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Lu B, He W, Liu C, Wang P, Yang P, Zhao Z, Qi J, Huang B. Differentiating Benign From Malignant Ovarian Masses With Solid Components: Diagnostic Performance of CEUS Combined With IOTA Simple Rules and O-RADS. ULTRASOUND IN MEDICINE & BIOLOGY 2024:S0301-5629(24)00229-1. [PMID: 38876911 DOI: 10.1016/j.ultrasmedbio.2024.05.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 05/19/2024] [Accepted: 05/22/2024] [Indexed: 06/16/2024]
Abstract
OBJECTIVE This study aimed to apply the International Ovarian Tumor Analysis (IOTA) Simple Rules (SR), the Ovarian-Adnexal Reporting and Data System (O-RADS) and contrast-enhanced ultrasound (CEUS) in an identical cohort of Chinese patients and to analyze their performance in discrimination of ovarian masses with solid components. METHODS This was a two-center retrospective study that included a total of 94 ovarian lesions in 86 women enrolled from January 2018 to February 2023. The lesions were classified by using the IOTA terminology and CEUS was performed for the lesions exhibiting solid components on ultrasonography, IOTA SR and O-RADS were applied, and CEUS images were analyzed retrospectively. We assessed the time to wash-in, time to peak intensity (PI), PI compared to myometrium, and time to wash-out, and observed statistically significant differences between benign and malignant lesions in the first three parameters. CEUS characteristics were employed to determine CEUS scores for benign (score 0) and malignant (score 3) lesions. Subsequently, the lesions were reassessed based on the IOTA SR and O-RADS classifications and CEUS scores. The sensitivity, specificity, and area under the receiver-operating-characteristics curve (AUC) of the different models were also determined. RESULTS Among the 94 ovarian lesions, 46 (48.9%) were benign and 48 (51.1%) were malignant. It was found that in the 60 lesions to which the SR could be applied, the sensitivity, specificity, and AUC was 0.900, 0.667, and 0.783, respectively. The sensitivity, specificity, and AUC of O-RADS was observed to be 1.000, 0.283 and 0.641, respectively. When SR and O-RADS were combined with CEUS, their sensitivity, specificity, and AUC values were increased to 0.917, 0.891, 0.904, and 0.958, 0.783, 0.871, respectively. CONCLUSION IOTA SR and O-RADS exhibited relatively low specificity in differentiating malignant from benign ovarian lesions with the solid components, and their diagnostic performance can be significantly improved when combined with CEUS.
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Affiliation(s)
- Beilei Lu
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China; Institute of Medical Ultrasound and Engineering, Fudan University, Shanghai, China
| | - Wanyuan He
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China; Institute of Medical Ultrasound and Engineering, Fudan University, Shanghai, China
| | - Chang Liu
- Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Educational Institute, Tongji University School of Medicine, Shanghai, China
| | - Pan Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ping Yang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhengyong Zhao
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; The Third People's Hospital of Honghe Hani and Yi Autonomous Prefecture, Yunnan, China
| | - Jiuling Qi
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China; Institute of Medical Ultrasound and Engineering, Fudan University, Shanghai, China.
| | - Beijian Huang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China; Institute of Medical Ultrasound and Engineering, Fudan University, Shanghai, China
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Hu F, Zhang G, Xu Z, Zuo Z, Huang N, Ge M, Liu X, Dong B. The diagnostic agreement of sarcopenic obesity with different definitions in Chinese community-dwelling middle-aged and older adults. Front Public Health 2024; 12:1356878. [PMID: 38903580 PMCID: PMC11188776 DOI: 10.3389/fpubh.2024.1356878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 05/17/2024] [Indexed: 06/22/2024] Open
Abstract
Background In 2022, the European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) launched a consensus on the diagnostic methods for sarcopenic obesity (SO). The study aimed to identify the prevalence and diagnostic agreement of SO using different diagnostic methods in a cohort of subjects from West China aged at least 50 years old. Methods A large multi-ethnic sample of 4,155 participants from the West China Health and Aging Trend (WCHAT) study was analyzed. SO was defined according to the newly published consensus of the ESPEN/EASO. Furthermore, SO was diagnosed as a combination of sarcopenia and obesity. The criteria established by the Asian Working Group for Sarcopenia 2019 (AWGS2019) were used to define sarcopenia. Obesity was defined by four widely used indicators: percent of body fat (PBF), visceral fat area (VFA), waist circumference (WC), and body mass index (BMI). Cohen's kappa was used to analyze the diagnostic agreement of the above five diagnostic methods. Results A total of 4,155 participants were part of the study, including 1,499 men (63.76 ± 8.23 years) and 2,656 women (61.61 ± 8.20 years). The prevalence of SO was 0.63-7.22% with different diagnostic methods. The diagnosis agreement of five diagnostic methods was poor-to-good (κ: 0.06-0.67). The consensus by the ESPEN/EASO had the poorest agreement with other methods (κ: 0.06-0.32). AWGS+VFA had the best agreement with AWGS+WC (κ = 0.67), and consensus by the ESPEN/EASO had the best agreement with AWGS+ PBF (κ = 0.32). Conclusion The prevalence and diagnostic agreement of SO varies considerably between different diagnostic methods. AWGS+WC has the highest diagnostic rate in the diagnosis of SO, whereas AWGS+BMI has the lowest. AWGS+VFA has a relatively good diagnostic agreement with other diagnostic methods, while the consensus of the ESPEN/EASO has a poor diagnostic agreement. AWGS+PBF may be suitable for the alternative diagnosis of the 2022 ESPEN/EASO.
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Affiliation(s)
- Fengjuan Hu
- National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Center of Gerontology and Geriatrics, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Gongchang Zhang
- National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Center of Gerontology and Geriatrics, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhigang Xu
- National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Zhiliang Zuo
- National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Center of Gerontology and Geriatrics, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ning Huang
- National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Center of Gerontology and Geriatrics, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Meiling Ge
- National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Center of Gerontology and Geriatrics, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiaolei Liu
- National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Center of Gerontology and Geriatrics, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Birong Dong
- National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Center of Gerontology and Geriatrics, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Patel-Lippmann KK, Wasnik AP, Akin EA, Andreotti RF, Ascher SM, Brook OR, Eskander RN, Feldman MK, Jones LP, Martino MA, Patel MD, Patlas MN, Revzin MA, VanBuren W, Yashar CM, Kang SK. ACR Appropriateness Criteria® Clinically Suspected Adnexal Mass, No Acute Symptoms: 2023 Update. J Am Coll Radiol 2024; 21:S79-S99. [PMID: 38823957 DOI: 10.1016/j.jacr.2024.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 02/28/2024] [Indexed: 06/03/2024]
Abstract
Asymptomatic adnexal masses are commonly encountered in daily radiology practice. Although the vast majority of these masses are benign, a small subset have a risk of malignancy, which require gynecologic oncology referral for best treatment outcomes. Ultrasound, using a combination of both transabdominal, transvaginal, and duplex Doppler technique can accurately characterize the majority of these lesions. MRI with and without contrast is a useful complementary modality that can help characterize indeterminate lesions and assess the risk of malignancy is those that are suspicious. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
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Affiliation(s)
| | | | - Esma A Akin
- The George Washington University Medical Center, Washington, District of Columbia; Commission on Nuclear Medicine and Molecular Imaging
| | | | - Susan M Ascher
- MedStar Georgetown University Hospital, Washington, District of Columbia
| | - Olga R Brook
- Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Ramez N Eskander
- University of California, San Diego, San Diego, California; American College of Obstetricians and Gynecologists
| | | | - Lisa P Jones
- Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Martin A Martino
- Ascension St. Vincent's, Jacksonville, Florida; University of South Florida, Tampa, Florida, Gynecologic oncologist
| | | | - Michael N Patlas
- Department of Medical Imaging, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Margarita A Revzin
- Yale University School of Medicine, New Haven, Connecticut; Committee on Emergency Radiology-GSER
| | | | - Catheryn M Yashar
- University of California, San Diego, San Diego, California; Commission on Radiation Oncology
| | - Stella K Kang
- Specialty Chair, New York University Medical Center, New York, New York
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Liu L, Cai W, Tian H, Wu B, Zhang J, Wang T, Hao Y, Yue G. Ultrasound image-based nomogram combining clinical, radiomics, and deep transfer learning features for automatic classification of ovarian masses according to O-RADS. Front Oncol 2024; 14:1377489. [PMID: 38812784 PMCID: PMC11133542 DOI: 10.3389/fonc.2024.1377489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 04/16/2024] [Indexed: 05/31/2024] Open
Abstract
Background Accurate and rapid discrimination between benign and malignant ovarian masses is crucial for optimal patient management. This study aimed to establish an ultrasound image-based nomogram combining clinical, radiomics, and deep transfer learning features to automatically classify the ovarian masses into low risk and intermediate-high risk of malignancy lesions according to the Ovarian- Adnexal Reporting and Data System (O-RADS). Methods The ultrasound images of 1,080 patients with 1,080 ovarian masses were included. The training cohort consisting of 683 patients was collected at the South China Hospital of Shenzhen University, and the test cohort consisting of 397 patients was collected at the Shenzhen University General Hospital. The workflow included image segmentation, feature extraction, feature selection, and model construction. Results The pre-trained Resnet-101 model achieved the best performance. Among the different mono-modal features and fusion feature models, nomogram achieved the highest level of diagnostic performance (AUC: 0.930, accuracy: 84.9%, sensitivity: 93.5%, specificity: 81.7%, PPV: 65.4%, NPV: 97.1%, precision: 65.4%). The diagnostic indices of the nomogram were higher than those of junior radiologists, and the diagnostic indices of junior radiologists significantly improved with the assistance of the model. The calibration curves showed good agreement between the prediction of nomogram and actual classification of ovarian masses. The decision curve analysis showed that the nomogram was clinically useful. Conclusion This model exhibited a satisfactory diagnostic performance compared to junior radiologists. It has the potential to improve the level of expertise of junior radiologists and provide a fast and effective method for ovarian cancer screening.
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Affiliation(s)
- Lu Liu
- Department of Ultrasound Medicine, South China Hospital, Medical School, Shenzhen University, Shenzhen, China
| | - Wenjun Cai
- Department of Ultrasound, Shenzhen University General Hospital, Medical School, Shenzhen University, Shenzhen, China
| | - Hongyan Tian
- Department of Ultrasound Medicine, South China Hospital, Medical School, Shenzhen University, Shenzhen, China
| | - Beibei Wu
- Department of Ultrasound Medicine, South China Hospital, Medical School, Shenzhen University, Shenzhen, China
| | - Jing Zhang
- Department of Ultrasound Medicine, South China Hospital, Medical School, Shenzhen University, Shenzhen, China
| | - Ting Wang
- Department of Ultrasound Medicine, South China Hospital, Medical School, Shenzhen University, Shenzhen, China
| | - Yi Hao
- Department of Ultrasound Medicine, South China Hospital, Medical School, Shenzhen University, Shenzhen, China
| | - Guanghui Yue
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
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Han J, Wen J, Hu W. Comparison of O-RADS with the ADNEX model and IOTA SR for risk stratification of adnexal lesions: a systematic review and meta-analysis. Front Oncol 2024; 14:1354837. [PMID: 38756655 PMCID: PMC11096596 DOI: 10.3389/fonc.2024.1354837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 04/15/2024] [Indexed: 05/18/2024] Open
Abstract
Purpose This study aims to systematically compare the diagnostic performance of the Ovarian-Adnexal Reporting and Data System with the International Ovarian Tumor Analysis Simple Rules and the Assessment of Different NEoplasias in the adneXa model for risk stratification of ovarian cancer and adnexal masses. Methods A literature search of online databases for relevant studies up to July 2023 was conducted by two independent reviewers. The summary estimates were pooled with the hierarchical summary receiver-operating characteristic model. The quality of the included studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 and the Quality Assessment of Diagnostic Accuracy Studies-Comparative Tool. Metaregression and subgroup analyses were performed to explore the impact of varying clinical settings. Results A total of 13 studies met the inclusion criteria. The pooled sensitivity and specificity for eight head-to-head studies between the Ovarian-Adnexal Reporting and Data System and the Assessment of Different NEoplasias in the adneXa model were 0.96 (95% CI 0.92-0.98) and 0.82 (95% CI 0.71-0.90) vs. 0.94 (95% CI 0.91-0.95) and 0.83 (95% CI 0.77-0.88), respectively, and for seven head-to-head studies between the Ovarian-Adnexal Reporting and Data System and the International Ovarian Tumor Analysis Simple Rules, the pooled sensitivity and specificity were 0.95 (95% CI 0.93-0.97) and 0.75 (95% CI 0.62-0.85) vs. 0.91 (95% CI 0.82-0.96) and 0.86 (95% CI 0.76-0.93), respectively. No significant differences were found between the Ovarian-Adnexal Reporting and Data System and the Assessment of Different NEoplasias in the adneXa model as well as the International Ovarian Tumor Analysis Simple Rules in terms of sensitivity (P = 0.57 and P = 0.21) and specificity (P = 0.87 and P = 0.12). Substantial heterogeneity was observed among the studies for all three guidelines. Conclusion All three guidelines demonstrated high diagnostic performance, and no significant differences in terms of sensitivity or specificity were observed between the three guidelines.
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Affiliation(s)
- Jing Han
- Department of Radiology, Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, China
| | - Jing Wen
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Wei Hu
- Department of Radiology, Yixing Traditional Chinese Medicine Hospital, Yixing, China
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Wu M, Zhang M, Qu E, Sun X, Zhang R, Mu L, Xiao L, Wen H, Wang R, Liu T, Meng X, Wu S, Chen Y, Su M, Wang Y, Gu J, Zhang X. A modified CEUS risk stratification model for adnexal masses with solid components: prospective multicenter study and risk adjustment. Eur Radiol 2024:10.1007/s00330-024-10639-1. [PMID: 38374482 DOI: 10.1007/s00330-024-10639-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 12/20/2023] [Accepted: 01/27/2024] [Indexed: 02/21/2024]
Abstract
OBJECTIVES To evaluate the additional advantages of integrating contrast-enhanced ultrasound (CEUS) into the Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) for the characterization of adnexal lesions with solid components. MATERIALS AND METHODS This prospective multicenter study recruited women suspected of having adnexal lesions with solid components between September 2021 and December 2022. All patients scheduled for surgery underwent preoperative CEUS and US examinations. The lesions were categorized according to the O-RADS US system, and quantitative CEUS indexes were recorded. Pathological results served as the reference standard. Univariable and multivariable analyses were performed to identify risk factors for malignancy in adnexal lesions with solid components. Receiver operating characteristic (ROC) curve analysis was employed to assess diagnostic performance. RESULTS A total of 180 lesions in 175 women were included in the study. Among these masses, 80 were malignant and 100 were benign. Multivariable analysis revealed that serum CA-125, the presence of acoustic shadowing, and peak intensity (PI) ratio (PImass/PIuterus) of solid components on CEUS were independently associated with adnexal malignancy. The modified CEUS risk stratification model demonstrated superior diagnostic value in assessing adnexal lesions with solid components compared to O-RADS US (AUC: 0.91 vs 0.78, p < 0.001) and exhibited comparable performance to the Assessment of Different NEoplasias in the adnexa (ADNEX) model (AUC 0.91 vs 0.86, p = 0.07). CONCLUSION Our findings underscore the potential value of CEUS as an adjunctive tool for enhancing the precision of diagnostic evaluations of O-RADS US. CLINICAL RELEVANCE STATEMENT The promising performance of the modified CEUS risk stratification model suggests its potential to mitigate unnecessary surgeries in the characterization of adnexal lesions with solid components. KEY POINTS • The additional value of CEUS to O-RADS US in distinguishing between benign and malignant adnexal lesions with solid components requires further evaluation. • The modified CEUS risk stratification model displayed superior diagnostic value and specificity in characterizing adnexal lesions with solid components when compared to O-RADS US. • The inclusion of CEUS demonstrated potential in reducing the need for unnecessary surgeries in the characterization of adnexal lesions with solid components.
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Affiliation(s)
- Manli Wu
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Man Zhang
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Enze Qu
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xiaofeng Sun
- Department of Ultrasound, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rui Zhang
- Department of Ultrasound, Children's Hospital of Shanxi (Women Health Center of Shanxi), Taiyuan, China
| | - Liang Mu
- Ultrasound Diagnosis Center, Shaanxi Provincial People's Hospital, Xi'an, China
| | - Li Xiao
- Department of Ultrasound, The Fifth People's Hospital of Chengdu, Chengdu, China
| | - Hong Wen
- Department of Ultrasound, Huizhou Central People's Hospital, Huizhou, China
| | - Ruili Wang
- Department of Ultrasound, Henan Provincial People's Hospital, Zhengzhou, China
| | - Tingting Liu
- Department of Ultrasound Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xiaotao Meng
- Department of Ultrasound, The Third Hospital of BaoGang Group, The Maternity Hospital Of Bao Tou, Baotou, China
| | - Shuangyu Wu
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ying Chen
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Manting Su
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ying Wang
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Jian Gu
- Department of Gynecology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
| | - Xinling Zhang
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
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Li Y, Shao G, Wu M, Zhang F, Zhang Y, Shao C. Evaluation of American College of Radiology Ovarian-Adnexal Reporting and Data System ultrasound to predict malignancy risk in adnexal lesions. J Obstet Gynaecol Res 2024; 50:225-232. [PMID: 37990446 DOI: 10.1111/jog.15831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 11/07/2023] [Indexed: 11/23/2023]
Abstract
AIMS To validate the diagnostic performance of Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound for preoperative adnexal lesions in an external center. The secondary aim was to evaluate the performance of a strategy test including O-RADS ultrasound evaluation and subjective assessment of higher malignant risk lesions. METHODS One hundred thirty patients with 158 ovarian-adnexal lesions were enrolled in the study. Each lesion was assigned an O-RADS score after real-time ultrasound examination by one experienced radiologist. A second subjective assessment by an expert was performed for O-RADS 4 and O-RADS 5 lesions. The histopathological diagnosis was used as the reference standard. RESULTS A total of 126 benign and 32 malignant adnexal masses were included in the study. The area under the receiver operating characteristic curve of O-RADS ultrasound was 0.950, with a cutoff value > O-RADS 3. The sensitivity, specificity, and negative and positive predictive values were 100% (95% confidence interval [CI], 0.867-1), 83.3% (95% CI, 0.754-0.892), 60.4% (95% CI, 0.460-0.732), and 100% (95% CI, 0.956-1), respectively. For the strategy test, the sensitivity, specificity, negative and positive predictive values were 100% (95% CI, 0.867-1), 92.1% (95% CI, 0.855-0.959), 76.2% (95% CI, 0.602-0.874), and 100% (95% CI, 0.960-1), respectively. In comparison with O-RADS ultrasound, the specificity and negative predictive value of the strategy test were slightly higher (p < 0.05). CONCLUSIONS Good diagnostic performance of the O-RADS ultrasound in adnexal lesions can be achieved by experienced radiologists in clinical practice. A second subjective assessment of sonographic findings can be applied to O-RADS 4 and 5 lesions.
