Cited by 510Ovarian cancer diagnosis and treatmentBRCA gene mutations in cancerBreast Lesions and Carcinomas

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Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study

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Van Calster, B., Van Hoorde, K., Valentin, L., Testa, A. C., Fischerova, D., Van Holsbeke, C., Savelli, L., Franchi, D., Epstein, E., Kaijser, J., Van Belle, V., Czekierdowski, A., Guerriero, S., Fruscio, R., Lanzani, C., Scala, F., Bourne, T., Timmerman, D., International Ovarian Tumour Analysis (IOTA) group·2014·BMJ

DOI 10.1136/bmj.g5920PMC PMC4198550

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Abstract

OBJECTIVES: To develop a risk prediction model to preoperatively discriminate between benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian tumours. DESIGN: Observational diagnostic study using prospectively collected clinical and ultrasound data. SETTING: 24 ultrasound centres in 10 countries. PARTICIPANTS: Women with an ovarian (including para-ovarian and tubal) mass and who underwent a standardised ultrasound examination before surgery. The model was developed on 3506 patients recruited between 1999 and 2007, temporally validated on 2403 patients recruited between 2009 and 2012, and then updated on all 5909 patients. MAIN OUTCOME MEASURES: Histological classification and surgical staging of the mass. RESULTS: The Assessment of Different NEoplasias in the adneXa (ADNEX) model contains three clinical and six ultrasound predictors: age, serum CA-125 level, type of centre (oncology centres v other hospitals), maximum diameter of lesion, proportion of solid tissue, more than 10 cyst locules, number of papillary projections, acoustic shadows, and ascites. The area under the receiver operating characteristic curve (AUC) for the classic discrimination between benign and malignant tumours was 0.94 (0.93 to 0.95) on temporal validation. The AUC was 0.85 for benign versus borderline, 0.92 for benign versus stage I cancer, 0.99 for benign versus stage II-IV cancer, and 0.95 for benign versus secondary metastatic. AUCs between malignant subtypes varied between 0.71 and 0.95, with an AUC of 0.75 for borderline versus stage I cancer and 0.82 for stage II-IV versus secondary metastatic. Calibration curves showed that the estimated risks were accurate. CONCLUSIONS: The ADNEX model discriminates well between benign and malignant tumours and offers fair to excellent discrimination between four types of ovarian malignancy. The use of ADNEX has the potential to improve triage and management decisions and so reduce morbidity and mortality associated with adnexal pathology.

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Fig 1 Calibration plots of predicted probabilities for each type of tumour. Data have been calculated using validation data (n=2403). Plots show how well the predicted probabilities (x axis) agree with observed probabilities (y axis). For perfect agreement, the calibration curve falls on the ideal diagonal line. Histograms below plots show distribution of predicted probabilitiesCC BY-NC · PubMed Central

Fig 2 Discrimination plot of ADNEX model after it was updated on pooled dataset (n=5909). For each predicted tumour type, box plots of probabilities are presented for each confirmed tumour type (reference standard). Red vertical lines show baseline probabilities for each type of tumour. For example, the baseline probability of a benign tumour is 0.681; for most women with a benign tumour the predicted probability of a benign tumour was higher than 0.9, whereas most women with an ovarian malignancy (most notably stage II-IV cancer) had clearly lower predicted probabilities of a benign tumourCC BY-NC · PubMed Central

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Ultrasound and Clinical Preoperative Characteristics for Discrimination Between Ovarian Metastatic Colorectal Cancer and Primary Ovarian Cancer: A Case-Control Study
Stukan, M., Alcázar, J. L., Gębicki, J., Epstein, E., Liro, M., Sufliarska, A., Szubert, S., Guerriero, S., Braicu, E. I., Szajewski, M., et al. (2019) · Diagnostics · doi:10.3390/diagnostics9040210 · Cited by 9
“In the largest published cohort of patients with ovarian metastatic cancers who underwent comprehensive ultrasound examination, the median tumor diameter was 86 mm; the majority (95%) had a solid component, with a median proportion of solid tissue of 100% (range 64–100) [14].”
Background
Comparison of Ultrasound and Tumor Marker CA125 in Diagnosis of Adnexal Mass Malignancies
Behnamfar, F., Esmaeilian, F., Adibi, A., & Rouholamin, S. (2022) · Advanced Biomedical Research · doi:10.4103/abr.abr_164_20 · Cited by 9
“All of the women in this set were initially evaluated for an adnexal mass and CA‐125 results would be expected to receive priority consideration in patients in this age group, for which malignancy is more uncommon.[12] In order to investigate the predictive role of ultrasound in malignancy of ovarian tumors, this stud…”
Background
Ovarian Masses: The Value of Acoustic Shadowing on Ultrasound Examination
Yoeli‐Bik, R., Lengyel, E. R., Mills, K. A., & Abramowicz, J. S. (2022) · Journal of Ultrasound in Medicine · doi:10.1002/jum.16100 · Cited by 9
“Modified from Van Calster et al.50 *The ADNEX model is the first risk model to differentiate between benign and malignant tumors while offering sub-classification of malignancies into borderline tumors, Stage I and Stage II–IV primary cancers, and secondary metastatic tumors.”
Method
Flawed external validation study of the ADNEX model to diagnose ovarian cancer
CALSTER, B. V., Steyerberg, E. W., Bourne, T., Timmerman, D., & Collins, P. G. S. (2016) · Gynecologic Oncology Reports · doi:10.1016/j.gore.2016.09.003 · Cited by 9
“It is useful to observe that the AUCs were 0.955 and 0.907, since this is in line with the center-specific values reported in the original publication describing the ADNEX model (Van Calster et al., 2014).”
