Journal of Computer Assisted Tomography最新文献

{"title":"Can Spectral CT Serve as a Surrogate for Perfusion CT to Evaluate Lymphovascular and Perineural Invasion in Gastric Cancer? A Prospective Study Using a One-Stop CT Protocol.","authors":"Tiezhu Ren, Long Ma, Yue Peng, Qianqian Chen, Yunhang Jing, Wei Ren, Yuan Xu, Xinan Su, Hongman Chen, Jiahui Liang, Wenjuan Zhang, Junlin Zhou","doi":"10.1097/RCT.0000000000001902","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001902","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the clinical utility of a \"One-stop\" spectral CT combined with perfusion CT scan for preoperative assessment of lymphovascular invasion (LVI) and perineural invasion (PNI) in gastric cancer (GC) and to investigate whether spectral CT parameters can serve as reliable surrogates for perfusion CT biomarkers in risk stratification.</p><p><strong>Methods: </strong>In this prospective study, 87 patients with histologically confirmed gastric adenocarcinoma underwent preoperative contrast-enhanced \"One-stop\" spectral CT combined with perfusion CT scan at our institution. Patients were stratified into LVI/PNI-positive (n=65) and LVI/PNI-negative (n=22) groups based on postoperative pathology. Spectral parameters-including iodine concentration (IC), effective atomic number (Zeff), and water concentration (WC)-were measured in arterial (AP) and venous (VP) phases. Perfusion parameters included blood volume (BV), blood flow (BF), mean transit time (MTT), permeability-surface area product (PS), and time to peak (Tmax). Intergroup comparisons, diagnostic performance evaluation, and correlation analyses between spectral and perfusion parameters were performed.</p><p><strong>Results: </strong>Significant differences were observed between LVI/PNI-positive and -negative groups for Zeff (in both AP and VP), IC (in VP), BV, and MTT (all P<0.05). In contrast, no significant differences were found for WC, BF, PS, or Tmax. A combined diagnostic model integrating spectral and perfusion parameters (AP+VP+P) achieved the highest performance, with an area under the curve (AUC) of 0.862 and an F1 score of 0.892. Notably, VP-IC demonstrated a strong positive correlation with BV (Spearman ρ=0.751, P<0.001), underscoring the potential of spectral CT to reflect tumor perfusion noninvasively.</p><p><strong>Conclusion: </strong>Spectral CT parameters, particularly VP-IC, show a strong correlation with the perfusion biomarker BV and offer comparable diagnostic accuracy for detecting LVI/PNI in GC. This supports the role of spectral CT as a viable surrogate for perfusion CT. The integrated \"One-stop\" protocol, enabling simultaneous acquisition of both data sets in a single scan, provides a streamlined and clinically practical approach to preoperative risk stratification.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149227939","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":"MRI Artifacts in Clinical Practice: Recognition, Pitfalls, and Practical Solutions.","authors":"Jonathan Gan, Ananya Panda, Yashant Aswani, Judy R James, Prabhakaran A V, Anu P Gayathri","doi":"10.1097/RCT.0000000000001908","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001908","url":null,"abstract":"<p><p>Magnetic resonance imaging (MRI) is integral to modern clinical practice owing to its superior soft-tissue contrast. However, the complexity of MRI physics predisposes examinations to numerous artifacts that may mimic pathology, obscure disease, or lead to misinterpretation in routine clinical settings. Failure to recognize these artifacts can result in diagnostic error, unnecessary additional imaging, or inappropriate clinical management. This practical review categorizes commonly encountered MRI artifacts by underlying mechanisms and highlights their typical imaging appearances across routine clinical applications. Emphasis is placed on differentiating artifacts from true pathology and on providing actionable strategies for artifact recognition, troubleshooting, and prevention during image acquisition and interpretation. By integrating imaging examples with clinically relevant explanations of the underlying physics, this review aims to equip practicing radiologists and trainees with a structured approach to confidently identify misleading findings and improve diagnostic accuracy in everyday practice.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149193788","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":"Association Between Fractal Dimension and Rupture Status in Intracranial Saccular Aneurysms: A CTA-Based Study.","authors":"Aykut Alkan, Semih Uslu, Savaş Hereklioğlu, Derya Karabulut, Ahmet Onur Çelik, Serdar Solak","doi":"10.1097/RCT.0000000000001934","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001934","url":null,"abstract":"<p><strong>Objective: </strong>To investigate the association between fractal dimension (FD) and rupture status in intracranial saccular aneurysms and to compare FD values between ruptured and unruptured aneurysms.