensional bounding boxes that encompassed inflamed appendices. CT protocols were unenhanced, 5-mm slice-thickness, 512 × 512 pixel matrix. The deep learning algorithm was based on faster region convolutional neural network (Faster R-CNN). Two board-certified radiologists visually graded model predictions on the test dataset using a 5-point Likert scale (0: no detection, 1: false, 2: poor, 3: fair, 4: good), with scores ≥ 3 considered true positives. Inter-rater agreement was assessed using weighted kappa statistics. The effects of intra-abdominal fat, periappendiceal fat-stranding, presence of appendicolith, and appendix diameter on the model's recall were analyzed using binary logistic regression.</p><p><strong>Results: </strong>The model showed a precision of 0.66 (87/132), a recall of 0.87 (87/100), and a false-positive rate per patient of 0.23 (45/200). The inter-rater agreement for Likert scores of 2-4 was κ = 0.76. The logistic regression analysis showed that only intra-abdominal fat had a significant impact on the model's precision (p = 0.02).</p><p><strong>Conclusion: </strong>We developed a model capable of detecting appendicitis on CT with a three-dimensional bounding box.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144642573","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":"Vision transformer and complex network analysis for autism spectrum disorder classification in T1 structural MRI.","authors":"Xingyu Gao, Yuchao Xu","doi":"10.1007/s11604-025-01832-3","DOIUrl":"https://doi.org/10.1007/s11604-025-01832-3","url":null,"abstract":"<p><strong>Background: </strong>Autism spectrum disorder (ASD) affects social interaction, communication, and behavior. Early diagnosis is important as it enables timely intervention that can significantly improve long-term outcomes, but current diagnostic, which rely heavily on behavioral observations and clinical interviews, are often subjective and time-consuming. This study introduces an AI-based approach that uses T1-weighted structural MRI (sMRI) scans, network analysis, and vision transformers to automatically diagnose ASD.</p><p><strong>Methods: </strong>sMRI data from 79 ASD patients and 105 healthy controls were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. Complex network analysis (CNA) features and ViT (Vision Transformer) features were developed for predicting ASD. Five models were developed for each type of features: logistic regression, support vector machine (SVM), gradient boosting (GB), K-nearest neighbors (KNN), and neural network (NN). 25 models were further developed by federating the two sets of 5 models. Model performance was evaluated using accuracy, area under the receiver operating characteristic curve (AUC-ROC), sensitivity, and specificity via fivefold cross-validation.</p><p><strong>Results: </strong>The federate model CNA(KNN)-ViT(NN) achieved highest performance, with accuracy 0.951 ± 0.067, AUC-ROC 0.980 ± 0.020, sensitivity 0.963 ± 0.050, and specificity 0.943 ± 0.047. The performance of the ViT-based models exceeds that of the complex network-based models on 80% of the performance metrics. By federating CNA models, the ViT models can achieve better performance.</p><p><strong>Conclusion: </strong>This study demonstrates the feasibility of using CNA and ViT models for the automated diagnosis of ASD. The proposed CNA(KNN)-ViT(NN) model achieved better accuracy in ASD classification based solely on T1 sMRI images. The proposed method's reliance on widely available T1 sMRI scans highlights its potential for integration into routine clinical examinations, facilitating more efficient and accessible ASD screening.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144636982","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":"Longitudinal MRI changes after focal therapy for prostate cancer: cryotherapy vs. microwave tissue coagulation.","authors":"Nana Kozawa, Kaori Yamada, Bunta Tokuda, Akiko Takahata, Yayoi Iwami, Toshiko Ito-Ihara, Atsuko Fujihara, Takumi Shiraishi, Takashi Ueda, Munehiro Ohashi, Osamu Ukimura, Kei Yamada","doi":"10.1007/s11604-025-01831-4","DOIUrl":"https://doi.org/10.1007/s11604-025-01831-4","url":null,"abstract":"<p><strong>Purpose: </strong>This study compared the longitudinal changes in multiparametric magnetic resonance imaging (mpMRI) findings following lesion-targeted focal cryotherapy with those after microwave tissue coagulation (MTC) therapy for localized prostate cancer with the aim of determining their modality-specific imaging characteristics and evolution over time.</p><p><strong>Materials and methods: </strong>The study included 16 patients (17 procedures) who underwent cryotherapy and 33 patients (34 procedures) who received MTC therapy between March 2017 and February 2024. Serial mpMRI scans were retrospectively reviewed for treatment-induced signal changes on T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, and dynamic contrast-enhanced magnetic resonance imaging (MRI). Three radiologists independently reviewed the images, and interobserver agreement was evaluated.