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Ovarian cancer reporting lexicon for computed tomography (CT) and magnetic resonance (MR) imaging developed by the SAR Uterine and Ovarian Cancer Disease-Focused Panel and the ESUR Female Pelvic Imaging Working Group

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Abstract

Objectives

Imaging evaluation is an essential part of treatment planning for patients with ovarian cancer. Variation in the terminology used for describing ovarian cancer on computed tomography (CT) and magnetic resonance (MR) imaging can lead to ambiguity and inconsistency in clinical radiology reports. The aim of this collaborative project between Society of Abdominal Radiology (SAR) Uterine and Ovarian Cancer (UOC) Disease-focused Panel (DFP) and the European Society of Uroradiology (ESUR) Female Pelvic Imaging (FPI) Working Group was to develop an ovarian cancer reporting lexicon for CT and MR imaging.

Methods

Twenty-one members of the SAR UOC DFP and ESUR FPI working group, one radiology clinical fellow, and two gynecologic oncology surgeons formed the Ovarian Cancer Reporting Lexicon Committee. Two attending radiologist members of the committee prepared a preliminary list of imaging terms that was sent as an online survey to 173 radiologists and gynecologic oncologic physicians, of whom 67 responded to the survey. The committee reviewed these responses to create a final consensus list of lexicon terms.

Results

An ovarian cancer reporting lexicon was created for CT and MR Imaging. This consensus-based lexicon has 6 major categories of terms: general, adnexal lesion-specific, peritoneal carcinomatosis-specific, lymph node-specific, metastatic disease -specific, and fluid-specific.

Conclusions

: This lexicon for CT and MR imaging evaluation of ovarian cancer patients has the capacity to improve the clarity and consistency of reporting disease sites seen on imaging.

Key Points

• This reporting lexicon for CT and MR imaging provides a list of consensus-based, standardized terms and definitions for reporting sites of ovarian cancer on imaging at initial diagnosis or follow-up.

• Use of standardized terms and morphologic imaging descriptors can help improve interdisciplinary communication of disease extent and facilitate optimal patient management.

• The radiologists should identify and communicate areas of disease, including difficult to resect or potentially unresectable disease that may limit the ability to achieve optimal resection.

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Fig. 1

Abbreviations

ACR:

American College of Radiology

CT:

Computed tomography

ESUR FPI:

European Society of Uroradiology Female Pelvic Imaging Working Group

MR:

Magnetic resonance

O-RADS:

Ovarian-Adnexal Reporting & Data System

PET/CT:

Positron emission tomography/computed tomography

SAR:

Society of Abdominal Radiology

UOC DFP:

Uterine and Ovarian Cancer Disease-Focused Panel

References

  1. Ovarian Cancer Statistics – Ovarian Cancer Research Alliance. In: OCRA. https://ocrahope.org/patients/about-ovarian-cancer/statistics/. Accessed 16 Mar 2020

  2. Torre LA, Trabert B, DeSantis CE et al (2018) Ovarian cancer statistics, 2018. CA Cancer J Clin 68:284–296. https://doi.org/10.3322/caac.21456

    Article  PubMed  PubMed Central  Google Scholar 

  3. Chi DS, Musa F, Dao F et al (2012) An analysis of patients with bulky advanced stage ovarian, tubal, and peritoneal carcinoma treated with primary debulking surgery (PDS) during an identical time period as the randomized EORTC-NCIC trial of PDS vs neoadjuvant chemotherapy (NACT). Gynecol Oncol 124:10–14. https://doi.org/10.1016/j.ygyno.2011.08.014

    Article  PubMed  Google Scholar 

  4. Forstner R, Sala E, Kinkel K et al (2010) ESUR guidelines: ovarian cancer staging and follow-up. Eur Radiol 20:2773–2780. https://doi.org/10.1007/s00330-010-1886-4

