Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-21T15:52:11.146Z Has data issue: false hasContentIssue false
  • English
  • Français

PREOPERATIVE MAGNETIC RESONANCE IMAGING DIAGNOSTIC FEATURES OF UTERINE LEIOMYOSARCOMAS: A SYSTEMATIC REVIEW

Published online by Cambridge University Press:  12 April 2018

Helen Kaganov ,
Alex Ades  and
David Stuart Fraser
Helen Kaganov
Affiliation:
Department of Obstetrics and Gynaecology, Box Hill Hospitalhelen.kaganov@gmail.com
Alex Ades
Affiliation:
Department of Obstetrics and Gynaecology, The Royal Women's Hospital
David Stuart Fraser
Affiliation:
Faculty of Science and Engineering
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives: There are no current established pathognomonic diagnostic features for uterine leiomyosarcomas in the pre- or perioperative setting. Recent inadvertent upstaging of this rare malignancy during laparoscopic morcellation of a presumed fibroid has prompted widespread debate among clinicians regarding the safety of current surgical techniques for management of fibroids. This study aims to conduct a systematic review investigating significant diagnostic features in magnetic resonance imaging (MRI) of uterine leiomyosarcomas.

Methods: A comprehensive database search was conducted guided by PRISMA recommendations for peer-reviewed publications to November 2017. Parameters available in MRI were compared for reliability and accuracy of diagnosis of leiomyosarcomas. A decision tree algorithm classifier model was constructed to investigate whether T1 and T2 MRI signal intensities are useful indicators.

Results: Nine eligible studies were identified for analysis. There appears to be a significant relationship between histopathological type and T1 and T2 intensity signals (p < .05). A decision tree model analyzing T1 and T2 signal intensity readings supports this trend, with a diagnostic specificity of 77.78 percent for uterine leiomyosarcomas. The apparent diffusion coefficient (ADC) values were not observed to have a significant relationship with tumor pathology (p = .18).

Conclusions: Various studies have investigated pre- and perioperative techniques in differentiating uterine leiomyosarcoma from benign fibroids. Given the rarity of the malignancy and lack of pathognomonic diagnostic parameters, there is difficulty in establishing definitive criteria. A decision tree model is proposed to aid diagnosis based on MRI signal intensities.