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Affiliation(s)
- Ya Li
- Department of Ultrasound, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Guangrui Shao
- Department of Radiology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Mei Wu
- Department of Ultrasound, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Feixue Zhang
- Department of Ultrasound, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yuqing Zhang
- Department of Ultrasound, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Chunchun Shao
- Center of Evidence-Based Medicine, Institute of Medicine Science, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
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Dang Thi Minh N, Nguyen Van T, Duong Duc H, Nguyen Tuan M, Duong Thi Tra G, Do Tuan D, Nguyen Tai D. IOTA simple rules: An efficient tool for evaluation of ovarian tumors by non-experienced but trained examiners - A prospective study. Heliyon 2024; 10:e24262. [PMID: 38293393 PMCID: PMC10827489 DOI: 10.1016/j.heliyon.2024.e24262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 11/03/2023] [Accepted: 01/05/2024] [Indexed: 02/01/2024] Open
Abstract
Objectives A simple and efficient tool for evaluating ovarian tumors in general hospitals where radiologists without experience in gynecological ultrasound is necessary. This study aims to evaluate the diagnostic performance of IOTA simple rules in initial classification of ovarian tumors by non-experienced examiners who have received simple training. Materials and method A prospective single-center study was conducted at Hanoi Obstetrics and Gynecology Hospital. Three resident gynecologists trained themselves for two weeks and then received hands-on practice under the supervision of experts for another two weeks. The examiners performed ultrasound on 424 eligible women scheduled for surgery for ovarian tumors and classified the tumors based on IOTA simple rules. The postoperative pathology of ovarian tumors was used as the gold standard. Results 90.8 % (385/424) of the tumors were benign. Simple rules were applicable in 399/424 (94.1 %) tumors, with a sensitivity of 84.8 % (95 % CI, 70.2-94.3), specificity of 98.9 % (95 % CI, 97.5-99.7), positive predictive value of 87.5 % (95 % CI, 73.3-95.9), and negative predictive value of 98.6 % (95 % CI, 97.1-99.5). The sensitivity of IOTA simple rules was higher in postmenopausal women (91.7 % vs. 81.0 %), while the specificity was higher in premenopausal women (99.4 % vs. 95.8 %). Accuracy was 100 % in all ten pregnant women were assessed using these rules. Conclusion In conclusion, in the hands of non-expert examiners who were trained thoroughly, IOTA simple rules are a simple and efficient tool for clinical practice in centers where expert radiologists in gynecology are not always available. The training program is simple and could be applied widely in other clinical centers. Further studies are necessary to evaluate the effectiveness of the IOTA simple rules in assessing ovarian tumors among pregnant women.
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Affiliation(s)
- Nguyet Dang Thi Minh
- Department of Obstetrics and Gynecology, Hanoi Medical University, 1 Ton That Tung Street, Dong Da District, Hanoi, 100000, Viet Nam
| | - Thi Nguyen Van
- Department of Quan Su Radiology, K Hospital 43 Quan su Street, Hoan Kiem district, Hanoi, 100000, Viet Nam
| | - Huu Duong Duc
- Department of Quan Su Radiology, K Hospital 43 Quan su Street, Hoan Kiem district, Hanoi, 100000, Viet Nam
| | - Minh Nguyen Tuan
- Department of Obstetrics and Gynecology, Hanoi Medical University, 1 Ton That Tung Street, Dong Da District, Hanoi, 100000, Viet Nam
| | - Giang Duong Thi Tra
- Department of Delivery, Hanoi Obstetrics and Gynecology Hospital, 929 La Thanh Street, Ba Dinh district, Hanoi, 100000, Viet Nam
| | - Dat Do Tuan
- Department of Obstetrics and Gynecology, Hanoi Medical University, 1 Ton That Tung Street, Dong Da District, Hanoi, 100000, Viet Nam
| | - Duc Nguyen Tai
- Prenatal screening and diagnostic center, Hanoi Obstetrics and Gynecology Hospital, 929 La Thanh Street, Ba Dinh district, Hanoi, 100000, Viet Nam
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Ruan L, Liu H, Xiang H, Ni Y, Feng Y, Zhou H, Qi M. Application of O-RADS US combined with MV-Flow to diagnose ovarian-adnexal tumors. Ultrasonography 2024; 43:15-24. [PMID: 38061878 PMCID: PMC10766884 DOI: 10.14366/usg.23061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 08/14/2023] [Accepted: 08/25/2023] [Indexed: 01/06/2024] Open
Abstract
PURPOSE This study aimed to explore the application of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) combined with MV-Flow (Samsung Medison Co., Ltd.) to diagnose ovarian-adnexal masses. METHODS A total of 112 ovarian-adnexal masses (81 benign and 31 malignant) from 105 consecutive patients were analyzed. The O-RADS US and vascular index from MV-Flow (VIMV) were measured and compared with the reference standard. O-RADS US and MV-Flow were tested for consistency. RESULTS Receiver operating characteristic curves were drawn for O-RADS US, MV-Flow, and their combination. The combined methods had the largest area under the curve (0.955), followed by O-RADS US (0.929) and MV-Flow (0.923). A mass was considered malignant when the O-RADS US classification was 5 and VIMV was ≥7.15. With this definition, MV-Flow had the highest sensitivity (87.10%), with consistent findings for the combined diagnostic methods and O-RADS US (83.87%). The specificity of the combined diagnostic methods (93.83%) was higher than that of MV-Flow (91.36%). O-RADS US had the lowest specificity (90.12%). The combined diagnostic methods had the highest coincidence rate (91.07%), and MV-Flow (90.18%) had a significantly higher coincidence rate than O-RADS US (88.39%). Both O-RADS US and MV-Flow showed good consistency among different physicians (former kappa, 0.974; latter intraclass correlation coefficient [ICC], 0.986). MV-Flow had a high consistency for the same physician (ICC, 1). CONCLUSION O-RADS US and MV-Flow exhibited good diagnostic efficacy, and their combined diagnostic efficacy was higher than that of each individually. O-RADS US and MV-Flow can improve the diagnosis of benign and malignant ovarian-adnexal masses.
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Affiliation(s)
- Linlin Ruan
- Obstetrics and Gynecology Ultrasound Department, First Affiliated Hospital of Xinjiang Medical University, Xinjiang Key Laboratory of Ultrasound Medicine, Urumqi, China
| | - Hui Liu
- Obstetrics and Gynecology Ultrasound Department, First Affiliated Hospital of Xinjiang Medical University, Xinjiang Key Laboratory of Ultrasound Medicine, Urumqi, China
| | - Hong Xiang
- Obstetrics and Gynecology Ultrasound Department, First Affiliated Hospital of Xinjiang Medical University, Xinjiang Key Laboratory of Ultrasound Medicine, Urumqi, China
| | - Yongkang Ni
- School of Public Health, Xinjiang Medical University, Urumqi, China
| | - Yuling Feng
- Obstetrics and Gynecology Ultrasound Department, First Affiliated Hospital of Xinjiang Medical University, Xinjiang Key Laboratory of Ultrasound Medicine, Urumqi, China
| | - Huili Zhou
- Obstetrics and Gynecology Ultrasound Department, First Affiliated Hospital of Xinjiang Medical University, Xinjiang Key Laboratory of Ultrasound Medicine, Urumqi, China
| | - Mengtong Qi
- Obstetrics and Gynecology Ultrasound Department, First Affiliated Hospital of Xinjiang Medical University, Xinjiang Key Laboratory of Ultrasound Medicine, Urumqi, China
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Wu Y, Miao K, Wang T, Xu C, Yao J, Dong X. Prediction model of adnexal masses with complex ultrasound morphology. Front Med (Lausanne) 2023; 10:1284495. [PMID: 38143444 PMCID: PMC10740199 DOI: 10.3389/fmed.2023.1284495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 11/20/2023] [Indexed: 12/26/2023] Open
Abstract
Background Based on the ovarian-adnexal reporting and data system (O-RADS), we constructed a nomogram model to predict the malignancy potential of adnexal masses with sophisticated ultrasound morphology. Methods In a multicenter retrospective study, a total of 430 subjects with masses were collected in the adnexal region through an electronic medical record system at the Fourth Hospital of Harbin Medical University during the period of January 2019-April 2023. A total of 157 subjects were included in the exception validation cohort from Harbin Medical University Tumor Hospital. The pathological tumor findings were invoked as the gold standard to classify the subjects into benign and malignant groups. All patients were randomly allocated to the validation set and training set in a ratio of 7:3. A stepwise regression analysis was utilized for filtering variables. Logistic regression was conducted to construct a nomogram prediction model, which was further validated in the training set. The forest plot, C-index, calibration curve, and clinical decision curve were utilized to verify the model and assess its accuracy and validity, which were further compared with existing adnexal lesion models (O-RADS US) and assessments of different types of neoplasia in the adnexa (ADNEX). Results Four predictors as independent risk factors for malignancy were followed in the preparation of the diagnostic model: O-RADS classification, HE4 level, acoustic shadow, and protrusion blood flow score (all p < 0.05). The model showed moderate predictive power in the training set with a C-index of 0.959 (95%CI: 0.940-0.977), 0.929 (95%CI: 0.884-0.974) in the validation set, and 0.892 (95%CI: 0.843-0.940) in the external validation set. It showed that the predicted consequences of the nomogram agreed well with the actual results of the calibration curve, and the novel nomogram was clinically beneficial in decision curve analysis. Conclusion The risk of the nomogram of adnexal masses with complex ultrasound morphology contained four characteristics that showed a suitable predictive ability and provided better risk stratification. Its diagnostic performance significantly exceeded that of the ADNEX model and O-RADS US, and its screening performance was essentially equivalent to that of the ADNEX model and O-RADS US classification.
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Affiliation(s)
| | | | | | | | | | - Xiaoqiu Dong
- Department of Ultrasound, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
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Yang Y, Wang H, Liu Z, Su N, Gao L, Tao X, Zhang R, Gu Y, Ma L, Wang R, Xu W, Xie Y, Zhang W, Zhang H, Xue G, Ru T, Dai Q, Li J, Jiang Y. Effect of differences in O-RADS lexicon interpretation between senior and junior sonologists on O-RADS classification and diagnostic performance. J Cancer Res Clin Oncol 2023; 149:12275-12283. [PMID: 37430161 PMCID: PMC10465637 DOI: 10.1007/s00432-023-05108-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 06/30/2023] [Indexed: 07/12/2023]
Abstract
PURPOSE To assess the consistency of Ovarian-Adnexal Reporting and Data System (O-RADS) lexicon interpretation between senior and junior sonologists and to investigate its impact on O-RADS classification and diagnostic performance. METHODS We prospectively studied 620 patients with adnexal lesions, all of whom underwent transvaginal or transrectal ultrasound performed by a senior sonologist (R1) who selected the O-RADS lexicon description and O-RADS category for the lesion after the examination. Meanwhile, the junior sonologist (R2) analyzed the images retained by R1 and divided the lesion in the same way. Pathological findings were used as a reference standard. kappa (к) statistics were used to assess the interobserver agreement. RESULTS Of the 620 adnexal lesions, 532 were benign and 88 were malignant. When using the O-RADS lexicon, R1 and R2 had almost perfect agreement regarding lesion category, external contour of solid lesions, presence of papillary inside cystic lesions, and fluid echogenicity (к: 0.81-1.00). Substantial agreement in solid components, acoustic shadow, vascularity and O-RADS categories (к: 0.61-0.80). Consistency in classifying classic benign lesions in the O-RADS category was only moderate (к = 0.535). No significant difference in diagnostic performance between them using O-RADS (P = 0.1211). CONCLUSION There was good agreement between senior and junior sonologists in the interpretation of the O-RADS lexicon and in the classification of O-RADS, except for a moderate agreement in the interpretation and classification of classic benign lesions. Differences in O-RADS category delineation between sonologists had no significant effect on the diagnostic performance of O-RADS.
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Affiliation(s)
- Ya Yang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Hongyan Wang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Zhenzhen Liu
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Na Su
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Luying Gao
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Xixi Tao
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Rui Zhang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Yang Gu
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Li Ma
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Ruojiao Wang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Wen Xu
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Yuhuan Xie
- Department of Ultrasound, Dongguan People’s Hospital Affiliated to Southern Medical University, Dongguan, China
| | - Wenjun Zhang
- Department of Ultrasound, Taihe Hospital, the Affiliated to Hubei University of Medicine, Shiyan, China
| | - Heng Zhang
- Department of Ultrasound, Zhuhai People’s Hospital, Zhuhai, China
| | - Gaiqin Xue
- Department of Ultrasound, Shanxi Provincial Cancer Hospital, Shanxi, China
| | - Tong Ru
- Prenatal Diagnosis Center, Drum Tower Hospital, Nanjing University Medical School, Nanjing, China
| | - Qing Dai
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Jianchu Li
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
| | - Yuxin Jiang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730 China
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12
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Su N, Yang Y, Liu Z, Gao L, Dai Q, Li J, Wang H, Jiang Y. Validation of the diagnostic efficacy of O-RADS in adnexal masses. Sci Rep 2023; 13:15667. [PMID: 37735610 PMCID: PMC10514283 DOI: 10.1038/s41598-023-42836-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 09/15/2023] [Indexed: 09/23/2023] Open
Abstract
The aim of this study was to validate the performance of the Ovarian-Adnexal Reporting and Data Systems (O-RADS) series models proposed by the American College of Radiology (ACR) in the preoperative diagnosis of adnexal masses (AMs). Two experienced sonologists examined 218 patients with AMs and gave the assessment results after the examination. Pathological findings were used as a reference standard. Of the 218 lesions, 166 were benign and 52 were malignant. Based on the receiver operating characteristic (ROC) curve, we defined a malignant lesion as O-RADS > 3 (i.e., lesions in O-RADS categories 4 and 5 were malignant). The area under the curve (AUC) of O-RADS (v2022) was 0.970 (95% CI 0.938-0.988), which wasn't statistically significantly different from the O-RADS (v1) combined Simple Rules Risk (SRR) assessment model with the largest AUC of 0.976 (95% CI 0.946-0.992) (p = 0.1534), but was significantly higher than the O-RADS (v1) (AUC = 0.959, p = 0.0133) and subjective assessment (AUC = 0.918, p = 0.0255). The O-RADS series models have good diagnostic performance for AMs. Where, O-RADS (v2022) has higher accuracy and specificity than O-RADS (v1). The accuracy and specificity of O-RADS (v1), however, can be further improved when combined with SRR assessment.
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Affiliation(s)
- Na Su
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China
| | - Ya Yang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China
| | - Zhenzhen Liu
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China
| | - Luying Gao
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China
| | - Qing Dai
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China
| | - Jianchu Li
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China
| | - Hongyan Wang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China.
| | - Yuxin Jiang
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China.
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Strachowski LM, Jha P, Phillips CH, Blanchette Porter MM, Froyman W, Glanc P, Guo Y, Patel MD, Reinhold C, Suh-Burgmann EJ, Timmerman D, Andreotti RF. O-RADS US v2022: An Update from the American College of Radiology's Ovarian-Adnexal Reporting and Data System US Committee. Radiology 2023; 308:e230685. [PMID: 37698472 DOI: 10.1148/radiol.230685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/13/2023]
Abstract
First published in 2019, the Ovarian-Adnexal Reporting and Data System (O-RADS) US provides a standardized lexicon for ovarian and adnexal lesions, enables stratification of these lesions with use of a numeric score based on morphologic features to indicate the risk of malignancy, and offers management guidance. This risk stratification system has subsequently been validated in retrospective studies and has yielded good interreader concordance, even with users of different levels of expertise. As use of the system increased, it was recognized that an update was needed to address certain clinical challenges, clarify recommendations, and incorporate emerging data from validation studies. Additional morphologic features that favor benignity, such as the bilocular feature for cysts without solid components and shadowing for solid lesions with smooth contours, were added to O-RADS US for optimal risk-appropriate scoring. As O-RADS US 4 has been shown to be an appropriate cutoff for malignancy, it is now recommended that lower-risk O-RADS US 3 lesions be followed with US if not excised. For solid lesions and cystic lesions with solid components, further characterization with MRI is now emphasized as a supplemental evaluation method, as MRI may provide higher specificity. This statement summarizes the updates to the governing concepts, lexicon terminology and assessment categories, and management recommendations found in the 2022 version of O-RADS US.
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Affiliation(s)
- Lori M Strachowski
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Priyanka Jha
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Catherine H Phillips
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Misty M Blanchette Porter
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Wouter Froyman
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Phyllis Glanc
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Yang Guo
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Maitray D Patel
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Caroline Reinhold
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Elizabeth J Suh-Burgmann
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Dirk Timmerman
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
| | - Rochelle F Andreotti
- From the Department of Radiology and Biomedical Imaging and Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, 1001 Potrero Ave, 1X57, San Francisco, CA 94110 (L.M.S.); Department of Radiology, Stanford University School of Medicine, Palo Alto, Calif (P.J.); Department of Radiology and Radiologic Sciences, Vanderbilt University Medical Center, Nashville, Tenn (C.H.P.); Department of Obstetrics, Gynecology, and Reproductive Sciences, Larner College of Medicine at the University of Vermont, Burlington, Vt (M.M.B.P.); Department of Obstetrics and Gynecology, University Hospitals and Department of Development and Regeneration, KU Leuven, Leuven, Belgium (W.F., D.T.); Department of Medical Imaging, Sunnybrook Health Science Centre, University of Toronto, Toronto, Canada (P.G.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Y.G.); Department of Radiology, Mayo Clinic Arizona, Phoenix, Ariz (M.D.P.); Department of Radiology, McGill University Health Centre, Montreal, Canada (C.R.); Department of Gynecologic Oncology, Kaiser Permanente Northern California, Walnut Creek, Calif (E.J.S.B.); and Department of Radiology and Radiological Sciences and Department of Obstetrics and Gynecology, Vanderbilt University College of Medicine, Nashville, Tenn (R.F.A.)