BackgroundMethodResultInfluential
Effect of differences in O-RADS lexicon interpretation between senior and junior sonologists on O-RADS classification and diagnostic performance
Yang, Y., Wang, H., Liu, Z., Su, N., Gao, L., Tao, X., Zhang, R., Gu, Y., Ma, L., Wang, R., et al. (2023) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-023-05108-z · Cited by 8
Performance of radiomics analysis in ultrasound imaging for differentiating benign from malignant adnexal masses: A systematic review and meta‐analysis
Moro, F., Ciancia, M., Maria, S., Baldassari, G., Tran, H. E., Carcagnì, A., Fagotti, A., & Testa, A. C. (2025) · Acta Obstetricia Et Gynecologica Scandinavica · doi:10.1111/aogs.15146 · Cited by 9
“In particular, the IOTA-Assessment of Different Neoplasia in the adneXa (ADNEX) model, which combines clinical and simple ultrasound variables, 4 has been proposed in international guidelines for the diagnosis and management of patients with adnexal masses.”
A multimodal uncertainty-aware AI system optimizes ovarian cancer risk assessment workflow
Wang, X., Lv, X., Wang, J., Zou, L., Chen, Z., Zhao, R., Zhao, L., Zhao, M., Zhang, X., Zhang, B., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01986-4 · Cited by 8
Malignant epithelioid neoplasm of the ileum with ACTB-GLI1 fusion mimicking an adnexal mass
Ambrosio, M., Virgilio, A., Raffone, A., Arena, A., Raimondo, D., Alletto, A., Seracchioli, R., & Casadio, P. (2022) · BMC Women s Health · doi:10.1186/s12905-022-01679-0 · Cited by 8
Evaluation of Adnexal Masses: The IOTA Concept
Manegold‐Brauer, G., Timmerman, D., & Hoopmann, M. (2022) · Ultraschall in der Medizin - European Journal of Ultrasound · doi:10.1055/a-1912-5361 · Cited by 8
Imaging of Adnexal Masses
Thakur, M., & Timmerman, D. (2016) · Clinical Obstetrics & Gynecology · doi:10.1097/grf.0000000000000261 · Cited by 8
“In a multicenter prospective cohort study, the ADNEX model discriminated well between benign and malignant tumors and offered a fair to excellent discrimination between the 4 types of malignancy.(23) Clinicians who do not perform diagnostic gynecological ultrasound scans themselves, should establish referral services…”
Method
Immunological parameters as a new lead in the diagnosis of ovarian cancer.
Baert, T., Timmerman, D., Vergote, I. B., & Coosemans, A. (2015) · PubMed Central · Cited by 8
Does Combing O‐RADS US and CA ‐125 Improve Diagnostic Accuracy in Assessing Adnexal Malignancy Risk in Women With Different Menopausal Status?
Wu, M., Wang, Q., Zhang, M., Cao, J., Chen, Y., Zheng, J., Luo, L., Su, M., Lin, X., Kuang, X., et al. (2022) · Journal of Ultrasound in Medicine · doi:10.1002/jum.16065 · Cited by 8
“88.(13,24,25) Nevertheless, the preoperative diagnosis of these three tumor subtypes still remains a challenge in current clinical practice.”
Background
Psychological impact of referral to an oncology hospital on patients with an ovarian mass
Lof, P., Engelhardt, E., van Gent, M., Mom, C., Dunné, F. R. R.-V., van Baal, W. V., Verhoeve, H., Hermsen, B., Verbruggen, M., Hemelaar, M., et al. (2022) · International Journal of Gynecological Cancer · doi:10.1136/ijgc-2022-003753 · Cited by 6
Diagnostic Performances of Ultrasound-Based Models for Predicting Malignancy in Patients with Adnexal Masses
Velayo, C. L., Reforma, K. N., Sicam, R. V. G., Diwa, M. H., Sy, A. D. R., & Tantengco, O. A. G. (2022) · Healthcare · doi:10.3390/healthcare11010008 · Cited by 8
“According to the results of the IOTA group’s recent studies, a cutoff risk set at 20% was related to the best balance between the ADNEX model’s sensitivity and specificity [14], while the cutoff for LR1 and LR2 was set at 0.”
Result
Evaluating the risk of malignancy in adnexal masses: validation of O-RADS and comparison with ADNEX model, SA, and RMI
Wang, R., & Yang, Z. (2023) · Ginekologia Polska · doi:10.5603/gp.a2023.0019 · Cited by 8
“The ADNEX model [10] includes nine variables: age (years), serum carbohydrate antigen 125 (CA125) level (U/mL), type of center (oncology center/other hospital), maximum diameter of the lesion (mm), maximal diameter of the largest solid part (mm), more than 10 locules (yes/no), number of papillary projections (0/1/2/3/…”
BackgroundMethod
Assessment of different NEoplasias in the adneXa model for differentiation of benign and malignant adnexal masses in Korean women
Nam, G. E., Lee, S. R., Jeong, K., Kim, S. H., Moon, H. S., & Chae, H. D. (2021) · Obstetrics & Gynecology Science · doi:10.5468/ogs.21012 · Cited by 8
“The general malignancy rate in a previous report was 27% [2].”
BackgroundMethodInfluential
Diagnostic imaging in gynecology
Łuczyńska, E., & Zbigniew, K. (2022) · Ginekologia Polska · doi:10.5603/gp.a2021.0209 · Cited by 8
Nomogram based on the O-RADS for predicting the malignancy risk of adnexal masses with complex ultrasound morphology
Gong, L., Li, X.-Y., Wu, Y., Dong, S., Zhang, S., Feng, Y.-N., Lv, Y.-E., Guo, X.-J., Peng, Y., Du, X.-S., et al. (2023) · Journal of Ovarian Research · doi:10.1186/s13048-023-01133-1 · Cited by 8
“Acoustic shadowing was included in IOTA SR and ADNEX model as one of the key benign features [8, 10], but it has not been included in the O-RADS classification system.”
