Radiology. Imaging cancer最新文献

{"title":"Comparison of Artificial Intelligence Detection and Short-Term Breast Cancer Risk Models within and beyond Their Intended Use in Mammography Screening.","authors":"Yao-Kuan Wang, Lesley Cockmartin, Tobias Wagner, Zan Klanecek, Nicholas Marshall, Valerie Celis, Chantal Van Ongeval, Andrej Studen, Robert Jeraj, Hilde Bosmans","doi":"10.1148/rycan.250609","DOIUrl":"10.1148/rycan.250609","url":null,"abstract":"<p><p>Purpose To compare artificial intelligence-based breast cancer detection and short-term breast cancer risk prediction models in their intended and nonintended settings over a single mammography screening round. Materials and Methods In this retrospective study, the Cohort of Screen-Age Women-Case Control dataset from Sweden (May 2008-December 2016; Hologic) was used, including patients with screen-detected and interval cancers, with interval cancers defined as a diagnosis more than 60 days after screening. Two examination-based settings were evaluated: detection (screening examinations) and short-term risk (screen-negative examinations). Mirai Risk, RSNA Detection (2023 challenge winner), Transpara Detection, and Transpara Risk models were assessed in both intended and nonintended settings. Discriminative performance was evaluated using the area under the receiver operating characteristic curve (AUC), and then clinically relevant sensitivity and specificity thresholds were compared. Results A total of 20 187 examinations (7430 women) were included, with 741 examinations leading to diagnosis within 2 years (524 screen-detected and 217 interval cancers) and 19 446 examinations without cancer. Transpara Detection and Transpara Risk achieved similar performance for detection (AUC for each, 0.92; 95% CI: 0.91, 0.93; <i>P</i> = .93) and outperformed the other models (all <i>P</i> < .001). Transpara Detection demonstrated the highest specificity (97.1%; 95% CI: 96.8, 97.3) at double-reading sensitivity (all <i>P</i> < .001). There was no evidence of a difference in specificity of Transpara Risk and RSNA Detection at this sensitivity (<i>P</i> = .29). For risk, Transpara Risk performed best (AUC, 0.81; 95% CI: 0.78, 0.84), with 49.8% sensitivity at 90% specificity (all <i>P</i> ≤ .002) for interval cancers. There was no evidence of a difference in AUC between Mirai Risk and Transpara Detection (<i>P</i> = .96). Conclusion Artificial intelligence-based mammographic detection and short-term breast cancer risk prediction models performed best in their intended settings. <b>Keywords:</b> Mammography, Breast, Computer Applications, Detection/Diagnosis, Screening, Technology Assessment, Model Validation <i>Supplemental material is available for this article.</i> © The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 5","pages":"e250609"},"PeriodicalIF":7.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620329/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149040510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HPV-associated Oropharyngeal Squamous Cell Carcinoma: An Imaging Framework for AJCC Version 9 TNM Staging.","authors":"Pranjal Rai, Adam L Holtzman, Alok A Bhatt","doi":"10.1148/rycan.260013","DOIUrl":"10.1148/rycan.260013","url":null,"abstract":"<p><p>Human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) is biologically and prognostically distinct from HPV-negative disease, and staging directly impacts treatment. The American Joint Committee on Cancer (AJCC) and Union for International Cancer Control version 9 TNM staging system incorporates unequivocal imaging-detected and/or clinically detected extranodal extension (iENE) into clinical nodal staging and definitive pathologic extranodal extension into pathologic nodal staging. Additionally, it provides more explicit anatomic definitions for advanced local disease (clinical T4) while maintaining T and M category definitions from the eighth edition. Radiologists play a central role in the multidisciplinary team by evaluating endophytic tumor extent, regional nodal disease and iENE, and distant metastasis using CT, MRI, and PET. This article reviews clinically relevant oropharyngeal anatomy and proposes a practical radiologic approach to assigning T, N, and M categories in HPV-associated OPSCC. It emphasizes cautious interpretation of iENE because of interreader variability and imperfect diagnostic performance, with further high-grade evidence needed to establish its consistently reproducible, incremental prognostic value as a clinical N category modifier. It also highlights multidisciplinary factors that guide selection of surgical resection versus nonsurgical therapy. Posttreatment evaluation is discussed in the context of blood-based biomarkers such as tumor tissue-modified viral HPV DNA. The goal of this article is to provide a practical, staging-focused imaging framework for evaluation of HPV-associated OPSCC. <b>Keywords:</b> CT, MR Imaging, Head/Neck, Neck, Pharynx, Surgery, Human Papillomavirus, Squamous Cell Carcinoma, Oropharynx, Transoral Robotic Surgery, Oropharyngeal Carcinoma, TTMV HPV DNA © RSNA, 2026.