European Journal of Radiology Open最新文献

{"title":"Diaphragmatic curvature analysis using dynamic digital radiography","authors":"Takuya Hino ,&nbsp;Akinori Tsunomori ,&nbsp;Noriaki Wada ,&nbsp;Akinori Hata ,&nbsp;Taiki Fukuda ,&nbsp;Yusei Nakamura ,&nbsp;Yoshitake Yamada ,&nbsp;Tomoyuki Hida ,&nbsp;Mizuki Nishino ,&nbsp;Masako Ueyama ,&nbsp;Atsuko Kurosaki ,&nbsp;Takeshi Kubo ,&nbsp;Shoji Kudoh ,&nbsp;Kousei Ishigami ,&nbsp;Hiroto Hatabu","doi":"10.1016/j.ejro.2025.100676","DOIUrl":"10.1016/j.ejro.2025.100676","url":null,"abstract":"<div><h3>Purpose</h3><div>To investigate area under diaphragm (AUD) obtained by dynamic digital radiography (DDR) for the differentiation between normal subjects and chronic obstructive pulmonary disease (COPD) patients.</div></div><div><h3>Methods</h3><div>This retrospective study included healthy volunteers and COPD patients recruited from 2009 to 2014 at Fukujuji Hospital, who received DDR and pulmonary functional test. AUD was defined as an area under a hemidiaphragm and above the line connecting the ipsilateral costophrenic angle to the top of the hemidiaphragm on DDR image. AUD in full inspiration minus AUD in full expiration (ΔAUD) was also calculated. The diaphragmatic surface was demarcated manually on DDR image to calculate AUD. Three-group comparison of AUD and ΔAUD among normal, mild COPD, and severe COPD subjects was tested with one-way analysis of variance, followed by multiple comparison with Tukey-Kramer method. The diagnostic accuracy of COPD by ΔAUD was assessed using receiver-operating-characteristics (ROC) curve.</div></div><div><h3>Results</h3><div>Sixty-eight participants (36 men, 29 COPD patients) were enrolled. AUD in full inspiration was larger in healthy volunteers than in COPD patients (right, p &lt; 0.001; left, p = 0.02). ΔAUD were different in the three-group comparison (right, normal, 208.7 ± 184.6 mm², mild COPD, −18.1 ± 117.5 mm², severe COPD −97.5 ± 150.0 mm², p &lt; 0.001; left, normal, 254.9 ± 131.5 mm², mild COPD, −12.5 ± 136.5 mm², severe COPD, −100.7 ± 134.1 mm², p &lt; 0.001). ROC curve showed high diagnostic performance of COPD by unilateral ΔAUD (right, area-under curve 0.942; left, area-under-curve 0.965).</div></div><div><h3>Conclusion</h3><div>The value of ΔAUD was smaller according to the severity of COPD. ΔAUD can be helpful in distinguishing healthy subjects from COPD patients.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100676"},"PeriodicalIF":2.9,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773008","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":"AI-driven assessment of over-scanning in chest CT: A systematic review and meta-analysis","authors":"Mo’men Bani-Ahmad ,&nbsp;Andrew England ,&nbsp;Laura McLaughlin ,&nbsp;Marwan Alshipli ,&nbsp;Kholoud Alzyoud ,&nbsp;Yasser H. Hadi ,&nbsp;Mark McEntee","doi":"10.1016/j.ejro.2025.100674","DOIUrl":"10.1016/j.ejro.2025.100674","url":null,"abstract":"<div><h3>Introduction</h3><div>Scan range is crucial for CT acquisitions. However, irrelevant over-scanning in CT is common and contributes to a significant radiation dose. This review explores the role of artificial intelligence (AI) in addressing manual over-scanning in chest CT imaging.</div></div><div><h3>Methods</h3><div>A systematic search of peer-reviewed publications was conducted between December 2015 and March 2025 in Embase, Scopus, Ovid, EBSCOhost, and PubMed. Two reviewers and an academic lecturer independently reviewed the articles to ensure adherence to inclusion criteria. The quality of the included studies was assessed using CLAIM and QUADAS-2 tools. Summary estimates on over-scanning at the upper and lower boundaries of the scan range in chest CT were derived using meta-analysis.</div></div><div><h3>Results</h3><div>Five studies employed AI algorithms to assess manual over-scanning in chest CT using either 2D topograms or 3D axial images at low and standard doses. These models accurately determine the extent of over-scanning, demonstrating strong agreement with radiologist evaluations. All included studies revealed significant variation in over-scanning at the superior (13.5 mm) and inferior (30.2 mm) boundaries of the scan range (p &lt; 0.001), with approximately two-thirds of the total over-scanning (43.2 mm) occurring at the inferior level (abdomen).