</p><p><strong>Results: </strong>Early post-treatment MRI findings indicated distinct modality-specific patterns. Cryotherapy-treated lesions frequently demonstrated marked T1 hyperintensity, whereas MTC-treated lesions predominantly showed slight hyperintensity. On T2-weighted imaging and diffusion-weighted imaging, cryotherapy-treated lesions were characterized by hyperintensity with a hypointense rim, while MTC therapy was more likely to result in heterogeneous hypointensity. Early rim enhancement was common on dynamic contrast-enhanced MRI following cryotherapy (71.4%) and MTC (83.3%) and resolved by 23 and 41 months, respectively. In the late phase (> 12 months), imaging findings generally progressed toward fibrosis, which was characterized by hypointensity across all sequences without enhancement, although convergence timing varied from patient to patient.</p><p><strong>Conclusions: </strong>While there are distinct modality-specific differences in MRI characteristics in the early phase after between focal cryotherapy and MTC therapy for localized prostate cancer, late-stage findings converge, primarily reflecting fibrosis. These MRI features can help when monitoring the treatment response and guide appropriate follow-up planning.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144600403","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":"Whole-tumor histogram analysis of synthetic MRI relaxation maps for nasopharyngeal carcinoma: correlations with histopathologic components.","authors":"Yiheng Zhou, Bowen Zheng, Jiankun Dai, Jing Zhao, Shuang Han, Jun Chang, Heng Zhang, Peng Wang, Shudong Hu","doi":"10.1007/s11604-025-01824-3","DOIUrl":"https://doi.org/10.1007/s11604-025-01824-3","url":null,"abstract":"<p><strong>Purpose: </strong>To explore the correlation between the histogram parameters from synthetic magnetic resonance imaging (syMRI) relaxation maps and histopathologic components in nasopharyngeal carcinoma (NPC).</p><p><strong>Methods: </strong>Eighty NPC patients who performed syMRI examination were retrospectively enrolled between September 2020 to June 2022, and whole-tumor histogram parameters from syMRI relaxation maps (T1, T2, PD) were obtained. The relationship between histogram parameters and histopathologic components were investigated using the Spearman correlation coefficient, and stepwise multiple linear regression analysis was used to select the independent factors. Kaplan-Meier analysis and log-rank test were performed to compare differences in progression-free survival between low and high histopathologic components.</p><p><strong>Results: </strong>The histogram parameters from T1 and T2 maps were significantly correlated with histopathologic components, including cellular, stromal, nuclear, cytoplasmic fractions, and nuclear/cytoplasmic (N/C) ratio (P < 0.007), whereas no significant correlations were found between any histogram parameters from PD and histopathologic components (P > 0.007). T1_mean was independently associated with cellular, stromal, nuclear fractions, and N/C ratio, and T2_skewness was independently associated with cytoplasmic fraction. High cellular, stromal, and nuclear fractions as well as N/C ratio, and low cytoplasmic fraction were correlated with poor progression-free survival.</p><p><strong>Conclusions: </strong>The syMRI quantitative parameters were significantly correlated with histopathologic components in NPC, which aids in adjusting treatment strategies and predicting prognosis at an early stage.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144591268","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":"Performance of a deep-learning-based lung nodule detection system using 0.25-mm thick ultra-high-resolution CT images.","authors":"Haruka Higashibori, Wataru Fukumoto, Sayaka Kusuda, Kazushi Yokomachi, Hidenori Mitani, Yuko Nakamura, Kazuo Awai","doi":"10.1007/s11604-025-01828-z","DOIUrl":"https://doi.org/10.1007/s11604-025-01828-z","url":null,"abstract":"<p><strong>Purpose: </strong>Artificial intelligence (AI) algorithms for lung nodule detection assist radiologists. As their performance using ultra-high-resolution CT (U-HRCT) images has not been evaluated, we investigated the usefulness of 0.25-mm slices at U-HRCT using the commercially available deep-learning-based lung nodule detection (DL-LND) system.</p><p><strong>Materials and methods: </strong>We enrolled 63 patients who underwent U-HRCT for lung cancer and suspected lung cancer. Two board-certified radiologists identified nodules more than 4 mm in diameter on 1-mm HRCT slices and set the reference standard consensually. They recorded all lesions detected on 5-, 1-, and 0.25-mm slices by the DL-LND system. Unidentified nodules were included in the reference standard. To examine the performance of the DL-LND system, the sensitivity, and positive predictive value (PPV) and the number of false positive (FP) nodules were recorded.</p><p><strong>Results: </strong>The mean number of lesions detected on 5-, 1-, and 0.25-mm slices was 5.1, 7.8 and 7.2 per CT scan. On 5-mm slices the sensitivity and PPV were 79.8% and 46.4%; on 1-mm slices they were 91.5% and 34.8%, and on 0.25-mm slices they were 86.7% and 36.1%. The sensitivity was significantly higher on 1- than 5-mm slices (p < 0.01) while the PPV was significantly lower on 1- than 5-mm slices (p < 0.01). A slice thickness of 0.25 mm failed to improve its performance. The mean number of FP nodules on 5-, 1-, and 0.25-mm slices was 2.8, 5.2, and 4.7 per CT scan.</p><p><strong>Conclusion: </strong>We found that 1 mm was the best slice thickness for U-HRCT images using the commercially available DL-LND system.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144575514","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}