    Article  PubMed  Google Scholar 

  5. Expert Panel on Women’s Imaging:, Kang SK, Reinhold C, et al (2018) ACR Appropriateness Criteria® staging and follow-up of ovarian cancer. J Am Coll Radiol 15:S198–S207https://doi.org/10.1016/j.jacr.2018.03.015

  6. Suidan RS, Ramirez PT, Sarasohn DM et al (2017) A multicenter assessment of the ability of preoperative computed tomography scan and CA-125 to predict gross residual disease at primary debulking for advanced epithelial ovarian cancer. Gynecol Oncol 145:27–31. https://doi.org/10.1016/j.ygyno.2017.02.020

    Article  PubMed  PubMed Central  Google Scholar 

  7. Rizzo S, De Piano F, Buscarino V et al (2020) Pre-operative evaluation of epithelial ovarian cancer patients: role of whole body diffusion weighted imaging MR and CT scans in the selection of patients suitable for primary debulking surgery. A single-centre study Eur J Radiol 123:108786. https://doi.org/10.1016/j.ejrad.2019.108786

    Article  PubMed  Google Scholar 

  8. Castellani F, Nganga EC, Dumas L et al (2019) Imaging in the pre-operative staging of ovarian cancer. Abdom Radiol (NY) 44:685–696. https://doi.org/10.1007/s00261-018-1779-6

    Article  Google Scholar 

  9. Chandrashekhara SH, Triveni GS, Kumar R (2016) Imaging of peritoneal deposits in ovarian cancer: A pictorial review. World J Radiol 8:513–517. https://doi.org/10.4329/wjr.v8.i5.513

    Article  PubMed  PubMed Central  Google Scholar 

  10. Elsayes KM, Kielar AZ, Chernyak V et al (2019) LI-RADS: a conceptual and historical review from its beginning to its recent integration into AASLD clinical practice guidance. J Hepatocell Carcinoma 6:49–69. https://doi.org/10.2147/JHC.S186239

    Article  PubMed  PubMed Central  Google Scholar 

  11. Grant EG, Tessler FN, Hoang JK et al (2015) Thyroid ultrasound reporting lexicon: white paper of the ACR Thyroid Imaging, Reporting and Data System (TIRADS) Committee. J Am Coll Radiol 12:1272–1279. https://doi.org/10.1016/j.jacr.2015.07.011

    Article  PubMed  Google Scholar 

  12. Weinreb JC, Barentsz JO, Choyke PL et al (2016) PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol 69:16–40. https://doi.org/10.1016/j.eururo.2015.08.052

    Article  PubMed  Google Scholar 

  13. D’Orsi CJ SE, et al (2013) ACR BI-RADS® Atlas, Breast Imaging Reporting and Data System. Reston, VA, American College of Radiology

  14. Andreotti RF, Timmerman D, Strachowski LM et al (2020) O-RADS US Risk Stratification and Management System: a consensus guideline from the ACR Ovarian-Adnexal Reporting and Data System Committee. Radiology 294:168–185. https://doi.org/10.1148/radiol.2019191150

    Article  PubMed  Google Scholar 

  15. Burnside ES, Sickles EA, Bassett LW et al (2009) The ACR BI-RADS experience: learning from history. J Am Coll Radiol 6:851–860. https://doi.org/10.1016/j.jacr.2009.07.023

    Article  PubMed  PubMed Central  Google Scholar 

  16. Chhatwal J, Alagoz O, Lindstrom MJ et al (2009) A logistic regression model based on the national mammography database format to aid breast cancer diagnosis. AJR Am J Roentgenol 192:1117–1127. https://doi.org/10.2214/AJR.07.3345

    Article  PubMed  PubMed Central  Google Scholar 

  17. Lee B, Whitehead MT (2017) Radiology reports: what YOU think you’re saying and what they think you’re saying. Curr Probl Diagn Radiol 46:186–195. https://doi.org/10.1067/j.cpradiol.2016.11.005