BackgroundMethod
The Roles of Ovarian-Adnexal Reporting and Data System US and Ovarian-Adnexal Reporting and Data System MRI in the Evaluation of Adnexal Lesions
Patel-Lippmann, K. K., Gupta, A., Martin, M. F., Phillips, C. H., Maturen, K. E., Jha, P., Sadowski, E. A., & Stein, E. B. (2024) · Radiology · doi:10.1148/radiol.233332 · Cited by 7
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Ronsini, C., Restaino, S., Vizzielli, G., Donna, M. C. D., Cucinella, G., Solazzo, M. C., Scaffa, C., FRANCISCIS, P. D., & Chiantera, V. (2025) · Medicina · doi:10.3390/medicina61050777 · Cited by 7
“Future prospective studies involving patients without suspected disease will be needed to improve the usability of these results.”
Inflammatory Indices vs. CA 125 for the Diagnosis of Early Ovarian Cancer: Evidence from a Multicenter Prospective Italian Cohort
Ronsini, C., Restaino, S., Ludovisi, M., Vizzielli, G., Donna, M. C. D., Cucinella, G., Solazzo, M. C., Scaffa, C., FRANCISCIS, P. D., Fordellone, M., et al. (2025) · Journal of Personalized Medicine · doi:10.3390/jpm15090426 · Cited by 7
Metabolic vulnerabilities in ovarian cancer decoding the nexus between nutrient adaptation and therapy resistance
Guo, X., Liu, Z., Li, X., Zhou, B., & Chen, J. (2026) · Journal of Advanced Research · doi:10.1016/j.jare.2026.01.047 · Cited by 7
Application of Ultrasound Scores (Subjective Assessment, Simple Rules Risk Assessment, ADNEX Model, O-RADS) to Adnexal Masses of Difficult Classification
Pelayo, M., Saúco, J. S., Sánchez-Zurdo, J., Perez‐Mies, B., Abarca-Martínez, L., Hidalgo, M. J. C., Sainz‐Bueno, J. A., Alcázar, J. L., & Pelayo‐Delgado, I. (2023) · Diagnostics · doi:10.3390/diagnostics13172785 · Cited by 7
Ovarian cancer risk among older patients with stable adnexal masses
Suh‐Burgmann, E., Hung, Y., & Schmittdiel, J. A. (2024) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2024.04.019 · Cited by 7
ACR Appropriateness Criteria® Clinically Suspected Adnexal Mass, No Acute Symptoms: 2023 Update
Patel-Lippmann, K. K., Wasnik, A. P., Akin, E. A., Andreotti, R. F., Ascher, S. M., Brook, O. R., Eskander, R. N., Feldman, M., Jones, L. P., Martino, M. A., et al. (2024) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2024.02.017 · Cited by 8
ACR Appropriateness Criteria® Postmenopausal Acute Pelvic Pain
Henrichsen, T. L., Maturen, K. E., Robbins, J. B., Akin, E. A., Ascher, S. M., Brook, O. R., Dassel, M., Friedman, L., Learman, L. A., Patlas, M. N., et al. (2021) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2021.02.003 · Cited by 7
Conservative Management of Asymptomatic Adnexal Masses Classified as Benign by the IOTA ADNEX Model: A Prospective Multicenter Portuguese Study
Brito, M., Borges, A. L., Rodrigues, S., Ambrósio, P., Condeço, R., Lacerda, A., Bernardo, M. J., Pinto, P., & Djokovic, D. (2021) · Diagnostics · doi:10.3390/diagnostics11111992 · Cited by 8
“Furthermore, the IOTA ADNEX model is the first prediction model that also provides the risk distribution between four malignancy categories (borderline tumors, stage I, stage II-IV primary cancers and secondary metastatic tumors in adnexal lesions) [16].”
Method
The learning curve and difficult points of the O-RADS ultrasound risk stratification system in 54 trainees
Zhou, S., Guo, Y., Wen, L., Zhao, B., & Liu, M. (2021) · ULTRASONOGRAPHY · doi:10.14366/usg.21158 · Cited by 8
“org improve the malignancy risk estimate and the management of AMs, many guidelines and structured reporting systems have been established, using subjective assessments, simple scoring, or statistically derived scoring [2-10].”
Background
Apatinib combined with SOX regimen for conversion therapy in advanced gastric cancer patients: a retrospective cohort study
Deng, Y.-Y., Jiang, D., Zhu, P.-F., Lu, H., Liu, Q., Zhang, X., Pan, S. L., Chen, Z.-L., & Yang, L. (2023) · World Journal of Surgical Oncology · doi:10.1186/s12957-023-02973-3 · Cited by 7
“integrated clinical predictors (age, serum CA-125 level, type of center) and ultrasound predictors to distinguish primary and metastatic ovarian tumors [27].”
Background
BARD1 Autoantibody Blood Test for Early Detection of Ovarian Cancer
Pilyugin, M., Ratajska, M., Stukan, M., Concin, N., Zeillinger, R., & Irminger‐Finger, I. (2021) · Genes · doi:10.3390/genes12070969 · Cited by 7
“There have also been attempts to simplify the IOTA algorithm [13,14].”