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 5","pages":"e260013"},"PeriodicalIF":7.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620332/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148760765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proof-of-Concept Study of Hyperpolarized [1-¹³C]Pyruvate MRI in Participants with Hepatocellular Carcinoma.","authors":"Uffe Kjærgaard, Nikolaj Bøgh, Malene Aastrup, Mattias Hedegaard Kristensen, Nichlas Vous Christensen, Kim Sivesgaard, Steffen Ringgaard, Lotte Bonde Bertelsen, Esben Søvsø Szocska Hansen, Henning Grønbæk, Gerda Elisabeth Villadsen, Christoffer Laustsen","doi":"10.1148/rycan.250784","DOIUrl":"10.1148/rycan.250784","url":null,"abstract":"<p><p>Purpose To assess the feasibility of hyperpolarized [1-¹³C]pyruvate MRI (HP-MRI) as an adjunct to standard CT/MRI-based Liver Imaging Reporting and Data System (LI-RADS) categorization for noninvasive metabolic characterization of hepatocellular carcinoma (HCC). Materials and Methods This prospective, exploratory, single-center study included participants with liver lesions and control participants who underwent HP-MRI between June 2023 and June 2025. Lesions identified on CT and/or MRI scans were categorized according to LI-RADS. HP-MRI metabolic readout included ratios from dynamic ¹³C imaging, such as the lactate-to-pyruvate (L/P) ratio, alanine-to-pyruvate (A/P) ratio, alanine-to-lactate (A/L) ratio, and corresponding tumor-to-background ratios (TBRs). Established HCCs were compared with indeterminate lesions that subsequently progressed to HCC using unpaired <i>t</i> tests and Hedges <i>g</i>. Results Fourteen participants were included (median age, 64 years; IQR, 53-70 years]; 14 [100%] male): 10 participants with lesions on CT/MRI scans and four control participants. A/P and A/L ratios were lower in indeterminate lesions that progressed (<i>n</i> = 4) than established HCCs (<i>n</i> = 5), both in absolute measures and indexed to TBRs (<i>P</i> < .05), whereas there was no evidence of differences in the L/P ratio. In contrast, L/P TBR was higher in indeterminate lesions that progressed than in established HCCs (<i>P</i> = .03). Alanine-indexed TBRs showed large effect sizes, with Hedges <i>g</i> ranging from 2.01 (95% CI: 0.33, 3.70) to 3.02 (95% CI: 0.97, 5.08). One LI-RADS category 3 (LR-3) lesion under surveillance showed no early progression, and progression could not be confirmed for an LR-4 lesion. Conclusion Adjunctive HP-MRI provided complementary lesion-level metabolic information beyond standard CT and/or MRI, and a reduced A/L ratio emerged as a candidate marker of malignant progression. <b>Keywords:</b> Liver, Oncology, Cirrhosis, Hepatocellular Carcinoma <i>Supplemental material is available for this article.</i> Clinical Trials Information System hosted by the European Medicines Agency (EU-CTIS 2024-512490-27-00) © RSNA, 2026.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 5","pages":"e250784"},"PeriodicalIF":7.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620327/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148841139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain Metabolic Activity Measured with ¹⁸F-FDG PET/CT Predicts Survival in Patients with Advanced Non-Small Cell Lung Cancer.","authors":"Sepideh Abdi","doi":"10.1148/rycan.269021","DOIUrl":"10.1148/rycan.269021","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 5","pages":"e269021"},"PeriodicalIF":7.