    Article  PubMed  Google Scholar 

  18. Magnetta MJ, Donovan AL, Jacobs BL et al (2018) Evidence-based reporting: a method to optimize prostate MRI communications with referring physicians. AJR Am J Roentgenol 210:108–112. https://doi.org/10.2214/AJR.17.18260

    Article  PubMed  Google Scholar 

  19. Wibmer A, Vargas HA, Sosa R et al (2014) Value of a standardized lexicon for reporting levels of diagnostic certainty in prostate MRI. AJR Am J Roentgenol 203:W651-657. https://doi.org/10.2214/AJR.14.12654

    Article  PubMed  Google Scholar 

  20. Franconeri A, Boos J, Fang J et al (2019) Adnexal mass staging CT with a disease-specific structured report compared to simple structured report. Eur Radiol 29:4851–4860. https://doi.org/10.1007/s00330-019-06037-7

    Article  PubMed  Google Scholar 

  21. Margolies LR, Pandey G, Horowitz ER, Mendelson DS (2016) Breast imaging in the era of big data: structured reporting and data mining. AJR Am J Roentgenol 206:259–264. https://doi.org/10.2214/AJR.15.15396

    Article  PubMed  Google Scholar 

  22. O-RADS MR Lexicon categories, terms and definitions. https://www.acr.org/-/media/ACR/Files/RADS/O-RADS/O-RADS-MR-Lexicon-Terms-Table-November-2020.pdf. Accessed 31 Oct 2020

  23. ISRCTN - ISRCTN51246892: MR in ovarian cancer. http://www.isrctn.com/ISRCTN51246892. Accessed 31 Oct 2020

  24. Eisenhauer EA, Therasse P, Bogaerts J et al (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 45:228–247. https://doi.org/10.1016/j.ejca.2008.10.026

    Article  CAS  PubMed  Google Scholar 

  25. Prat J, FIGO Committee on Gynecologic Oncology (2014) Staging classification for cancer of the ovary, fallopian tube, and peritoneum. Int J Gynaecol Obstet 124:1–5https://doi.org/10.1016/j.ijgo.2013.10.001

  26. Berek JS, Kehoe ST, Kumar L, Friedlander M (2018) Cancer of the ovary, fallopian tube, and peritoneum. Int J Gynaecol Obstet 143(Suppl 2):59–78. https://doi.org/10.1002/ijgo.12614

    Article  PubMed  Google Scholar 

  27. Eskander RN, Kauderer J, Tewari KS et al (2018) Correlation between surgeon’s assessment and radiographic evaluation of residual disease in women with advanced stage ovarian cancer reported to have undergone optimal surgical cytoreduction: an NRG Oncology/Gynecologic Oncology Group study. Gynecol Oncol 149:525–530. https://doi.org/10.1016/j.ygyno.2018.03.043

    Article  PubMed  PubMed Central  Google Scholar 

  28. O’Neill AC, Somarouthu B, Tirumani SH et al (2017) Patterns and prognostic importance of hepatic involvement in patients with serous ovarian cancer: a single-institution experience with 244 patients. Radiology 282:160–170. https://doi.org/10.1148/radiol.2016152595

    Article  PubMed  Google Scholar 

  29. Andreotti RF, Timmerman D, Benacerraf BR et al (2018) Ovarian-adnexal reporting lexicon for ultrasound: a white paper of the ACR Ovarian-Adnexal Reporting and Data System Committee. J Am Coll Radiol 15:1415–1429. https://doi.org/10.1016/j.jacr.2018.07.004

    Article  PubMed  Google Scholar 

  30. Pannu HK, Bristow RE, Montz FJ, Fishman EK (2003) Multidetector CT of peritoneal carcinomatosis from ovarian cancer. Radiographics 23:687–701. https://doi.org/10.1148/rg.233025105

  31. Pannu HK, Oliphant M (2015) The subperitoneal space and peritoneal cavity: basic concepts. Abdom Imaging 40:2710–2722. https://doi.org/10.1007/s00261-015-0429-5