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Shi Y, Li H, Wu X, Li X, Yang M. O-RADS combined with contrast-enhanced ultrasound in risk stratification of adnexal masses. J Ovarian Res 2023; 16:153. [PMID: 37537697 PMCID: PMC10399045 DOI: 10.1186/s13048-023-01243-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 07/17/2023] [Indexed: 08/05/2023] Open
Abstract
BACKGROUND Ovarian-Adnexal Reporting and Data System (O-RADS) for ultrasound is a lexicon and risk stratification system that includes all risk categories and relevant management recommendation. It has high sensitivity in diagnosing malignant adnexal tumors, but the specificity is lower. OBJECTIVE To explore the value of O-RADS combined with contrast-enhanced ultrasound (CEUS) in risk stratification of adnexal masses. METHODS A retrospective study was performed on 85 patients with 100 adnexal masses that preoperatively underwent conventional ultrasound as well as CEUS examination and obtained the postoperative pathological results. The masses were classified into O-RADS2, 3, 4, and 5 by conventional ultrasound. After contrast enhancement, the classification of O-RADS was adjusted according to CEUS imaging features. The O-RADS 2 and 3 lesions with suspected malignant features like irregular blood vessels or internal inhomogeneous hyperenhancement were upgraded to O-RADS 4, and the O-RADS 4 lesions with the above features were upgraded to O-RADS 5. The O-RADS 4 lesions with suspicious benign angiographic features like a regular vessel, interior hypoenhancement or non-enhancement were downgraded to O-RADS 3; the O-RADS 5 lesions with rim ring-enhancement and interior non-enhancement were downgraded to O-RADS 3. The sensitivity, specificity, accuracy, PPV, NPV, and AUC of the two methods were compared, taking pathological results as the gold standard. RESULTS The sensitivity, specificity, accuracy, PPV, NPV, and AUC of O-RADS and O-RADS combined with CEUS in the diagnosis of malignant adnexal tumors were 96.6%, 66.2%, 75.0%, 53.8%, 97.9%, 0.910 and 96.6%, 91.5%, 93.0%, 82.4%, 98.5%, 0.962, respectively. The specificity, accuracy, PPV, and AUC of O-RADS combined with CEUS were considerably higher than those of O-RADS (P < 0.01). Furthermore, both methods had excellent sensitivity and NPV but there were no significant differences between them(P > 0.05). CONCLUSION Combination of O-RADS and CEUS can significantly improve the specificity and PPV in diagnosing malignant adnexal tumors. It seems promising in the clinical application of risk stratification of adnexal masses.
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Affiliation(s)
- Yanyun Shi
- Department of Ultrasonography, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Xinglong Lane, Changzhou, China
| | - Huan Li
- Department of Ultrasonography, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Xinglong Lane, Changzhou, China.
| | - Xiuhua Wu
- Department of Ultrasonography, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Xinglong Lane, Changzhou, China
| | - Xiaoqin Li
- Department of Ultrasonography, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Xinglong Lane, Changzhou, China
| | - Min Yang
- Department of Ultrasonography, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Xinglong Lane, Changzhou, China
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Lee S, Lee JE, Hwang JA, Shin H. O-RADS US: A Systematic Review and Meta-Analysis of Category-specific Malignancy Rates. Radiology 2023; 308:e223269. [PMID: 37642566 DOI: 10.1148/radiol.223269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Background Ovarian-Adnexal Reporting and Data System (O-RADS) US provides a standardized method with which to stratify lesions into risk of malignancy categories, which is crucial for proper management. Purpose To perform a systematic review and meta-analysis to estimate malignancy rates for each O-RADS US score and evaluate the diagnostic performance of combined O-RADS US scores 4 and 5 in the diagnosis of malignancy. Materials and Methods A systematic literature search from the inception of the MEDLINE, EMBASE, and Web of Science databases through January 27, 2023, was performed for articles that reported using the O-RADS US stratification system and included malignancy rates per each O-RADS score. Bivariate random-effects models were used to determine the pooled malignancy rates for each O-RADS US score and to obtain summary estimates of the diagnostic performance of combined O-RADS US scores 4 and 5 in the diagnosis of malignant lesions. Results The final analysis included 18 studies consisting of 11 605 patients and 11 818 ovarian-adnexal lesions, with 2996 malignant (25.4%) and 8822 benign (74.6%) lesions. No malignant lesions were reported in O-RADS 1 category. The pooled percentages of malignancy were 0.6% (95% CI: 0.3, 1.0) for O-RADS 2, 3.9% (95% CI: 2.5, 5.4) for O-RADS 3, 43.5% (95% CI: 33.8, 53.2) for O-RADS 4, and 87.3% (95% CI: 83.0, 91.7) for O-RADS 5. The pooled sensitivity and specificity of combined O-RADS scores 4 and 5 in the diagnosis of malignant lesions were 95.6% (95% CI: 94.0, 97.2) and 76.6% (95% CI: 70.4, 82.7), respectively. Conclusion Each O-RADS US score provided the intended probability of malignant lesions as outlined by the O-RADS risk stratification system. When O-RADS US scores 4 and 5 were combined as a predictor for malignancy, O-RADS US showed a high sensitivity and moderate specificity. Clinical trial registration no. CRD42022352166 © RSNA, 2023 Supplemental material is available for this article.
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Affiliation(s)
- Sunyoung Lee
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea (S.L.); Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon, Republic of Korea (J.E.L.); Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea (J.A.H.); and Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.)
| | - Ji Eun Lee
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea (S.L.); Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon, Republic of Korea (J.E.L.); Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea (J.A.H.); and Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.)
| | - Jeong Ah Hwang
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea (S.L.); Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon, Republic of Korea (J.E.L.); Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea (J.A.H.); and Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.)
| | - Hyejung Shin
- From the Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea (S.L.); Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon, Republic of Korea (J.E.L.); Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea (J.A.H.); and Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (H.S.)
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Yuan K, Huang YJ, Mao MY, Li T, Wang SJ, He DN, Liu WF, Li MX, Zhu XM, Chen XY, Zhu YX. Contrast-enhanced US to Improve Diagnostic Performance of O-RADS US Risk Stratification System for Malignancy. Radiology 2023; 308:e223003. [PMID: 37552073 DOI: 10.1148/radiol.223003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023]
Abstract
Background The Ovarian-Adnexal Reporting and Data System (O-RADS) has limited specificity for malignancy. Contrast-enhanced US can help distinguish malignant from benign lesions, but its added value to O-RADS has not yet been assessed. Purpose To establish a diagnostic model combining O-RADS and contrast-enhanced US and to validate whether O-RADS plus contrast-enhanced US has a better diagnostic performance than O-RADS alone. Materials and Methods This prospective study included participants from May 2018 to March 2021 who underwent contrast-enhanced US before surgery and had lesions categorized as O-RADS 3, 4, or 5 by US, with a histopathologic reference standard. From April 2021 to July 2022, participants with pathologically confirmed ovarian-adnexal lesions were recruited for the validation group. In the pilot group, the initial enhancement time and enhancement intensity in comparison with the uterine myometrium, contrast agent distribution pattern, and dynamic changes in enhancement of lesions were assessed. Contrast-enhanced US features were used to calculate contrast-enhanced US scores for benign (score ≤2) and malignant (score ≥4) lesions. Lesions were then re-rated according to O-RADS category plus contrast-enhanced US scores. Receiver operating characteristic curves were constructed and compared using the DeLong method. The combined system was validated in an independent group. Results The pilot group included 76 women (mean age, 44 years ± 13 [SD]), and the validation group included 46 women (mean age, 42 years ± 14). Differences in initial enhancement time (P < .001), enhancement intensity (P < .001), and dynamic changes in enhancement (P < .001) between benign and malignant lesions were observed in the pilot group. Contrast-enhanced US scores were calculated using these features. The O-RADS risk stratification was upgraded one level for contrast-enhanced US scores of 4 or more and downgraded one level for contrast-enhanced US scores of 2 or less. In the validation group, the diagnostic performance of O-RADS plus contrast-enhanced US score was higher (area under the receiver operating characteristic curve [AUC] = 0.93) than O-RADS (AUC = 0.71, P < .001). Conclusion Contrast-enhanced US improved the diagnostic performance for malignancy of the O-RADS categories 3-5. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Grant in this issue.
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Affiliation(s)
- Kun Yuan
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Yu-Jun Huang
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Mu-Yi Mao
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Tian Li
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Song-Juan Wang
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Dan-Ni He
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Wen-Fen Liu
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Meng-Xiong Li
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Xiao-Min Zhu
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Xin-Yu Chen
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
| | - Yun-Xiao Zhu
- From the Department of Medical Ultrasonics (K.Y., Y.J.H., M.Y.M., S.J.W., D.N.H., W.F.L., X.M.Z., X.Y.C., Y.X.Z.) and Department of Obstetrics and Gynecology (T.L., M.X.L.), The Seventh Affiliated Hospital of Sun Yat-Sen University, 628 Zhenyuan Road, Xinhu Street, Guangming District, Shenzhen 518107, People's Republic of China
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Wu M, Zhang M, Cao J, Wu S, Chen Y, Luo L, Lin X, Su M, Zhang X. Predictive accuracy and reproducibility of the O-RADS US scoring system among sonologists with different training levels. Arch Gynecol Obstet 2023; 308:631-637. [PMID: 35994107 DOI: 10.1007/s00404-022-06752-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 08/12/2022] [Indexed: 11/02/2022]
Abstract
PURPOSE To investigate the predictive performance and reproducibility of Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) system in evaluating adnexal masses between sonologists with varying levels of expertise. METHODS This was a single-center retrospective study conducted between May 2019 and May 2020, which included 147 adnexal mases with pathological results. Four sonologists with varying experiences independently assigned an O-RADS US category to each adnexal mass twice. The intra- and inter-observer agreement was assessed using weighted kappa values. The area under the curve (AUC), sensitivity, specificity, positive and negative predictive value (PPV and NPV) were assessed for each sonologist. RESULTS Of the 147 adnexal mases, 115 (78.2%) lesions were benign and 32 (21.8%) lesions were malignant. Considering O-RADS > 3 as a predictor for adnexal malignancy, the predictive accuracies of the four sonologists were excellent, with AUCs ranging from 0.831 to 0.926. The predictive accuracies of O-RADS US by experienced sonologists were significantly higher compared to inexperienced sonologists (all P values < 0.005). The O-RADS US presented high sensitivity and NPV value for each sonologist. With regard to the reproducibility of O-RADS, the intra- and inter-observer agreement among experienced sonologists performed better than inexperienced sonologists. CONCLUSION O-RADS showed difference in the predictive accuracy and reproducibility in the evaluation of adnexal masses among sonologists with different levels of expertise. Training is required for inexperienced sonologists before the generalization of O-RADS classification system in clinical practice.
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Affiliation(s)
- Manli Wu
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, People's Republic of China
| | - Man Zhang
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, People's Republic of China
| | - Junyan Cao
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, People's Republic of China
| | - Shuangyu Wu
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, People's Republic of China
| | - Ying Chen
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, People's Republic of China
| | - Liping Luo
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, People's Republic of China
| | - Xin Lin
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, People's Republic of China
| | - Manting Su
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, People's Republic of China
| | - Xinling Zhang
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, People's Republic of China.
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Yoeli-Bik R, Longman RE, Wroblewski K, Weigert M, Abramowicz JS, Lengyel E. Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort. JAMA Netw Open 2023; 6:e2323289. [PMID: 37440228 PMCID: PMC10346125 DOI: 10.1001/jamanetworkopen.2023.23289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 05/30/2023] [Indexed: 07/14/2023] Open
Abstract
Importance Ultrasonography-based risk models can help nonexpert clinicians evaluate adnexal lesions and reduce surgical interventions for benign tumors. Yet, these models have limited uptake in the US, and studies comparing their diagnostic accuracy are lacking. Objective To evaluate, in a US cohort, the diagnostic performance of 3 ultrasonography-based risk models for differentiating between benign and malignant adnexal lesions: International Ovarian Tumor Analysis (IOTA) Simple Rules with inconclusive cases reclassified as malignant or reevaluated by an expert, IOTA Assessment of Different Neoplasias in the Adnexa (ADNEX), and Ovarian-Adnexal Reporting and Data System (O-RADS). Design, Setting, and Participants This retrospective diagnostic study was conducted at a single US academic medical center and included consecutive patients aged 18 to 89 years with adnexal masses that were managed surgically or conservatively between January 2017 and October 2022. Exposure Evaluation of adnexal lesions using the Simple Rules, ADNEX, and O-RADS. Main Outcomes and Measures The main outcome was diagnostic performance, including area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios. Surgery or follow-up were reference standards. Secondary analyses evaluated the models' performances stratified by menopause status and race. Results The cohort included 511 female patients with a 15.9% malignant tumor prevalence (81 patients). Mean (SD) ages of patients with benign and malignant adnexal lesions were 44.1 (14.4) and 52.5 (15.2) years, respectively, and 200 (39.1%) were postmenopausal. In the ROC analysis, the AUCs for discriminative performance of the ADNEX and O-RADS models were 0.96 (95% CI, 0.93-0.98) and 0.92 (95% CI, 0.90-0.95), respectively. After converting the ADNEX continuous individualized risk into the discrete ordinal categories of O-RADS, the ADNEX performance was reduced to an AUC of 0.93 (95% CI, 0.90-0.96), which was similar to that for O-RADS. The Simple Rules combined with expert reevaluation had 93.8% sensitivity (95% CI, 86.2%-98.0%) and 91.9% specificity (95% CI, 88.9%-94.3%), and the Simple Rules combined with malignant classification had 93.8% sensitivity (95% CI, 86.2%-98.0%) and 88.1% specificity (95% CI, 84.7%-91.0%). At a 10% risk threshold, ADNEX had 91.4% sensitivity (95% CI, 83.0%-96.5%) and 86.3% specificity (95% CI, 82.7%-89.4%) and O-RADS had 98.8% sensitivity (95% CI, 93.3%-100%) and 74.4% specificity (95% CI, 70.0%-78.5%). The specificities of all models were significantly lower in the postmenopausal group. Subgroup analysis revealed high performances independent of race. Conclusions and Relevance In this diagnostic study of a US cohort, the Simple Rules, ADNEX, and O-RADS models performed well in differentiating between benign and malignant adnexal lesions; this outcome has been previously reported primarily in European populations. Risk stratification models can lead to more accurate and consistent evaluations of adnexal masses, especially when used by nonexpert clinicians, and may reduce unnecessary surgeries.
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Affiliation(s)
- Roni Yoeli-Bik
- Department of Obstetrics and Gynecology, University of Chicago, Chicago, Illinois
| | - Ryan E. Longman
- Department of Obstetrics and Gynecology, University of Chicago, Chicago, Illinois
| | - Kristen Wroblewski
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois
| | - Melanie Weigert
- Department of Obstetrics and Gynecology, University of Chicago, Chicago, Illinois
| | | | - Ernst Lengyel
- Department of Obstetrics and Gynecology, University of Chicago, Chicago, Illinois
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Roseland ME, Maturen KE, Shampain KL, Wasnik AP, Stein EB. Adnexal Mass Imaging: Contemporary Guidelines for Clinical Practice. Radiol Clin North Am 2023; 61:671-685. [PMID: 37169431 DOI: 10.1016/j.rcl.2023.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Several recent guidelines have been published to improve accuracy and consistency of adnexal mass imaging interpretation and to guide management. Guidance from the American College of Radiology (ACR) Appropriateness Criteria establishes preferred adnexal imaging modalities and follow-up. Moreover, the ACR Ovarian-Adnexal Reporting Data System establishes a comprehensive, unified set of evidence-based guidelines for classification of adnexal masses by both ultrasound and MR imaging, communicating risk of malignancy to further guide management.
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Affiliation(s)
- Molly E Roseland
- Michigan Medicine, University of Michigan, University Hospital B1D502D, 1500 East Medical Center Dr., Ann Arbor, MI 48109, USA.
| | - Katherine E Maturen
- Michigan Medicine, University of Michigan, University Hospital B1D502D, 1500 East Medical Center Dr., Ann Arbor, MI 48109, USA
| | - Kimberly L Shampain
- Michigan Medicine, University of Michigan, University Hospital B1D502D, 1500 East Medical Center Dr., Ann Arbor, MI 48109, USA
| | - Ashish P Wasnik
- Michigan Medicine, University of Michigan, University Hospital B1D502D, 1500 East Medical Center Dr., Ann Arbor, MI 48109, USA
| | - Erica B Stein
- Michigan Medicine, University of Michigan, University Hospital B1D502D, 1500 East Medical Center Dr., Ann Arbor, MI 48109, USA
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Xu J, Huang Z, Zeng J, Zheng Z, Cao J, Su M, Zhang X. Value of Contrast-Enhanced Ultrasound Parameters in the Evaluation of Adnexal Masses with Ovarian-Adnexal Reporting and Data System Ultrasound. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:1527-1534. [PMID: 37032238 DOI: 10.1016/j.ultrasmedbio.2023.02.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/15/2023] [Accepted: 02/23/2023] [Indexed: 05/17/2023]
Abstract
OBJECTIVE The aim of this study was to determine whether incorporating qualitative parameters of contrast-enhanced ultrasound (CEUS) can increase the accuracy of adnexal lesion assessments with Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound category 4 or 5. METHODS Retrospective analysis of patients with adnexal masses who underwent conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) examinations between January and August of 2020. The study investigators reviewed and analyzed the morphological features of each mass before categorizing the US images independently according to the O-RADS system published by the American College of Radiology. In the CEUS analysis, the initial time and intensity of enhancement involving the wall and/or septation of the mass were compared with the uterine myometrium. Internal components of each mass were observed for signs of enhancement. The sensitivity, specificity, and Youden's index were calculated as the contrast variables and O-RADS. RESULTS Receiver operating characteristic curve analysis revealed that the best cutoff value was higher than O-RADS 4. When information on the extent of enhancement was applied to selectively upgrade O-RADS category 4 and selectively downgrade O-RADS category 5, the overall sensitivity increased to 90.2%, while the level of specificity (91.3%) remained the same. CONCLUSION Incorporating additional information from CEUS with respect to the extent of enhancement helped to improve the sensitivity of O-RADS category 4 and 5 masses without loss of specificity.
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Affiliation(s)
- Jing Xu
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Zeping Huang
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Jie Zeng
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Zhijuan Zheng
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Junyan Cao
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Manting Su
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Xinling Zhang
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China.
