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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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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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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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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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