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620319/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149040461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Superresolution US Imaging of Rabbit Lymph Node Microvasculature for Metastasis Diagnosis.","authors":"Hongsheng Ye, Xiaoxian Li, Chuan Peng, Qing Li, Liang Yang, Jichong He, Li Meng, Peng Li, Yixin Hu, Lingling Li, Jianhua Zhou","doi":"10.1148/rycan.250674","DOIUrl":"10.1148/rycan.250674","url":null,"abstract":"<p><p>Purpose To compare the diagnostic performance of superresolution US (SRUS) with that of US and contrast-enhanced US (CEUS) for detecting lymph node (LN) metastasis in rabbits. Materials and Methods US, CEUS, and SRUS were performed in 30 rabbits with 16 egg yolk-induced hyperplastic and 14 VX2 tumor-bearing metastatic LNs. Qualitative US, CEUS, and SRUS features and quantitative SRUS-based parameters of LN microvasculature were analyzed. Major qualitative features and quantitative parameters associated with metastatic LNs were identified, with histopathologic evaluation as reference. Spearman correlation between features and parameters was analyzed. Results Among qualitative features, chaotic microvasculature at SRUS achieved the highest area under the receiver operating characteristic curve of 0.92 (95% CI: 0.81, 1.00), outperforming cortical thickening at US (0.67 [95% CI: 0.51, 0.82]; <i>P</i> = .012), arterial phase enhancing pattern at CEUS (0.72 [95% CI: 0.57, 0.86]; <i>P</i> = .018), and SRUS vascular pattern (0.72 [95% CI: 0.55, 0.89]; <i>P</i> = .028). Among quantitative parameters, fractal dimension yielded the optimal area under the receiver operating characteristic curve of 0.92 (95% CI: 0.79, 1.00), outperforming vessel density (0.70 [95% CI: 0.48, 0.88]; <i>P</i> = .046), flow-weighted vessel density (0.70 [95% CI: 0.49, 0.88]; <i>P</i> = .046), and direction entropy (0.71 [95% CI: 0.51, 0.89]; <i>P</i> = .046). Chaotic microvasculature and fractal dimension were strongly correlated (ρ = 0.80; <i>P</i> < .001), and both correlated well with microvascular density (ρ = 0.82 and 0.65, respectively; both <i>P</i> < .001). Conclusion Chaotic microvasculature and fractal dimension assessed at SRUS showed improved diagnostic performance for detecting metastatic LNs in rabbits compared with US and CEUS and enabled noninvasive evaluation of microvascular tortuosity. <b>Keywords:</b> Ultrasound-Contrast, Ultrasound <i>Supplemental material is available for this article.</i> © The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 5","pages":"e250674"},"PeriodicalIF":7.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620326/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149040453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synthetic Phase-Sensitive Inversion Recovery and Extramural Vascular Invasion Scoring Systems for Vascular Invasion Detection and Metastasis Risk in Rectal Cancer.","authors":"Yuxi Ge, Xiaofei Wu, Heng Zhang, Zi Wang, Kang Wang, Wenjie Chai, Wenbo Xu, Jiankun Dai, Yutian Zhao, Shudong Hu","doi":"10.1148/rycan.250564","DOIUrl":"10.1148/rycan.250564","url":null,"abstract":"<p><p>Purpose To develop and validate a modified extramural vascular invasion (EMVI) scoring system with synthetic phase-sensitive inversion recovery (SyPSIR) images to improve vascular invasion detection and metastasis prediction in patients with rectal cancer. Materials and Methods Participants with rectal cancer were eligible for this single-center prospective study between October 2020 and June 2024, with follow-up intervals of 3-6 months (median follow-up, 23 months; range, 3-50 months). All participants underwent EMVI evaluation using conventional T2-weighted imaging-based and modified synthetic phase-sensitive inversion recovery-incorporated scoring systems, with diagnostic performance for pathologic EMVI detection evaluated against histopathology. Receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of the pathologic EMVI results. Kaplan-Meier survival analysis and multivariable Cox regression analysis were used to compare the prognostic performance of the scoring systems, and a nomogram for metastasis risk stratification was developed. Results This study included 356 participants (mean age, 65 years ± 10 [SD]; 238 males) with rectal cancer (304 with pathologically confirmed EMVI). The modified EMVI scoring system demonstrated better diagnostic performance for pathologic EMVI detection than the conventional T2-weighted imaging system (sensitivity: 59%-80% vs 33%-49%; area under the receiver operating characteristic curve: 0.72-0.80 vs 0.59-0.68; <i>P</i> < .05). Multivariable Cox regression analysis confirmed that a modified MRI-based EMVI (mrEMVI) was the most independent predictor of metastasis-free survival (MFS) (hazard ratio, 10.76; <i>P</i> < .001), with Kaplan-Meier analysis demonstrating its better prognostic stratification ability in both the training and validation cohorts. A prognostic nomogram incorporating the modified mrEMVI, mucinous component, mrN stage, mrT stage, and tumor deposit achieved excellent discrimination for 3-year MFS (area under the receiver operating characteristic curve, 0.86-0.98), with reasonable calibration, and demonstrated clinical utility across relevant decision thresholds. Conclusion The modified EMVI scoring system outperformed the conventional T2-weighted imaging system in both pathologic EMVI detection and metastasis prediction. The integrated nomogram incorporating the modified mrEMVI provides a robust tool for accurate 3-year MFS prediction. <b>Keywords:</b> Abdomen/GI, MR-Imaging, Diagnosis, Prognosis & Prediction <i>Supplemental material is available for this article.