Radiology. Imaging cancer最新文献

{"title":"Association of Clinical and US Features with Malignancy of Breast Tumors: Investigating Shear-Wave Elastography and Radiomics.","authors":"Brandon K K Fields, Bonnie N Joe","doi":"10.1148/rycan.249028","DOIUrl":"10.1148/rycan.249028","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e249028"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865323","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":"Measurable Disease in Glioblastoma using PET-based Response Assessment in Neuro-Oncology (PET RANO 1.0).","authors":"Netanja I Harlianto","doi":"10.1148/rycan.259001","DOIUrl":"10.1148/rycan.259001","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e259001"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791658/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143034064","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":"Evaluation of Local Tumor Outcomes Following Microwave Ablation of Colorectal Liver Metastases Using CT Imaging: A Comparison of Visual versus Quantitative Methods.","authors":"Joshua D Shur, Nuria Porta, Leila Kafaei, Laura Pendower, James McCall, Nasir Khan, Wim Oyen, Dow-Mu Koh, Edward Johnston","doi":"10.1148/rycan.230147","DOIUrl":"10.1148/rycan.230147","url":null,"abstract":"<p><p>Purpose To compare visual versus quantitative ablation confirmation for identifying local tumor progression and residual tumor following microwave ablation (MWA) of colorectal liver metastases (CRLM). Materials and Methods This retrospective study included patients undergoing MWA of CRLM from October 2014 to February 2018. Two independent readers visually assessed pre- and postprocedure images and semiquantitatively scored for incomplete ablation, using a six-point Likert scale, and extracted quantitative imaging metrics of minimal ablative margin (MAM) and percentage of tumor outside of the ablation zone, using both rigid and deformable registration. Diagnostic accuracy and intra- and interobserver agreement were assessed. Results The study included 60 patients (median age, 71 years [IQR, 60-74.5 years]; 38 male) with 97 tumors with a median diameter of 1.3 cm (IQR, 1.0-1.8 cm). Median follow-up time was 749 days (IQR, 330-1519 days). Median time to complete rigid and deformable workflows was 3.0 minutes (IQR, 3.0-3.2 minutes) and 14.0 minutes (IQR,13.9-14.4 minutes), respectively. MAM with deformable registration had the highest intra- and interobserver agreement, with Gwet AC1 of 0.92 and 0.67, respectively, significantly higher than interobserver agreement of visual assessment (Gwet AC1, 0.18; <i>P</i> < .0001). Overall, quantitative methods using MAM had generally higher sensitivity, of up to 95.6%, than visual methods (67.3%, <i>P</i> < .001), at a cost of lower specificity (40% vs 71.1%, <i>P</i> < .001), using deformable image registration. Conclusion Quantitative ablation margin metrics provide more reliable assessment of outcomes than visual comparison using pre- and postprocedure diagnostic images following MWA of CRLM. <b>Keywords:</b> Interventional-Body, Liver, Neoplasms, Ablation Techniques <i>Supplemental material is available for this article</i>. Published under a CC BY 4.0 license.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e230147"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791670/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143034063","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":"Quantitative 3-T Multiparametric MRI Parameters as Predictors of Aggressive Prostate Cancer.","authors":"Daniel Hyeong Seok Kim, Ida Sonni, Tristan Grogan, Anthony Sisk, Vishnu Murthy, William Hsu, KyungHyun Sung, David S Lu, Robert E Reiter, Steven S Raman","doi":"10.1148/rycan.240011","DOIUrl":"10.1148/rycan.240011","url":null,"abstract":"<p><p>Purpose To determine which quantitative 3-T multiparametric MRI (mpMRI) parameters correlate with and help predict the presence of aggressive large cribriform pattern (LCP) and intraductal carcinoma (IDC) prostate cancer (PCa) at whole-mount histopathology (WMHP). Materials and Methods This retrospective study included 130 patients (mean age ± SD, 62.6 years ± 7.2; 100% male) with 141 PCa lesions who underwent preoperative prostate 3-T mpMRI, radical prostatectomy, and WMHP between January 2019 and December 2022. Lesions at WMHP were matched to 3-T mpMRI lesions with American College of Radiology Prostate Imaging Reporting and Data System version 2.1 scores of at least 3 or higher, and the following parameters were derived: apparent diffusion coefficient (ADC), volume transfer constant, rate constant, and initial area under the curve (iAUC). Each lesion was categorized into three subcohorts with increasing aggressiveness: LCP negative and IDC negative (subcohort 1), LCP positive and IDC negative (subcohort 2), and LCP positive and IDC negative (subcohort 3). Analysis of variance was performed to assess differences, Jonckheere test was performed to establish trends, and a classification and regression tree (CART) was used to establish a prediction model. Results Of the 141 total lesions, there were 41 (29.1%), 49 (34.8%), and 51 (36.2%) lesions in subcohorts 1, 2, and 3, with mean ADCs of 892 × 10^-6 mm²/sec ± 20, 826 × 10^-6 mm²/sec ± 209, and 763 × 10^-6 mm²/sec ± 163 (<i>P</i> = .007) and mean iAUCs of 5.4 mmol/L/sec ± 2.5, 6.7 mmol/L/sec ± 3.0, and 6.9 mmol/L/sec ± 3.5 (<i>P</i> = .04), respectively. ADC was negatively correlated (<i>P</i> = .004), and rate constant and iAUC were positively correlated (<i>P</i> = .048 and <i>P</i> = .04, respectively) with increasing histologic PCa aggressiveness. The CART model correctly allocated 39.0%, 24.5%, and 84.3% of PCa lesions to subcohorts 1, 2, and 3, respectively. Conclusion Quantitative 3-T mpMRI parameters significantly correlated with and helped predict aggressive LCP and IDC PCa at WMHP. <b>Keywords:</b> Prostate, MRI, Pathology © RSNA, 2025.