</div></div><div><h3>Conclusions</h3><div>Integrating AI tools into the over-scanning evaluation process may optimise chest CT imaging protocols and enhance patient safety by reducing over-scanning and radiation dose through real-time monitoring and retrospective analysis.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100674"},"PeriodicalIF":2.9,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724529","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":"Evaluation of assumed tumour volume in multiple myeloma using dual-energy spectral CT and its correlation between haematological findings","authors":"Tetsuya Kosaka ,&nbsp;Chisaki Masuda ,&nbsp;Sachiho Tatebe ,&nbsp;Risen Hirai ,&nbsp;Akira Tanimura","doi":"10.1016/j.ejro.2025.100675","DOIUrl":"10.1016/j.ejro.2025.100675","url":null,"abstract":"<div><h3>Objectives</h3><div>To measure the assumed tumour volume in the humerus of patients with multiple myeloma using dual-energy spectral computed tomography (DESCT) and to evaluate the correlation with haematological indicators.</div></div><div><h3>Methods</h3><div>We retrospectively analysed 82 DESCT examinations of 22 patients diagnosed with multiple myeloma. After extracting the bilateral humeri and removing the bone tissue, we measured the volume of the assumed tumour area using a single threshold based on Hounsfield unit values and double thresholds using material density images. We analysed the correlations between tumour volume and haematological indicators (β2-microglobulin, M-protein, free light chain, albumin, lactate dehydrogenase) and the trends after treatment intervention.</div></div><div><h3>Results</h3><div>A moderate correlation was identified between the assumed tumour volume in the initial scan and the β2-microglobulin level, with a correlation coefficient of ρ = 0.69 for the volume calculated from a single threshold value of Hounsfield unit and ρ = 0.57 for the volume calculated from a double threshold value of the bone(fat) material density image. No significant correlation was found between the assumed tumour volume and the M-protein or free light chain levels. In patients who underwent three or more follow-up evaluations after the initial examination, there was a similarity in the changes in the assumed tumour volume and β2-microglobulin levels after treatment.</div></div><div><h3>Conclusion</h3><div>Extracting assumed tumour volume using DESCT has sufficient potential as a biomarker for multiple myeloma.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100675"},"PeriodicalIF":2.9,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721098","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 accuracy of MRI radiomics in predicting lymph node metastasis in prostate cancer: A systematic review","authors":"Alireza Teymouri ,&nbsp;Mohammad Saeid Khonji ,&nbsp;Parisa Alaghi ,&nbsp;Sina Azadnajafabad ,&nbsp;Ava Teymouri ,&nbsp;Sina Delazar","doi":"10.1016/j.ejro.2025.100673","DOIUrl":"10.1016/j.ejro.2025.100673","url":null,"abstract":"<div><h3>Purpose</h3><div>Prostate cancer (PCa) is frequently associated with pelvic lymph node metastasis (PLNM), which may be missed by conventional imaging, particularly in micrometastatic disease. MRI-based radiomics offers potential to improve detection. This review evaluates recent advancements and diagnostic accuracy of MRI radiomics for predicting PLNM in PCa patients.</div></div><div><h3>Methods</h3><div>PubMed, Embase, and Web of Science were systematically searched through January 1, 2025, using terms like “prostate cancer,” “radiomics,” and “pelvic lymph node metastasis.” Eligible studies were assessed using the Radiomics Quality Score (RQS). Study characteristics and performance metrics were narratively synthesized. Pooled area under the receiver operating characteristic curve (AUC) was calculated for PLNM prediction in studies using prostate as regions of interest (ROI), reported with 95 % confidence intervals (CI); p-value &lt; 0.05 was considered significant.