</i> © The Author(s) 2026. Published by the Radiological Society of North America under CC BY 4.0 license.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 5","pages":"e250564"},"PeriodicalIF":7.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620328/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148991245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CD105-targeted Peptide PET Probe for Imaging Tumor Blood Vessels.","authors":"Muthuvel Panneerselvam, Lacey R McNally","doi":"10.1148/rycan.269020","DOIUrl":"10.1148/rycan.269020","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 5","pages":"e269020"},"PeriodicalIF":7.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620323/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148892426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Circulating Proteins for Pretreatment Risk Stratification in Image-guided Liver Therapy.","authors":"Shakthi Kumaran Ramasamy, Ripal T Gandhi","doi":"10.1148/rycan.260429","DOIUrl":"10.1148/rycan.260429","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 5","pages":"e260429"},"PeriodicalIF":7.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620474/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148685549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multimodal Imaging of Response to Salvage Prostate Ablation.","authors":"Rocio Roldan-Testillano, Claudia Covarrubias, Tatiana Cabrera Aleksandrova, Tamim Niazi, Rafael Sanchez-Salas, Maurice Anidjar","doi":"10.1148/rycan.260149","DOIUrl":"10.1148/rycan.260149","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 5","pages":"e260149"},"PeriodicalIF":7.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148892406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal Mammographic Breast Density Changes and Associated Factors in Older Korean Women.","authors":"Somin Jeon, Junghyun Yoon, Thi Huyen Trang Nguyen, Yoosoo Chang, Seungho Ryu, Yoonyoung Jang, Boyoung Park","doi":"10.1148/rycan.250332","DOIUrl":"10.1148/rycan.250332","url":null,"abstract":"<p><p>Purpose To evaluate breast density changing trajectories in women age 60 years or older and identify their associated factors. Materials and Methods Data were obtained from the Korean National Health Insurance Service Database, which includes six biennial mammography screenings from January 2009 to December 2020. Women age 60 years or older who participated in screenings in 2009-2010 and 2019-2020 and at least two screenings in between were included. Breast density was classified using the Breast Imaging Reporting and Data System (BI-RADS). Group-based trajectory modeling was used to identify patterns of breast density changes across the six screening cycles. Logistic regression was used to examine breast cancer risk factors associated with the increasing or decreasing breast density trajectories. Results Among 674 993 women (mean age, 65.0 years ± 4.3 [SD]; 51% BI-RADS 1 at baseline), five distinct breast density change trajectories were identified: persistent fatty (20.5%), persistent BI-RADS 2 (36.1%), and persistent BI-RADS 3 (15.4%). Group 2 (17.2%) showed increased density, and group 3 (10.8%) demonstrated decreased density. Several breast cancer risk factors were associated with the breast density trajectories. For example, older women (adjusted odds ratio, 0.98; 95% CI: 0.97, 0.98; <i>P</i> < .001) and women with a higher baseline body mass index and a greater increase in body mass index over time were less likely to have increased breast density. Conclusion Five distinct breast density change trajectories were identified among Korean women who were age 60 years or older. Women with initially low breast density and more breast cancer risk factors were more likely to show increasing trajectory, whereas those with initially high density and fewer risk factors tended to show decreasing density. <b>Keywords:</b> Breast Density, Breast Density Change, Older Women, Reproductive Factors, Breast Cancer © RSNA, 2026.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"8 4","pages":"e250332"},"PeriodicalIF":7.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13435068/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148227749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}