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Pelayo M, Sancho-Sauco J, Sanchez-Zurdo J, Abarca-Martinez L, Borrero-Gonzalez C, Sainz-Bueno JA, Alcazar JL, Pelayo-Delgado I. Ultrasound Features and Ultrasound Scores in the Differentiation between Benign and Malignant Adnexal Masses. Diagnostics (Basel) 2023; 13:2152. [PMID: 37443546 DOI: 10.3390/diagnostics13132152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 05/31/2023] [Accepted: 06/16/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND Several ultrasound (US) features help ultrasound experts in the classification of benign vs. malignant adnexal masses. US scores serve in this differentiation, but they all have misdiagnoses. The main objective of this study is to evaluate what ultrasound characteristics are associated with malignancy influencing ultrasound scores. METHODS This is a retrospective analysis of ultrasound features of adnexal lesions of women managed surgically. Ultrasound characteristics were analyzed, and masses were classified by subjective assessment of the ultrasonographer (SA) and other ultrasound scores (IOTA Simple Rules Risk Assessment SRRA, ADNEX model, and O-RADS). RESULTS Of a total of 187 adnexal masses studied, 134 were benign (71.7%) and 53 were malignant (28.3%). SA, IOTA SRRA, ADNEX model with or without CA125 and O-RADS had high levels of sensitivity (93.9%, 81.1%, 94.3%, 88.7%, 98.1%) but lower specificity (80.2%, 82.1%, 82.8%, 77.6%, 73.1%) with similar AUC (0.87, 0.87, 0.92, 0.90, 0.86). Ultrasound features significantly related with malignancy were the presence of irregular contour, absence of acoustic shadowing, vascularized solid areas, ≥1 papillae, vascularized septum, and moderate-severe ascites. CONCLUSION IOTA SRRA, ADNEX model, and O-RADS can help in the classification of benign and malignant masses. Certain ultrasound characteristics studied in ultrasound scores are associated with malignancy.
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Affiliation(s)
- Mar Pelayo
- HM Puerta del Sur, HM Rivas Hospital, 3428521 Madrid, Spain
| | - Javier Sancho-Sauco
- Department of Obstetrics and Gynecology, Universitary Hospital Ramón y Cajal, Alcalá de Henares University, 3428034 Madrid, Spain
| | | | - Leopoldo Abarca-Martinez
- Department of Obstetrics and Gynecology, Universitary Hospital Ramón y Cajal, Alcalá de Henares University, 3428034 Madrid, Spain
| | | | | | - Juan Luis Alcazar
- Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, 3431008 Pamplona, Spain
| | - Irene Pelayo-Delgado
- Department of Obstetrics and Gynecology, Universitary Hospital Ramón y Cajal, Alcalá de Henares University, 3428034 Madrid, Spain
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22
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Yang Y, Ju H, Huang Y. Diagnostic performance of IOTA SR and O-RADS combined with CA125, HE4, and risk of malignancy algorithm to distinguish benign and malignant adnexal masses. Eur J Radiol 2023; 165:110926. [PMID: 37418798 DOI: 10.1016/j.ejrad.2023.110926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 05/18/2023] [Accepted: 06/09/2023] [Indexed: 07/09/2023]
Abstract
PURPOSE To compare the diagnostic performance of International Ovarian Tumour Analysis Simple Rules (IOTA SR) and Ovarian-Adnexal Reporting and Data System (O-RADS), and to analyse whether combining IOTA SR and O-RADS with the biomarkers cancer antigen 125 (CA125), human epididymis protein 4 (HE4), and risk of malignancy algorithm (ROMA) further improves diagnostic performance in women with different menopause status. METHODS This study retrospectively included patients with ovarian adnexal masses confirmed by surgical pathology between September 2021 and February 2022. The area under the curve (AUC), sensitivity, and specificity were calculated to evaluate the diagnostic efficacy of IOTA SR, O-RADS, and their combination with CA125, HE4, and ROMA. RESULTS This study included 1,179 ovarian adnexal masses. In all women, the AUC of IOTA SR was comparable to O-RADS (0.879 vs. 0.889, P = 0.361), and O-RADS had a significantly higher sensitivity than IOTA SR (95.77 % vs. 87.32 %, P < 0.001). In premenopausal women, O-RADS had a significantly higher AUC than other diagnostic strategies (all P < 0.05), and the sensitivity, specificity, and accuracy were 93.33 %, 84.74 %, and 85.59 %, respectively. In postmenopausal women, IOTA SR + ROMA had a significantly higher AUC than other diagnostic strategies (all P < 0.05), and the sensitivity, specificity, and accuracy were 85.37 %, 93.88 %, and 90.00 %, respectively. CONCLUSIONS Our study supports the high diagnostic value of IOTA SR or O-RADS alone in all women, and O-RADS was more sensitive than IOTA SR. In premenopausal women, O-RADS had the highest diagnostic value. In postmenopausal women, IOTA SR outperformed O-RADS, and IOTA SR + ROMA had the highest diagnostic value.
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Affiliation(s)
- Yang Yang
- Department of Ultrasound, China Medical University, Shengjing Hospital, No. 36 Sanhao Street, Heping District, Shenyang, 110004 Liaoning Province, China
| | - Hao Ju
- Department of Ultrasound, China Medical University, Shengjing Hospital, No. 36 Sanhao Street, Heping District, Shenyang, 110004 Liaoning Province, China
| | - Ying Huang
- Department of Ultrasound, China Medical University, Shengjing Hospital, No. 36 Sanhao Street, Heping District, Shenyang, 110004 Liaoning Province, China.
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Wang T, Cui W, Nie F, Huang X, Huang L, Liu L, Zhu Y, Zheng R. Comparative Study of the Efficacy of the Ovarian-Adnexa Reporting and Data System Ultrasound Combined With Contrast-Enhanced Ultrasound and the ADNEX MR Scoring System in the Diagnosis of Adnexal Masses. ULTRASOUND IN MEDICINE & BIOLOGY 2023:S0301-5629(23)00170-9. [PMID: 37321953 DOI: 10.1016/j.ultrasmedbio.2023.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/23/2023] [Accepted: 05/22/2023] [Indexed: 06/17/2023]
Abstract
OBJECTIVE The aims of this study were to develop the Ovarian-Adnexa Reporting and Data System (O-RADS) and O-RADS + contrast-enhanced ultrasound (O-RADS CEUS) scoring system to distinguish adnexal masses (AMs) and to compare the diagnostic efficacy of these systems with that of a magnetic resonance imaging scoring system (ADNEX MR). METHODS We retrospectively evaluated 278 ovarian masses from 240 patients between May 2017 and July 2022. Pathology and adequate follow-up were used as reference standards for comparing the validity of O-RADS, O-RADS CEUS and ADNEX MR scoring to diagnose AMs. Area under the curve (AUC), sensitivity and specificity were calculated. The inter-class correlation coefficient (ICC) was calculated to evaluate inter-reader agreement (IRA) between the two sonographers and two radiologists who analyzed the findings with the three modalities. RESULTS The AUCs of O-RADS, O-RADS CEUS and ADNEX MR scores were 0.928 (95% confidence interval [CI]: 0.895-0.956), 0.951(95% CI: 0.919-0.973) and 0.964 (95% CI: 0.935-0.983), respectively. Their sensitivities were 95.7%, 94.3 and 91.4%, and their specificities were 81.3%, 92.3% and 97.1%, respectively. The three modalities had accuracies of 84.9%, 92.8% and 95.7%, respectively. O-RADS had the highest sensitivity but significantly lower specificity (p < 0.001), whereas the ADNEX MR scoring had the highest specificity (p < 0.001) but lower sensitivity (p < 0.001). O-RADS CEUS had intermediate sensitivity and specificity (p < 0.001). CONCLUSION The addition of CEUS significantly improves the efficacy of O-RADS in diagnosing AMs. The diagnostic efficacy of the combination is comparable to that of the ADNEX MR scoring system.
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Affiliation(s)
- Ting Wang
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou 730030, China; Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China; Gansu Province Medical Engineering Research Center for Intelligence Ultrasound, Lanzhou, China
| | - Wenjun Cui
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Gansu, China
| | - Fang Nie
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou 730030, China; Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China; Gansu Province Medical Engineering Research Center for Intelligence Ultrasound, Lanzhou, China.
| | - Xiao Huang
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou 730030, China; Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China; Gansu Province Medical Engineering Research Center for Intelligence Ultrasound, Lanzhou, China
| | - Lele Huang
- Department of Nuclear Medicine, Lanzhou University Second Hospital, Gansu, China
| | - Luping Liu
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou 730030, China; Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China; Gansu Province Medical Engineering Research Center for Intelligence Ultrasound, Lanzhou, China
| | - Yangyang Zhu
- Ultrasound Medical Center, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou 730030, China; Gansu Province Clinical Research Center for Ultrasonography, Lanzhou, China; Gansu Province Medical Engineering Research Center for Intelligence Ultrasound, Lanzhou, China
| | - Rongfang Zheng
- Department of Gynaecology, Lanzhou University Second Hospital, Gansu, China
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Sadowski EA, Rockall A, Thomassin-Naggara I, Barroilhet LM, Wallace SK, Jha P, Gupta A, Shinagare AB, Guo Y, Reinhold C. Adnexal Lesion Imaging: Past, Present, and Future. Radiology 2023; 307:e223281. [PMID: 37158725 DOI: 10.1148/radiol.223281] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Currently, imaging is part of the standard of care for patients with adnexal lesions prior to definitive management. Imaging can identify a physiologic finding or classic benign lesion that can be followed up conservatively. When one of these entities is not present, imaging is used to determine the probability of ovarian cancer prior to surgical consultation. Since the inclusion of imaging in the evaluation of adnexal lesions in the 1970s, the rate of surgery for benign lesions has decreased. More recently, data-driven Ovarian-Adnexal Reporting and Data System (O-RADS) scoring systems for US and MRI with standardized lexicons have been developed to allow for assignment of a cancer risk score, with the goal of further decreasing unnecessary interventions while expediting the care of patients with ovarian cancer. US is used as the initial modality for the assessment of adnexal lesions, while MRI is used when there is a clinical need for increased specificity and positive predictive value for the diagnosis of cancer. This article will review how the treatment of adnexal lesions has changed due to imaging over the decades; the current data supporting the use of US, CT, and MRI to determine the likelihood of cancer; and future directions of adnexal imaging for the early detection of ovarian cancer.
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Affiliation(s)
- Elizabeth A Sadowski
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
| | - Andrea Rockall
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
| | - Isabelle Thomassin-Naggara
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
| | - Lisa M Barroilhet
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
| | - Sumer K Wallace
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
| | - Priyanka Jha
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
| | - Akshya Gupta
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
| | - Atul B Shinagare
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
| | - Yang Guo
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
| | - Caroline Reinhold
- From the Departments of Radiology (E.A.S.) and Obstetrics and Gynecology (E.A.S., L.M.B., S.K.W.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI 53792-3252; Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, London, UK (A.R.); Department of Radiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France (I.T.N.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (P.J.); Department of Imaging Sciences, University of Rochester, Rochester, NY (A.G.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (A.B.S., Y.G.); Augmented Imaging Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, and Department of Radiology, McGill University, Montreal, Canada (C.R.); and Montreal Imaging Experts, Montreal, Canada (C.R.)
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Lu B, Liu C, Qi J, He W, Shi T, Zhu Y, Huang B. Comparison of contrast-enhanced ultrasound, IOTA simple rules and O-RADS for assessing the malignant risk of sonographically appearing solid ovarian masses. J Gynecol Obstet Hum Reprod 2023; 52:102564. [PMID: 36868504 DOI: 10.1016/j.jogoh.2023.102564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 02/02/2023] [Accepted: 02/26/2023] [Indexed: 03/05/2023]
Abstract
PURPOSE To explore the diagnostic accuracy of ovarian solid tumors by 2D ultrasound and contrast-enhanced ultrasound (CEUS). MATERIALS AND METHODS We retrospectively evaluated the CEUS characteristics of prospectively enrolled 16 benign and 19 malignant ovarian solid tumors. We performed International Ovarian Tumor Analysis (IOTA) simple rules and Ovarian-Adnexal Reporting and Data System (O-RADS) for all lesions, and evaluated their characteristics on CEUS. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of IOTA simple rules, O-RADS and CEUS in the diagnosis of ovarian solid malignancies were calculated. RESULTS The combination of time to wash-in earlier than or equal to the myometrium, time to PI earlier than or equal to the myometrium and the intensity at peak were higher than or equal to myometrium with sensibility of 0.947, specificity of 0.938, and PPV of 0.947, NPV of 0.938 which were higher than IOTA simple rules and O-RADS. According to the definition of ovarian solid tumor, the diagnostic accuracy of O-RADS 3 and CEUS were both 100%, CEUS improved the accuracy of O-RADS 4 from 47.4% to 87.5%, the accuracy of solid smooth CS 4 in O-RADS 5 and CEUS were both 100%, CEUS improved the accuracy of solid irregular in O-RADS 5 from 70% to 87.5%. CONCLUSION For ovarian solid tumors that are difficult to distinguish between benign and malignant, the introduction of CEUS on the basis of 2D classification criteria can significantly improve the diagnostic accuracy.
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Affiliation(s)
- Beilei Lu
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, PR China; Shanghai Institute of Medical Imaging, Shanghai 200032, PR China; Institute of Medical Ultrasound and Engineering, Fudan University, Shanghai 200032, PR China
| | - Chang Liu
- Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Shanghai 200072, PR China
| | - Jiuling Qi
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, PR China; Shanghai Institute of Medical Imaging, Shanghai 200032, PR China; Institute of Medical Ultrasound and Engineering, Fudan University, Shanghai 200032, PR China.
| | - Wanyuan He
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, PR China; Shanghai Institute of Medical Imaging, Shanghai 200032, PR China; Institute of Medical Ultrasound and Engineering, Fudan University, Shanghai 200032, PR China.
| | - Tingyan Shi
- Ovarian Cancer Program, Division of Gynecology Oncology, Department of Obstetrics and Gynecology, Zhongshan Hospital, Fudan University, 200032 PR China
| | - Yuli Zhu
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, PR China; Shanghai Institute of Medical Imaging, Shanghai 200032, PR China; Institute of Medical Ultrasound and Engineering, Fudan University, Shanghai 200032, PR China
| | - Beijian Huang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, PR China; Shanghai Institute of Medical Imaging, Shanghai 200032, PR China; Institute of Medical Ultrasound and Engineering, Fudan University, Shanghai 200032, PR China.
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Pelayo M, Pelayo-Delgado I, Sancho-Sauco J, Sanchez-Zurdo J, Abarca-Martinez L, Corraliza-Galán V, Martin-Gromaz C, Pablos-Antona MJ, Zurita-Calvo J, Alcázar JL. Comparison of Ultrasound Scores in Differentiating between Benign and Malignant Adnexal Masses. Diagnostics (Basel) 2023; 13:diagnostics13071307. [PMID: 37046525 PMCID: PMC10093240 DOI: 10.3390/diagnostics13071307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 03/26/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
Subjective ultrasound assessment by an expert examiner is meant to be the best option for the differentiation between benign and malignant adnexal masses. Different ultrasound scores can help in the classification, but whether one of them is significantly better than others is still a matter of debate. The main aim of this work is to compare the diagnostic performance of some of these scores in the evaluation of adnexal masses in the same set of patients. This is a retrospective study of a consecutive series of women diagnosed as having a persistent adnexal mass and managed surgically. Ultrasound characteristics were analyzed according to IOTA criteria. Masses were classified according to the subjective impression of the sonographer and other ultrasound scores (IOTA simple rules -SR-, IOTA simple rules risk assessment -SRRA-, O-RADS classification, and ADNEX model -with and without CA125 value-). A total of 122 women were included. Sixty-two women were postmenopausal (50.8%). Eighty-one women had a benign mass (66.4%), and 41 (33.6%) had a malignant tumor. The sensitivity of subjective assessment, IOTA SR, IOTA SRRA, and ADNEX model with or without CA125 and O-RADS was 87.8%, 66.7%, 78.1%, 95.1%, 87.8%, and 90.2%, respectively. The specificity for these approaches was 69.1%, 89.2%, 72.8%, 74.1%, 67.9%, and 60.5%, respectively. All methods with similar AUC (0.81, 0.78, 0.80, 0.88, 0.84, and 0.75, respectively). We concluded that IOTA SR, IOTA SRRA, and ADNEX models with or without CA125 and O-RADS can help in the differentiation of benign and malignant masses, and their performance is similar to the subjective assessment of an experienced sonographer.
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Affiliation(s)
- Mar Pelayo
- Department of Radiology, Hospital HM Puerta del Sur, 28938 Móstoles, Spain;
- Department of Radiology, Hospital HM Rivas, 28521 Madrid, Spain
| | - Irene Pelayo-Delgado
- Department of Obstetrics and Gynecology, Hospital Ramon y Cajal, 28034 Madrid, Spain; (J.S.-S.); (L.A.-M.); (V.C.-G.); (C.M.-G.); (M.J.P.-A.); (J.Z.-C.)
- Correspondence: (I.P.-D.); (J.L.A.)
| | - Javier Sancho-Sauco
- Department of Obstetrics and Gynecology, Hospital Ramon y Cajal, 28034 Madrid, Spain; (J.S.-S.); (L.A.-M.); (V.C.-G.); (C.M.-G.); (M.J.P.-A.); (J.Z.-C.)
| | | | - Leopoldo Abarca-Martinez
- Department of Obstetrics and Gynecology, Hospital Ramon y Cajal, 28034 Madrid, Spain; (J.S.-S.); (L.A.-M.); (V.C.-G.); (C.M.-G.); (M.J.P.-A.); (J.Z.-C.)
| | - Virginia Corraliza-Galán
- Department of Obstetrics and Gynecology, Hospital Ramon y Cajal, 28034 Madrid, Spain; (J.S.-S.); (L.A.-M.); (V.C.-G.); (C.M.-G.); (M.J.P.-A.); (J.Z.-C.)
| | - Carmen Martin-Gromaz
- Department of Obstetrics and Gynecology, Hospital Ramon y Cajal, 28034 Madrid, Spain; (J.S.-S.); (L.A.-M.); (V.C.-G.); (C.M.-G.); (M.J.P.-A.); (J.Z.-C.)
| | - María Jesús Pablos-Antona
- Department of Obstetrics and Gynecology, Hospital Ramon y Cajal, 28034 Madrid, Spain; (J.S.-S.); (L.A.-M.); (V.C.-G.); (C.M.-G.); (M.J.P.-A.); (J.Z.-C.)
| | - Julia Zurita-Calvo
- Department of Obstetrics and Gynecology, Hospital Ramon y Cajal, 28034 Madrid, Spain; (J.S.-S.); (L.A.-M.); (V.C.-G.); (C.M.-G.); (M.J.P.-A.); (J.Z.-C.)
| | - Juan Luis Alcázar
- Department of Obstetrics and Gynecology, Clinica Universidad de Navarra, 31008 Pamplona, Spain
- Correspondence: (I.P.-D.); (J.L.A.)