</div></div><div><h3>Results</h3><div>Nine studies (2021–2024) involving 2344 PCa patients were included. Radiomics models using prostate as ROI achieved a pooled AUC of 0.78 (95 %CI: 0.72–0.84) with mild heterogeneity (I² = 19.81 %, p &lt; 0.38). Models with lymph nodes as ROI showed AUCs of 0.93–0.95. Integrating imaging reports and clinical data often improved diagnostic accuracy. Radiomics outperformed clinical nomograms in five studies, although the difference was insignificant in one study (p &gt; 0.05). Median RQS was 16/36; studies lacked prospective design and cost-effectiveness analysis.</div></div><div><h3>Conclusion</h3><div>MRI radiomics predicts PLNM with moderate accuracy, particularly when using pelvic lymph nodes as ROI. Standardized protocols, feature extraction, and clinical data integration are crucial for consistency. Prospective studies with larger cohorts are needed to validate these findings.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100673"},"PeriodicalIF":2.9,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721165","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":"Combination of imaging features on pancreatic CT for predicting early recurrence after upfront pancreatoduodenectomy of pancreatic ductal adenocarcinoma","authors":"Shuanglin Zhang ,&nbsp;Yi-Xuan Guo ,&nbsp;Gui-Xue Dai ,&nbsp;Xiumin Qi ,&nbsp;Hao Wang ,&nbsp;Yongping Zhou ,&nbsp;Kai Zhang ,&nbsp;Fang-Ming Chen","doi":"10.1016/j.ejro.2025.100672","DOIUrl":"10.1016/j.ejro.2025.100672","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aimed to identify preoperative computed tomography (CT) imaging features for predicting early recurrence after upfront pancreatoduodenectomy of pancreatic ductal adenocarcinoma (PDAC), and to assess the diagnostic performance and prognostic relevance of their combination.</div></div><div><h3>Methods</h3><div>This study retrospectively included PDAC patients who underwent pancreatoduodenectomy and preoperative pancreatic CT between January 2016 and December 2023. Early recurrence is defined based on imaging evidence or pathology within 12 months after surgery. Significant imaging features for early recurrence were identified using univariate and multivariate analyses. Disease-free survival (DFS) and overall survival (OS) were analyzed in relation to these significant imaging features.</div></div><div><h3>Results</h3><div>A total of 149 patients were evaluated (median age: 67 years; interquartile range: 41–89 years; 82 men), among whom 70 (47.0 %) experienced early recurrence. Rim enhancement, tumor necrosis, peripancreatic tumor infiltration, and suspicious metastatic lymph nodes, were independently associated with early recurrence. When any two or more of these four significant imaging features were combined, the specificity was 86.1 % (68/79) and the sensitivity was 88.6 % (60/70). DFS and OS were significantly worse in PDAC patients with two or more of these features compared to those with none or only one (all log-rank <em>P</em> &lt; 0.001).</div></div><div><h3>Conclusion</h3><div>A combination of two or more imaging features such as rim enhancement, tumor necrosis, peripancreatic tumor infiltration, and suspicious metastatic lymph nodes, could be used as a prognostic imaging marker for early recurrence, demonstrating effective diagnostic performance and an association with DFS and OS after pancreatoduodenectomy of PDAC.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100672"},"PeriodicalIF":1.8,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711448","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":"Deep-learning-based 3D content-based image retrieval system on chest HRCT: Performance assessment for interstitial lung diseases and usual interstitial pneumonia","authors":"Akira Oosawa ,&nbsp;Atsuko Kurosaki ,&nbsp;Atsushi Miyamoto ,&nbsp;Shigeo Hanada ,&nbsp;Yuichiro Nei ,&nbsp;Hiroshi Nakahama ,&nbsp;Yui Takahashi ,&nbsp;Takahiro Mitsumura ,&nbsp;Hisashi Takaya ,&nbsp;Tomohisa Baba ,&nbsp;Tae Iwasawa ,&nbsp;Masatoshi Hori ,&nbsp;Shoji Kido ,&nbsp;Takashi Ogura ,&nbsp;Noriyuki Tomiyama ,&nbsp;Kazuma Kishi ,&nbsp;Meiyo Tamaoka","doi":"10.1016/j.ejro.2025.100670","DOIUrl":"10.1016/j.ejro.2025.100670","url":null,"abstract":"<div><h3>Background</h3><div>Diffuse parenchymal lung diseases have various conditions and CT imaging findings. Differentiating interstitial lung diseases (ILDs) and determining the presence or absence of usual interstitial pneumonia (UIP), can be challenging, even for experienced radiologists. To address this challenge, we developed a 3D-content-based image retrieval system (CBIR) and investigated its clinical usefulness.