Background
Accurate prediction of benign and malignant adnexal tumors in surgical resection and conservative treatment: construction and external validation of a diagnostic model based on CEUS, HE4, and O-RADS US v2022 evaluation
Liu, C., Zhu, Y., Dai, K.-J., Tan, B., Dong, H., Lin, J., He, R. L., Lu, M., & Li, Y. (2025) · Journal of Ovarian Research · doi:10.1186/s13048-025-01707-1 · Cited by 6
Circulating biomarkers for the preoperative diagnosis of uterine sarcoma: A systematic review and meta-analysis
Taliento, C., Bruyn, C. D., Ceusters, J., Timmerman, D., den Bosch, T. V., & Coosemans, A. (2025) · Maturitas · doi:10.1016/j.maturitas.2025.108634 · Cited by 6
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Barbu, L. A., Cercelaru, L., Şurlin, V., Mogoantă, S. Ş., Cojan, T. Ș. Ț., Mărgăritescu, N.-D., Cojan, A.-M. Ț., Popescu, M., Căluianu, V., Mogoș, G. F. R., et al. (2025) · Life · doi:10.3390/life15101601 · Cited by 6
Ultrasound-based deep learning model as an assistant improves the diagnosis of ovarian tumors: a multicenter study
Wang, Y., Zhang, J., He, Y., Wang, X., Wu, X., Zhang, W., Gong, M., Gao, D., Liu, S., Liu, P., et al. (2025) · Insights into Imaging · doi:10.1186/s13244-025-02112-4 · Cited by 7
Accuracy of O-RADS System in Differentiating Between Benign and Malignant Adnexal Masses Assessed via External Validation by Inexperienced Gynecologists
Buranaworathitikul, P., Wisanumahimachai, V., Phoblap, N., Porngasemsart, Y., Rugfoong, W., Yotchana, N., Uthaichalanont, P., Jiampochaman, T., Kunanukulwatana, C., Thiamkaew, A., et al. (2024) · Cancers · doi:10.3390/cancers16223820 · Cited by 6
Beyond the Image: Performance of O-RADS, ADNEX, IOTA Simple Rules & RMI 4 in differentiating benign and malignant adnexal masses – An Indian perspective
Khastgir, G., Siwatch, S., Singh, T., Jain, V., Sikka, P., & Srinivasan, R. (2025) · European Journal of Obstetrics & Gynecology and Reproductive Biology · doi:10.1016/j.ejogrb.2025.114585 · Cited by 6
Adnexal tumors in menopausal women: surgery or surveillance?
Burgess, B. T., & Ueland, F. R. (2019) · Menopause The Journal of The North American Menopause Society · doi:10.1097/gme.0000000000001330 · Cited by 6
Diagnostic Performance of Ultrasound-Based International Ovarian Tumor Analysis Simple Rules and Assessment of Different NEoplasias in the adneXa Model for Predicting Malignancy in Women with Ovarian Tumors: A Prospective Cohort Study
Rashmi, N., Singh, S., Begüm, J., & Sable, M. (2023) · Women s Health Reports · doi:10.1089/whr.2022.0072 · Cited by 6
Symptoms, ultrasound imaging and biochemical markers alone or in combination for the diagnosis of ovarian cancer in women with symptoms suspicious of ovarian cancer
Rai, N., Champaneria, R., Snell, K. I. E., Mallett, S., Bayliss, S. E., Neal, R. D., Balogun, M., Kehoe, S. T., Deeks, J. J., Sundar, S. S., et al. (2015) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd011964 · Cited by 6
Ovarian mass‐differentiating benign from malignant. Why the International Ovarian Tumour Analysis rules should be implemented in Australasia
Abramowicz, J. S., Condous, G. S., & Timmerman, D. (2018) · Australasian Journal of Ultrasound in Medicine · doi:10.1002/ajum.12108 · Cited by 6
Characteristics and prognosis of borderline ovarian tumors in pre and postmenopausal patients
Tal, O., Herman, H. G., Gluck, O., Levy, T., Kerner, R., Bar, J., & Sagiv, R. (2020) · Archives of Gynecology and Obstetrics · doi:10.1007/s00404-020-05652-w · Cited by 6
“In 2014 Van Calster and colleagues [26] demonstrated that the combination of the following parameters can be used for successful preoperative discrimination between benign and malignant ovarian masses: age, serum CA-125 levels and different sonographic parameters (lesion diameter, solid tissue, cyst locules, papillary…”
Background
Management of Adnexal Masses
Batra, N., & Gupta, B. (2023) · Springer eBooks · doi:10.1007/978-3-031-36179-1_1 · Cited by 6
Analysis of Diagnostic Efficacy of the International Ovarian Tumor Analysis ADNEX Model and the ACR O-RADS US (Ovarian-Adnexal Reporting and Data System) for Benign and Malignant Ovarian Tumors: A Retrospective Study in a Tumor Center in Northeast China
Zhong, D., Gao, X.-Q., Li, H., Wang, H., & Liu, Y. (2024) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-024-01170-2 · Cited by 5
“The use of a single, fixed cutoff value should be avoided according to the ADNEX model application guidance [6], because it may lead to a non-patient-centered diagnostic decision.”
Influential
Clinical value of ACR O-RADS combined with CA125 in the risk stratification of adnexal masses
Pan, R., Zhang, S., Zhang, X., Xu, T., Cui, X., Li, R., Yu, M., & Zhang, B. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1369900 · Cited by 5
Diagnostic Performance of O‐ RADS US (Version 2019 and Version 2022) Incorporating Acoustic Shadowing by Junior Radiologists
Wu, C.-I., Wu, L.-H., Shang, J., Xie, H., & Peng, R. (2025) · Journal of Ultrasound in Medicine · doi:10.1002/jum.16644 · Cited by 5
Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnexal masses
Liu, L., Cai, W., Zheng, F., Tian, H., Li, Y., Wang, T., Chen, X., & Zhu, W. (2025) · Insights into Imaging · doi:10.1186/s13244-024-01874-7 · Cited by 7
Imaging in gynecological disease (28): clinical and ultrasound characteristics of serous and mucinous cystadenomas in the adnexa
Mascilini, F., Moro, F., Pasciuto, T., Sladkevicius, P., Froyman, W., Jokubkiene, L., Holsbeke, C. V., Franchi, D., Epstein, E., Guerriero, S., et al. (2025) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.29248 · Cited by 5
Adnexal Mass Imaging: Contemporary Guidelines for Clinical Practice
Roseland, M. E., Maturen, K. E., Shampain, K. L., Wasnik, A. P., & Stein, E. B. (2023) · Radiologic Clinics of North America · doi:10.1016/j.rcl.2023.02.002 · Cited by 5
Prediction of ovarian cancer prognosis using statistical radiomic features of ultrasound images
Zuo, R., Li, X., Hu, J., Wang, W., Lü, B., Zhang, H., Cheng, X., Lu, W., Qin, J., Liu, P., et al. (2024) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ad4a02 · Cited by 5
“…for example [based on three factors namely age, Cancer Antigen 125 (CA125), and a combination of six ultrasound features including diameter of lesion, blood flow and proportion of solid tissue], provides excellent discrimination between benign and malignant ovarian tumors (Van Calster et al 2014).”
