Skip to main content
SpringerLink
Log in

How to improve O-RADS MRI score for rating adnexal masses with cystic component?

  • Urogenital
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To test the performance of the Ovarian-Adnexal Reporting Data System (O-RADS) MRI in characterizing adnexal masses with cystic components and to test new specific MRI features related to cystic components to improve the ability of the O-RADS MRI score to stratify lesions according to their risk of malignancy.

Methods

The EURopean ADnexal study (EURAD) database was retrospectively queried to identify adnexal masses with a cystic component. One junior and 13 radiologists independently reviewed cases blinded to the pathological diagnosis. For each lesion, the size of the whole lesion, morphological appearance, number of loculi, presence of a thickened wall, thickened septae, signal intensity of the cystic components on T1-weighted/T2-weighted/diffusion weighted, mean value of the apparent diffusion coefficient, and O-RADS MRI score were reported. Univariate and multivariate logistic regression analysis was performed to determine significant features to predict malignancy.

Results

The final cohort consisted of 585 patients with 779 pelvic masses who underwent pelvic MRI to characterize an adnexal mass(es). Histology served as the standard of reference. The diagnostic performance of the O-RADS MRI score was 0.944, 95%CI [0.922–0.961]. Significant criteria associated with malignancy included an O-RADS MRI score ≥ 4, ADCmean of cystic component > 1.69, number of loculi > 3, lesion size > 75 mm, the presence of a thick wall, and a low T1-weighted, a high T2-weighted, and a low diffusion-weighted signal intensity of the cystic component. Multivariate analysis demonstrated that an O-RADS MRI score ≥ combined with an ADC mean of the cystic component > 1.69, size > 75 mm, and low diffusion-weighted signal of the cystic component significantly improved the diagnostic performance up to 0.958, 95%CI [0.938–0.973].

Conclusion

Cystic component analysis may improve the diagnosis performance of the O-RADS MRI score in adnexal cystic masses.

Key Points

• O-RADS MRI score combined with specific cystic features (area under the receiving operating curve, AUROC = 0.958) improves the diagnostic performance of the O-RADS MRI score (AUROC = 0.944) for predicting malignancy in this cohort.

• Cystic features that improve the prediction of malignancy are ADC mean > 1.69 (OR = 7); number of loculi ≥ 3 (OR = 5.16); lesion size > 75 mm (OR = 4.40); the presence of a thick wall (OR = 3.59); a high T2-weighted signal intensity score 4 or 5 (OR = 3.30); a low T1-weighted signal intensity score 1, 2, or 3 (OR = 3.45); and a low diffusion-weighted signal intensity (OR = 2.12).

• An adnexal lesion with a cystic component rated O-RADS MRI score 4 and an ADC value of the cystic component < 1.69 associated with a low diffusion-weighted signal, has virtually a 0% risk of malignancy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

ADC:

Apparent diffusion coefficient

AUROC:

Area under the receiving operating curve

CI:

Confidence interval

DWI:

Diffusion-weighted imaging

ESUR:

European Society of Urogenital Radiology

EURAD:

EURopean ADnexal study

IOTA:

International Ovarian Tumor Analysis

MRI:

Magnetic resonance imaging

OR:

Odds ratio

O-RADS:

Ovarian-Adnexal Reporting Data System

PID:

Pelvic inflammatory disease

STD:

Standard deviation

TIC:

Time intensity curve

References

  1. Thomassin-Naggara I, Aubert E, Rockall A et al (2013) Adnexal masses: development and preliminary validation of an MR imaging scoring system. Radiology 267:432–443. https://doi.org/10.1148/radiol.13121161

    Article  PubMed  Google Scholar 

  2. Thomassin-Naggara I, Poncelet E, Jalaguier-Coudray A et al (2020) Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) score for risk stratification of sonographically indeterminate adnexal masses. JAMA Netw Open 3:e1919896. https://doi.org/10.1001/jamanetworkopen.2019.19896

    Article  PubMed  PubMed Central  Google Scholar 

  3. Thomassin-Naggara I, Belghitti M, Milon A et al (2021) O-RADS MRI score: analysis of misclassified cases in a prospective multicentric European cohort. Eur Radiol. https://doi.org/10.1007/s00330-021-08054-x

  4. Siegelman ES, Outwater EK (1999) Tissue characterization in the female pelvis by means of MR imaging. Radiology 212:5–18. https://doi.org/10.1148/radiology.212.1.r99jl455