</div></div><div><h3>Methods</h3><div>Using deep learning technology, we developed a prototype system that analyzes thin-slice whole lung HRCT images, automatically registers them in a database, and retrieves similar images. To evaluate search performance, we used a database of 2058 cases and assessed image similarity between query and retrieved cases using a 5-point visual score (5: Similar, 4: Somewhat similar, 3: Neither, 2: Somewhat dissimilar, 1: Dissimilar). To assess clinical usefulness, we evaluated the concordance of labels (ILD/non-ILD, with/without UIP) between query and retrieved cases, using a database of 301 cases across 57 diseases.</div></div><div><h3>Results</h3><div>For search performance, the mean score of visual similarity between 70 queries and their top 5 retrieved cases was 4.37 ± 0.83. For clinical usefulness, label concordance between 25 queries and their top 5 retrieved cases was assessed across 4 labels. For ILD, the mean concordance of labels was 0.94 ± 0.15, while for non-ILD, it was 0.64 ± 0.31. For cases with UIP, the mean concordance of labels was 0.86 ± 0.17, while for cases without UIP, it was 0.83 ± 0.24.</div></div><div><h3>Conclusions</h3><div>Our CBIR system showed high accuracy for identifying cases with/without UIP, suggesting its potential to support UIP differentiation in clinical practice.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100670"},"PeriodicalIF":1.8,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144694930","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":"Comparative evaluation of four reconstruction techniques for prostate T2-weighted MRI: Sensitivity encoding, compressed sensing, deep learning, and super-resolution","authors":"Noriko Nishioka ,&nbsp;Noriyuki Fujima ,&nbsp;Satonori Tsuneta ,&nbsp;Daisuke Kato ,&nbsp;Takashi Kamiishi ,&nbsp;Masato Yoshikawa ,&nbsp;Rina Kimura ,&nbsp;Keita Sakamoto ,&nbsp;Ryuji Matsumoto ,&nbsp;Takashige Abe ,&nbsp;Jihun Kwon ,&nbsp;Masami Yoneyama ,&nbsp;Kohsuke Kudo","doi":"10.1016/j.ejro.2025.100671","DOIUrl":"10.1016/j.ejro.2025.100671","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate and compare the image quality and lesion conspicuity of prostate T2-weighted imaging (T2WI) using four reconstruction methods: conventional Sensitivity Encoding (SENSE), compressed sensing (CS), model-based deep learning reconstruction (DL), and deep learning super-resolution reconstruction (SR).</div></div><div><h3>Methods</h3><div>This retrospective study included 49 patients who underwent multiparametric MRI (mpMRI) or biparametric MRI (bpMRI) for suspected prostate cancer. Axial T2WI was acquired using two protocols: conventional SENSE and CS-based acquisition. From the CS-based data, three reconstruction methods (CS, DL, and SR) were applied to generate additional images. Two board-certified radiologists independently assessed overall image quality and sharpness using a 4-point Likert scale (1 = poor, 4 = excellent). Quantitative analysis included signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and sharpness index. PI-RADS T2WI scoring and lesion conspicuity were preliminarily evaluated in 18 individuals with pathologically confirmed prostate cancer. Statistical comparisons were conducted using the Wilcoxon signed-rank test.</div></div><div><h3>Results</h3><div>SR consistently achieved the highest scores in both qualitative (overall image quality, image sharpness) and quantitative (SNR, CNR, sharpness index) assessments, compared with SENSE, CS, and DL (all pairwise comparisons, Bonferroni-corrected p &lt; 0.0001). In lesion-based analysis, SR showed a trend toward improved lesion conspicuity, although PI-RADS T2WI scores were similar across reconstruction.