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MR imaging findings of unusual leiomyoma and malignant uterine myometrial tumors: what the radiologist should know

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Abstract

Uterine sarcomas account for less than 1% of gynecological malignancies and 2–5% of all uterine malignancies. Such sarcomas mainly include leiomyosarcoma (LMS) and endometrial stromal sarcoma (ESS). Additionally, inflammatory myofibroblastic tumor (IMT) and endometrial carcinoma arising in adenomyosis can occur as uterine myometrial tumors. Their differentiation from leiomyoma (LM), particularly degenerated LM and the malignant tumors, is challenging, but preoperative diagnosis is very important for the patient’s management. We demonstrate the useful and compulsory findings to differentiate between uterine myometrial malignant tumors and degenerated LM with an unusual appearance.

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References

  1. Oliva E, Zaloudek CJ, Soslow RA. Mesenchymal tumors of the uterus. In: Kurman RJ, Ronnett BM, Ellenson L, editors. Blaustein’s pathology of the female tract. New York: Springer; 2019. p. 535–647.

    Chapter  Google Scholar 

  2. Paul PG, Rengaraj V, Das T, Garg R, Thomas M, Khurd AS. Uterine sarcomas in patients undergoing surgery for presumed leiomyomas: 10 years’ experience. J Minim Invasive Gynecol. 2016;23:384–9.

    Article  CAS  Google Scholar 

  3. Lakhman Y, Veeraraghavan H, Chaim J, Feier D, Goldman DA, Moskowitz CS, et al. Differentiation of uterine leiomyosarcoma from atypical leiomyoma: diagnostic accuracy of qualitative mr imaging features and feasibility of texture analysis. Eur Radiol. 2017;27:2903–15.

    Article  Google Scholar 

  4. Ando T, Kato H, Furui T, Morishige KI, Goshima S, Matsuo M. Uterine smooth muscle tumours with hyperintense area on T1 weighted images: differentiation between leiomyosarcomas and leiomyomas. Br J Radiol. 2018;91:20170767.

    Article  Google Scholar 

  5. Lin G, Yang LY, Huang YT, Ng KK, Ng SH, Ueng SH, et al. 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. 2016;43:333–42.

    Article  Google Scholar 

  6. Tamai K, Koyama T, Saga T, Morisawa N, Fujimoto K, Mikami Y, et al. The utility of diffusion-weighted MR imaging for differentiating uterine sarcomas from benign leiomyomas. Eur Radiol. 2008;18:723–30.

    Article  Google Scholar 

  7. Takeuchi M, Matsuzaki K, Nishitani H. Hyperintense uterine myometrial masses on T2-weighted magnetic resonance imaging: differentiation with diffusion-weighted magnetic resonance imaging. J Comput Assist Tomogr. 2009;33:834–7.

    Article  Google Scholar 

  8. Namimoto T, Yamashita Y, Awai K, Nakaura T, Yanaga Y, Hirai T, et al. Combined use of T2-weighted and diffusion-weighted 3-T MR imaging for differentiating uterine sarcomas from benign leiomyomas. Eur Radiol. 2009;19:2756–64.

    Article  Google Scholar 

  9. Tasaki A, Asatani MO, Umezu H, Kashima K, Enomoto T, Yoshimura N, et al. Differential diagnosis of uterine smooth muscle tumors using diffusion-weighted imaging: correlations with the apparent diffusion coefficient and cell density. Abdom Imaging. 2015;40:1742–52.

    Article  Google Scholar 

  10. Sato K, Yuasa N, Fujita M, Fukushima Y. Clinical application of diffusion-weighted imaging for preoperative differentiation between uterine leiomyoma and leiomyosarcoma. Am J Obstet Gynecol. 2014;210(368):e1-8.

    Google Scholar 

  11. Ochiai R, Fujii S, Kudo A, Mukuda N, Murakami A, Fukunaga T, et al. A case of uterine leiomyosarcoma mimicking red degeneration. Rinshouhoushasen. 2019;64:1549–54 ((in Japanese)).