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Gong LP, Li XY, Wu YN, Dong S, Zhang S, Feng YN, Lv YE, Guo XJ, Peng YQ, Du XS, Tian JW, Sun CX, Sun LT. Nomogram based on the O-RADS for predicting the malignancy risk of adnexal masses with complex ultrasound morphology. J Ovarian Res 2023; 16:57. [PMID: 36945000 PMCID: PMC10029304 DOI: 10.1186/s13048-023-01133-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/09/2023] [Indexed: 03/23/2023] Open
Abstract
OBJECTIVE The accurate preoperative differentiation of benign and malignant adnexal masses, especially those with complex ultrasound morphology, remains a great challenge for junior sonographers. The purpose of this study was to develop and validate a nomogram based on the Ovarian-Adnexal Reporting and Data System (O-RADS) for predicting the malignancy risk of adnexal masses with complex ultrasound morphology. METHODS A total of 243 patients with data on adnexal masses with complex ultrasound morphology from January 2019 to December 2020 were selected to establish the training cohort, while 106 patients with data from January 2021 to December 2021 served as the validation cohort. Univariate and multivariate analyses were used to determine independent risk factors for malignant tumors in the training cohort. Subsequently, a predictive nomogram model was developed and validated in the validation cohort. The calibration, discrimination, and clinical net benefit of the nomogram model were assessed separately by calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Finally, we compared this model to the O-RADS. RESULTS The O-RADS category, an elevated CA125 level, acoustic shadowing and a papillary projection with color Doppler flow were the independent predictors and were incorporated into the nomogram model. The area under the ROC curve (AUC) of the nomogram model was 0.958 (95% CI, 0.932-0.984) in the training cohort. The specificity and sensitivity were 0.939 and 0.893, respectively. This nomogram also showed good discrimination in the validation cohort (AUC = 0.940, 95% CI, 0.899-0.981), with a sensitivity of 0.915 and specificity of 0.797. In addition, the nomogram model showed good calibration efficiency in both the training and validation cohorts. DCA indicated that the nomogram was clinically useful. Furthermore, the nomogram model had higher AUC and net benefit than the O-RADS. CONCLUSION The nomogram based on the O-RADS showed a good predictive ability for the malignancy risk of adnexal masses with complex ultrasound morphology and could provide help for junior sonographers.
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Affiliation(s)
- Li-Ping Gong
- Department of Ultrasound, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang Province, China
| | - Xiao-Ying Li
- Department of Ultrasound, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang Province, China
| | - Ying-Nan Wu
- Department of Ultrasound, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang Province, China
| | - Shuang Dong
- Department of Ultrasound, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang Province, China
| | - Shuang Zhang
- Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang Province, China
| | - Ya-Nan Feng
- Department of Ultrasound, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang Province, China
| | - Ya-Er Lv
- Department of Ultrasound, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang Province, China
| | - Xi-Juan Guo
- Department of Ultrasound, Shijiazhuang Obstetrics and Gynecology Hospital, Shijiazhuang, 050011, Hebei Province, China
| | - Yan-Qing Peng
- Department of Ultrasound, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang Province, China
| | - Xiao-Shan Du
- Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang Province, China
| | - Jia-Wei Tian
- Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang Province, China
| | - Cong-Xin Sun
- Department of Ultrasound, Shijiazhuang Obstetrics and Gynecology Hospital, Shijiazhuang, 050011, Hebei Province, China.
| | - Li-Tao Sun
- Department of Ultrasound, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang Province, China.
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Beyond the AJR: O-RADS Ultrasound Risk Stratification Performs Within Expected Range With Excellent Diagnostic Performance in Nonselected Female Patients in the United States. AJR Am J Roentgenol 2023; 220:450. [PMID: 35895300 DOI: 10.2214/ajr.22.28303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
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Hack K, Strachowski L, Andreotti RF, Ghandehari H, Jha P, Lim C, Patel C, Glanc P. O-RADS US Risk Stratification and Management System: Case-based Learning Approach for Daily Practice. Radiographics 2023; 43:e220079. [PMID: 36821507 DOI: 10.1148/rg.220079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Affiliation(s)
- Kalesha Hack
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, MG160, 2075 Bayview Ave, Toronto, ON, Canada M4N 3M5 (K.H., H.G., C.L., C.P., P.G.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (L.S., P.J.); and Department of Radiology, Vanderbilt University, Nashville, Tenn (R.F.A.)
| | - Lori Strachowski
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, MG160, 2075 Bayview Ave, Toronto, ON, Canada M4N 3M5 (K.H., H.G., C.L., C.P., P.G.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (L.S., P.J.); and Department of Radiology, Vanderbilt University, Nashville, Tenn (R.F.A.)
| | - Rochelle F Andreotti
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, MG160, 2075 Bayview Ave, Toronto, ON, Canada M4N 3M5 (K.H., H.G., C.L., C.P., P.G.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (L.S., P.J.); and Department of Radiology, Vanderbilt University, Nashville, Tenn (R.F.A.)
| | - Hournaz Ghandehari
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, MG160, 2075 Bayview Ave, Toronto, ON, Canada M4N 3M5 (K.H., H.G., C.L., C.P., P.G.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (L.S., P.J.); and Department of Radiology, Vanderbilt University, Nashville, Tenn (R.F.A.)
| | - Priyanka Jha
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, MG160, 2075 Bayview Ave, Toronto, ON, Canada M4N 3M5 (K.H., H.G., C.L., C.P., P.G.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (L.S., P.J.); and Department of Radiology, Vanderbilt University, Nashville, Tenn (R.F.A.)
| | - Christopher Lim
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, MG160, 2075 Bayview Ave, Toronto, ON, Canada M4N 3M5 (K.H., H.G., C.L., C.P., P.G.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (L.S., P.J.); and Department of Radiology, Vanderbilt University, Nashville, Tenn (R.F.A.)
| | - Chirag Patel
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, MG160, 2075 Bayview Ave, Toronto, ON, Canada M4N 3M5 (K.H., H.G., C.L., C.P., P.G.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (L.S., P.J.); and Department of Radiology, Vanderbilt University, Nashville, Tenn (R.F.A.)
| | - Phyllis Glanc
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, MG160, 2075 Bayview Ave, Toronto, ON, Canada M4N 3M5 (K.H., H.G., C.L., C.P., P.G.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (L.S., P.J.); and Department of Radiology, Vanderbilt University, Nashville, Tenn (R.F.A.)
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Koch AH, Jeelof LS, Muntinga CLP, Gootzen TA, van de Kruis NMA, Nederend J, Boers T, van der Sommen F, Piek JMJ. Analysis of computer-aided diagnostics in the preoperative diagnosis of ovarian cancer: a systematic review. Insights Imaging 2023; 14:34. [PMID: 36790570 PMCID: PMC9931983 DOI: 10.1186/s13244-022-01345-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 12/05/2022] [Indexed: 02/16/2023] Open
Abstract
OBJECTIVES Different noninvasive imaging methods to predict the chance of malignancy of ovarian tumors are available. However, their predictive value is limited due to subjectivity of the reviewer. Therefore, more objective prediction models are needed. Computer-aided diagnostics (CAD) could be such a model, since it lacks bias that comes with currently used models. In this study, we evaluated the available data on CAD in predicting the chance of malignancy of ovarian tumors. METHODS We searched for all published studies investigating diagnostic accuracy of CAD based on ultrasound, CT and MRI in pre-surgical patients with an ovarian tumor compared to reference standards. RESULTS In thirty-one included studies, extracted features from three different imaging techniques were used in different mathematical models. All studies assessed CAD based on machine learning on ultrasound, CT scan and MRI scan images. Per imaging method, subsequently ultrasound, CT and MRI, sensitivities ranged from 40.3 to 100%; 84.6-100% and 66.7-100% and specificities ranged from 76.3-100%; 69-100% and 77.8-100%. Results could not be pooled, due to broad heterogeneity. Although the majority of studies report high performances, they are at considerable risk of overfitting due to the absence of an independent test set. CONCLUSION Based on this literature review, different CAD for ultrasound, CT scans and MRI scans seem promising to aid physicians in assessing ovarian tumors through their objective and potentially cost-effective character. However, performance should be evaluated per imaging technique. Prospective and larger datasets with external validation are desired to make their results generalizable.
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Affiliation(s)
- Anna H. Koch
- grid.413532.20000 0004 0398 8384Department of Gynaecology and Obstetrics and Catharina Cancer Institute, Catharina Hospital, 5623 EJ Eindhoven, Noord-Brabant, The Netherlands
| | - Lara S. Jeelof
- grid.413532.20000 0004 0398 8384Department of Gynaecology and Obstetrics and Catharina Cancer Institute, Catharina Hospital, 5623 EJ Eindhoven, Noord-Brabant, The Netherlands
| | - Caroline L. P. Muntinga
- grid.413532.20000 0004 0398 8384Department of Gynaecology and Obstetrics and Catharina Cancer Institute, Catharina Hospital, 5623 EJ Eindhoven, Noord-Brabant, The Netherlands
| | - T. A. Gootzen
- grid.413532.20000 0004 0398 8384Department of Gynaecology and Obstetrics and Catharina Cancer Institute, Catharina Hospital, 5623 EJ Eindhoven, Noord-Brabant, The Netherlands
| | - Nienke M. A. van de Kruis
- grid.413532.20000 0004 0398 8384Department of Gynaecology and Obstetrics and Catharina Cancer Institute, Catharina Hospital, 5623 EJ Eindhoven, Noord-Brabant, The Netherlands
| | - Joost Nederend
- grid.413532.20000 0004 0398 8384Department of Radiology, Catharina Hospital, 5623 EJ Eindhoven, Noord-Brabant, The Netherlands
| | - Tim Boers
- grid.6852.90000 0004 0398 8763Department of Electrical Engineering, VCA Group, University of Technology Eindhoven, 5600 MB Eindhoven, Noord-Brabant The Netherlands
| | - Fons van der Sommen
- grid.6852.90000 0004 0398 8763Department of Electrical Engineering, VCA Group, University of Technology Eindhoven, 5600 MB Eindhoven, Noord-Brabant The Netherlands
| | - Jurgen M. J. Piek
- grid.413532.20000 0004 0398 8384Department of Gynaecology and Obstetrics and Catharina Cancer Institute, Catharina Hospital, 5623 EJ Eindhoven, Noord-Brabant, The Netherlands
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Alcázar JL, Rodriguez-Guzman L, Vara J, Amor F, Diaz L, Vaccaro H. Gynecologic Imaging and Reporting Data System for classifying adnexal masses. Minerva Obstet Gynecol 2023; 75:69-79. [PMID: 36790399 DOI: 10.23736/s2724-606x.22.05122-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
INTRODUCTION To perform a systematic review and meta-analysis of the diagnostic performance of the so-called Gynecologic Imaging and Report Data System (GI-RADS) for classifying adnexal masses. EVIDENCE ACQUISITION A search for studies reporting about the use of GI-RADS system for classifying adnexal masses from January 2009 to December 2021 was performed in Medline (Pubmed), Google Scholar, Scopus, Cochrane, and Web of Science databases. Pooled sensitivity, specificity, positive and negative likelihood ratios and diagnostic odd ratio (DOR) were calculated. Studies' quality was evaluated using QUADAS-2. EVIDENCE SYNTHESIS We identified 510 citations. Ultimately, 26 studies comprising 7350 masses were included. Mean prevalence of ovarian malignancy was 26%. The risk of bias was high in eight studies for domain "patient selection" and low for "index test," "reference test" domains for all studies. Overall, pooled estimated sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio and DOR of GI-RADS system for classifying adnexal masses were 94% (95% confidence interval [CI]=91-96%), 90% (95% CI=87-92%), 9.1 (95% CI=7.0-11.9), and 0.07 (95% CI=0.05-0.11), and 132 (95% CI=78-221), respectively. Heterogeneity was high for both sensitivity and specificity. Meta-regression showed that multiple observers and study's design explained this heterogeneity among studies. CONCLUSIONS GI-RADS system has a good diagnostic performance for classifying adnexal masses.
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Affiliation(s)
- Juan L Alcázar
- Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, Pamplona, Spain -
| | | | - Julio Vara
- Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Fernando Amor
- Panoramic Ultrasonic Ultrasound Center, Santiago, Chile
| | - Linder Diaz
- AGB Ultrasonography Center, Clínica Sanatorio Alemán S.A., Concepción, Chile
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Phillips CH, Guo Y, Strachowski LM, Jha P, Reinhold C, Andreotti RF. The Ovarian/Adnexal Reporting and Data System for Ultrasound: From Standardized Terminology to Optimal Risk Assessment and Management. Can Assoc Radiol J 2023; 74:44-57. [PMID: 35831958 DOI: 10.1177/08465371221108057] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) lexicon and risk assessment tool for ultrasound (US) provides a framework for characterization of ovarian and adnexal pathology with the ultimate goal of harmonizing reporting and patient management strategies. Since the first O-RADS US publication in 2018, multiple validation studies have shown O-RADS US to have excellent diagnostic accuracy, with the majority of these studies using O-RADS 4 as the optimal cut-off for detecting ovarian cancer. Most of the existing validation studies include a dedicated training phase and confirm that ORADS US categories and lexicon descriptors are associated with high level inter-read agreement, regardless of radiologist training level or practice experience. O-RADS US has a similar inter-reader agreement when compared to Gynecologic Imaging Reporting and Data System (GIRADS), Assessment of Different Neoplasias in the adnexa (ADNEX), and International Tumor Analysis Group (IOTA) simple rules. System descriptors have been shown to correlate with expected malignancy rates and the O-RADS US risk stratification system has been shown to perform in the expected range of malignancy risk per category. Further directions will focus on clarifying governing concepts and lexicon terminology as well as further refining risk stratification categories based on data from published validation studies.
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Affiliation(s)
- Catherine H Phillips
- Department of Radiology and Radiological Sciences, 612495Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yang Guo
- Department of Radiology, 381760Brigham and Women's Hospital, Boston, MA, USA
| | - Loretta M Strachowski
- Department of Radiology and Biomedical Imaging, Department of Obstetrics, Gynecology, and Reproductive Sciences, 192653University of California, San Francisco, CA, USA
| | - Priyanka Jha
- Department of Radiology and Biomedical Imaging, 192653University of California, San Francisco, CA, USA
| | - Caroline Reinhold
- Department of Radiology, McGill University Health Centre, 54473McGill University, Montreal, QC, Canada.,Co-Director, Augmented Intelligence Precision Health Laboratory, Research Institute of the McGill University Health Center, Montreal, Canada.,Montreal Imaging Experts Inc., Montreal, Canada
| | - Rochelle F Andreotti
- Department of Radiology and Radiological Sciences, Department of Obstetrics and Gynecology, 612495Vanderbilt University Medical Center, Nashville, TN, USA
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Wang R, Li X, Li S, Fang S, Zhao C, Yang H, Yang Z. Clinical value of O-RADS combined with serum CA125 and HE4 for the diagnosis of ovarian tumours. Acta Radiol 2023; 64:821-828. [PMID: 35291856 DOI: 10.1177/02841851221087376] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Ovarian tumors (OTs) are common gynecological tumors in women. It is very important to correctly distinguish benign and malignant OTs. PURPOSE To assess the diagnostic performance of the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) and evaluate the clinical value of O-RADS combined with serum carbohydrate antigen 125 (CA125) and human epididymis protein 4 (HE4) in differentiating benign from malignant OTs. MATERIAL AND METHODS A retrospective analysis was performed on 431 cases including pathology and clinical data. The receiver operating characteristic (ROC) curve was drawn, and sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. RESULTS In premenopausal women, O-RADS and O-RADS combined with serum CA125 and HE4 showed sensitivity at 92.2% and 94.8%, specificity at 91.8% and 93.4%, and accuracy at 91.9% and 93.8%, respectively. In postmenopausal women, the sensitivity of O-RADS, O-RADS combined with serum CA125 and HE4 was 94.8% and 95.8%, specificity was 83.9% and 93.6%, and accuracy was 90.5% and 95.6%, respectively. The sensitivity, specificity, and accuracy of O-RADS combined with CA125 and HE4 in premenopausal and postmenopausal women were higher than that of O-RADS (P<0.05). CONCLUSION O-RADS has high diagnostic performance in OTs. When O-RADS is combined with CA125 and HE4 in the diagnosis of OTs, the sensitivity and specificity are improved, which is helpful to improve the diagnostic efficiency of OTs and has high clinical application value.
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Affiliation(s)
- Rongling Wang
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Xiumei Li
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Shuqin Li
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Shibao Fang
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Cheng Zhao
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Hui Yang
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Zongli Yang
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
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Timmerman S, Valentin L, Ceusters J, Testa AC, Landolfo C, Sladkevicius P, Van Holsbeke C, Domali E, Fruscio R, Epstein E, Franchi D, Kudla MJ, Chiappa V, Alcazar JL, Leone FPG, Buonomo F, Coccia ME, Guerriero S, Deo N, Jokubkiene L, Kaijser J, Scambia G, Andreotti R, Timmerman D, Bourne T, Van Calster B, Froyman W. External Validation of the Ovarian-Adnexal Reporting and Data System (O-RADS) Lexicon and the International Ovarian Tumor Analysis 2-Step Strategy to Stratify Ovarian Tumors Into O-RADS Risk Groups. JAMA Oncol 2023; 9:225-233. [PMID: 36520422 PMCID: PMC9856950 DOI: 10.1001/jamaoncol.2022.5969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Importance Correct diagnosis of ovarian cancer results in better prognosis. Adnexal lesions can be stratified into the Ovarian-Adnexal Reporting and Data System (O-RADS) risk of malignancy categories with either the O-RADS lexicon, proposed by the American College of Radiology, or the International Ovarian Tumor Analysis (IOTA) 2-step strategy. Objective To investigate the diagnostic performance of the O-RADS lexicon and the IOTA 2-step strategy. Design, Setting, and Participants Retrospective external diagnostic validation study based on interim data of IOTA5, a prospective international multicenter cohort study, in 36 oncology referral centers or other types of centers. A total of 8519 consecutive adult patients presenting with an adnexal mass between January 1, 2012, and March 1, 2015, and treated either with surgery or conservatively were included in this diagnostic study. Twenty-five patients were excluded for withdrawal of consent, 2777 were excluded from 19 centers that did not meet predefined data quality criteria, and 812 were excluded because they were already in follow-up at recruitment. The analysis included 4905 patients with a newly detected adnexal mass in 17 centers that met predefined data quality criteria. Data were analyzed from January 31 to March 1, 2022. Exposures Stratification into O-RADS categories (malignancy risk <1%, 1% to <10%, 10% to <50%, and ≥50%). For the IOTA 2-step strategy, the stratification is based on the individual risk of malignancy calculated with the IOTA 2-step strategy. Main Outcomes and Measures Observed prevalence of malignancy in each O-RADS risk category, as well as sensitivity and specificity. The reference standard was the status of the tumor at inclusion, determined by histology or clinical and ultrasonographic follow-up for 1 year. Multiple imputation was used for uncertain outcomes owing to inconclusive follow-up information. Results Median age of the 4905 patients was 48 years (IQR, 36-62 years). Data on race and ethnicity were not collected. A total of 3441 tumors (70%) were benign, 978 (20%) were malignant, and 486 (10%) had uncertain classification. Using the O-RADS lexicon resulted in 1.1% (24 of 2196) observed prevalence of malignancy in O-RADS 2, 4% (34 of 857) in O-RADS 3, 27% (246 of 904) in O-RADS 4, and 78% (732 of 939) in O-RADS 5; the corresponding results for the IOTA 2-step strategy were 0.9% (18 of 1984), 4% (58 of 1304), 30% (206 of 690), and 82% (756 of 927). At the 10% risk threshold (O-RADS 4-5), the O-RADS lexicon had 92% sensitivity (95% CI, 87%-96%) and 80% specificity (95% CI, 74%-85%), and the IOTA 2-step strategy had 91% sensitivity (95% CI, 84%-95%) and 85% specificity (95% CI, 80%-88%). Conclusions and Relevance The findings of this external diagnostic validation study suggest that both the O-RADS lexicon and the IOTA 2-step strategy can be used to stratify patients into risk groups. However, the observed malignancy rate in O-RADS 2 was not clearly below 1%.