</div></div><div><h3>Conclusion</h3><div>SR reconstruction demonstrated superior image quality in both qualitative and quantitative assessments and showed potential benefits for lesion visualization. These findings, although based on a small sample, suggest that SR may be a promising approach for prostate MRI and warrants further investigation in larger populations.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100671"},"PeriodicalIF":1.8,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679963","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":"Limited additional value of dual-layer spectral 4DCT compared with conventional 4DCT for preoperative localization in primary hyperparathyroidism","authors":"Jorian P. Krol ,&nbsp;Tessa Veerbeek ,&nbsp;Laura N. Deden ,&nbsp;Frank B.M. Joosten ,&nbsp;Marie Louise E. Bernsen ,&nbsp;Cornelis H. Slump ,&nbsp;Wim J.G. Oyen","doi":"10.1016/j.ejro.2025.100669","DOIUrl":"10.1016/j.ejro.2025.100669","url":null,"abstract":"<div><h3>Purpose</h3><div>Primary hyperparathyroidism, characterized by excessive parathyroid hormone secretion, is typically caused by solitary parathyroid adenomas or multiglandular disease. Accurate preoperative localization is critical for successful surgical parathyroidectomy. While four-dimensional CT (4DCT) is commonly used for this purpose, spectral-CT techniques have recently been introduced, offering improved tissue differentiation. Rapid kV switching and dual-source spectral-CT have been studied, however, this is the first study that evaluates the effectiveness of dual-layer-CT in preoperatively locating parathyroid adenomas in a larger population.</div></div><div><h3>Approach</h3><div>From April 2020 to October 2023, patients with confirmed primary hyperparathyroidism underwent dual-layer spectral 4DCT before surgery. Spectral reconstructions (MonoE40keV, Iodine-Density, Z-effective, Iodine-no-Water, Virtual Non-Contrast) were analyzed alongside conventional CT reconstructions. Mean attenuation values were compared using one-way ANOVA. ROC curves with paired-sample analysis assessed the ability of different reconstructions to distinguish between thyroid and parathyroid tissue, and lymph nodes and parathyroid tissue.</div></div><div><h3>Results</h3><div>Thirty-six patients with thirty-nine parathyroid adenomas were analyzed. Conventional CT reconstructions demonstrated significantly higher AUC values for differentiating thyroid from parathyroid tissue across all phases compared to spectral reconstructions (0.83–0.95 vs. 0.65–0.89, p-value 0.007-&lt;0.001). No significant difference was found between conventional and spectral reconstructions in distinguishing lymph nodes from parathyroid tissue (0.64–0.96 vs. 0.58–0.96, p-value 0.070–0.957). Virtual non-contrast (VNC) reconstructions showed smaller attenuation differences and lower AUC values in arterial and delayed phases compared to true non-contrast (p = 0.031 and 0.034).</div></div><div><h3>Conclusions</h3><div>Dual-layer spectral-CT is comparable or inferior to conventional CT in tissue differentiation. VNC reconstructions are not recommended as a substitute for true non-contrast due to inconsistent results. In this cohort, dual-layer spectral 4DCT did not demonstrate clear clinical advantage; further validation is warranted.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100669"},"PeriodicalIF":1.8,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470000","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":"CT-based deep learning radiomics analysis for preoperative Lauren classification in gastric cancer and explore the tumor microenvironment","authors":"Ming Cheng ,&nbsp;Yimin Guo ,&nbsp;Huiping Zhao ,&nbsp;Hanyue Zhang ,&nbsp;Pan Liang ,&nbsp;Jianbo Gao","doi":"10.1016/j.ejro.2025.100667","DOIUrl":"10.1016/j.ejro.2025.100667","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aimed to investigate the usefulness of CT-based deep learning radiomics analysis (DLRA) for preoperatively differentiating Lauren classification in gastric cancer (GC) patients and explore the tumor microenvironment.