    Google Scholar 

  12. Koyama T, Togashi K, Konishi I, Kobayashi H, Ueda H, Kataoka ML, et al. MR imaging of endometrial stromal sarcoma: correlation with pathologic findings. AJR Am J Roentgenol. 1999;173:767–72.

    Article  CAS  Google Scholar 

  13. Furukawa R, Akahane M, Yamada H, Kiryu S, Sato J, Komatsu S, et al. 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. 2010;31:975–9.

    Article  Google Scholar 

  14. Fujii S, Nosaka K, Mukuda N, Fukunaga T, Sato S, Ogawa T. MR Imaging of an intramural adenosarcoma with pathologic correlation. Magn Reson Med Sci. 2018;17:1–2.

    Article  Google Scholar 

  15. Huang YL, Ueng SH, Chen K, Huang YT, Lu HY, Ng KK, et al. 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. 2019;19:63.

    Article  Google Scholar 

  16. Kim TH, Kim JW, Kim SY, Kim SH, Cho JY. What MRI features suspect malignant pure mesenchymal uterine tumors rather than uterine leiomyoma with cystic degeneration? J Gynecol Oncol. 2018;29:e26.

    Article  Google Scholar 

  17. Li HM, Liu J, Qiang JW, Gu WY, Zhang GF, Ma FH. Endometrial stromal sarcoma of the uterus: magnetic resonance imaging findings including apparent diffusion coefficient value and its correlation with Ki-67 Expression. Int J Gynecol Cancer. 2017;27:1877–87.

    Article  Google Scholar 

  18. Fujii S, Kaneda S, Tsukamoto K, Kakite S, Kanasaki Y, Matsusue E, et al. Diffusion-weighted imaging of uterine endometrial stromal sarcoma: a report of 2 cases. J Comput Assist Tomogr. 2010;34:377–9.

    Article  Google Scholar 

  19. Takahashi A, Kurosawa M, Uemura M, Kitazawa J, Hayashi Y. Anaplastic lymphoma kinase-negative uterine inflammatory myofibroblastic tumor containing the ETV6-NTRK3 fusion gene: a case report. J Int Med Res. 2018;46:3498–503.

    Article  CAS  Google Scholar 

  20. Mohammad N, Haimes JD, Mishkin S, Kudlow BA, Leong MY, Chew SH, et al. ALK is a specific diagnostic marker for inflammatory myofibroblastic tumor of the uterus. Am J Surg Pathol. 2018;42:1353–9.

    Article  Google Scholar 

  21. Parra-Herran C, Lee CH, Bennett JA, Rebban JT. Inflammatory myofibroblastic tumour WHO classification of tumours Editorial Board WHO classification of tumours of female reproductive organs. Lyon: International Agency for Research on Cancer; 2020.

    Google Scholar 

  22. Horger M, Pfannenberg C, Bitzer M, Wehrmann M, Claussen CD. Synchronous gastrointestinal and musculoskeletal manifestations of different subtypes of inflammatory myofibroblastic tumor: CT MRI and pathological features. Eur Radiol. 2005;15:1713–6.

    Article  Google Scholar 

  23. Koshiyama M, Suzuki A, Ozawa M, Fujita K, Sakakibara A, Kawamura M, et al. Adenocarcinomas arising from uterine adenomyosis: a report of four cases. Int J Gynecol Pathol. 2002;21:239–45.

    Article  Google Scholar 

  24. Colman HI, Rosenthal AH. Carcinoma developing in areas of adenomyosis. Obstet Gynecol. 1959;14:342–8.

    CAS  PubMed  Google Scholar 

  25. Tamai K, Togashi K, Ito T, Morisawa N, Fujiwara T, Koyama T. MR imaging findings of adenomyosis: correlation with histopathologic features and diagnostic pitfalls. Radiographics. 2005;25:21–40.

    Article  Google Scholar 

  26. Hachiya K, Kato H, Kawaguchi S, Kojima T, Nishikawa Y, Fujiwara S, et al. Red degeneration of a uterine fibroid following the administration of gonadotropin releasing hormone agonists. J Obstet Gynaecol. 2016;36:1018–9.