</p><p><strong>Methods: </strong>This retrospective study included 145 patients with intracranial saccular aneurysms, comprising 72 ruptured and 73 unruptured cases. Aneurysms were segmented from computed tomography angiography images using semiautomated techniques. Two-dimensional (2D) fractal analysis was performed on binary and outline images generated from the segmented aneurysms using ImageJ with the FracLac plugin, and FD values were calculated using the box-counting method. Conventional morphologic parameters, including aneurysm size, aspect ratio (AR), and size ratio (SR), were also assessed. Group comparisons, multivariable logistic regression, and receiver operating characteristic (ROC) analyses were performed.</p><p><strong>Results: </strong>Binary FD values were significantly lower in ruptured than in unruptured aneurysms (1.742±0.018 vs. 1.753±0.016, P=0.015), whereas outline FD values showed no significant difference. In multivariable logistic regression analysis, standardized binary FD, AR, and SR were identified as independent predictors of aneurysm rupture. ROC analysis demonstrated modest discriminatory performance for binary FD, with an area under the curve of 0.620 (95% CI: 0.529-0.711). At an optimal cutoff value of 1.745, binary FD yielded a sensitivity of 65.8%, specificity of 47.2%, positive predictive value of 54.7%, and negative predictive value of 57.6%.</p><p><strong>Conclusion: </strong>Binary FD differed significantly between ruptured and unruptured intracranial saccular aneurysms and remained independently associated with rupture status after adjustment for conventional morphologic parameters. However, given the retrospective design and the modest discriminatory performance of FD, these findings should be interpreted as an association with rupture status rather than evidence of prospective rupture-risk prediction.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149193804","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":"A Pilot Study of Photon Counting CT Spectral Analysis Following Pancreatic Adenocarcinoma Resection to Differentiate Local Recurrence From Postsurgical Fibrosis.","authors":"Samantha Platt, Bhavik Bansal, Barun Bagga, Thomas O'Donnell, Bari Dane","doi":"10.1097/RCT.0000000000001935","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001935","url":null,"abstract":"<p><strong>Objective: </strong>To assess photon counting CT (PCCT) spectral parameters in the differentiation of locally recurrent pancreatic adenocarcinoma (PDAC) from benign postsurgical fibrosis after PDAC surgical resection.</p><p><strong>Methods: </strong>Twenty-two patients [12 male, mean±SD: age 71 (8) y] who underwent pancreas protocol PCCT following surgery for PDAC were retrospectively identified. Local recurrence required tissue histopathology or enlarging FDG-avid soft tissue. Nonrecurrence required soft-tissue reduction with stable or decreased CA 19-9. Two blinded radiologists independently drew regions of interest within the surgical bed soft tissue to determine iodine density (I), I normalized to aortic enhancement (I%), fat fraction, and extracellular volume (ECV), which were compared using the Mann-Whitney U test. A P<0.05 indicated statistical significance. The intraclass correlation coefficient was used to assess inter-reader reliability. ROC analysis was performed using mean measurements.</p><p><strong>Results: </strong>On pancreatic parenchymal phase imaging, median [IQR] postcontrast attenuation for patients with nonrecurrence (n=10) and recurrence (n=11) was 32.3 (16.4 to 42.9 HU) and 57.0 (50.2 to 65.5 HU)(P=0.001); enhancement was 23.7 (10.2 to 26.0 HU) and 40.0 (34.4 to 44.5 HU) (P=0.001); I was 0.6 (0.5 to 0.90 mg/mL) and 1.8 (1.5 to 2.0 mg/mL) (P<0.001); I% was 8.3 (6.3% to 11.1%) and 34.3 (29.8% to 40.9%) (P<0.001); and ECV was 5.8 (4.4 to 6.9 mL) and 23.0 (18.0 to 25.8 mL) (P<0.001), respectively. To differentiate nonrecurrent from recurrent soft tissue, a postcontrast 45.7 HU threshold had 100% sensitivity and 80% specificity [AUC=0.92 (0.80-1.00)]; enhancement of 31.9 HU had 81.8% sensitivity and 100% specificity [AUC=0.98 (0.93-1.00)]; 14.0 mL ECV had 100% sensitivity and 100% specificity [AUC=1.00 (1.00-1.00)]; 1.27 mg/mL I had 90.9% sensitivity and 100% specificity [AUC=0.99 (0.98-1.00)]; and 20.3% I% had 100% sensitivity and 100% specificity (AUC=1.00). Inter-reader agreement was near-perfect (ICCs 0.86 to 0.96).</p><p><strong>Conclusions: </strong>PCCT spectral parameters demonstrated excellent diagnostic performance in differentiating locally recurrent PDAC from postsurgical fibrosis on pancreatic parenchymal phase imaging.