    Article  CAS  PubMed  Google Scholar 

  5. McKee TC, Dave J, Kania L et al (2019) Are hemorrhagic cysts hyperintense enough on T1-weighted MRI to be distinguished from renal cell carcinomas? A retrospective analysis of 204 patients. AJR Am J Roentgenol 213:1267–1273. https://doi.org/10.2214/AJR.19.21257

    Article  PubMed  Google Scholar 

  6. Abraham AS, Simon B, Eapen A et al (2020) Role of cross-sectional imaging (CT/MRI) in characterization and distinguishing benign from malignant/potentially malignant cystic lesions of pancreas. J Clin Imaging Sci 10:28. https://doi.org/10.25259/JCIS_15_2020

    Article  PubMed  PubMed Central  Google Scholar 

  7. Bükte Y, Paksoy Y, Genç E, Uca AU (2005) Role of diffusion-weighted MR in differential diagnosis of intracranial cystic lesions. Clin Radiol 60:375–383. https://doi.org/10.1016/j.crad.2004.05.019

    Article  PubMed  Google Scholar 

  8. Nakayama T, Yoshimitsu K, Irie H et al (2005) Diffusion-weighted echo-planar MR imaging and ADC mapping in the differential diagnosis of ovarian cystic masses: usefulness of detecting keratinoid substances in mature cystic teratomas. J Magn Reson Imaging 22:271–278. https://doi.org/10.1002/jmri.20369

    Article  PubMed  Google Scholar 

  9. Wang T, Li W, Wu X et al (2016) Tubo-ovarian abscess (with/without pseudotumor area) mimicking ovarian malignancy: role of diffusion-weighted MR imaging with apparent diffusion coefficient values. PLoS One 11:e0149318. https://doi.org/10.1371/journal.pone.0149318

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Ghossain MA, Buy JN, Lignères C et al (1991) Epithelial tumors of the ovary: comparison of MR and CT findings. Radiology 181:863–870. https://doi.org/10.1148/radiology.181.3.1947112

    Article  CAS  PubMed  Google Scholar 

  11. Togashi K, Nishimura K, Itoh K et al (1987) Ovarian cystic teratomas: MR imaging. Radiology 162:669–673. https://doi.org/10.1148/radiology.162.3.3809479

    Article  CAS  PubMed  Google Scholar 

  12. Togashi K, Nishimura K, Kimura I et al (1991) Endometrial cysts: diagnosis with MR imaging. Radiology 180:73–78. https://doi.org/10.1148/radiology.180.1.2052726

    Article  CAS  PubMed  Google Scholar 

  13. Glastonbury CM (2002) The shading sign. Radiology 224:199–201. https://doi.org/10.1148/radiol.2241010361

    Article  PubMed  Google Scholar 

  14. Moteki T, Horikoshi H, Endo K (2002) Relationship between apparent diffusion coefficient and signal intensity in endometrial and other pelvic cysts. Magn Reson Imaging 20:463–470. https://doi.org/10.1016/S0730-725X(02)00524-6

    Article  PubMed  Google Scholar 

  15. Forstner R, Thomassin-Naggara I, Cunha TM et al (2017) ESUR recommendations for MR imaging of the sonographically indeterminate adnexal mass: an update. Eur Radiol 27:2248–2257. https://doi.org/10.1007/s00330-016-4600-3

    Article  PubMed  Google Scholar 

  16. Abdel Wahab C, Jannot A-S, Bonaffini PA et al (2020) Diagnostic algorithm to differentiate benign atypical leiomyomas from malignant uterine sarcomas with diffusion-weighted MRI. Radiology 297:361–371. https://doi.org/10.1148/radiol.2020191658

    Article  PubMed  Google Scholar 

  17. Stevens SK, Hricak H, Stern JL (1991) Ovarian lesions: detection and characterization with gadolinium-enhanced MR imaging at 1.5 T. Radiology 181:481–488. https://doi.org/10.1148/radiology.181.2.1924792

    Article  CAS  PubMed  Google Scholar 

  18. Chan JHM, Tsui EYK, Luk SH et al (2001) Diffusion-weighted MR imaging of the liver: distinguishing hepatic abscess from cystic or necrotic tumor. Abdom Imaging 26:161–165. https://doi.org/10.1007/s002610000122

    Article  CAS  PubMed  Google Scholar 

  19. Kim H-J, Lee S-Y, Shin YR et al (2016) The value of diffusion-weighted imaging in the differential diagnosis of ovarian lesions: a meta-analysis. PLoS One 11:e0149465. https://doi.org/10.1371/journal.pone.0149465