    Article  PubMed  PubMed Central  Google Scholar 

  32. Hauptmann S, Friedrich K, Redline R, Avril S (2017) Ovarian borderline tumors in the 2014 WHO classification: evolving concepts and diagnostic criteria. Virchows Arch 470:125–142. https://doi.org/10.1007/s00428-016-2040-8

    Article  CAS  PubMed  Google Scholar 

  33. Hansell DM, Bankier AA, MacMahon H et al (2008) Fleischner Society: glossary of terms for thoracic imaging. Radiology 246:697–722. https://doi.org/10.1148/radiol.2462070712

    Article  PubMed  Google Scholar 

  34. Vargas HA, Huang EP, Lakhman Y et al (2017) Radiogenomics of high-grade serous ovarian cancer: multireader multi-institutional study from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group. Radiology 285:482–492. https://doi.org/10.1148/radiol.2017161870

    Article  PubMed  Google Scholar 

  35. NCI dictionary of cancer terms (2011) In: Natl. Cancer Inst. https://www.cancer.gov/publications/dictionaries/cancer-terms. Accessed 8 Aug 2019

  36. Seltzer SE (1987) Analysis of the tethered-bowel sign on abdominal CT as a predictor of malignant ascites. Gastrointest Radiol 12:245–249

    Article  CAS  PubMed  Google Scholar 

  37. Tirkes T, Sandrasegaran K, Patel AA, et al (2012) Peritoneal and retroperitoneal anatomy and its relevance for cross-sectional imaging. Radiographics 32:437–451. https://doi.org/10.1148/rg.322115032

  38. Brink JA, Wagner BJ (2018) Pathways for the spread of disease in the abdomen and pelvis. In: Hodler J, Kubik-Huch RA, von Schulthess GK (eds) Diseases of the abdomen and pelvis 2018–2021: diagnostic imaging - IDKD Book. Springer International Publishing, Cham, pp 57–65

    Chapter  Google Scholar 

  39. Nougaret S, Addley HC, Colombo PE, et al (2012) Ovarian carcinomatosis: how the radiologist can help plan the surgical approach. Radiographics 32:1775–1800; discussion 1800–1803. https://doi.org/10.1148/rg.326125511

  40. Nougaret S, Lakhman Y, Reinhold C, et al (2016) The wheel of the mesentery: imaging spectrum of primary and secondary mesenteric neoplasms--how can radiologists help plan treatment?: resident and fellow education feature. Radiographics 36:412–413. https://doi.org/10.1148/rg.2016150186

  41. Auh YH, Rubenstein WA, Markisz JA et al (1986) Intraperitoneal paravesical spaces: CT delineation with US correlation. Radiology 159:311–317. https://doi.org/10.1148/radiology.159.2.3515415

    Article  CAS  PubMed  Google Scholar 

  42. Sahdev A (2016) CT in ovarian cancer staging: how to review and report with emphasis on abdominal and pelvic disease for surgical planning. Cancer Imaging 16:19. https://doi.org/10.1186/s40644-016-0076-2

    Article  PubMed  PubMed Central  Google Scholar 

  43. Jager GJ, Barentsz JO, Oosterhof GO et al (1996) Pelvic adenopathy in prostatic and urinary bladder carcinoma: MR imaging with a three-dimensional TI-weighted magnetization-prepared-rapid gradient-echo sequence. AJR Am J Roentgenol 167:1503–1507. https://doi.org/10.2214/ajr.167.6.8956585

    Article  CAS  PubMed  Google Scholar 

  44. Rockall AG, Sohaib SA, Harisinghani MG et al (2005) Diagnostic performance of nanoparticle-enhanced magnetic resonance imaging in the diagnosis of lymph node metastases in patients with endometrial and cervical cancer. J Clin Oncol 23:2813–2821. https://doi.org/10.1200/JCO.2005.07.166