    Article  Google Scholar 

  27. Kawakami S, Togashi K, Konishi I, Kimura I, Fukuoka M, Mori T, et al. Red degeneration of uterine leiomyoma: MR appearance. J Comput Assist Tomogr. 1994;18:925–8.

    Article  CAS  Google Scholar 

  28. Nakai G, Yamada T, Hamada T, Atsukawa N, Tanaka Y, Yamamoto K, et al. Pathological findings of uterine tumors preoperatively diagnosed as red degeneration of leiomyoma by MRI. Abdom Radiol (NY). 2017;42:1825–31.

    Article  Google Scholar 

  29. Ueda H, Togashi K, Konishi I, Kataoka ML, Koyama T, Fujiwara T, et al. Unusual appearances of uterine leiomyomas: MR imaging findings and their histopathologic backgrounds. Radiographics. 1999;19:131–45.

    Article  Google Scholar 

  30. Akbulut M, Gündoğan M, Yörükoğlu A. Clinical and pathological features of lipoleiomyoma of the uterine corpus: a review of 76 cases. Balkan Med J. 2014;31:224–9.

    Article  Google Scholar 

  31. Kitajima K, Kaji Y, Imanaka K, Sugihara R, Sugimura K. MRI findings of uterine lipoleiomyoma correlated with pathologic findings. AJR Am J Roentgenol. 2007;189:W100–4.

    Article  Google Scholar 

  32. Ono H, Kanematsu M, Kato H, Toyoki H, Hayasaki Y, Furui T, et al. MR imaging findings of uterine pyomyoma: radiologic-pathologic correlation. Abdom Imaging. 2014;39:797–801.

    Article  Google Scholar 

  33. Haimes AB, Zimmerman RD, Morgello S, Weingarten K, Becker RD, Jennis R, et al. MR imaging of brain abscesses. AJR Am J Roentgenol. 1989;152:1073–85.

    Article  CAS  Google Scholar 

  34. Yamashita Y, Torashima M, Takahashi M, Tanaka N, Katabuchi H, Miyazaki K, et al. Hyperintense uterine leiomyoma at T2-weighted MR imaging: differentiation with dynamic enhanced MR imaging and clinical implications. Radiology. 1993;189:721–5.

    Article  CAS  Google Scholar 

  35. Thomassin-Naggara I, Dechoux S, Bonneau C, Morel A, Rouzier R, Carette MF, et al. How to differentiate benign from malignant myometrial tumours using MR imaging. Eur Radiol. 2013;23:2306–14.

    Article  Google Scholar 

  36. Abdel Wahab C, Jannot AS, Bonaffini PA, Bourillon C, Cornou C, Lefrère-Belda MA, et al. Diagnostic algorithm to differentiate benign atypical leiomyomas from malignant uterine sarcomas with diffusion-weighted MRI. Radiology. 2020;297:361–71.

    Article  Google Scholar 

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Acknowledgements

We thank Hiroaki Komatsu, Shinya Sato, Tetsuro Oishi, for their help in the tumor board, as well as Kanae Nosaka for her assistance with the pathological diagnosis and advices.

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Authors and Affiliations

  1. Division of Radiology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, Tottori, 683-8504, Japan

    Shinya Fujii, Naoko Mukuda, Ryoya Ochiai, Hiroto Yunaga, Atsushi Murakami, Takuro Gonda, Misato Kishimoto, Daisuke Yamaji & Mana Ishibashi

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  1. Shinya Fujii
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  2. Naoko Mukuda
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  3. Ryoya Ochiai
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Correspondence to Shinya Fujii.

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Fujii, S., Mukuda, N., Ochiai, R. et al. MR imaging findings of unusual leiomyoma and malignant uterine myometrial tumors: what the radiologist should know. Jpn J Radiol 39, 527–539 (2021). https://doi.org/10.1007/s11604-021-01096-7

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  • DOI: https://doi.org/10.1007/s11604-021-01096-7

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