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Affiliation(s)
- Stefan Timmerman
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium.,Department of Obstetrics and Gynecology, University Hospital Leuven, Leuven, Belgium
| | - Lil Valentin
- Department of Obstetrics and Gynecology, Skåne University Hospital, Malmö, Sweden.,Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Jolien Ceusters
- Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium
| | - Antonia C Testa
- Dipartimento Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli, IRCSS, Rome, Italy
| | - Chiara Landolfo
- Queen Charlotte's and Chelsea Hospital, Imperial College, London, United Kingdom
| | - Povilas Sladkevicius
- Department of Obstetrics and Gynecology, Skåne University Hospital, Malmö, Sweden.,Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | | | - Ekaterini Domali
- First Department of Obstetrics and Gynecology, Alexandra Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Robert Fruscio
- Clinic of Obstetrics and Gynecology, University of Milan-Bicocca, San Gerardo Hospital, Monza, Italy
| | - Elisabeth Epstein
- Department of Clinical Science and Education, Karolinska Institutet and Department of Obstetrics and Gynecology, Södersjukhuset, Stockholm, Sweden
| | - Dorella Franchi
- Preventive Gynecology Unit, Division of Gynecology, European Institute of Oncology IRCCS, Milan, Italy
| | - Marek J Kudla
- Department of Perinatology and Oncological Gynecology, Faculty of Medical Sciences, Medical University of Silesia, Katowice, Poland
| | - Valentina Chiappa
- Department of Gynecologic Oncology, National Cancer Institute of Milan, Milan, Italy
| | - Juan L Alcazar
- Department of Obstetrics and Gynecology, Clinica Universidad de Navarra, School of Medicine, Pamplona, Spain
| | - Francesco P G Leone
- Department of Obstetrics and Gynecology, Biomedical and Clinical Sciences Institute L. Sacco, University of Milan, Milan, Italy
| | - Francesca Buonomo
- Institute for Maternal and Child Health-IRCCS "Burlo Garofolo," Trieste, Italy
| | - Maria Elisabetta Coccia
- Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence, Italy
| | - Stefano Guerriero
- Department of Obstetrics and Gynecology, University of Cagliari, Policlinico Universitario Duilio Casula, Monserrato, Cagliari, Italy
| | - Nandita Deo
- Department of Obstetrics and Gynaecology, Whipps Cross Hospital, London, United Kingdom
| | - Ligita Jokubkiene
- Department of Obstetrics and Gynecology, Skåne University Hospital, Malmö, Sweden.,Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Jeroen Kaijser
- Department of Obstetrics and Gynecology, Ikazia Hospital, Rotterdam, the Netherlands
| | - Giovanni Scambia
- Dipartimento Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli, IRCSS, Rome, Italy
| | - Rochelle Andreotti
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee.,Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Dirk Timmerman
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium.,Department of Obstetrics and Gynecology, University Hospital Leuven, Leuven, Belgium
| | - Tom Bourne
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium.,Queen Charlotte's and Chelsea Hospital, Imperial College, London, United Kingdom
| | - Ben Van Calster
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium.,Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, the Netherlands
| | - Wouter Froyman
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium.,Department of Obstetrics and Gynecology, University Hospital Leuven, Leuven, Belgium
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Wu M, Wang Q, Zhang M, Cao J, Chen Y, Zheng J, Luo L, Su M, Lin X, Kuang X, Zhang X. Does Combing O-RADS US and CA-125 Improve Diagnostic Accuracy in Assessing Adnexal Malignancy Risk in Women With Different Menopausal Status? JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2023; 42:675-685. [PMID: 35880406 DOI: 10.1002/jum.16065] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 07/03/2022] [Accepted: 07/10/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES To evaluate the individual and combined performances of the Ovarian-adnexal Reporting and Data System Ultrasound (O-RADS US) and serum cancer antigen 125 (CA-125) in assessing adnexal malignancy risk in women with different menopausal status. METHODS This retrospective study included patients with adnexal masses scheduled for surgery based on their preoperative US and histopathology results between January 2018 and January 2020. O-RADS were used to assess adnexal malignancy by two experienced radiologists. The area under the receiver operating characteristic curves (AUCs) were used to compare the accuracy of O-RADS and a combination of O-RADS and CA-125. The weighted κ index was used to evaluate the inter-reviewer agreement. RESULTS Overall, the data of 443 lesions in 443 patients were included, involving 312 benign lesions and 131 malignant lesions. There were 361 premenopausal and 82 postmenopausal patients. The inter-reviewer agreement for the two radiologists was very good (weighted κ: 0.833). Combing O-RADS US and CA-125 significantly increased diagnostic accuracy for classifying malignant from benign adnexal masses, compared with O-RADS US alone (AUC: 0.97 vs 0.95, P < .001 for premenopausal population and AUC: 0.93 vs 0.85, P < .001 for postmenopausal population). The AUCs of O-RADS with and without CA-125 ranged from 0.50 to 0.99 for different adnexal pathology subtypes (ie, benign, borderline, Stage I-IV, and metastatic tumors). CONCLUSION The addition of CA-125 helps improve discrimination of O-RADS US between benign and malignant adnexal masses, especially in postmenopausal women.
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Affiliation(s)
- Manli Wu
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Qingjuan Wang
- Department of Ultrasound, Third Hospital of Longgang, Shenzhen, Guangdong Province, China
| | - Man Zhang
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Junyan Cao
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Ying Chen
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Jian Zheng
- Department of Ultrasound, Third Hospital of Longgang, Shenzhen, Guangdong Province, China
| | - Liping Luo
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Manting Su
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Xin Lin
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Xiaohong Kuang
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Xinling Zhang
- Department of Ultrasound, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
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Wang H, Wang L, An S, Ma Q, Tu Y, Shang N, Pan Y. American college of radiology ovarian-adnexal reporting and data system ultrasound (O-RADS): Diagnostic performance and inter-reviewer agreement for ovarian masses in children. Front Pediatr 2023; 11:1091735. [PMID: 36969276 PMCID: PMC10030612 DOI: 10.3389/fped.2023.1091735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 02/20/2023] [Indexed: 03/29/2023] Open
Abstract
Objective To evaluate the diagnostic performance and inter-observer agreement of the American College of Radiology Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS) in the diagnosis of ovarian masses in children. Methods From June 2012 to December 2021, 163 ovarian masses in 159 patients with pathologic results were retrospectively analyzed. Each mass was classified into an O-RADS category according to the criteria. The diagnostic performance of O-RADS for detecting malignant ovarian masses was assessed using histopathology as the reference standard. Kappa (k) statistic was used to assess inter-observer agreement between a less-experienced and a well-experienced radiologist. Results Out of 163 ovarian masses, 18 (11.0%) were malignant and 145 (89.0%) were benign. The malignancy rates of O-RADS 5, O-RADS 4, and O-RADS 3 masses were 72.7%, 34.6%, and 4.8%, respectively. The area under the receiver operating characteristic curve was 0.944 (95% CI, 0.908-0.981). The optimal cutoff value for predicting malignant ovarian masses was > O-RADS 3 with a sensitivity, specificity, and accuracy of 94.4%, 86.2% and 86.2% respectively. The inter-observer agreement of the O-RADS category was good (k = 0.777). Conclusions O-RADS has a high diagnostic performance for children with ovarian masses. It provides an effective malignant risk classification for ovarian masses in children, which shows high consistency between radiologists with different levels of experience.
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Surgical outcomes of adnexal masses classified by IOTA ultrasound simple rules. Sci Rep 2022; 12:21848. [PMID: 36528698 PMCID: PMC9759574 DOI: 10.1038/s41598-022-26441-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 12/14/2022] [Indexed: 12/23/2022] Open
Abstract
IOTA (International Ovarian Tumor Analysis) Simple Rules classifies adnexal masses as benign, malignant, or indeterminate based on sonographic features. We seek to determine if IOTA inappropriately directed women to surgery, or more aggressive surgery, than their final diagnosis warranted. This is a retrospective study of sonographically detected adnexal masses with known clinical outcomes from two institutions (n = 528). Surgically managed patients (n = 172) were categorized based on pathology and compared using Chi-square and t-test for categorical and continuous variables respectively. A logistic regression was used to predict characteristics that predicted surgery or imaging follow up of indeterminate masses. Of the 528 masses imaged, 29% (n = 155) underwent surgery for benign pathology. Only 1.9% (n = 10) underwent surgery after classification as malignant by IOTA for what was ultimately a benign mass. Surgical complications occurred in 10 cases (5.8%), all benign. Fifteen (3.2%) patients went into surgically induced menopause for benign masses, one of which was inaccurately classified by IOTA as malignant. Of the 41 IOTA indeterminate masses, the presence of soft tissue nodules on ultrasound was the only statistically significant predictor of the patient being triaged directly to surgery (OR 1.79, p = 0.04). Our findings support that the IOTA ultrasound classification system can provide clinical guidance without incurring unnecessary surgeries or surgical complications.
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IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study. Cancers (Basel) 2022; 14:cancers14225631. [PMID: 36428723 PMCID: PMC9688181 DOI: 10.3390/cancers14225631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/23/2022] [Accepted: 10/28/2022] [Indexed: 11/18/2022] Open
Abstract
Objectives: We were the first to combine IETA ultrasonic features with GI-RADS and tumor biomarkers for the surveillance of endometrial carcinoma. The aim was to evaluate the efficacy of single IETA ultrasonography GI-RADS classification and combined tumor biomarkers in differentiating benign and malignant lesions in the uterine cavity and endometrium. Methods: A total of 497 patients with intrauterine and endometrial lesions who had been treated surgically between January 2017 and December 2021 were enrolled; all of them had undergone ultrasound examinations before surgery. We analyzed the correlation between the terms of ultrasonic signs of the uterine cavity and endometrial lesions defined by the expert consensus of IETA and the benign and malignant lesions and then classified these ultrasonic signs by GI-RADS. In addition, the tumor biomarkers CA125, CA15-3, CA19-9 and HE4 were combined by adjusting the classification. The results of the comprehensive analysis were compared with pathological results to analyze their diagnostic efficacy. Results: (1) The statistic analysis confirmed that there were seven independent predictors of malignant lesions, including thickened endometrium (premenopause ≥ 18.5 mm, postmenopause ≥ 15.5 mm), non-uniform endometrial echogenicity (heterogeneous with irregular cysts), endometrial midline appearance (not defined), the endometrial-myometrial junction (interrupted or not defined), intracavitary fluid (ground glass or "mixed" echogenicity), color score (3~4 points) and vascular pattern (focal origin multiple vessels or multifocal origin multiple vessels). (2) In traditional ultrasound GI-RADS (U-T-GI-RADS), if category 4a was taken as the cut-off value of benign and malignant, the diagnostic sensitivity, specificity, PPV, NPV and diagnostic accuracy were 97.2%, 65.2%, 44.0%, 98.8% and 72.2%, respectively, and the area under the ROC curve (AUC) was 0.812. If 4b was taken as the cut-off value, the diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 88.1%, 92.0%, 75.6%, 96.5% and 91.2%, 0.900, respectively. The diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 75.2%, 98.5%, 93.2%, 93.4%, 93.4% and 0.868, respectively, when taking category 5 as the cutoff point. In modified ultrasound GI-RADS (U-M-GI-RADS), if 4a was taken as the cut-off value, The diagnostic efficacy was the same as U-T-GI-RADS. If 4b was taken as the cut-off value, the diagnostic sensitivity, specificity, PPV, NPV, diagnostic accuracy and AUC were 88.1%, 92.3%, 76.2%, 96.5%, 91.3% and 0.902, respectively. If 4c was taken as the cutoff point, the diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 75.2%, 98.7%, 94.3%, 93.4%, 93.6% and 0.870, respectively. The diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 66.1%, 99.7%, 98.6%, 91.3%, 92.4% and 0.829, respectively, if taking category 5 as the cutoff point. (3) In the comprehensive diagnostic method of U-T-GI-RADS combined tumor biomarkers results, the AUC of class 4a, 4b and 5 as the cutoff value was 0.877, 0.888 and 0.738, respectively. The AUC of class 4a, 4b, 4c and 5 as the cutoff value in the comprehensive diagnostic method of U-M-GI-RADS combined tumor biomarkers results was 0.877, 0.888, 0.851 and 0.725, respectively. There was no significant difference in diagnostic efficiency between the two comprehensive diagnostic methods. Conclusions: In this study, no matter which diagnostic method was used, the best cutoff value for predicting malignant EC was ≥GI-RADS 4b. The GI-RADS classification had good performance in discriminating EC. The tumor biomarkers, CA125, CA19-9, CA15-3 and HE4, could improve the diagnostic efficacy for preoperative endometrial carcinoma assessment.
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Chen GY, Hsu TF, Chan IS, Liu CH, Chao WT, Shih YC, Jiang LY, Chang YH, Wang PH, Chen YJ. Comparison of the O-RADS and ADNEX models regarding malignancy rate and validity in evaluating adnexal lesions. Eur Radiol 2022; 32:7854-7864. [PMID: 35583711 DOI: 10.1007/s00330-022-08803-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 04/10/2022] [Accepted: 04/13/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVE This study aimed to compare the ability of the O-RADS and ADNEX models to classify benign or malignant adnexal lesions. METHODS This retrospective single-center study included women who underwent surgery for adnexal lesions. Two gynecologists independently categorized the adnexal lesions according to the O-RADS and ADNEX models. Four additional readers were included to validate the new quick-access O-RADS flowchart. RESULTS Among the 322 patients included in this study, 264 (82.0%) had a benign diagnosis, and 58 (18.0%) had a malignant diagnosis. The malignant rates of O-RADS 2, O-RADS 3, O-RADS 4, and O-RADS 5 were 0%, 3.0%, 37.7%, and 78.9%, respectively. The AUC of the O-RADS in the 322 patients was 0.93. On comparing the O-RADS and ADNEX models in the remaining 281 patients, the AUCs of the O-RADS, ADNEX model with CA125, and ADNEX model without CA125 were 0.92, 0.95, and 0.94, respectively. When setting a uniform cutoff of ≥ 10% (≥ O-RADS 4) to predict malignancy, the O-RADS had higher sensitivity than the ADNEX model (96.6% vs. 91.4%), and relatively similar specificity. In addition, the readers with the quick-access flowchart spent less time categorizing O-RADS than the readers with only the original O-RADS table (mean analysis time: 99 min 15 s vs. 111 min 55 s). CONCLUSIONS The O-RADS classification of the adnexal lesions as benign or malignant was comparable to that of the ADNEX model and had higher sensitivity at the 10% cutoff value. A quick-access O-RADS flowchart was helpful in O-RADS categorization and might shorten the analysis time. KEY POINTS • Both O-RADS and ADNEX models had good diagnostic performance in distinguishing adnexal malignancy, and O-RADS had higher sensitivity than ADNEX model in uniform 10% cutoff to predict malignancy. • Quick-access O-RADS flowchart was developed to help review O-RADS classification and might help reduce the analysis time.
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Affiliation(s)
- Guan-Yeu Chen
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Obstetrics and Gynecology, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Teh-Fu Hsu
- Department of Emergency Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,College of Nursing, National Yang Ming Chiao Tung University, Taipei, Taiwan.,School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - I-San Chan
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Obstetrics and Gynecology, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chia-Hao Liu
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Obstetrics and Gynecology, National Yang Ming Chiao Tung University, Taipei, Taiwan.,School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Wei-Ting Chao
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Obstetrics and Gynecology, National Yang Ming Chiao Tung University, Taipei, Taiwan.,School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ying-Chu Shih
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Obstetrics and Gynecology, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ling-Yu Jiang
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Obstetrics and Gynecology, National Yang Ming Chiao Tung University, Taipei, Taiwan.,School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yen-Hou Chang
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Obstetrics and Gynecology, National Yang Ming Chiao Tung University, Taipei, Taiwan.,School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Peng-Hui Wang
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Obstetrics and Gynecology, National Yang Ming Chiao Tung University, Taipei, Taiwan.,School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Department of Medical Research, China Medical University Hospital, Taichung, Taiwan.,The Female Cancer Foundation, Taipei, Taiwan
| | - Yi-Jen Chen
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan. .,Department of Obstetrics and Gynecology, National Yang Ming Chiao Tung University, Taipei, Taiwan. .,School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan. .,Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
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Application of O-RADS Ultrasound Lexicon-Based Logistic Regression Analysis Model in the Diagnosis of Solid Component-Containing Ovarian Malignancies. BIOMED RESEARCH INTERNATIONAL 2022; 2022:7187334. [PMID: 36330455 PMCID: PMC9626203 DOI: 10.1155/2022/7187334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 10/11/2022] [Indexed: 12/02/2022]
Abstract
Objective To use the logistic regression model to evaluate the value of ultrasound characteristics in the Ovarian-Adnexal Reporting and Data System ultrasound lexicon in determining ovarian solid component-containing mass benignancy/malignancy. Methods We retrospectively analyzed the data of 172 patients with adnexal masses discovered by ultrasound, and diagnosis was confirmed by postoperative pathological tests from January 2019 to December 2021. Thirteen ovarian tumor-related parameters in the benign and malignant ovarian tumor groups were selected for univariate analyses. Statistically significant parameters were included in multivariate logistic regression analyses to construct a logistic regression diagnosis model, and the diagnostic performance of the model in predicting ovarian malignancies was calculated. Results Of the 172 adnexal tumors, 104 were benign, and 68 were malignant. There were differences in cancer antigen 125, maximum mass diameter, maximum solid component diameter, multilocular cyst with solid component, external contour, whether acoustic shadows were present in the solid component, number of papillae, vascularity, presence/absence of ascites, and presence/absence of peritoneal thickening or nodules between the benign ovarian tumor and malignancy groups (p < 0.05). Logistic regression analyses showed that maximum solid component diameter, whether acoustic shadows were present in the solid component, number of papillae, and presence/absence of ascites were included in the logistic regression model, and the area under the receiver operating characteristic curve for this regression model in predicting ovarian malignancy was 0.962 (95% confidence interval: 0.933~0.990; p < 0.001). Logit (p) ≥ −0.02 was used as the cutoff value, and the prediction accuracy, sensitivity, specificity, positive predictive value, and negative predictive values were 93.6%, 86.8%, 98.1%, 96.7%, and 91.9%, respectively. Conclusion The logistic regression model containing the maximum solid component diameter, whether acoustic shadows were present in the solid component, number of papillae, and presence/absence of ascites can help in determining the benignancy/malignancy of solid component-containing masses.
