Skip to main content

Advertisement

SpringerLink
Log in

MR Imaging of uterine sarcomas: a comprehensive review with radiologic-pathologic correlation

  • Review
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

The aim of this article is to summarize the MRI features of each sarcoma subtype and to correlate them with its pathological findings. Literature review through PubMed/Medline database to identify relevant articles on uterine sarcomas, with a special emphasis on their MRI findings and pathological features. While several, more generalistic, MRI findings of a uterine tumour should raise suspicion for malignancy (including irregular contour, intra-tumoral necrosis/hemorrhage and low ADC values), some particular features may suggest their specific histological subtype such as the gross lymphovascular invasion associated with endometrial stromal sarcomas, the “bag of worms” appearance of the low-grade endometrial stromal sarcoma and the “lattice-like” aspect of adenosarcomas which results from the mixed composition of solid and multiseptated cystic components. Knowledge of the different histological uterine sarcoma subtypes, their specific MRI features and comprehension of their pathological background allows for a more confident diagnosis and may indicate the correct histological subtype.

Graphic abstract

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
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Data availability

Not applicable.

Code availability

Not applicable.

Abbreviations

ADC:

Apparent diffusion coefficient

AS:

Adenosarcoma

ESS:

Endometrial stromal sarcoma

CA125:

Cancer antigen 125

CE-MRI:

Contrast-enhanced magnetic resonance imaging

DWI:

Diffusion-weighted imaging

HG-ESS:

High-grade endometrial stromal sarcoma

HLRCC:

Hereditary leiomyomatosis and renal cell carcinoma

LDH:

Lactate dehydrogenase

LG-ESS:

Low-grade endometrial stromal sarcoma

LM:

Leiomyoma

LMS:

Leiomyosarcoma

MRI:

Magnetic resonance imaging

T2WI:

T2-weighted imaging

SI:

Signal intensity

UUS:

Undifferentiated uterine sarcoma

References

  1. Memarzadeh S, Berek J (2019) Uterine sarcoma: Classification, epidemiology, clinical manifestations, and diagnosis. Uptodate. https://www.uptodate.com/contents/uterine-sarcoma-classification-epidemiology-clinical-manifestations-and-diagnosis. Accessed 28 June 2021

  2. F letcher CDM (2014) The evolving classification of soft tissue tumours - an update based on the new 2013 WHO classification. Histopathology 64:2–11. https://doi.org/https://doi.org/10.1111/his.12267

    Article  PubMed  Google Scholar 

  3. Koivisto-Korander R, Butzow R, Koivisto AM, Leminen A (2008) Clinical outcome and prognostic factors in 100 cases of uterine sarcoma: Experience in Helsinki University Central Hospital 1990-2001. Gynecol Oncol 111:74–81. https://doi.org/https://doi.org/10.1016/j.ygyno.2008.06.002

    Article  PubMed  Google Scholar 

  4. Kim K et al (2020) Tumours of the uterine corpus. In: WHO Classification of Tumours: Female Genital Tumours, 5th edn pp 245–308

  5. Brooks SE, Zhan M, Cote T, Baquet CR (2004) Surveillance, Epidemiology, and End Results analysis of 2677 cases of uterine sarcoma 1989-1999. Gynecol Oncol 93:204–208. https://doi.org/https://doi.org/10.1016/j.ygyno.2003.12.029

    Article  PubMed  Google Scholar 

  6. Felix AS et al. (2013) The etiology of uterine sarcomas: A pooled analysis of the epidemiology of endometrial cancer consortium. Br J Cancer 108:727–734. https://doi.org/https://doi.org/10.1038/bjc.2013.2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Schwartz SM et al. (1996) Exogenous sex hormone use, correlates of endogenous hormone levels, and the incidence of histologic types of sarcoma of the uterus. Cancer 77:717–724. https://doi.org/https://doi.org/10.1002/(SICI)1097-0142(19960215)77:4<717::AID-CNCR18>3.0.CO;2-3