BackgroundMethod
Performance of O-RADS MRI Score in Differentiating Benign From Malignant Ovarian Teratomas: MR Feature Analysis for Differentiating O-RADS 4 From O-RADS 2
Petrocelli, R., Doshi, A. M., Slywotzky, C. M., Savino, M., Melamud, K., Tong, A. Y., & Hindman, N. M. (2024) · Journal of Computer Assisted Tomography · doi:10.1097/rct.0000000000001629 · Cited by 5
Multimodal Deep Learning Based on Ultrasound Images and Clinical Data for Better Ovarian Cancer Diagnosis
Su, C., Miao, K., Zhang, L., Yu, X., Guo, Z., Li, D., Xu, M., Zhang, Q., & Dong, X. (2025) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-025-01566-8 · Cited by 7
Algorithmic Approach to Sonography of Adnexal Masses: An Evolving Paradigm
Bhalla, D., Manchanda, S., & Vyas, S. (2020) · Current Problems in Diagnostic Radiology · doi:10.1067/j.cpradiol.2020.08.008 · Cited by 5
Ovarian-Adnexal Reporting and Data Systems MR Imaging
Melamud, K., Hindman, N. M., & Sadowski, E. A. (2022) · Magnetic Resonance Imaging Clinics of North America · doi:10.1016/j.mric.2022.06.004 · Cited by 5
Strumal Carcinoid Tumor of the Ovary: Report of Rare Occurrence with Review of Literature
Shen, L., Yang, A.-Q., & Jin, L. (2022) · Diagnostics · doi:10.3390/diagnostics12112706 · Cited by 5
“The probabilities provided by the ADNEX model [25] were as follows: The incidence rate of benign tumors, malignant tumors, and borderline tumors was 64.”
Method
Comparison of performance between O-RADS, IOTA simple rules risk assessment and ADNEX model in the discrimination of ovarian Brenner tumors
Shang, J., Lei, T., Wu, L., Lin, M., & Xie, H. (2023) · Archives of Gynecology and Obstetrics · doi:10.1007/s00404-022-06903-8 · Cited by 4
Ultrasonographic diagnosis of adnexal masses: interobserver agreement in the interpretation of videos, using IOTA terminology
Massobrio, R., Mariani, L. L., Conti, D., Grandis, T. D., Buonomo, F., Badellino, E., Novara, L., Bounous, V. E., Perotto, S., Mancarella, M., et al. (2023) · Archives of Gynecology and Obstetrics · doi:10.1007/s00404-023-07233-z · Cited by 5
Clinical practice guidelines for molecular tumor marker, 2nd edition review part 2
Kikuchi, Y., Shimada, H., Yamasaki, F., Yamashita, T., Araki, K., Horimoto, K., Yajima, S., Yashiro, M., Yokoi, K., Cho, H., et al. (2024) · International Journal of Clinical Oncology · doi:10.1007/s10147-024-02497-0 · Cited by 5
ReClassification of Patients with Ambiguous CA125 for Optimised Pre-Surgical Triage
Stephens, A. N., Hobbs, S. J., Kang, S.-W., Oehler, M. K., Jobling, T. W., & Allman, R. (2024) · Diagnostics · doi:10.3390/diagnostics14070671 · Cited by 5
Adenomatoid tumor of the fallopian tube: A case report and a review of the literature
Mitta, K., Michos, G., Athanasiadou, E. A., Papanikolaou, E. G. E., Tsakiridis, I. G., & Mamopoulos, A. M. (2024) · International Journal of Surgery Case Reports · doi:10.1016/j.ijscr.2024.110268 · Cited by 5
“The calculated risk for a malignant ovarian tumor was determined to be 9.1 % [13].”
BackgroundInfluential
Accuracy of Pretreatment Ultrasonography Assessment of Intra-Abdominal Spread in Epithelial Ovarian Cancer: A Prospective Study
Tomasińska, A., Stukan, M., Badocha, M., & Myszewska, A. (2021) · Diagnostics · doi:10.3390/diagnostics11091600 · Cited by 5
“Prediction of malignancy was based on the examiner’s subjective assessment, or if ambiguous in appearance, multivariable predictive models described elsewhere were used [20,21].”
Method
Ovarian Masses-Applicable IOTA ADNEX Model versus Morphological Findings for Accurate Diagnosis and Treatment
Buţureanu, T., Socolov, D. G., Matasariu, D. R., Ursache, A., Apetrei, A.-M., Dumitraşcu, I., Vasilache, I.-A., Rudisteanu, D., Boiculese, V. L., & Lozneanu, L. (2021) · Applied Sciences · doi:10.3390/app112210789 · Cited by 5
“It includes three clinical criteria (age, CA 125 serum level, and the type of center: oncological/other types of hospitals) and six ultrasound features (the maximum tumoral diameter in mm, the maximum diameter of the solid component in mm; more than 10 loculus, number of papillary projections, presence/absence of acou…”
Background
Reservations Regarding O-RADS Recommendations
Suh‐Burgmann, E., FLANAGAN, T. A., & Brasic, N. (2020) · Radiology · doi:10.1148/radiol.2020192559 · Cited by 5
Maternal adnexal masses in pregnancy
Djokovic, D., Pinto, P., & Reis, I. S. (2025) · Best Practice & Research Clinical Obstetrics & Gynaecology · doi:10.1016/j.bpobgyn.2025.102643 · Cited by 4
Clustered flexible calibration plots for binary outcomes using random effects modeling
Barreñada, L., Cock, B. D., Wynants, L., & CALSTER, B. V. (2025) · Research Synthesis Methods · doi:10.1017/rsm.2025.10046 · Cited by 5
Machine learning-enhanced gas sensor technology identifies ovarian and endometrial cancer of all stages through plasma volatile organic compound patterns
Eriksson, J., Puglisi, D., Herbst, F., Dobilas, A., Shtepliuk, I., Joneborg, U., Falconer, H., Rådestad, A. F., & Borgfeldt, C. (2025) · EBioMedicine · doi:10.1016/j.ebiom.2025.106027 · Cited by 4
ADNEX-AI: automated extraction of ultrasound predictors for interpretable ovarian cancer risk stratification
Geysels, A., Garofalo, G., Timmerman, S., Ceusters, J., Buonomo, F., Fischerová, D., Testa, A. C., Moro, F., Sladkevicius, P., Jokubkiene, L., et al. (2025) · npj Precision Oncology · doi:10.1038/s41698-025-01215-x · Cited by 4
“TheAssessmentofDifferentNEoplasias in the adneXa (ADNEX) model, developed by the International Ovarian TumourAnalysis(IOTA)group,isthebestperformingmodelandhasbeen externallyvalidatedinnumerousstudies 6 – 8 .”