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Katlariwala P, Wilson MP, Pi Y, Chahal BS, Croutze R, Patel D, Patel V, Low G. Reliability of ultrasound ovarian-adnexal reporting and data system amongst less experienced readers before and after training. World J Radiol 2022; 14:319-328. [PMID: 36186517 PMCID: PMC9521430 DOI: 10.4329/wjr.v14.i9.319] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 06/14/2022] [Accepted: 09/14/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND The 2018 ovarian-adnexal reporting and data system (O-RADS) guidelines are aimed at providing a system for consistent reports and risk stratification for ovarian lesions found on ultrasound. It provides key characteristics and findings for lesions, a lexicon of descriptors to communicate findings, and risk characterization and associated follow-up recommendation guidelines. However, the O-RADS guidelines have not been validated in North American institutions or amongst less experienced readers.
AIM To evaluate the diagnostic accuracy and inter-reader reliability of ultrasound O-RADS risk stratification amongst less experienced readers in a North American institution with and without pre-test training.
METHODS A single-center retrospective study was performed using 100 ovarian/adnexal lesions of varying O-RADS scores. Of these cases, 50 were allotted to a training cohort and 50 to a testing cohort via a non-randomized group selection process in order to approximately equal distribution of O-RADS categories both within and between groups. Reference standard O-RADS scores were established through consensus of three fellowship-trained body imaging radiologists. Three PGY-4 residents were independently evaluated for diagnostic accuracy and inter-reader reliability with and without pre-test O-RADS training. Sensitivity, specificity, positive predictive value, negative predictive value (NPV), and area under the curve (AUC) were used to measure accuracy. Fleiss kappa and weighted quadratic (pairwise) kappa values were used to measure inter-reader reliability. Statistical significance was P < 0.05.
RESULTS Mean patient age was 40 ± 16 years with lesions ranging from 1.2 to 22.5 cm. Readers demonstrated excellent specificities (85%-100% pre-training and 91%-100% post-training) and NPVs (89%-100% pre-training and 91-100% post-training) across the O-RADS categories. Sensitivities were variable (55%-100% pre-training and 64%-100% post-training) with malignant O-RADS 4 and 5 Lesions pre-training and post-training AUC values of 0.87-0.95 and 0.94-098, respectively (P < 0.001). Nineteen of 22 (86%) misclassified cases in pre-training were related to mischaracterization of dermoid features or wall/septation morphology. Fifteen of 17 (88%) of post-training misclassified cases were related to one of these two errors. Fleiss kappa inter-reader reliability was ‘good’ and pairwise inter-reader reliability was ‘very good’ with pre-training and post-training assessment (k = 0.76 and 0.77; and k = 0.77-0.87 and 0.85-0.89, respectively).
CONCLUSION Less experienced readers in North America achieved excellent specificities and AUC values with very good pairwise inter-reader reliability. They may be subject to misclassification of potentially malignant lesions, and specific training around dermoid features and smooth vs irregular inner wall/septation morphology may improve sensitivity.
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Affiliation(s)
- Prayash Katlariwala
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton T6G 2B7, AB, Canada
| | - Mitchell P Wilson
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton T6G 2B7, AB, Canada
| | - Yeli Pi
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton T6G 2B7, AB, Canada
| | - Baljot S Chahal
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton T6G 2B7, AB, Canada
| | - Roger Croutze
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton T6G 2B7, AB, Canada
| | - Deelan Patel
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton T6G 2B7, AB, Canada
| | - Vimal Patel
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton T6G 2B7, AB, Canada
| | - Gavin Low
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton T6G 2B7, AB, Canada
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Antil N, Raghu PR, Shen L, Tiyarattanachai T, Chang EM, Ferguson CWK, Ho AA, Lutz AM, Mariano AJ, Morimoto LN, Kamaya A. Interobserver agreement between eight observers using IOTA simple rules and O-RADS lexicon descriptors for adnexal masses. Abdom Radiol (NY) 2022; 47:3318-3326. [PMID: 35763052 PMCID: PMC9388428 DOI: 10.1007/s00261-022-03580-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 06/04/2022] [Accepted: 06/06/2022] [Indexed: 01/18/2023]
Abstract
PURPOSE To evaluate interobserver agreement in assigning imaging features and classifying adnexal masses using the IOTA simple rules versus O-RADS lexicon and identify causes of discrepancy. METHODS Pelvic ultrasound (US) examinations in 114 women with 118 adnexal masses were evaluated by eight radiologists blinded to the final diagnosis (4 attendings and 4 fellows) using IOTA simple rules and O-RADS lexicon. Each feature category was analyzed for interobserver agreement using intraclass correlation coefficient (ICC) for ordinal variables and free marginal kappa for nominal variables. The two-tailed significance level (a) was set at 0.05. RESULTS For IOTA simple rules, interobserver agreement was almost perfect for three malignant lesion categories (M2-4) and substantial for the remaining two (M1, M5) with k-values of 0.80-0.82 and 0.68-0.69, respectively. Interobserver agreement was almost perfect for two benign feature categories (B2, B3), substantial for two (B4, B5) and moderate for one (B1) with k-values of 0.81-0.90, 0.69-0.70 and 0.60, respectively. For O-RADS, interobserver agreement was almost perfect for two out of ten feature categories (ascites and peritoneal nodules) with k-values of 0.89 and 0.97. Interobserver agreement ranged from fair to substantial for the remaining eight feature categories with k-values of 0.39-0.61. Fellows and attendings had ICC values of 0.725 and 0.517, respectively. CONCLUSION O-RADS had variable interobserver agreement with overall good agreement. IOTA simple rules had more uniform interobserver agreement with overall excellent agreement. Greater reader experience did not improve interobserver agreement with O-RADS.
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Affiliation(s)
- Neha Antil
- Department of Radiology, Stanford Hospital and Clinics, Stanford, CA, USA
| | - Preethi R Raghu
- Department of Radiology, University of CA - San Francisco, San Francisco, CA, USA.
| | - Luyao Shen
- Department of Radiology, Stanford Hospital and Clinics, Stanford, CA, USA
| | | | - Edwina M Chang
- Department of Radiology, Santa Clara Valley Medical Center, San Jose, CA, USA
| | - Craig W K Ferguson
- Department of Radiology, University of Alberta Hostpial, Edmonton, Alberta, Canada
| | - Amanzo A Ho
- Department of Radiology, Stanford Hospital and Clinics, Stanford, CA, USA
| | - Amelie M Lutz
- Department of Radiology, Stanford Hospital and Clinics, Stanford, CA, USA
| | - Aladin J Mariano
- Department of Radiology, Stanford Hospital and Clinics, Stanford, CA, USA
| | - L Nayeli Morimoto
- Department of Radiology, Stanford Hospital and Clinics, Stanford, CA, USA
| | - Aya Kamaya
- Department of Radiology, Stanford Hospital and Clinics, Stanford, CA, USA
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Guo Y, Phillips CH, Suarez-Weiss K, Roller LA, Frates MC, Benson CB, Shinagare AB. Interreader Agreement and Intermodality Concordance of O-RADS US and MRI for Assessing Large, Complex Ovarian-Adnexal Cysts. Radiol Imaging Cancer 2022; 4:e220064. [PMID: 36178350 PMCID: PMC9530774 DOI: 10.1148/rycan.220064] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/27/2023]
Abstract
Purpose To assess interreader agreement of the Ovarian-Adnexal Reporting and Data System (O-RADS) and intermodality concordance between US and MRI for characterizing complex adnexal cysts measuring 5 cm or larger. Materials and Methods This retrospective study included 58 "complex cysts" measuring at least 5 cm in size observed at both US and MRI in 54 women (median age, 37 years ± 12 [SD]; seven postmenopausal women) between July 2017 and June 2020, identified from an electronic US database. A separate set of two blinded radiologists independently reviewed the US or MR images to assign the O-RADS category, and an adjudicator resolved discrepancies (a total of six readers). Lesion outcome (49 benign, eight malignant, one lost to follow-up) was recorded. Interreader agreement of O-RADS US and O-RADS MRI and concordance between US and MRI were analyzed. Results Interreader agreement was fair for US (κ = 0.31), moderate for MRI (κ = 0.43), and moderate between US and MRI (κ = 0.58). A significant positive correlation was found between O-RADS US and MRI (τ = 0.72, P < .001). The O-RADS 4 threshold yielded the highest accuracy for both US and MRI (area under the receiver operating characteristic curve = 0.92 and 0.995, respectively). Considering O-RADS US 4 or 5 as potentially malignant and 1-3 as benign, eight lesions that were assessed as potentially malignant at US were correctly downgraded to benign by using findings at MRI. Using findings at MRI, one malignant lesion that was assessed as benign at US was upgraded to potentially malignant. Conclusion O-RADS US and MRI had excellent performance and positive correlation, but significant interobserver variability remains. Keywords: Ovary, MR Imaging, Ultrasonography © RSNA, 2022 See also the commentary by Baumgarten in this issue.
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Baumgarten DA. O-RADS: Good Enough for Everyday Practice or a Work in Progress? Radiol Imaging Cancer 2022; 4:e220121. [PMID: 36178353 PMCID: PMC9530757 DOI: 10.1148/rycan.220121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 09/14/2022] [Accepted: 09/15/2022] [Indexed: 06/16/2023]
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Vara J, Manzour N, Chacón E, López-Picazo A, Linares M, Pascual MÁ, Guerriero S, Alcázar JL. Ovarian Adnexal Reporting Data System (O-RADS) for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis. Cancers (Basel) 2022; 14:cancers14133151. [PMID: 35804924 PMCID: PMC9264796 DOI: 10.3390/cancers14133151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 06/22/2022] [Accepted: 06/22/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary We performed a systematic review and meta-analysis aiming to assess the diagnostic performance of the Ovarian Adnexal Report Data System (O-RADS) using transvaginal ultrasound for classifying adnexal masses. Data from 11 studies comprising 4634 masses showed that the pooled estimated sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of O-RADS system for classifying adnexal masses were 97% (95% confidence interval (CI) = 94%–98%), 77% (95% CI = 68%–84%), 4.2 (95% CI= 2.9–6.0), 0.04 (95% CI = 0.03–0.07), and 96 (95% CI = 50–185), respectively. We concluded that the O-RADS system has good sensitivity and moderate specificity for classifying adnexal masses. Abstract In this systematic review and meta-analysis, we aimed to assess the pooled diagnostic performance of the so-called Ovarian Adnexal Report Data System (O-RADS) for classifying adnexal masses using transvaginal ultrasound, a classification system that was introduced in 2020. We performed a search for studies reporting the use of the O-RADS system for classifying adnexal masses from January 2020 to April 2022 in several databases (Medline (PubMed), Google Scholar, Scopus, Cochrane, and Web of Science). We selected prospective and retrospective cohort studies using the O-RADS system for classifying adnexal masses with histologic diagnosis or conservative management demonstrating spontaneous resolution or persistence in cases of benign appearing masses after follow-up scan as the reference standard. We excluded studies not related to the topic under review, studies not addressing O-RADS classification, studies addressing MRI O-RADS classification, letters to the editor, commentaries, narrative reviews, consensus documents, and studies where data were not available for constructing a 2 × 2 table. The pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio (DOR) were calculated. The quality of the studies was evaluated using QUADAS-2. A total of 502 citations were identified. Ultimately, 11 studies comprising 4634 masses were included. The mean prevalence of ovarian malignancy was 32%. The risk of bias was high in eight studies for the “patient selection” domain. The risk of bias was low for the “index test” and “reference test” domains for all studies. Overall, the pooled estimated sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and DOR of the O-RADS system for classifying adnexal masses were 97% (95% confidence interval (CI) = 94%–98%), 77% (95% CI = 68%–84%), 4.2 (95% CI = 2.9–6.0), 0.04 (95% CI = 0.03–0.07), and 96 (95% CI = 50–185), respectively. Heterogeneity was moderate for sensitivity and high for specificity. In conclusion, the O-RADS system has good sensitivity and moderate specificity for classifying adnexal masses.
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Affiliation(s)
- Julio Vara
- Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, 31008 Pamplona, Spain; (J.V.); (N.M.); (E.C.); (A.L.-P.)
| | - Nabil Manzour
- Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, 31008 Pamplona, Spain; (J.V.); (N.M.); (E.C.); (A.L.-P.)
| | - Enrique Chacón
- Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, 31008 Pamplona, Spain; (J.V.); (N.M.); (E.C.); (A.L.-P.)
| | - Ana López-Picazo
- Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, 31008 Pamplona, Spain; (J.V.); (N.M.); (E.C.); (A.L.-P.)
| | - Marta Linares
- Department of Obstetrics and Gynecology, Universitiy Hospital Puerta del Mar, 11009 Cadiz, Spain;
| | - Maria Ángela Pascual
- Department of Obstetrics, Gynecology, and Reproduction, Hospital Universitari Dexeus, 08028 Barcelona, Spain;
| | - Stefano Guerriero
- Department of Obstetrics and Gynecology, University of Cagliari, Policlinico Universitario Duilio Casula, 09042 Monserrato, Cagliari, Italy;
| | - Juan Luis Alcázar
- Department of Obstetrics and Gynecology, Clínica Universidad de Navarra, 31008 Pamplona, Spain; (J.V.); (N.M.); (E.C.); (A.L.-P.)
- Correspondence: ; Tel.: +34-948-296234; Fax: +34-948296500
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Lai HW, Lyu GR, Kang Z, Li LY, Zhang Y, Huang YJ. Comparison of O-RADS, GI-RADS, and ADNEX for Diagnosis of Adnexal Masses: An External Validation Study Conducted by Junior Sonologists. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2022; 41:1497-1507. [PMID: 34549454 DOI: 10.1002/jum.15834] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 08/09/2021] [Accepted: 08/15/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVE To externally validate the Ovarian-adnexal Reporting and Data System (O-RADS) and evaluate its performance in differentiating benign from malignant adnexal masses (AMs) compared with the Gynecologic Imaging Reporting and Data System (GI-RADS) and Assessment of Different NEoplasias in the adneXa (ADNEX). METHODS A retrospective analysis was performed on 734 cases from the Second Affiliated Hospital of Fujian Medical University. All patients underwent transvaginal or transabdominal ultrasound examination. Pathological diagnoses were obtained for all the included AMs. O-RADS, GI-RADS, and ADNEX were used to evaluate AMs by two sonologists, and the diagnostic efficacy of the three systems was analyzed and compared using pathology as the gold standard. We used the kappa index to evaluate the inter-reviewer agreement (IRA). RESULTS A total of 734 AMs, including 564 benign masses, 69 borderline masses, and 101 malignant masses were included in this study. O-RADS (0.88) and GI-RADS (0.90) had lower sensitivity than ADNEX (0.95) (P < .05), and the PPV of O-RADS (0.98) was higher than that of ADNEX (0.96) (P < .05). These three systems showed good IRA. CONCLUSION O-RADS, GI-RADS, and ADNEX showed little difference in diagnostic performance among resident sonologists. These three systems have their own characteristics and can be selected according to the type of center, access to patients' clinical data, or personal comfort.
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Affiliation(s)
- Hong-Wei Lai
- Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Guo-Rong Lyu
- Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
- Quanzhou Medical College, Quanzhou, China
| | - Zhuo Kang
- Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Li-Ya Li
- Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Ying Zhang
- Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Yi-Jun Huang
- Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
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Hack K, Gandhi N, Bouchard-Fortier G, Chawla TP, Ferguson SE, Li S, Kahn D, Tyrrell PN, Glanc P. External Validation of O-RADS US Risk Stratification and Management System. Radiology 2022; 304:114-120. [PMID: 35438559 DOI: 10.1148/radiol.211868] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Background The Ovarian-Adnexal Reporting and Data System (O-RADS) US risk stratification and management system (O-RADS US) was designed to improve risk assessment and management of ovarian and adnexal lesions. Validation studies including both surgical and nonsurgical treatment as the reference standard remain lacking. Purpose To externally validate O-RADS US in women who underwent either surgical or nonsurgical treatment and to determine if incorporating acoustic shadowing as a benign finding improves diagnostic performance. Materials and Methods This retrospective study included consecutive women who underwent pelvic US between August 2015 and April 2017 at a tertiary referral oncology center. Two independent readers blinded to clinical and histologic outcome assigned an O-RADS risk category and an International Ovarian Tumor Analysis (IOTA) Assessment of Different NEoplasias in the adneXa (ADNEX) model risk of malignancy score to assessable lesions. Reference standards were surgical histopathology or 2-year imaging follow-up. Receiver operating characteristic (ROC) curve analysis was used to evaluate performance of the O-RADS US, ADNEX, and modified O-RADS models incorporating acoustic shadowing. Results In total, 227 women (mean age, 52 years ± 16 [SD]) with 262 ovarian or adnexal lesions were evaluated. Of these lesions, 187 (71%) were benign and 75 (29%) were malignant. The proportion of malignancy was 0% (0 of 100) for O-RADS 2, 3% (one of 32) for O-RADS 3, 35% (22 of 63) for O-RADS 4, and 78% (52 of 67) for O-RADS 5. The area under the ROC curve (AUC) for O-RADS and ADNEX was 0.91 (95% CI: 0.88, 0.94) and 0.95 (95% CI: 0.92, 0.97; P = .01), respectively. The addition of acoustic shadowing as a benign finding improved O-RADS AUC to 0.94 (95% CI: 0.91, 0.96; P = .01). Use of O-RADS 4 as a threshold yielded a sensitivity of 99% (74 of 75; 95% CI: 96, 100) and a specificity of 70% (131 of 187; 95% CI: 64, 77). Conclusion In a tertiary referral oncology center, the Ovarian-Adnexal Reporting and Data System US risk stratification and management system enabled accurate distinction of benign from malignant ovarian and adnexal lesions. Adding acoustic shadowing as a benign finding improved its diagnostic performance. © RSNA, 2022 See also the editorial by Levine in this issue.