    Article  CAS  PubMed  Google Scholar 

  8. Hosh M et al (2016) Uterine Sarcoma: Analysis of 13,089 Cases Based on Surveillance, Epidemiology, and End Results Database. Int J Gynecol Cancer 26:1098–104. https://doi.org/https://doi.org/10.1097/IGC.0000000000000720

    Article  PubMed  Google Scholar 

  9. Barral M et al (2017) Magnetic resonance imaging features of uterine sarcoma and mimickers. Abdom Radiol 42:1762–1772. https://doi.org/https://doi.org/10.1007/s00261-017-1076-9

    Article  Google Scholar 

  10. Chayed Z, Kristensen LK, Ousager LB, Rønlund K, Bygum A (2021) Hereditary leiomyomatosis and renal cell carcinoma: a case series and literature review. Orphanet J Rare Dis 16:34. https://doi.org/https://doi.org/10.1186/s13023-020-01653-9

    Article  PubMed  PubMed Central  Google Scholar 

  11. Hodge JC, Morton CC (2007) Genetic heterogeneity among uterine leiomyomata: Insights into malignant progression. Hum Mol Genet 16 Spec No 1:R7–13. https://doi.org/10.1093/hmg/ddm043

  12. Lakhman Y et al. (2017) Differentiation of Uterine Leiomyosarcoma from Atypical Leiomyoma: Diagnostic Accuracy of Qualitative MR Imaging Features and Feasibility of Texture Analysis. Eur Radiol 27:2903–2915. https://doi.org/https://doi.org/10.1007/s00330-016-4623-9

    Article  PubMed  Google Scholar 

  13. Skorstad M, Kent A, Lieng M (2016) Preoperative evaluation in women with uterine leiomyosarcoma. A nationwide cohort study. Acta Obstet Gynecol Scand 95:1228–1234. https://doi.org/https://doi.org/10.1111/aogs.13008

    Article  PubMed  Google Scholar 

  14. Bi Q et al. (2018) Utility of Clinical Parameters and Multiparametric MRI as Predictive Factors for Differentiating Uterine Sarcoma From Atypical Leiomyoma. Acad Radiol 25:993–1002. https://doi.org/https://doi.org/10.1016/j.acra.2018.01.002

    Article  PubMed  Google Scholar 

  15. Potikul C et al. (2016) Uterine sarcoma: Clinical presentation, treatment and survival outcomes in Thailand. Asian Pacific J Cancer Prev 17:1759–1767. https://doi.org/https://doi.org/10.7314/APJCP.2016.17.4.1759

    Article  Google Scholar 

  16. Tong A et al. (2019) MRI screening for uterine leiomyosarcoma. J Magn Reson Imaging 49:e282–e294. https://doi.org/10.1002/jmri.26630. https://doi.org/10.1002/jmri.26630

  17. Tropé CG, Abeler VM, Kristensen GB (2012) Diagnosis and treatment of sarcoma of the uterus. A review. Acta Oncol (Madr) 51:694–705. https://doi.org/https://doi.org/10.3109/0284186X.2012.689111

    Article  Google Scholar 

  18. Kaganov H, Ades A, Fraser DS (2018) Preoperative Magnetic Resonance Imaging Diagnostic Features of Uterine Leiomyosarcomas: A Systematic Review. Int J Technol Assess Health Care 34:172–179. https://doi.org/https://doi.org/10.1017/S0266462318000168

    Article  PubMed  Google Scholar 

  19. Zhao WC, Bi FF, Li D, Yang Q (2015) Incidence and clinical characteristics of unexpected uterine sarcoma after hysterectomy and myomectomy for uterine fibroids: A retrospective study of 10,248 cases. Onco Targets Ther 8:2943–2948. https://doi.org/https://doi.org/10.2147/OTT.S92978

    Article  PubMed  PubMed Central  Google Scholar 

  20. Li D et al. (2020) A real-world study on diagnosis and treatment of uterine sarcoma in Western China. Int J Biol Sci 16:388-395. https://doi.org/https://doi.org/10.7150/ijbs.39773