Advances in ovarian cancer screening and early detection: from biomarkers to multivariate index assays
Salomón, C., Razo-Azamar, M., Gentry‐Maharaj, A., Rice, G. E., & Menon, U. (2026) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2025.2608820 · Cited by 4
Developing and validating ultrasound‐based machine‐learning models incorporating radiomics features to predict malignancy in adnexal masses
Moro, F., Ciancia, M., Berardino, S. D., Baldassari, G., Mascilini, F., Ciccarone, F., Nero, C., Tran, H. E., Pasciuto, T., Boldrini, L., et al. (2026) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.70203 · Cited by 4
Terms, definitions and measurements to describe the sonographic features of adnexal tumors: updated consensus opinion from the International Ovarian Tumor Analysis ( IOTA ) Group
Timmerman, D., Valentin, L., Testa, A. C., Froyman, W., Landolfo, C., Kotlarz, A., Fischerová, D., CALSTER, B. V., Bourne, T., & Collaborators (2026) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.70191 · Cited by 4
Laparoscopic Surgery for Ovarian Neoplasms – What is Possible, What is Useful?
Droste, A., Anić, K., & Hasenburg, A. (2022) · Geburtshilfe und Frauenheilkunde · doi:10.1055/a-1787-9144 · Cited by 4
Comparisons of Effectiveness in Differentiating Benign from Malignant Ovarian Masses between Conventional and Modified Risk of Malignancy Index (RMI)
Tantipalakorn, C., Tinnangwattana, D., Lerthiranwong, T., Luewan, S., & Tongsong, T. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20010888 · Cited by 6
Impact of Medical Device Regulation on use of ultrasound‐based prediction models in clinical practice
Kotlarz, A., Froyman, W., Valentin, L., Testa, A. C., Hove, M. V., CALSTER, B. V., Bourne, T., & Timmerman, D. (2024) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.27675 · Cited by 4
AIUM Practice Parameter for the Performance of Ultrasound of the Female Pelvis, 2024 Revision
(2024) · Journal of Ultrasound in Medicine · doi:10.1002/jum.16556 · Cited by 4
Real-world performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model for the pre-operative classification of ovarian tumors
Lems, E., Mongula, J. E., Muntinga, C. L. P., Leemans, J. C., Evert, J. S. H., Smit, R. A., van der Steeg, J. W., Pijlman, B. M., Coppus, S. F. P. J., Bongers, M. Y., et al. (2025) · International Journal of Gynecological Cancer · doi:10.1016/j.ijgc.2025.101917 · Cited by 4
Ovarian tumor: a review
Kashyap, P. (2021) · International Journal of Reproduction Contraception Obstetrics and Gynecology · doi:10.18203/2320-1770.ijrcog20213510 · Cited by 4
“The change in CA125 level overtime may be more helpful than a single value and therefore it is useful for follow up of patients of ovarian cancer after treatment.(23)”
Background
Comparison of International Ovarian Tumor Analysis ADNEX model and Ovarian-Adnexal Reporting and Data System with final histological diagnosis in adnexal masses: a retrospective study
Filiz, A. A., Kahyaoğlu, S., & Atalay, C. (2023) · Obstetrics & Gynecology Science · doi:10.5468/ogs.23061 · Cited by 4
“After applying the ADNEX model to a patient with an adnexal mass, the lesion was classified into five categories: benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic tumors [9,10].”
Method
Current and Emerging Strategies for Tubo-Ovarian Cancer Diagnostics
Brincat, M., Mira, A. R., & Lawrence, A. C. (2023) · Diagnostics · doi:10.3390/diagnostics13213331 · Cited by 4
GI-RADS versus O-RADS in the differential diagnosis of adnexal masses: a systematic review and head-to-head meta-analysis
Perez, M., Meseguer, A., Vara, J., Jiménez, J. C. V., Garcia, I. B., Lozano, M., Orozco, R., & Alcázar, J. L. (2024) · ULTRASONOGRAPHY · doi:10.14366/usg.24105 · Cited by 4
The Clinical Relevance of Distinguishing Between Simple and Complex Adnexal Cystic Structures by Ultrasound in Peri- and Postmenopause
Erdodi, B., Szöllösi, G. J., Tóth, Z., Krasznai, Z. T., & Jakab, A. (2025) · Cancers · doi:10.3390/cancers17081370 · Cited by 4
“Nonetheless, CA-125 remains an integral component of advanced diagnostic models such as the ADNEX model, where it contributes to the differentiation of malignant subtypes [18].”