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149167268","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":"Artificial Intelligence Iterative Reconstruction in Multiphase Abdominopelvic CT: Added Value for Anatomic Evaluation of Uterine Artery.","authors":"Qianqian Qu, Haiyang Geng, Ting Meng, Qingshi Zeng, Kai Deng","doi":"10.1097/RCT.0000000000001933","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001933","url":null,"abstract":"<p><strong>Objective: </strong>To assess the anatomic evaluation performance of the uterine artery (UA) on routine multiphase abdominopelvic CT images, and to investigate whether artificial intelligence iterative reconstruction (AIIR) can improve this performance to a level comparable to that on CTA images.</p><p><strong>Methods: </strong>This retrospective study included 50 patients who underwent multiphase abdominopelvic CT. Aarterial phase (AP) images were reconstructed with AIIR (group B) in addition to the routine hybrid iterative reconstruction (HIR) (group A). Another 50 patients who underwent routine abdominal aorta CTA were retrospectively identified, and their images were reconstructed with HIR (group C). The anatomic evaluation performance of UA in terms of the interpretability of origins, branching pattern, and lumen diameter was compared across the 3 image sets. The objective image quality was also compared.</p><p><strong>Results: </strong>A total of 100 patients (age 18 to 65 y) were investigated, and 300 UAs were evaluated (150 images × 2 UAs). Both group B and group C outperformed group A in terms of the proportion of UAs with identifiable origins (90% and 88% vs. 68%), classifiable branching pattern (89% and 87% vs. 71%), and totally measurable diameter (63% and 67% vs. 33%) (all P<0.017). No significant differences were found between groups B and C for any of these proportions (all P>0.017). The measured diameters exhibited excellent intraobserver agreement with ICC values of 0.90, 0.93, and 0.98 for groups A, B, and C, respectively. The UA attenuation was highest in group C, followed by group B and group A (all P<0.017). Group B exhibited the lowest noise in all scenarios (all P<0.017). No significant difference was found in the CNR of UA between group B and group C (all P>0.017). Sensitivity analysis excluding hypertensive patients confirmed the stability of the results.</p><p><strong>Conclusions: </strong>Anatomic evaluation performance of UA on routine multiphase abdominopelvic CT images is suboptimal. However, when AIIR is applied, both the interpretability of anatomic features and the image quality of UA are comparable to those obtained with dedicated CTA.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149136932","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":"Comparison and Combination of Radiomics, Deep Learning, and Subjective Assessment for Differentiating Immature and Mature Ovarian Teratomas on Abdominal CT.","authors":"Jongwoo Park, June Young Seo, Sang Youn Kim, Jeong Yeon Cho, Taek Min Kim","doi":"10.1097/RCT.0000000000001927","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001927","url":null,"abstract":"<p><strong>Objective: </strong>Preoperatively, ovarian teratomas are often misclassified into immature and mature types, potentially resulting in adverse clinical outcomes. This study compared the diagnostic accuracy of radiomics-based machine learning (ML), deep learning (DL), and subjective radiologic assessment for differentiating immature from mature ovarian teratomas on abdominal computed tomography (CT) and evaluated whether combining these approaches improves discrimination.</p><p><strong>Methods: </strong>We retrospectively reviewed imaging data of 31 cases with pathologically confirmed immature teratomas and 61 age- and size-matched cases of mature teratomas (mean age=18.1±9.2 y vs. 20.9±10.0 y). Two radiologists independently annotated predefined CT features to construct a multivariable logistic regression model. Radiomics features were extracted from precontrast CT with 3 masks: whole tumor, calcification, and fat. Radiomics models were developed using 4 ML pipelines (logistic regression, random forest, support vector machine, and neural network). DL models were constructed with a 3D-ResNet18 on full-volume and tumor-segmented CT, with and without transfer learning (TL). A combined model was constructed by averaging their calibrated predicted probabilities. The diagnostic performance was assessed by the mean area under the receiver-operating characteristic curve (AUC).</p><p><strong>Results: </strong>In the full cohort, the 4 individual approaches performed similarly, with overlapping CIs: wavelet-transformed precontrast radiomics 0.820 (95% CI: 0.798-0.841), precontrast radiomics 0.817, subjective assessment 0.814, and DL 0.810. Combining them outperformed every individual approach (0.865; ΔAUC: 0.045, 95% CI: 0.032-0.060; Holm-adjusted P<0.001). Among the 81 tumors containing calcification, where calcification-mask radiomics could also be evaluated, all approaches performed better, and the combined model again outperformed each of them (0.891; ΔAUC: 0.035), as did the combined model among the 90 tumors containing fat (0.872; ΔAUC: 0.047; both P<0.001).