Keywords

FibroidsImagingLeiomyosarcomaMorcellationMRI
Type
Assessment
Information
International Journal of Technology Assessment in Health Care , Volume 34 , Issue 2 , 2018 , pp. 172 - 179
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Janus, C, White, M, Dottino, P, Brodman, M, Goodman, H. Uterine leiomyosarcoma-magnetic resonance imaging. Gynecol Oncol. 1989;32:79–81.CrossRefGoogle ScholarPubMed
2.Takemori, M, Nishimura, R, Sugimura, K. Magnetic resonance imaging of uterine leiomyosarcoma. Arch Gynecol Obstet. 1992;251:215–218.Google Scholar
3.Pattani, SJ, Kier, R, Deal, R, Luchansky, E. MRI of uterine leiomyosarcoma. Magn Reson Imaging. 1995;13:331–333.Google Scholar
4.Tanaka, YO, Nishida, M, Tsunoda, H, Okamoto, Y, Yoshikawa, H. Smooth muscle tumors of uncertain malignant potential and leiomyosarcomas of the uterus: MR findings. J Magn Reson Imaging. 2004;20:998–1007.Google Scholar
5.Fukunishi, H, Funaki, K, Ikuma, K, et al. Unsuspected uterine leiomyosarcoma: Magnetic resonance imaging findings before and after focused ultrasound surgery. Int J Gynecol Cancer. 2007;17:724–728.Google Scholar
6.Tamai, K, Koyama, T, Saga, T, et al. The utility of diffusion-weighted MR imaging for differentiating uterine sarcomas from benign leiomyomas. Eur Radiol. 2008;18:723–730.Google Scholar
7.Samuel, A, Fennessy, FM, Tempany, CMC, a, Stewart E. Avoiding treatment of leiomyosarcomas: The role of magnetic resonance in focused ultrasound surgery. Fertil Steril. 2008;90:850.e9–12.Google Scholar
8.Cornfeld, D, Israel, G, Martel, M, Weinreb, J, Schwartz, P, McCarthy, S. MRI appearance of mesenchymal tumors of the uterus. Eur J Radiol. 2010;74:241–249.Google Scholar
9.Lin, G, Yang, L-Y, Huang, Y-T, 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;43:333–342.CrossRefGoogle ScholarPubMed
10.Etiology, Parker WH., symptomatology, and diagnosis of uterine myomas. Fertil Steril. 2007;87:725–736.Google Scholar
11.Pritts, EA, Parker, WH, Brown, J, Olive, DL. Outcome of occult uterine leiomyosarcoma after surgery for presumed uterine fibroids: A systematic review. J Minim Invasive Gynecol. 2015;22:26–33.Google Scholar
12.Cardozo, ER, Clark, AD, Banks, NK, Henne, MB, Stegmann, BJ, Segars, JH. The estimated annual cost of uterine leiomyomata in the United States. Am J Obstet Gynecol. 2012;206:211.e1–211.e9.Google Scholar
13.Soliman, AM, Yang, H, Du, EX, Kelkar, SS, Winkel, C. The direct and indirect costs of uterine fibroid tumors: A systematic review of the literature between 2000 and 2013. Am J Obstet Gynecol. 2015;213:141–160.Google Scholar
14.Wallis, L. FDA warns against power morcellation for hysterectomy and fibroids. Am J Nurs. 2014;114:16.Google Scholar
15.del Carmen, MG. Uterine leiomyosarcoma. Uncommon gynecologic cancers. Chichester, UK: John Wiley & Sons, Ltd; 2014:167–177.Google Scholar
16.Gadducci, A. Prognostic factors in uterine sarcoma. Best Pract Res Clin Obstet Gynaecol. 2011;25:783–795.CrossRefGoogle ScholarPubMed
17.Toro, JR, Travis, LB, Wu, HJ, Zhu, K, Fletcher, CDM, Devesa, SS. Incidence patterns of soft tissue sarcomas, regardless of primary site, in the surveillance, epidemiology and end results program, 1978–2001: An analysis of 26,758 cases. Int J Cancer. 2006;119:2922–2930.Google Scholar
18.Tinelli, A. Uterine leiomyosarcomas and leiomyomas: Two similar uterine solid tumors, totally different for prognosis. http://www.sciedupress.com/journal/index.php/jst/article/view/430 (accessed March 6, 2018).Google Scholar
19.Hayashi, T, Horiuchi, A, Aburatani, H, et al. Potential biomarker for human uterine leiomyosarcoma. J Clin Med Res. 2014;6:392–394.Google Scholar
20.Sahdev, A, Sohaib, SA, Jacobs, I, Shepherd, JH, Oram, DH, Reznek, RH. MR imaging of uterine sarcomas. AJR Am J Roentgenol. 2001;177:1307–1311.Google Scholar
21.Rha, SE, Byun, JY, Jung, SE, et al. CT and MRI of uterine sarcomas and their mimickers. AJR Am J Roentgenol. 2003;181:1369–1374.Google Scholar
22.Kurjak, A, Kupesic, S, Shalan, H, Jukic, S, Kosuta, D, Ilijas, M. Uterine sarcoma: A report of 10 cases studied by transvaginal color and pulsed Doppler sonography. Gynecol Oncol. 1995;59:342–346.Google Scholar