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kawamura N et al. (2002) Transcervical needle biopsy for the differential diagnosis between uterine sarcoma and leiomyoma. Cancer 94:1713–1720. https://doi.org/10.1002/cncr.10382

  22. Kawamura N. et al. (2002) Transcervical needle biopsy of uterine myoma-like tumors using an automatic biopsy gun. Fertil Steril 77:1060–1064. https://doi.org/https://doi.org/10.1016/S0015-0282(02)03064-9

    Article  PubMed  Google Scholar 

  23. Matsuda M. et al. (2014) Preoperative diagnosis of usual leiomyoma, atypical leiomyoma, and leiomyosarcoma. Sarcoma vol. 2014, Article ID 498682, 6 pages. https://doi.org/10.1155/2014/498682.

  24. Wais M et al. (2017) A Multicentre Retrospective Review of Clinical Characteristics of Uterine Sarcoma. J Obstet Gynaecol Canada 39:652–658. https://doi.org/https://doi.org/10.1016/j.jogc.2017.03.090

    Article  Google Scholar 

  25. Lucas R, Cunha TM (2016) Uterine Sarcomas. In MRI and CT of the Female Pelvis, 2nd ed. Medical Radiol, pp 209–224. https://doi.org/10.1007/174_2016_90

  26. Santos P, Cunha TM (2015) Uterine sarcomas: Clinical presentation and MRI features. Diagnostic Interv Radiol 21:4–9. https://doi.org/https://doi.org/10.5152/dir.2014.14053

    Article  Google Scholar 

  27. Lin G et al. (2016) Comparison of the diagnostic accuracy of contrast-enhanced MRI and diffusion-weighted MRI in the differentiation between uterine leiomyosarcoma / smooth muscle tumor with uncertain malignant potential and benign leiomyoma. J Magn Reson Imaging 43:333–342. https://doi.org/https://doi.org/10.1002/jmri.24998

    Article  PubMed  Google Scholar 

  28. Wahab CA et al. (2020) Diagnostic algorithm to differentiate benign atypical leiomyomas from malignant uterine sarcomas with diffusion-weighted MRI. Radiology 297:361–371 (2020). https://doi.org/https://doi.org/10.1148/RADIOL.2020191658

    Article  PubMed  Google Scholar 

  29. Juhasz-Böss I et al (2018) Uterine leiomyosarcoma. Oncol Res Treat 41:680–686. https://doi.org/https://doi.org/10.1159/000494299

    Article  PubMed  Google Scholar 

  30. Sato K, Yuasa N, Fujita M, Fukushima Y (2014) Clinical application of diffusion-weighted imaging for preoperative differentiation between uterine leiomyoma and leiomyosarcoma. Am J Obstet Gynecol 210:368.e1–368.e8. https://doi.org/https://doi.org/10.1016/j.ajog.2013.12.028

    Article  Google Scholar 

  31. Sumi A et al. (2015) Assessment of mr imaging as a tool to differentiate between the major histological types of uterine sarcomas. Magn Reson Med Sci 14:295–304. https://doi.org/https://doi.org/10.2463/mrms.2014-0023

    Article  PubMed  Google Scholar 

  32. Oliva E (2011) Practical issues in uterine pathology from banal to bewildering: The remarkable spectrum of smooth muscle neoplasia. Mod Pathol 29:S104–20. https://doi.org/10.1038/modpathol.2015.139

  33. Veras E et al. (2011) Low-grade leiomyosarcoma and late-recurring smooth muscle tumors of the uterus: A heterogenous collection of frequently misdiagnosed tumors associated with an overall favorable prognosis relative to conventional uterine leiomyosarcomas. Am J Surg Pathol 35:1626–1637 (2011). https://doi.org/https://doi.org/10.1097/PAS.0b013e31822b44d2

    Article  PubMed  Google Scholar 

  34. Huang YT, Huang YL, Ng KK, Lin G (2019) Current status of magnetic resonance imaging in patients with malignant uterine neoplasms: A review. Korean J Radiol 20:18–33. https://doi.org/https://doi.org/10.3348/kjr.2018.0090