    Article  PubMed  Google Scholar 

  45. Ganeshalingam S, Koh D-M (2009) Nodal staging. Cancer Imaging 9:104–111. https://doi.org/10.1102/1470-7330.2009.0017

    Article  PubMed  PubMed Central  Google Scholar 

  46. Shinagare AB, Davenport MS, Park H et al (2020) Lexicon for renal mass terms at CT and MRI: a consensus of the society of abdominal radiology disease-focused panel on renal cell carcinoma. Abdom Radiol (NY). https://doi.org/10.1007/s00261-020-02644-x

    Article  Google Scholar 

  47. Go JL, Zee CS (1998) Unique CT imaging advantages. Hemorrhage and calcification. Neuroimaging Clin N Am 8:541–558

    CAS  PubMed  Google Scholar 

  48. El-Sherief AH, Lau CT, Wu CC, et al (2014) International association for the study of lung cancer (IASLC) lymph node map: radiologic review with CT illustration. Radiographics 34:1680–1691. https://doi.org/10.1148/rg.346130097

  49. Bazemore AW, Smucker DR (2002) Lymphadenopathy and malignancy. Am Fam Physician 66:2103–2110

    PubMed  Google Scholar 

  50. Efremidou EI (2012) Surgical anatomy of the axilla. Hell J Surg 84:128–133. https://doi.org/10.1007/s13126-012-0015-z

    Article  Google Scholar 

  51. McIntosh LJ, O’Neill AC, Bhanusupriya S et al (2017) Prognostic significance of supradiaphragmatic lymph nodes at initial presentation in patients with stage III high-grade serous ovarian cancer. Abdom Radiol (NY) 42:2513–2520. https://doi.org/10.1007/s00261-017-1158-8

    Article  CAS  Google Scholar 

  52. Hynninen J, Auranen A, Carpén O et al (2012) FDG PET/CT in staging of advanced epithelial ovarian cancer: frequency of supradiaphragmatic lymph node metastasis challenges the traditional pattern of disease spread. Gynecol Oncol 126:64–68. https://doi.org/10.1016/j.ygyno.2012.04.023

    Article  PubMed  Google Scholar 

  53. Restrepo CS, Eraso A, Ocazionez D, et al (2008) The diaphragmatic crura and retrocrural space: normal imaging appearance, variants, and pathologic conditions. Radiographics 28:1289–1305. https://doi.org/10.1148/rg.285075187

  54. Im H-J, Kim Y-I, Paeng JC et al (2012) Retrocrural lymph node metastasis disclosed by (18)F-FDG PET/CT: a predictor of supra-diaphragmatic spread in ovarian cancer. Nucl Med Mol Imaging 46:41–47. https://doi.org/10.1007/s13139-011-0115-7

    Article  PubMed  Google Scholar 

  55. Mirilas P, Skandalakis JE (2010) Surgical anatomy of the retroperitoneal spaces, Part III: retroperitoneal blood vessels and lymphatics. Am Surg 76:139–144

    Article  PubMed  Google Scholar 

  56. Lucey BC, Stuhlfaut JW, Soto JA (2005) Mesenteric lymph nodes seen at imaging: causes and significance. Radiographics 25:351–365. https://doi.org/10.1148/rg.252045108

  57. Valentini V, Gambacorta MA, Barbaro B et al (2016) International consensus guidelines on clinical target volume delineation in rectal cancer. Radiother Oncol 120:195–201. https://doi.org/10.1016/j.radonc.2016.07.017

    Article  PubMed  Google Scholar 

  58. Bontumasi N, Jacobson JA, Caoili E, Brandon C, Kim SM, Jamadar D (2014) Inguinal lymph nodes: size, number, and other characteristics in asymptomatic patients by CT. Surg Radiol Anat 36:1051–1055. https://doi.org/10.1007/s00276-014-1255-0