Influential
Adneksiyal kitlelerde Risk of Malignancy Index versiyonları ile Assesment of Different Neoplasias in the Adnexa (ADNEX) skorlama sisteminin karşılaştırılması
Sandal, K., Polat, M., Yassa, M., Günay, T., Erdem, G., & Güzin, K. (2018) · Zeynep Kamil Tıp Bülteni · doi:10.16948/zktipb.445755 · Cited by 4
Combining A Second-Generation Multivariate Index Assay with Ovarian Imaging Improves the Preoperative Assessment of An Adnexal Mass
Bullock, R. G., Smith, A., Munroe, D. G., Ueland, F. R., Goodrich, S. T., Pappas, T. C., Fredericks, T. I., & Bonato, V. (2019) · Journal of Surgical Oncology · doi:10.31487/j.jso.2019.03.04 · Cited by 4
Ultrasound differentiation between benign versus malignant adnexal masses in pregnant patients
Rabiej-Wronska, E., Wiechec, M., Pitynski, K., Wiercinska, E., & Kotlarz, A. (2021) · Ginekologia Polska · doi:10.5603/gp.a2021.0176 · Cited by 4
Surgery of Benign Ovarian Masses by a Gynecological Cancer Surgeon: A Cohort Study in a Tertiary Cancer Centre
Quaranta, M., Nath, R., Mehra, G., Diab, Y. M. S. K., & Sayasneh, A. (2020) · Cureus · doi:10.7759/cureus.9201 · Cited by 4
“The IOTA ADNEX model was calculated when the required parameters were retrievable retrospectively [2].”
BackgroundMethod
Ultrasonic diagnosis of ovarian masses: can the playing field be leveled and raised at the same time?
Benacerraf, B. R. (2016) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2015.12.045 · Cited by 4
Conservative management of adnexal tumors: how to tell good from bad
Jurkovic, D. (2023) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.26158 · Cited by 4
The Use of Machine Learning Models and Radiomics for Segmentation and Classification of Adnexal Masses on Ultrasound: A Multi-Cohort Retrospective StudyPreprint
Barcroft, J., Linton‐Reid, K., Landolfo, C., Al‐Memar, M., Parker, N., Kyriacou, C., Munaretto, M., Fantauzzi, M., Cooper, N., Yazbek, J., et al. (2023) · medRxiv · doi:10.1101/2023.04.26.23289150 · Cited by 4
“Various ultrasound-based diagnostic models, using a combination of ultrasound features with or without serological markers (CA125) exist to support the classification of adnexal masses, including the Risk of malignancy index (RMI)(6), International Ovarian Tumour Analysis (IOTA) Simple Rules (SR) (7), the IOTA Assessm…”
Method
Adnexal Lesion Discrimination Using Deep Learning Analysis of Dynamic Contrast-enhanced US Images
Wu, M., Yang, H., Chen, Y., Wu, S., Liang, T., Zhang, M., Qu, E., Sun, X., Zhang, R., Mu, L., et al. (2025) · Radiology Artificial Intelligence · doi:10.1148/ryai.240786 · Cited by 3
Diagnostic accuracy of ultrasound models for assessment of ovarian tumors: systematic review and meta‐analysis
Lems, E., Koch, A. H., Delvaux, E. J. L. G., Leemans, J. C., Bongers, M. Y., Lok, C. A. R., Ramaekers, B. L. T., & Geomini, P. M. A. J. (2025) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.70135 · Cited by 3
“…Ovarian Tumor Analysis (IOTA) group have developed several ultrasound models, including the Logistic Regression model 2 (LR2) 12 , Simple ultrasound-based Rules (SR) 13 and Assessment of Different NEoplasias in the adneXa (ADNEX) model 14 , all of which outperform the RMI in study settings 9,15 .”
Key Measures for Evaluating Diagnostic Accuracy in Multi-Class Classification: An Overview and Simulation-Based Comparison
Ryu, L., Han, K., Jung, I., Park, Y. W., Ahn, S. S., & Hwang, D. (2026) · Korean Journal of Radiology · doi:10.3348/kjr.2025.1447 · Cited by 3
“Several studies have employed the PDI to evaluate model performance in predicting ovarian tumor subclasses [29-31].”
A new risk-scoring system to predict Xp11.2 translocation renal cell carcinoma in adults
Shi, Q., Liu, N., Zhu, Y., Qu, F., Xu, L., Li, X., Zhang, G., Guo, H., Li, D., & Gan, W. (2021) · Journal of International Medical Research · doi:10.1177/0300060521997661 · Cited by 3
“3% specificity.(21) Scoring systems for identification of endometrial cancer or atypical hyperplasia can likewise provide a high diagnostic value.”
Background
Application of O‐RADS Ultrasound Lexicon‐Based Logistic Regression Analysis Model in the Diagnosis of Solid Component‐Containing Ovarian Malignancies
Luo, H., Lin, Z., Wu, L., Wang, Y., Ning, H., Feng, Y., Cheng, Y., Wen, X., & Liu, X. (2022) · BioMed Research International · doi:10.1155/2022/7187334 · Cited by 4
“…preoperative diagnostic accuracy of ovarian tumors, many ultrasound-based integrated scoring systems have been proposed and used, such as Risk of Malignancy Index, gynecologic imaging-RADS, International Ovarian Tumor Analysis logistic regression models, simpli ﬁ ed rules, and ADNEX mode [6 – 9].”
Accuracy of machine learning in the preoperative identification of ovarian borderline tumors: a meta-analysis
Qi, L., Li, X., Yang, Y. S., Zhao, M., Lin, A., & Ma, L. (2024) · Clinical Radiology · doi:10.1016/j.crad.2024.02.012 · Cited by 3
Correlation of ovarian adnexal reporting and data system classification with histopathological examination in diagnosis of adnexal masses
Takkar, N., Arora, P., Goel, B., Kaur, R., Kaur, N., & Aggarwal, P. (2025) · International Journal of Reproduction Contraception Obstetrics and Gynecology · doi:10.18203/2320-1770.ijrcog20250197 · Cited by 3
Integrating ultrasound-CT-MR for preoperative multi-task prediction in ovarian cancer: achieving diagnostic parity with multidisciplinary team consensus
Yu, J., Hu, P., Dai, R., Liu, X., Zhang, S., Xu, Y., Gao, Y., Lü, B., Wang, W., Niu, Y., et al. (2026) · npj Digital Medicine · doi:10.1038/s41746-026-02875-0 · Cited by 3
“27,47 .”