    Article  PubMed  Google Scholar 

  35. DeMulder D, Ascher SM (2018) Uterine leiomyosarcoma: Can MRI differentiate leiomyosarcoma from benign leiomyoma before treatment? American Journal of Roentgenology 211:1405–1415. https://doi.org/https://doi.org/10.2214/AJR.17.19234

    Article  Google Scholar 

  36. Li HM et al. (2017) Diffusion-Weighted Imaging for Differentiating Uterine Leiomyosarcoma from Degenerated Leiomyoma. J Comput Assist Tomogr 41:599–606. https://doi.org/https://doi.org/10.1097/RCT.0000000000000565

    Article  CAS  PubMed  Google Scholar 

  37. Sun S et al. (2019) How to differentiate uterine leiomyosarcoma from leiomyoma with imaging. Diagn Interv Imaging 100:619–634. https://doi.org/https://doi.org/10.1016/j.diii.2019.07.007

    Article  CAS  PubMed  Google Scholar 

  38. Thomassin-Naggara I et al. (2013) How to differentiate benign from malignant myometrial tumours using MR imaging. Eur Radiol 23:2306–2314. https://doi.org/https://doi.org/10.1007/s00330-013-2819-9

    Article  PubMed  Google Scholar 

  39. Namimoto T et al. (2009) Combined use of T2-weighted and diffusion-weighted 3-T MR imaging for differentiating uterine sarcomas from benign leiomyomas. Eur Radiol 19:2756–2764. https://doi.org/https://doi.org/10.1007/s00330-009-1471-x

    Article  PubMed  Google Scholar 

  40. Nakagawa M et al. (2019) Machine Learning to Differentiate T2-Weighted Hyperintense Uterine Leiomyomas from Uterine Sarcomas by Utilizing Multiparametric Magnetic Resonance Quantitative Imaging Features. Acad Radiol 26:1390–1399. https://doi.org/https://doi.org/10.1016/j.acra.2018.11.014

    Article  PubMed  Google Scholar 

  41. Rio G, Lima M, Gil R, Horta M, Cunha TM (2019) T2 hyperintense myometrial tumors: can MRI features differentiate leiomyomas from leiomyosarcomas? Abdom Radiol 44:3388–3397. https://doi.org/https://doi.org/10.1007/s00261-019-02097-x

    Article  Google Scholar 

  42. Bi Q et al. (2020) The value of clinical parameters combined with magnetic resonance imaging (MRI) features for preoperatively distinguishing different subtypes of uterine sarcomas: An observational study (STROBE compliant). Med (United States) 99:e19787. https://doi.org/https://doi.org/10.1097/MD.0000000000019787

    Article  Google Scholar 

  43. Zhang GF, Zhang H, Tian XM, Zhang H (2014) Magnetic resonance and diffusion-weighted imaging in categorization of uterine sarcomas: Correlation with pathological findings. Clin Imaging 38:836–844. https://doi.org/https://doi.org/10.1016/j.clinimag.2014.06.004

    Article  PubMed  Google Scholar 

  44. Chan JK et al. (2008) Endometrial stromal sarcoma: A population-based analysis. Br J Cancer 99:1210–1215. https://doi.org/https://doi.org/10.1038/sj.bjc.6604527

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Seagle BLL, Shilpi A, Buchanan S, Goodman C, Shahabi S (2017) Low-grade and high-grade endometrial stromal sarcoma: A National Cancer Database study. Gynecol Oncol 146:254–262. https://doi.org/https://doi.org/10.1016/j.ygyno.2017.05.036

    Article  PubMed  Google Scholar 

  46. Koyama T et al. (1999) MR imaging of endometrial stromal sarcoma: Correlation with pathologic findings. Am J Roentgenol 173:767–772. https://doi.org/https://doi.org/10.2214/ajr.173.3.10470920