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Timmerman D, Ameye L, Fischerova D et al (2010) Simple ultrasound rules to distinguish between benign and malignant adnexal masses before surgery: prospective validation by IOTA group. BMJ 341:c6839–c6839. https://doi.org/10.1136/bmj.c6839

    Article  PubMed  PubMed Central  Google Scholar 

  21. Outwater E, Schiebler ML, Owen RS, Schnall MD (1993) Characterization of hemorrhagic adnexal lesions with MR imaging: blinded reader study. Radiology 186:489–494. https://doi.org/10.1148/radiology.186.2.8421756

    Article  CAS  PubMed  Google Scholar 

  22. Tanaka Y, Nakai G, Yamamura K et al (2019) Analysis of MRI values and hemoglobin and total protein concentrations of cystic ovarian tumors. J Magn Reson Imaging 49:1133–1140. https://doi.org/10.1002/jmri.26299

    Article  PubMed  Google Scholar 

Download references

Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Service de radiologie, Hôpital Tenon, Sorbonne Université, APHP, 75020, Paris, France

    Victoria Assouline, Marc Bazot & Isabelle Thomassin-Naggara

  2. Service de radiologie, Hôpital Tenon, Sorbonne Université, Institut Universitaire de Cancérologie, 75020, Paris, France

    Victoria Assouline, Yohann Dabi, Marc Bazot & Isabelle Thomassin-Naggara

  3. Service de gynécologie et obstétrique, Hôpital Tenon, Sorbonne Université, APHP, 75020, Paris, France

    Yohann Dabi

  4. Institut Paoli Calmettes, Marseille, France

    Aurélie Jalaguier-Coudray

  5. Centre for Radiology, Clinical Centre of Vojvodina, Medical Faculty, University of Novi Sad, Novi Sad, Serbia

    Sanja Stojanovic

  6. Department of Radiology, Lapeyronie Hospital, Montpellier, France

    Ingrid Millet

  7. Institut Desbrest d’Epidémiologie et de Santé Publique, IDESP UMR UA11 INSERM - Univ. Montpellier, Montpellier, France

    Ingrid Millet

  8. Department of Medical Imaging, McGill University Health Centre, Montreal, Canada

    Caroline Reinhold

Authors
  1. Victoria Assouline
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yohann Dabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aurélie Jalaguier-Coudray
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sanja Stojanovic
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ingrid Millet
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Caroline Reinhold
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Marc Bazot
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Isabelle Thomassin-Naggara
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

EURAD study group

Corresponding author

Correspondence to Victoria Assouline.

Ethics declarations

Guarantor:

The scientific guarantor of this publication is Isabelle Thomassin-Naggara.

Conflict of Interest:

The authors of this manuscript declare relationships with the following companies: Isabelle Thomassin-Naggara: General Electric, Hologic, Canon, Guerbet, ICAD (topic : breast imaging or endometriosis).

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and Biometry:

One of the authors has significant statistical expertise.

Informed Consent:

Written informed consent was obtained from all subjects (patients) in this study.

Ethical Approval:

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap:Some study subjects or cohorts have been previously reported in:

1. Thomassin-Naggara I, Poncelet E, Jalaguier-Coudray A, et al (2020) Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) score for risk stratification of sonographically indeterminate adnexal masses. JAMA Netw Open 3:e1919896. 10.1001/jamanetworkopen.2019.19896

2. On behalf of EURAD study group, Thomassin-Naggara I, Belghitti M, et al (2021) O-RADS MRI score: analysis of misclassified cases in a prospective multicentric European cohort. Eur Radiol. 10.1007/s00330-021-08054-x

Methodology

• retrospective

• diagnostic or prognostic study

• multicenter study

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

EURAD study group: I. Thomassin-Naggara, MD, PhD; E.Poncelet, MD; A. Jalaguier-Coudray, MD; A. Guerra, MD; L.S. Fournier, MD, PhD; S. Stojanovic, MD, PhD; I. Millet, MD, PhD; N. Bharwani, FRCR; V. Juhan, MD; T. M. Cunha, MD; G. Masselli, MD, PhD; C. Balleyguier, MD, PhD; C. Malhaire, MD; N. Perrot, MD; M. Bazot, MD; P. Taourel, MD, PhD, MSC; E. Darai, MD, PhD; and A.G. Rockall, MRCP, FRCR

Supplementary Information

ESM 1

(DOCX 24 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Assouline, V., Dabi, Y., Jalaguier-Coudray, A. et al. How to improve O-RADS MRI score for rating adnexal masses with cystic component?. Eur Radiol 32, 5943–5953 (2022). https://doi.org/10.1007/s00330-022-08644-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-022-08644-3

Keywords

Search

Navigation