  59. Akin O, Sala E, Moskowitz CS et al (2008) Perihepatic metastases from ovarian cancer: sensitivity and specificity of CT for the detection of metastases with and those without liver parenchymal invasion. Radiology 248:511–517. https://doi.org/10.1148/radiol.2482070371

    Article  PubMed  Google Scholar 

  60. Kerr VE, Cadman E (1985) Pulmonary metastases in ovarian cancer. Analysis of 357 patients. Cancer 56:1209–1213. https://doi.org/10.1002/1097-0142(19850901)56:5%3c1209::aid-cncr2820560542%3e3.0.co;2-y

    Article  CAS  PubMed  Google Scholar 

  61. Shinagare AB, O’Neill AC, Cheng S et al (2015) Advanced high-grade serous ovarian cancer: frequency and timing of thoracic metastases and the implications for chest imaging follow-up. Radiology 277:733–740. https://doi.org/10.1148/radiol.2015142467

    Article  PubMed  Google Scholar 

  62. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) Ovarian cancer—ovarian.pdf.

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Funding

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

Author information

Author notes

  1. Elizabeth Sadowski contributed equally to the first author.

Authors and Affiliations

  1. Department of Radiology, Brigham and Women’s Hospital/Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA

    Atul B. Shinagare & Hyesun Park

  2. Departments of Radiology, Obstetrics and Gynecology, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, E3/372, Madison, WI, 53792-3252, USA

    Elizabeth A. Sadowski

  3. Beth Israel Deaconess Medical Center, 1 Deaconess Rd, Boston, MA, 02215, USA

    Olga R. Brook

  4. Department of Radiology, Universitätsklinikum Salzburg, PMU Salzburg, Müllner Hauptstr. 48, 5020, Salzburg, Austria

    Rosemarie Forstner

  5. Division of Gynecologic Oncology, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave. H4/664A, Madison, WI, 53792, USA

    Sumer K. Wallace

  6. Department of Radiology, Northwestern University Feinberg School of Medicine, 676 N Saint Clair, Chicago, IL, 60611, USA

    Jeanne M. Horowitz

  7. Division of Gynecologic Oncology, Brigham and Women’s Hospital, 75 Francis Street, Boston, MA, 02115, USA

    Neil Horowitz

  8. Medical Imaging, Rambam Health Care Campus, Haifa, Israel

    Marcia Javitt

  9. Department of Radiology, University of California San Francisco, 505 Parnassus Avenue, Box 0628, San Francisco, CA, 94143-0628, USA

    Priyanka Jha

  10. Department of Diagnostic Radiology and Nuclear Medicine, Kyoto University Hospital, 54 Shogoinkawahara-cho, Sakyo-ku, Kyoto City, Kyoto, 6068507, Japan

    Aki Kido

  11. Department of Radiology, Memorial Sloan Kettering Cancer Center, 300 East 66 Street, New York, NY, 10065, USA

    Yulia Lakhman & Herbert Alberto Vargas

  12. Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114, USA

    Susanna I. Lee

  13. Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, V.le Regina Elena, 324 00161, Rome, Italy

    Lucia Manganaro

  14. Department of Radiology and Obstetrics and Gynecology, University of Michigan Hospitals, 1500 E Med Ctr Dr, Ann Arbor, MI, 48109, USA

    Katherine E. Maturen

  15. Department of Radiology, IRCM INSERM, U1194 SIRIC, Montpellier, France

    Stephanie Nougaret

  16. Department of Radiology and Biomedical Imaging, Obstetrics, Gynecology and Reproductive Sciences, UCSF, 505 Parnassus Ave, L-374, San Francisco, CA, 94143-0628, USA

    Liina Poder

  17. University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA

    Gaiane M. Rauch

  18. Augmented Intelligence & Precision Health Laboratory of the Research Institute of McGill University Health Centre, McGill University, Montreal, Canada, 1001 Decarie boul., Montreal, Quebec, H4A 3J1, Canada