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e240011"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791667/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142922680","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":"Molecular Imaging of Paragangliomas and Pheochromocytomas.","authors":"Brian J Burkett, Derek R Johnson","doi":"10.1148/rycan.240440","DOIUrl":"10.1148/rycan.240440","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e240440"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791660/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143010602","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":"Improving Ovarian Cancer Detection: Can CEUS Refine the O-RADS System?","authors":"Deborah A Baumgarten","doi":"10.1148/rycan.240397","DOIUrl":"10.1148/rycan.240397","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e240397"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865325","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":"Potential of AI System to Enhance Early Breast Cancer Detection in Screening Mammography.","authors":"Allison Dortilus, Maggie Chung","doi":"10.1148/rycan.249027","DOIUrl":"10.1148/rycan.249027","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e249027"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791656/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865328","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":"Recommendations from Imaging, Oncology, and Radiology Organizations to Guide Management in Prostate Cancer: Summary of Current Recommendations.","authors":"Andy Mew, Eva Chau, Kaustav Bera, Nikhil Ramaiya, Sree Harsha Tirumani","doi":"10.1148/rycan.240091","DOIUrl":"10.1148/rycan.240091","url":null,"abstract":"<p><p>Prostate cancer is the second most common malignancy among male individuals in the United States and requires careful imaging approaches because of its varied presentations. This review examines prostate cancer imaging guidelines from leading organizations, including the American College of Radiology, American Urological Association, European Association of Urology, American Society of Clinical Oncology, and National Comprehensive Cancer Network, and serves as a reference highlighting commonalities and divergences in current imaging recommendations across prostate cancer states. We outline these organizations and their methods, focusing on their approaches to panel expertise, guideline development, evidence grading, and revision schedules. We then compare and contrast the role of various imaging modalities across states of prostate cancer management in the following categories: clinically suspected prostate cancer, clinically established prostate cancer: active surveillance or staging, monitoring metastatic disease, and posttreatment follow-up: recurrent or residual disease. Overall, there is consensus on the importance of multiparametric MRI in diagnosis and staging prior to active surveillance and the emerging role of prostate-specific membrane antigen (PSMA) PET/CT in metastatic and recurrent disease. However, there is disparity in imaging recommendations for detecting metastases in unfavorable intermediate-risk prostate cancer and views on current applications of PSMA PET/CT. Ultimately, variations in radiologic expertise exist among guideline panels, and there continue to be inconsistencies in imaging recommendations in prostate cancer. <b>Keywords:</b> Prostate, Genital/Reproductive, Oncology <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e240091"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791666/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142953971","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":"Radiologically Negative Colorectal Diaphragmatic Metastasis Mimicking Liver Lesion.","authors":"Xiaoying Fu, Zechuan Jin, Hai-Ning Chen","doi":"10.1148/rycan.240225","DOIUrl":"10.1148/rycan.240225","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e240225"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791677/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142786879","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":"Assessing HCC Response to Locoregional Therapies: Diagnostic Performance of LI-RADS Nonradiation Treatment Response Algorithm Version 2024 and the Role of Ancillary Features.","authors":"Radhika Rajeev, Hero K Hussain","doi":"10.1148/rycan.259002","DOIUrl":"10.1148/rycan.259002","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 1","pages":"e259002"},"PeriodicalIF":5.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791663/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143034062","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}