    Article  CAS  Google Scholar 

  47. Furukawa R et al. (2010) Endometrial stromal sarcoma located in the myometrium with a low-intensity rim on T2-weighted images: Report of three cases and literature review. J Magn Reson Imaging 31:975–979. https://doi.org/https://doi.org/10.1002/jmri.22126

    Article  PubMed  Google Scholar 

  48. NCCN Clinical Practice Guidelines in Oncology: Uterine Neoplasms (Version 3.2019). In National Comprehensive Cancer Network. https://www.nccn.org/login?ReturnURL=https://www.nccn.org/professionals/physician_gls/pdf/uterine.pdf. Accessed 22 April 2021

  49. Ferreira J, Félix A, Lennerz JK, Oliva E (2018) Recent advances in the histological and molecular classification of endometrial stromal neoplasms. Virchows Arch 473:665–678. https://doi.org/https://doi.org/10.1007/s00428-018-2470-6

    Article  PubMed  Google Scholar 

  50. Hoang L, Chiang S, Lee CH (2018) Endometrial stromal sarcomas and related neoplasms: new developments and diagnostic considerations. Pathology 50:162–177. https://doi.org/https://doi.org/10.1016/j.pathol.2017.11.086

    Article  CAS  PubMed  Google Scholar 

  51. Koontz JI et al. (2001) Frequent fusion of the JAZF1 and JJAZ1 genes in endometrial stromal tumors. Proc Natl Acad Sci USA 98:6348–6353. https://doi.org/https://doi.org/10.1073/pnas.101132598

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Chiang S et al. (2011) Frequency of known gene rearrangements in endometrial stromal tumors. Am J Surg Pathol 35:1364–1372. https://doi.org/https://doi.org/10.1097/PAS.0b013e3182262743

    Article  PubMed  Google Scholar 

  53. Huang YL et al. (2019) Utility of diffusion-weighted and contrast-enhanced magnetic resonance imaging in diagnosing and differentiating between high- and low-grade uterine endometrial stromal sarcoma. Cancer Imaging 19:63. https://doi.org/https://doi.org/10.1186/s40644-019-0247-z

    Article  PubMed  PubMed Central  Google Scholar 

  54. Ueda M et al. (2001) MR imaging findings of uterine endometrial stromal sarcoma: Differentiation from endometrial carcinoma. Eur Radiol 11:28–33. https://doi.org/https://doi.org/10.1007/s003300000541

    Article  CAS  PubMed  Google Scholar 

  55. Lee CH et al. (2012)14-3-3 fusion oncogenes in high-grade endometrial stromal sarcoma. Proc. Natl. Acad. Sci. U. S. A., 109:929–934 (2012). https://doi.org/https://doi.org/10.1073/pnas.1115528109.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Lee CH et al. (2012) The clinicopathologic features of YWHAE-FAM22 endometrial stromal sarcomas: A histologically high-grade and clinically aggressive tumor. Am J Surg Patho 36:641–). https://doi.org/10.1097/PAS.0b013e31824a7b1a.

  57. Lewis N et al. (2018) ZC3H7B-BCOR high-grade endometrial stromal sarcomas: A report of 17 cases of a newly defined entity. Mod. Pathol. 31:674-–84. https://doi.org/https://doi.org/10.1038/modpathol.2017.162.

    Article  PubMed  Google Scholar 

  58. Chiang S et al. (2017) BCOR is a robust diagnostic immunohistochemical marker of genetically diverse high-grade endometrial stromal sarcoma, including tumors exhibiting variant morphology. Mod Pathol 30:1251–1261. https://doi.org/https://doi.org/10.1038/modpathol.2017.42

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Tirumani SH et al. (2013) Current concepts in the imaging of uterine sarcoma. Abdom Imaging 38:397–411. https://doi.org/https://doi.org/10.1007/s00261-012-9919-x

    Article  PubMed  Google Scholar 

  60. Kanjeekal S, Chambers A, Fung Kee Fung M, Verma S (2005) Systemic therapy for advanced uterine sarcoma: A systematic review of the literature. Gynecol Oncol 97:624–637. https://doi.org/https://doi.org/10.1016/j.ygyno.2005.01.041