    Caroline Reinhold

  19. Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK

    Evis Sala

  20. Sorbonne Université, Assistance Publique – Hôpitaux de Paris, Service d’Imagerie, 4 rue de la Chine, 75020, Paris, France

    Isabelle Thomassin-Naggara

  21. Division of Diagnostic Imaging, Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., FCT 15.6074, MSC 1182, Houston, TX, 77030, USA

    Aradhana Venkatesan

  22. Clinical Center of Vojvodina, Center of Radiology, Faculty of Medicine, University of Novi Sad, 1-9 Hajduk Veljkova str. 21000, Novi Sad, Serbia

    Olivera Nikolic

  23. Division of Surgery and Cancer, Imperial College London, Hammersmith Campus, ICTEM Building, Du Cane Rd, London, W12 0NN, UK

    Andrea G. Rockall

Authors
  1. Atul B. Shinagare
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  2. Elizabeth A. Sadowski
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  3. Hyesun Park
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  4. Olga R. Brook
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  5. Rosemarie Forstner
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  6. Sumer K. Wallace
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  7. Jeanne M. Horowitz
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  8. Neil Horowitz
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  9. Marcia Javitt
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  10. Priyanka Jha
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  11. Aki Kido
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  12. Yulia Lakhman
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  13. Susanna I. Lee
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  14. Lucia Manganaro
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  15. Katherine E. Maturen
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  21. Isabelle Thomassin-Naggara
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  22. Herbert Alberto Vargas
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  23. Aradhana Venkatesan
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  24. Olivera Nikolic
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  25. Andrea G. Rockall
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Corresponding author

Correspondence to Atul B. Shinagare.

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Guarantor

The scientific guarantors of this publication are Atul Shinagare, Elizabeth Sadowski, and Andrea Rockall.

Conflict of interest

The authors of this manuscript declare the following relationships outside the subject matter:

Author: Atul B. Shinagare, MD.

Disclosures:

Not relevant to the subject of this paper: Consultant, Virtualscopics, Imaging Endpoints.

Author: Yulia Lakhman, MD.

Disclosures:

Yulia Lakhman was supported in part through the NIH/NCI Cancer Center Support Grant P30 CA008748 (paid to the institution).

outside the scope of this work: shareholder Y-mAbs Inc.

Name: Susanna I. Lee MD, PhD.

Disclosures:

Wolters-Kluwer and Springer (Royalties).

Author: Isabelle Thomassin-Naggara, MD, PhD.

Disclosures:

GE, Siemens, Hologic, Canon, Guebet (remunerated lecture in breast imaging not related to the subject of the paper).

Full name: Hebert Alberto Vargas, MD.

Disclosures:

Dr. Vargas is supported in part by a National Institutes of Health/National Cancer Institute Cancer Center Support Grant to Memorial Sloan Kettering Cancer Center (P30-CA008748).

Co-Author: Andrea Rockall, MBBS, MRCP, FRCR.

Disclosures:

Reports personal fees from Guerbet Laboratories, outside the submitted work. The institution received academic grants from the Imperial Cancer Research UK Centre and Imperial National Institute of Health Research Biomedical Research Centre, outside the submitted work.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was not required for this study because this was a quality improvement study that did not include human or animal subjects.

Ethical approval

Institutional Review Board approval was not required for this study because this was a quality improvement study that did not include human or animal subjects.

Study subjects or cohorts overlap

This study or part of it has not been previously reported. A summary of the study was presented as an oral presentation at RSNA 2020.

Methodology

• Multicenter expert consensus

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Shinagare, A.B., Sadowski, E.A., Park, H. et al. Ovarian cancer reporting lexicon for computed tomography (CT) and magnetic resonance (MR) imaging developed by the SAR Uterine and Ovarian Cancer Disease-Focused Panel and the ESUR Female Pelvic Imaging Working Group. Eur Radiol 32, 3220–3235 (2022). https://doi.org/10.1007/s00330-021-08390-y

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  • DOI: https://doi.org/10.1007/s00330-021-08390-y

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