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Affiliation(s)
- Kalesha Hack
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, MG-130c, Toronto, ON, Canada M4N 3M5 (K.H.); Department of Medical Imaging, Peterborough Regional Health Centre, Peterborough, ON, Canada (N.G.); Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Toronto, Princess Margaret Cancer Centre/University Health Network and Sinai Health System, Toronto, ON, Canada (G.B.F.); Department of Medical Imaging, University of Toronto, Division of Abdominal Imaging, Joint Department of Medical Imaging, Toronto, ON, Canada (T.P.C.); Department of Obstetrics and Gynecology, University of Toronto, Ontario Health-Cancer Care Ontario, Division of Gynecologic Oncology, University Health Network and Sinai Health System, Toronto, ON, Canada (S.E.F.); Department of Medical Imaging and Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada (S.L.); Department of Business Administration, Wilfrid Laurier University, Waterloo, ON, Canada (D.K.); Department of Medical Imaging, Department of Statistical Sciences, and Institute of Medical Science, University of Toronto, Toronto, ON, Canada (P.N.T.); and Department of Obstetrics and Gynecology, University of Toronto, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Department of Medical Imaging, Body Division, Toronto, ON, Canada (P.G.)
| | - Niket Gandhi
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, MG-130c, Toronto, ON, Canada M4N 3M5 (K.H.); Department of Medical Imaging, Peterborough Regional Health Centre, Peterborough, ON, Canada (N.G.); Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Toronto, Princess Margaret Cancer Centre/University Health Network and Sinai Health System, Toronto, ON, Canada (G.B.F.); Department of Medical Imaging, University of Toronto, Division of Abdominal Imaging, Joint Department of Medical Imaging, Toronto, ON, Canada (T.P.C.); Department of Obstetrics and Gynecology, University of Toronto, Ontario Health-Cancer Care Ontario, Division of Gynecologic Oncology, University Health Network and Sinai Health System, Toronto, ON, Canada (S.E.F.); Department of Medical Imaging and Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada (S.L.); Department of Business Administration, Wilfrid Laurier University, Waterloo, ON, Canada (D.K.); Department of Medical Imaging, Department of Statistical Sciences, and Institute of Medical Science, University of Toronto, Toronto, ON, Canada (P.N.T.); and Department of Obstetrics and Gynecology, University of Toronto, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Department of Medical Imaging, Body Division, Toronto, ON, Canada (P.G.)
| | - Genevieve Bouchard-Fortier
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, MG-130c, Toronto, ON, Canada M4N 3M5 (K.H.); Department of Medical Imaging, Peterborough Regional Health Centre, Peterborough, ON, Canada (N.G.); Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Toronto, Princess Margaret Cancer Centre/University Health Network and Sinai Health System, Toronto, ON, Canada (G.B.F.); Department of Medical Imaging, University of Toronto, Division of Abdominal Imaging, Joint Department of Medical Imaging, Toronto, ON, Canada (T.P.C.); Department of Obstetrics and Gynecology, University of Toronto, Ontario Health-Cancer Care Ontario, Division of Gynecologic Oncology, University Health Network and Sinai Health System, Toronto, ON, Canada (S.E.F.); Department of Medical Imaging and Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada (S.L.); Department of Business Administration, Wilfrid Laurier University, Waterloo, ON, Canada (D.K.); Department of Medical Imaging, Department of Statistical Sciences, and Institute of Medical Science, University of Toronto, Toronto, ON, Canada (P.N.T.); and Department of Obstetrics and Gynecology, University of Toronto, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Department of Medical Imaging, Body Division, Toronto, ON, Canada (P.G.)
| | - Tanya P Chawla
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, MG-130c, Toronto, ON, Canada M4N 3M5 (K.H.); Department of Medical Imaging, Peterborough Regional Health Centre, Peterborough, ON, Canada (N.G.); Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Toronto, Princess Margaret Cancer Centre/University Health Network and Sinai Health System, Toronto, ON, Canada (G.B.F.); Department of Medical Imaging, University of Toronto, Division of Abdominal Imaging, Joint Department of Medical Imaging, Toronto, ON, Canada (T.P.C.); Department of Obstetrics and Gynecology, University of Toronto, Ontario Health-Cancer Care Ontario, Division of Gynecologic Oncology, University Health Network and Sinai Health System, Toronto, ON, Canada (S.E.F.); Department of Medical Imaging and Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada (S.L.); Department of Business Administration, Wilfrid Laurier University, Waterloo, ON, Canada (D.K.); Department of Medical Imaging, Department of Statistical Sciences, and Institute of Medical Science, University of Toronto, Toronto, ON, Canada (P.N.T.); and Department of Obstetrics and Gynecology, University of Toronto, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Department of Medical Imaging, Body Division, Toronto, ON, Canada (P.G.)
| | - Sarah E Ferguson
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, MG-130c, Toronto, ON, Canada M4N 3M5 (K.H.); Department of Medical Imaging, Peterborough Regional Health Centre, Peterborough, ON, Canada (N.G.); Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Toronto, Princess Margaret Cancer Centre/University Health Network and Sinai Health System, Toronto, ON, Canada (G.B.F.); Department of Medical Imaging, University of Toronto, Division of Abdominal Imaging, Joint Department of Medical Imaging, Toronto, ON, Canada (T.P.C.); Department of Obstetrics and Gynecology, University of Toronto, Ontario Health-Cancer Care Ontario, Division of Gynecologic Oncology, University Health Network and Sinai Health System, Toronto, ON, Canada (S.E.F.); Department of Medical Imaging and Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada (S.L.); Department of Business Administration, Wilfrid Laurier University, Waterloo, ON, Canada (D.K.); Department of Medical Imaging, Department of Statistical Sciences, and Institute of Medical Science, University of Toronto, Toronto, ON, Canada (P.N.T.); and Department of Obstetrics and Gynecology, University of Toronto, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Department of Medical Imaging, Body Division, Toronto, ON, Canada (P.G.)
| | - Siying Li
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, MG-130c, Toronto, ON, Canada M4N 3M5 (K.H.); Department of Medical Imaging, Peterborough Regional Health Centre, Peterborough, ON, Canada (N.G.); Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Toronto, Princess Margaret Cancer Centre/University Health Network and Sinai Health System, Toronto, ON, Canada (G.B.F.); Department of Medical Imaging, University of Toronto, Division of Abdominal Imaging, Joint Department of Medical Imaging, Toronto, ON, Canada (T.P.C.); Department of Obstetrics and Gynecology, University of Toronto, Ontario Health-Cancer Care Ontario, Division of Gynecologic Oncology, University Health Network and Sinai Health System, Toronto, ON, Canada (S.E.F.); Department of Medical Imaging and Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada (S.L.); Department of Business Administration, Wilfrid Laurier University, Waterloo, ON, Canada (D.K.); Department of Medical Imaging, Department of Statistical Sciences, and Institute of Medical Science, University of Toronto, Toronto, ON, Canada (P.N.T.); and Department of Obstetrics and Gynecology, University of Toronto, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Department of Medical Imaging, Body Division, Toronto, ON, Canada (P.G.)
| | - Daniel Kahn
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, MG-130c, Toronto, ON, Canada M4N 3M5 (K.H.); Department of Medical Imaging, Peterborough Regional Health Centre, Peterborough, ON, Canada (N.G.); Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Toronto, Princess Margaret Cancer Centre/University Health Network and Sinai Health System, Toronto, ON, Canada (G.B.F.); Department of Medical Imaging, University of Toronto, Division of Abdominal Imaging, Joint Department of Medical Imaging, Toronto, ON, Canada (T.P.C.); Department of Obstetrics and Gynecology, University of Toronto, Ontario Health-Cancer Care Ontario, Division of Gynecologic Oncology, University Health Network and Sinai Health System, Toronto, ON, Canada (S.E.F.); Department of Medical Imaging and Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada (S.L.); Department of Business Administration, Wilfrid Laurier University, Waterloo, ON, Canada (D.K.); Department of Medical Imaging, Department of Statistical Sciences, and Institute of Medical Science, University of Toronto, Toronto, ON, Canada (P.N.T.); and Department of Obstetrics and Gynecology, University of Toronto, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Department of Medical Imaging, Body Division, Toronto, ON, Canada (P.G.)
| | - Pascal N Tyrrell
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, MG-130c, Toronto, ON, Canada M4N 3M5 (K.H.); Department of Medical Imaging, Peterborough Regional Health Centre, Peterborough, ON, Canada (N.G.); Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Toronto, Princess Margaret Cancer Centre/University Health Network and Sinai Health System, Toronto, ON, Canada (G.B.F.); Department of Medical Imaging, University of Toronto, Division of Abdominal Imaging, Joint Department of Medical Imaging, Toronto, ON, Canada (T.P.C.); Department of Obstetrics and Gynecology, University of Toronto, Ontario Health-Cancer Care Ontario, Division of Gynecologic Oncology, University Health Network and Sinai Health System, Toronto, ON, Canada (S.E.F.); Department of Medical Imaging and Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada (S.L.); Department of Business Administration, Wilfrid Laurier University, Waterloo, ON, Canada (D.K.); Department of Medical Imaging, Department of Statistical Sciences, and Institute of Medical Science, University of Toronto, Toronto, ON, Canada (P.N.T.); and Department of Obstetrics and Gynecology, University of Toronto, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Department of Medical Imaging, Body Division, Toronto, ON, Canada (P.G.)
| | - Phyllis Glanc
- From the Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, MG-130c, Toronto, ON, Canada M4N 3M5 (K.H.); Department of Medical Imaging, Peterborough Regional Health Centre, Peterborough, ON, Canada (N.G.); Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University of Toronto, Princess Margaret Cancer Centre/University Health Network and Sinai Health System, Toronto, ON, Canada (G.B.F.); Department of Medical Imaging, University of Toronto, Division of Abdominal Imaging, Joint Department of Medical Imaging, Toronto, ON, Canada (T.P.C.); Department of Obstetrics and Gynecology, University of Toronto, Ontario Health-Cancer Care Ontario, Division of Gynecologic Oncology, University Health Network and Sinai Health System, Toronto, ON, Canada (S.E.F.); Department of Medical Imaging and Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada (S.L.); Department of Business Administration, Wilfrid Laurier University, Waterloo, ON, Canada (D.K.); Department of Medical Imaging, Department of Statistical Sciences, and Institute of Medical Science, University of Toronto, Toronto, ON, Canada (P.N.T.); and Department of Obstetrics and Gynecology, University of Toronto, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Department of Medical Imaging, Body Division, Toronto, ON, Canada (P.G.)
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Gupta A, Jha P, Baran TM, Maturen KE, Patel-Lippmann K, Zafar HM, Kamaya A, Antil N, Barroilhet L, Sadowski E. Ovarian Cancer Detection in Average-Risk Women: Classic- versus Nonclassic-appearing Adnexal Lesions at US. Radiology 2022; 303:603-610. [PMID: 35315722 DOI: 10.1148/radiol.212338] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background Several US risk stratification schemas for assessing adnexal lesions exist. These multiple-subcategory systems may be more multifaceted than necessary for isolated adnexal lesions in average-risk women. Purpose To explore whether a US-based classification scheme of classic versus nonclassic appearance can be used to help appropriately triage women at average risk of ovarian cancer without compromising diagnostic performance. Materials and Methods This retrospective multicenter study included isolated ovarian lesions identified at pelvic US performed between January 2011 and June 2014, reviewed between September 2019 and September 2020. Lesions were considered isolated in the absence of ascites or peritoneal implants. Lesions were classified as classic or nonclassic based on sonographic appearance. Classic lesions included simple cysts, hemorrhagic cysts, endometriomas, and dermoids. Otherwise, lesions were considered nonclassic. Outcomes based on histopathologic results or clinical or imaging follow-up were recorded. Diagnostic performance and frequency of malignancy were calculated. Frequency of malignancy between age groups was compared using the χ2 test, and Poisson regression was used to explore relationships between imaging features and malignancy. Results A total of 970 isolated lesions in 878 women (mean age, 42 years ± 14 [SD]) were included. The malignancy rate for classic lesions was less than 1%. Of 970 lesions, 53 (6%) were malignant. The malignancy rate for nonclassic lesions was 32% (33 of 103) when blood flow was present and 8% (16 of 194) without blood flow (P < .001). For women older than 60 years, the malignancy rate was 50% (10 of 20 lesions) when blood flow was present and 13% (five of 38) without blood flow (P = .004). The sensitivity, specificity, positive predictive value, and negative predictive value of the classic-versus-nonclassic schema was 93% (49 of 53 lesions), 73% (669 of 917 lesions), 17% (49 of 297 lesions), and 99% (669 of 673 lesions), respectively, for detection of malignancy. Conclusion Using a US classification schema of classic- or nonclassic-appearing adnexal lesions resulted in high sensitivity and specificity in the diagnosis of malignancy in ovarian cancer. The highest risk of cancer was in isolated nonclassic lesions with blood flow in women older than 60 years. © RSNA, 2022 See also the editorial by Baumgarten in this issue.
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Affiliation(s)
- Akshya Gupta
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
| | - Priyanka Jha
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
| | - Timothy M Baran
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
| | - Katherine E Maturen
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
| | - Krupa Patel-Lippmann
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
| | - Hanna M Zafar
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
| | - Aya Kamaya
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
| | - Neha Antil
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
| | - Lisa Barroilhet
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
| | - Elizabeth Sadowski
- From the Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14620 (A.G., T.M.B.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (P.J.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (K.E.M.); Department of Radiology, Vanderbilt University Medical Center, Nashville, Tenn (K.P.L.); Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pa (H.M.Z.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.K., N.A.); and Department of Obstetrics and Gynecology (L.B.) and Department of Radiology (E.S.), University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wis
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Guo Y, Zhao B, Zhou S, Wen L, Liu J, Fu Y, Xu F, Liu M. A comparison of the diagnostic performance of the O-RADS, RMI4, IOTA LR2, and IOTA SR systems by senior and junior doctors. Ultrasonography 2022; 41:511-518. [PMID: 35196832 PMCID: PMC9262660 DOI: 10.14366/usg.21237] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 01/31/2022] [Indexed: 11/04/2022] Open
Abstract
Purpose This study compared the diagnostic performance of the Ovarian-Adnexal Reporting and Data System (O-RADS), the Risk of Malignancy Index 4 (RMI4), the International Ovarian of Tumor Analysis Logistic Regression Model 2 (IOTA LR2), and the IOTA Simple Rules (IOTA SR) in predicting the malignancy of adnexal masses (AMs). Methods This retrospective study included 575 women with AMs between 2017 and 2020. All clinical messages, ultrasound images, and pathological findings were collected. Two senior doctors (group I) and two junior doctors (group II) used the four systems to classify AMs. The postoperative pathological diagnosis was used as the gold standard to evaluate the diagnostic efficiency. A receiver operating characteristic curve was used to test the diagnostic performance. The interrater agreement between the two groups was tested using kappa values. Results Of all 592 AMs, 447 (75.5%) were benign, 123 (20.8%) were malignant, and 22 (3.7%) were borderline. The intergroup consistency test yielded kappa values of 0.71, 0.92, 0.68, and 0.77 for the O-RADS, RMI4, IOTA LR2, and IOTA SR, respectively. To predict malignant lesions, the areas under the curve of the O-RADS, RMI4, IOTA LR2, and IOTA SR systems were 0.90, 0.89, 0.90, and 0.86 for group I and 0.89, 0.87, 0.88, and 0.84 for group II, respectively. The O-RADS had the highest sensitivity (91.0% in group I and 84.8% in group II). Conclusion The four diagnostic systems could compensate for junior doctors’ inexperience in predicting malignant adnexal lesions. The O-RADS performed best and showed the highest sensitivity.
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Affiliation(s)
- Yuyang Guo
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Baihua Zhao
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Shan Zhou
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Lieming Wen
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jieyu Liu
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yaqian Fu
- Health Management Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Fang Xu
- Department of Ultrasonography, The First Hospital of Changsha, Changsha, China
| | - Minghui Liu
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital, Central South University, Changsha, China
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50
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Xie WT, Wang YQ, Xiang ZS, Du ZS, Huang SX, Chen YJ, Tang LN. Efficacy of IOTA simple rules, O-RADS, and CA125 to distinguish benign and malignant adnexal masses. J Ovarian Res 2022; 15:15. [PMID: 35067220 PMCID: PMC8785584 DOI: 10.1186/s13048-022-00947-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 01/16/2022] [Indexed: 12/23/2022] Open
Abstract
Objective Ovarian cancer is the most deadly deadliest gynecological tumor in the female reproductive system. Therefore, the present study sought to determine the diagnostic performance of International Ovarian Tumor Analysis Simple Rules (IOTA SR), the Ovarian-Adnexal Reporting and Data System (O-RADS), and Cancer Antigen 125 (CA125) in discriminating benign and malignant ovarian tumors. The study also assessed whether a combination of the two ultrasound categories systems and CA125 can improve the diagnostic performance. Methods A total of 453 patients diagnosed with ovarian tumors were retrospectively enrolled from Fujian Cancer Hospital between January 2017 and September 2020. The data collected from patients included age, maximum lesion diameter, location, histopathology, levels of CA125, and detailed ultrasound reports. Additionally, all ultrasound images were independently assessed by two ultrasound physicians with more than 5 years of experience in the field, according to the IOTA simple rules and O-RADS guidelines. Furthermore, the area under the curve (AUC), sensitivity, and specificity of the above mentioned predictors were calculated using the receiver operating characteristic curve. Results Out of the 453 patients, 184 had benign lesions, while 269 had malignant ovarian tumors. In addition, the AUCs of IOTA SR, O-RADS, and CA125 in the overall population were 0.831, 0.804, and 0.812, respectively, and the sensitivities of IOTA SR, O-RADS, and CA125 were 94.42, 94.42, and 80.30%, respectively. On the other hand, the AUCs of IOTA SR combined with CA125, O-RADS combined with CA125, and IOTA SR plus O-RADS combined with CA125 were 0.900, 0.891, and 0.909, respectively. The findings also showed that the AUCs of a combination of the three approaches were significantly higher than those of individual strategies (p<0.05) but not significantly higher than the AUC of a combination of two methods (p>0.05). Conclusion The findings showed that a combination of IOTA SR or O-RADS in combination with CA125 may improve the ability to distinguish benign from malignant ovarian tumors. Supplementary Information The online version contains supplementary material available at 10.1186/s13048-022-00947-9.
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