</p><p><strong>Conclusion: </strong>Radiomics shows moderate performance in CT-based discrimination between immature and mature ovarian teratomas, with subjective radiologic assessment and DL performing at a comparable level. Combining the 3 consistently outperformed anyone alone, indicating that quantitative image analysis complements rather than replaces expert visual interpretation and may help reduce preoperative misclassification.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110374","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-Body MRI of Inflammatory and Infectious Musculoskeletal Diseases: Emphasis on Chronic Nonbacterial Osteomyelitis and Systemic Inflammatory Disorders.","authors":"Dâmaris V C Gonçalves, Marília da C Fagundes, Marcelo D Maruichi, Alípio G Ormond Filho, Júlio B Guimarães","doi":"10.1097/RCT.0000000000001932","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001932","url":null,"abstract":"<p><p>Whole-body magnetic resonance imaging (WBMRI) has emerged as the primary imaging tool for multifocal inflammatory and infectious musculoskeletal diseases. By extending coverage from the vertex to the toes in a single, radiation-free examination, WBMRI enables the detection of clinically occult lesions, disease-specific pattern recognition across bone marrow, joints, entheses, and muscles, and objective monitoring of disease activity and treatment response. This review describes the WBMRI findings-with detailed imaging features and distribution patterns-in chronic nonbacterial osteitis, SAPHO syndrome, seronegative spondyloarthritis, rheumatoid arthritis, juvenile idiopathic arthritis, polymyalgia rheumatica, idiopathic inflammatory myopathies, and fever of unknown origin, with emphasis on validated quantitative scoring tools, disease-specific acquisition protocols, and structured reporting strategies for the practicing radiologist. WBMRI provides unique clinical value by mapping total lesion burden, supporting differential diagnosis, identifying biopsy targets, and tracking treatment response. Disease-specific protocols-tailored to the pathophysiological target of each condition-are essential for maximizing diagnostic yield. Quantitative scoring tools and advanced MRI sequences may improve the characterization of disease burden and longitudinal assessment.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110384","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-Body MRI in Neurocutaneous Syndromes: Imaging Phenotypes, Surveillance Strategies, and Pitfalls.","authors":"Zohaib Y Ahmad, Laura M Fayad, Shivani Ahlawat","doi":"10.1097/RCT.0000000000001931","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001931","url":null,"abstract":"<p><p>Neurocutaneous syndromes associated with peripheral nerve sheath tumors (PNSTs), particularly neurofibromatosis type 1 (NF1) and schwannomatosis (SWN), are characterized by variable tumor burden and multisystem involvement. Whole-body magnetic resonance imaging (WB-MRI) has emerged as an important imaging technique for screening, surveillance, lesion characterization, and treatment monitoring in both pediatric and adult populations. Updated molecular and imaging-based classification systems have further refined characterization of PNST phenotypes. In NF1, WB-MRI enables detection of internal tumor burden, longitudinal assessment of plexiform neurofibromas (PNs), and risk stratification for malignant peripheral nerve sheath tumor (MPNST) development. Diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping improves differentiation between benign and malignant peripheral nerve sheath tumors with emerging data on premalignant precursor lesions called atypical neurofibromatous neoplasms of uncertain biologic potential (ANNUBP). In SWN, evolving diagnostic criteria and genotype-phenotype correlations have increased the importance of imaging in young patients presenting with solitary schwannoma or meningioma. WB-MRI can establish internal tumor burden, define disease extent, and support surveillance strategies across genetically defined SWN subtypes. This review summarizes current applications of WB-MRI in NF1 and SWN, including imaging phenotypes, surveillance strategies, advanced imaging biomarkers, treatment response assessment, and common technical and interpretive pitfalls.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149069365","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":"Super-Resolution Deep Learning Reconstruction for 3-Dimensional T1-Weighted Gradient-Echo Imaging in Contrast-Enhanced Liver MRI: Comparison With Conventional and Standard Deep Learning Reconstructions.","authors":"Kentaro Nishiuchi, Keitaro Sofue, Kazuma Tsukamoto, Yuichiro Somiya, Tomonari Ishida, Ryutaro Yano, Akihiko Umeno, Ryohei Kozuki, Takeru Yamaguchi, Eisuke Ueshima, Yoshiko Ueno, Takahiro Tsuboyama, Atsuhiro Masuda, Izumi Imaoka, Takamichi Murakami","doi":"10.1097/RCT.0000000000001926","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001926","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the image quality of super-resolution deep learning reconstruction (SR-DLR) for 3-dimensional (3D) T1-weighted gradient-echo (GRE) imaging in contrast-enhanced MRI, compared with conventional reconstruction (Conv.) and standard deep learning reconstruction (DLR).