Comparison of sensitivity for Risk of Ovarian Malignancy Algorithm (ROMA) and Assessment of Different NEoplasias in the adneXa (ADNEX) model for predicting ovarian cancer in a woman with adnexal masses
Tangjanyatham, P., & Chaowawanit, W. (2025) · International Journal of Gynecological Cancer · doi:10.1016/j.ijgc.2025.101827 · Cited by 3
Head-to-head comparison of the RMI and ADNEX models to estimate the risk of ovarian malignancy: a systematic review and meta-analysis of external validation studies
Barreñada, L., Ledger, A., Kotlarz, A., Dhiman, P., Collins, P. G. S., Wynants, L., Verbakel, J. Y. J., Valentin, L., Timmerman, D., & CALSTER, B. V. (2025) · BMJ Open · doi:10.1136/bmjopen-2025-104141 · Cited by 3
Case Report: Borderline tumor and primary peritoneal carcinoma - a rare synchronism
Rei, M., Raposo, S., Figueiredo, P., Sousa, R. G., & Sá, L. (2019) · F1000Research · doi:10.12688/f1000research.20420.1 · Cited by 3
Ultrasound features of polypoid endometriosis: a case report and a short review of Literature
Mancarella, M., Sgrò, L. G., Fuso, L., Campisi, P., Biglia, N., & Mariani, L. L. (2021) · Journal of Endometriosis and Pelvic Pain Disorders · doi:10.1177/22840265211053093 · Cited by 3
Diffusion-weighted magnetic resonance sequence and CA125/CEA ratio can be used as add-on tools to ultrasound for the differentiation of ovarian from non-ovarian pelvic masses
Pereira, P. N., Derchain, S., Yoshida, A., Barros, R. H. D. O., Jales, R. M., & Sarian, L. O. (2023) · PLoS ONE · doi:10.1371/journal.pone.0283212 · Cited by 3
“The ultrasound (US) and cancer antigen 125 (CA125)-based malignancy prediction model of the International Ovarian Tumor Analysis (IOTA) group called ADNEX has been designed to categorize adnexal masses as benign, borderline, malignant (initial, advanced) or metastatic [7].”
Background
Subjective assessment and IOTA ADNEX model in evaluation of adnexal masses in patients with history of breast cancer
Pozzati, F., Sassu, C. M., Marini, G., Mascilini, F., Biscione, A., Giannarelli, D., Garganese, G., Fragomeni, S. M., Scambia, G., Testa, A. C., et al. (2023) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.26253 · Cited by 3

Authors: Van Calster, B., Van Hoorde, K., Valentin, L., Testa, A. C., Fischerova, D., Van Holsbeke, C., Savelli, L., Franchi, D., Epstein, E., Kaijser, J., Van Belle, V., Czekierdowski, A., Guerriero, S., Fruscio, R., Lanzani, C., Scala, F., Bourne, T., Timmerman, D., & International Ovarian Tumour Analysis (IOTA) group
Affiliations: Lund University (SE)
Università Cattolica del Sacro Cuore (IT)
IRCCS Azienda Ospedliero-Universitaria di Bologna Policlinico di Sant'Orsola (IT)
European Institute of Oncology (IT)
Karolinska University Hospital (SE)
Universitair Ziekenhuis Leuven (BE)
Medical University of Lublin (PL)
Azienda Ospedaliero-Universitaria Cagliari (IT)
University of Milan (IT)
Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale" (IT)
ORCID: Valentin, L.
Testa, A. C.
Savelli, L.
Franchi, D.
Epstein, E.
Kaijser, J.
Czekierdowski, A.
Guerriero, S.
Fruscio, R.
Bourne, T.
Timmerman, D.
Venue: BMJ
Publisher: BMJ
Published: 2014-10-15
Volume: 349
Issue: oct07 3
Pages: g5920-g5920
ISSN: 1756-1833 (ISSN-L)
DOI: 10.1136/bmj.g5920
PMC: PMC4198550
OpenAlex: W2099878111
Cited by: 510
References: 57
Citations by year: 2026: 52 · 2025: 60 · 2024: 70 · 2023: 54 · 2022: 55 · 2021: 59 · 2020: 36 · 2019: 24 · 2018: 30 · 2017: 19 · 2016: 27 · 2015: 19 · 2014: 4
FWCI: 27.87
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc
Locations: BMJ (publishedVersion, cc-by-nc)
PubMed Central (publishedVersion, cc-by-nc)
PubMed (publishedVersion)
BOA (University of Milano-Bicocca) (submittedVersion, cc-by-nc)
Lirias (KU Leuven) (submittedVersion, cc-by-nc)
UNICA IRIS Institutional Research Information System (University of Cagliari) (submittedVersion, other-oa)
Lund University Publications (Lund University) (submittedVersion, other-oa)
HighWire Press Open Archive (submittedVersion)
PubliCatt (Università Cattolica del Sacro Cuore) (submittedVersion, cc-by-nc)
Spiral (Imperial College London) (submittedVersion, other-oa)
Funders: National Institute for Health and Care Research
Imperial College London
Imperial College Healthcare NHS Trust
Fonds Wetenschappelijk Onderzoek (G049312N)
iMinds
Malmö Högskola
Skånes universitetssjukhus
Vlaamse regering (G049312N)
Medical Research Council
Topics: Health Sciences › Medicine › Oncology › Ovarian cancer diagnosis and treatment
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › BRCA gene mutations in cancer
Health Sciences › Medicine › Pathology and Forensic Medicine › Breast Lesions and Carcinomas
Keywords: ovarian cancer, ADNEX model, preoperative risk prediction, ovarian ultrasonography, borderline ovarian tumors, CA125, surgical staging, adnexal mass, triage
MeSH terms: Adnexal Diseases, Adult, Female, Humans, Neoplasm Staging, Ovarian Neoplasms, Predictive Value of Tests, Prospective Studies, Ultrasonography, Models, Statistical, Risk Assessment

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Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study

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