23.Indraccolo, U, Luchetti, G, Indraccolo, SR. Malignant transformation of uterine leiomyomata. Eur J Gynaecol Oncol. 2008;29:543–544.Google Scholar
24.Santos, P, Cunha, TM. Uterine sarcomas: Clinical presentation and MRI features. Diagn Interv Radiol. 2015;21:4–9.Google Scholar
25.Rockall, AG, Freeman, SJ, Mitchell, DG, Sala, E, Reinhold, C. The added role of MR imaging in treatment stratification of patients with gynecologic malignancies: What the radiologist needs to know. Radiology. 2013;266:717–740.Google Scholar
26.D'Angelo, E, Prat, J. Uterine sarcomas: A review. Gynecol Oncol. 2010;116:131–139.Google Scholar
27.Moher, D, Liberati, A, Tetzlaff, J, Altman, DG. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ. 2009;339:b2535–b2535.Google Scholar
28.R Core Team. R: A language and environment for statistical computing. R version 3.2.2. R Foundation for Statistical Computing. 2015.Google Scholar
29.Patil, TR. Performance analysis of naive Bayes and J48 classification algorithm for data classification. Int J Comput Sci Appl. 2013;6:256–261.Google Scholar
30.Szabó I. Transvaginal color Doppler for assessment of uterine vascularity in cases of uterine fibroids and sarcomas. Ultrasound Rev Obstet Gynecol. 2003;3:294–299.Google Scholar
31.Hata, K, Hata, T, Maruyama, R, Hirai, M. Uterine sarcoma: Can it be differentiated from uterine leiomyoma with Doppler ultrasonography? A preliminary report. Ultrasound Obstet Gynecol. 1997;9:101–104.Google Scholar
32.Goto, A, Takeuchi, S, Sugimura, K, Maruo, T. Usefulness of Gd-DTPA contrast-enhanced dynamic MRI and serum determination of LDH and its isozymes in the differential diagnosis of leiomyosarcoma from degenerated leiomyoma of the uterus. Int J Gynecol Cancer. 2002;12:354–361.Google Scholar
33.Zhang, G-F, Zhang, H, Tian, X-M, Zhang, H. Magnetic resonance and diffusion-weighted imaging in categorization of uterine sarcomas: Correlation with pathological findings. Clin Imaging. 2014;38:836–844.Google Scholar
34.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.e1–368.e8.Google Scholar
35.Buy, JN, Ghossain, M. Gynecological imaging a reference guide to diagnosis. New York: Springer; 2013:787–793.Google Scholar
36.Motoshima, S, Irie, H, Nakazono, T, Kamura, T, Kudo, S. Diffusion-weighted MR imaging in gynecologic cancers. J Gynecol Oncol. 2011;22:275–287.Google Scholar
37.Dale, BM, Braithwaite, AC, Boll, DT, Merkle, EM. Field strength and diffusion encoding technique affect the apparent diffusion coefficient measurements in diffusion-weighted imaging of the abdomen. Invest Radiol. 2010;45:104–108.Google Scholar
38.Kim, HJ, Lee, SY, Shin, YR, Park, CS, Kim, K. The value of diffusion-weighted imaging in the differential diagnosis of ovarian lesions: A meta-analysis. PLoS One. 2016;11:e0149465.Google Scholar
39.Shibata, S, Kawamura, N, Ito, F, et al. Diagnostic accuracy of needle biopsy of uterine leiomyosarcoma. Oncol Rep. 2000;7:595–597.Google Scholar
40.Kawamura, N, Ichimura, T, Ito, F, et al. Transcervical needle biopsy for the differential diagnosis between uterine sarcoma and leiomyoma. Cancer. 2002;94:1713–1720.CrossRefGoogle ScholarPubMed
41.Tsujimura, A, Kawamura, N, Ichimura, T, Honda, K-I, Ishiko, O, Ogita, S. Telomerase activity in needle biopsied uterine myoma-like tumors: Differential diagnosis between uterine sarcomas and leiomyomas. Int J Oncol. 2002;20:361–365.Google Scholar
42.Tulandi, T, Ferenczy, A. Biopsy of uterine leiomyomata and frozen sections before laparoscopic morcellation. J Minim Invasive Gynecol. 2014;21:963–966.Google Scholar
Supplementary material: Image

Kaganov et al. supplementary material

Kaganov et al. supplementary material 1

Download Kaganov et al. supplementary material(Image)
Image 60.1 KB
Supplementary material: Image

Kaganov et al. supplementary material

Kaganov et al. supplementary material 2

Download Kaganov et al. supplementary material(Image)
Image 57.5 KB
Supplementary material: Image

Kaganov et al. supplementary material

Kaganov et al. supplementary material 3

Download Kaganov et al. supplementary material(Image)
Image 78.4 KB