</p><p><strong>Materials and methods: </strong>This retrospective study included 50 patients (mean age: 71.5 y) with 76 hepatic lesions who underwent contrast-enhanced dynamic liver MRI at 3T. Portal venous phase images were reconstructed using Conv., DLR, and SR-DLR. Quantitative analyses measured liver signal-to-noise ratio (SNR), contrast ratio (CR) between liver parenchyma and lesions, edge rise distance (ERD), and edge rise slope (ERS). Qualitative assessments of image noise, sharpness, contrast, motion artifacts, overall image quality, and lesion conspicuity were performed independently by 2 radiologists using a 5-point scale. Coronal multiplanar reformatted (MPR) images were also evaluated. Statistical comparisons were performed using the Friedman test with Bonferroni correction.</p><p><strong>Results: </strong>Liver SNR was comparable between SR-DLR and DLR. SR-DLR produced sharper edges (lower ERD, higher ERS) and higher lesion-to-liver CR than Conv. and DLR (P<0.001). The overall CR differences were primarily driven by cystic lesions, whereas improvements in malignant lesions were modest. Qualitatively, SR-DLR received the highest ratings for sharpness, overall image quality, and lesion conspicuity, particularly on MPR images (P<0.001). SR-DLR images exhibited slightly higher image noise and motion-related artifacts than DLR.</p><p><strong>Conclusion: </strong>SR-DLR improved spatial resolution, sharpness, and lesion conspicuity in contrast-enhanced MRI compared with Conv. and DLR, indicating potential to improve the diagnostic performance of dynamic liver MRI.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149030541","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 Utility of Ovarian-Adnexal Reporting and Data System Magnetic Resonance Imaging for Risk Stratifying Adnexal Masses: An Assessment of Diagnostic Efficacy and Interrater Reliability.","authors":"Zeynep Dönmez, Ahmet Akçay, Ümmühan Ebru Karabulut, Bahar Atasoy, Abdusselim Adil Peker, Hüseyin Toprak, Mehmet Ali Gültekin","doi":"10.1097/RCT.0000000000001929","DOIUrl":"https://doi.org/10.1097/RCT.0000000000001929","url":null,"abstract":"<p><strong>Objective: </strong>Accurate characterization of adnexal masses is essential for determining malignancy risk and guiding clinical management. While the O-RADS MRI system provides standardized risk stratification, the impact of MRI acquisition protocols on diagnostic performance and interrater reliability remains unclear. This study aimed to evaluate the diagnostic performance of O-RADS MRI, assess interrater reliability between readers with different experience levels, and investigate the contribution of dynamic contrast-enhanced MRI to reader concordance.</p><p><strong>Materials and methods: </strong>A total of 387 patients with 496 adnexal masses were retrospectively analyzed. Histopathologic diagnosis was obtained through surgery or biopsy, while lesions without histopathology were considered benign if they remained stable or regressed during at least 9 months of imaging follow-up. Two radiologists with different levels of experience independently evaluated all MRI examinations using the O-RADS MRI lexicon. Diagnostic performance was assessed using sensitivity, specificity, and receiver operating characteristic (ROC) analysis with area under the curve (AUC). Interobserver agreement was evaluated using the Cohen κ statistic.</p><p><strong>Results: </strong>Both readers demonstrated high diagnostic performance. Sensitivity, specificity, and accuracy were 96.8%, 94.1%, and 95.2% for reader 1, and 96.8%, 92.9%, and 94.4% for reader 2. AUC values were 0.976 (95% CI: 0.940-0.992) and 0.970 (95% CI: 0.933-0.989), respectively. Interobserver agreement was substantial for benign-malignant classification (κ = 0.757; 95% CI: 0.624-0.889) and excellent for O-RADS category assignment (κ = 0.941; 95% CI: 0.919-0.962). Diagnostic performance was comparable between dynamic and nondynamic protocols; however, dynamic MRI demonstrated higher interobserver agreement, particularly for lesion classification.</p><p><strong>Conclusion: </strong>O-RADS MRI provides high diagnostic performance and strong interobserver agreement in the evaluation of adnexal masses. Although dynamic contrast-enhanced MRI does not significantly improve diagnostic accuracy, it may enhance reader concordance, particularly in lesions with equivocal imaging features.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012210","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}