    Article  CAS  PubMed  Google Scholar 

  61. Clement PB, Scully RE (1990) Mullerian adenosarcoma of the uterus: A clinicopathologic analysis of 100 cases with a review of the literature. Hum Pathol 21:363–381. https://doi.org/https://doi.org/10.1016/0046-8177(90)90198-E

    Article  CAS  PubMed  Google Scholar 

  62. Clement PB (1989) Mullerian adenosarcomas of the uterus with sarcomatous overgrowth. A clinicopathological analysis of 10 cases. Am J Surg Pathol 13:28–38. https://doi.org/https://doi.org/10.1097/00000478-198901000-00004

    Article  CAS  PubMed  Google Scholar 

  63. Arend R et al. (2010) Long-term outcome and natural history of uterine adenosarcomas. Gynecol Oncol 119:305–308. https://doi.org/https://doi.org/10.1016/j.ygyno.2010.07.001

    Article  PubMed  Google Scholar 

  64. Carroll A et al. (2014) Uterine adenosarcoma: An analysis on management, outcomes, and risk factors for recurrence. Gynecol Oncol 135:455–461. https://doi.org/https://doi.org/10.1016/j.ygyno.2014.10.022

    Article  PubMed  PubMed Central  Google Scholar 

  65. Lucas R, Dias JL, Cunha TM (2015) Added value of diffusion-weighted mri in detection of cervical cancer recurrence: Comparison with morphologic and dynamic contrast-enhanced mri sequences. Diagnostic Interv Radiol 21:368–375. https://doi.org/10.5152/dir.2015.14427

  66. Takeuchi M et al. (2009) Adenosarcoma of the uterus: magnetic resonance imaging characteristics. Clin Imaging 33:244–247. https://doi.org/https://doi.org/10.1016/j.clinimag.2008.11.003

    Article  PubMed  Google Scholar 

  67. Plaxe SC, Mundt AJ (2021) Overview of endometrial carcinoma. Uptodate. https://www.uptodate.com/contents/overview-of-endometrial-carcinoma. Accessed 22 Aug 2021

  68. Capozzi VA et al. (2020) Endometrial stromal sarcoma: A review of rare mesenchymal uterine neoplasm. J Obstet Gynaecol Res 46:2221–2236. https://doi.org/https://doi.org/10.1111/jog.14436

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

No funding to declare.

Author information

Authors and Affiliations

  1. Department of Radiology, Centro Hospitalar Universitário de Lisboa Central, Alameda Santo António dos Capuchos, 1169-050, Lisbon, Portugal

    Filipa Alves e Sousa

  2. Department of Pathology, Instituto Português de Oncologia de Lisboa Francisco Gentil, R. Prof. Lima Basto, 1099-023, Lisbon, Portugal

    Joana Ferreira

  3. Nova Medical School, Universidade Nova de Lisboa, Lisbon, Portugal

    Joana Ferreira

  4. Department of Radiology, Instituto Português de Oncologia de Lisboa Francisco Gentil, R. Prof. Lima Basto, 1099-023, Lisbon, Portugal

    Teresa Margarida Cunha

Authors
  1. Filipa Alves e Sousa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joana Ferreira
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Teresa Margarida Cunha
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to this paper with conception and design, literature review, critical revision, and approval of the final version. Manuscript writing and preparation of figures and tables were made by FAS. JF contributed with partial writing of the manuscript concerning pathology concepts and collected histology and macroscopy figures. TMC collected all cases and supervised the manuscript writing and editing.

Corresponding author

Correspondence to Filipa Alves e Sousa.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sousa, F.A.e., Ferreira, J. & Cunha, T.M. MR Imaging of uterine sarcomas: a comprehensive review with radiologic-pathologic correlation. Abdom Radiol 46, 5687–5706 (2021). https://doi.org/10.1007/s00261-021-03263-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-021-03263-w

Keywords

Search

Navigation