</div></div><div><h3>Methods</h3><div>578 patients were recruited from January 2015 to June 2024, and divided into the training cohort (n = 311), the internal validation cohort (n = 132), and the external validation cohort (n = 135). Clinical characteristics were collected. Radiomics features were extracted from CT images at arterial phase (AP) and venous phase (VP). A radiomics nomogram incorporating radiomics signature and clinical information was built for distinguishing Lauren classification, and its discrimination, calibration, and clinical usefulness were evaluated. RNA sequencing data from The Cancer Imaging Archive database were used to perform transcriptomics analysis.</div></div><div><h3>Results</h3><div>The nomogram incorporating the two radiomics signatures and clinical characteristics exhibited good discrimination of Lauren classification on all cohorts [overall C-indexes 0.815 (95 % CI: 0.739–0.869) in the training cohort, 0.785 (95 % CI: 0.702–0.834) in the internal validation cohort, 0.756 (95 % CI: 0.685–0.816) in the external validation cohort]. It outperformed the clinical model in predictive ability. The calibration and decision curve substantiated the model's excellent fitness and clinical applicability. Further, transcriptomics analysis showed that the differentially expressed genes of different Lauren types were mainly enriched in pathways related to cell contraction and migration, and the infiltration degree of various immune cells was also significantly different.</div></div><div><h3>Conclusions</h3><div>DLRA effectively differentiated Lauren classification in GC, and our analysis of transcriptomic data across different Lauren subtypes revealed the heterogeneity within the GC microenvironment.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100667"},"PeriodicalIF":1.8,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330263","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":"High-pitch photon-counting detector computed tomography angiography of the coronary arteries: Qualitative and quantitative evaluation of monoenergetic image reconstructions","authors":"Andreas Strassl ,&nbsp;Francesco Lauriero ,&nbsp;Maria Alejandra Rueda ,&nbsp;Christian Wassipaul ,&nbsp;Michael Weber ,&nbsp;Christian Loewe ,&nbsp;Dietrich Beitzke ,&nbsp;Lucian Beer","doi":"10.1016/j.ejro.2025.100666","DOIUrl":"10.1016/j.ejro.2025.100666","url":null,"abstract":"<div><h3>Background</h3><div>Dual-source photon-counting detector computed tomography (PCDCT) offers the opportunity to perform cardiac examinations within one beat and simultaneously the acquisition of spectral information. This study, evaluated subjective and objective image quality of virtual monoenergetic image (VMI) reconstructions using data from a first-generation, dual-source PCDCT scanner, operated in high-pitch scanning mode.</div></div><div><h3>Methods</h3><div>We retrospectively included 30 patients who underwent a clinically indicated CTA of the coronary arteries. VMI were reconstructed at five different energy levels. Subjective image quality was assessed by three radiologists according to a four-point Likert scale for four different quality features. To evaluate objective image quality, SNR and CNR were calculated via ROIs placed in the aorta, coronary arteries, myocardium, pectoral muscle, and epicardial fat.</div></div><div><h3>Results</h3><div>VMI at 40, 50, 60, and 70 keV showed equal mean scores (4/4) for subjective vascular contrast, followed by 80 keV reconstructions with a mean score of 3/4. The 40 keV reconstruction yielded the lowest range (3−4) in Likert scores and highest percentage of reader agreement (80 %). Minor differences in subjective image noise, sharpness, and plaque visualization were observed with positive trends toward higher keV levels. SNR and CNR were superior for 40 keV, with a mean of 34.8 ± 1.7HU and 45.4 ± 2.7HU, respectively. Mean applied contrast volume was 65 ml, resulting in a mean CT value of 1150HU for 40 keV VMI.</div></div><div><h3>Conclusion</h3><div>First-generation PCDCT-derived VMI at 40 and 50 keV offer satisfying subjective and objective image quality, even when acquired in high-pitch scanning mode.</div></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"15 ","pages":"Article 100666"},"PeriodicalIF":1.8,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279997","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}