Skip to main content

Advertisement

Log in

Quantitative imaging of uterine cancers with diffusion-weighted MRI and 18-fluorodeoxyglucose PET/CT

  • Special Section: Quantitative Imaging
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Imaging plays an important role in the diagnosis and treatment of women with uterine cervical and endometrial cancers. Quantitative imaging, through MRI, PET/CT, and hybrid PET/MRI, allows for characterization of primary tumors beyond anatomic and qualitative descriptors. MRI diffusion-weighted imaging (DWI) yields an apparent diffusion coefficient (ADC), which can be applied in both the pre-and post-treatment assessment of uterine tumors. PET/CT assesses metabolic activity, and measurement of tumor standardized uptake value (SUV) is a useful metric in the staging of uterine malignancies. Hybrid PET/MRI is an emerging modality that combines the soft tissue contrast of MRI with the molecular imaging capability of PET. This review provides an overview of these quantitative imaging modalities, and their current and potential roles in the assessment of uterine cervical and cancer.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021. https://doi.org/10.3322/caac.21660.

    Article  PubMed  Google Scholar 

  2. Amant F, Mirza MR, Koskas M, Creutzberg CL. Cancer of the corpus uteri. Int J Gynaecol Obstet. 2018;143 Suppl 2:37-50. https://doi.org/10.1002/ijgo.12612.

    Article  PubMed  Google Scholar 

  3. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394-424. https://doi.org/10.3322/caac.21492.

    Article  PubMed  Google Scholar 

  4. Prabhakar HB, Kraeft JJ, Schorge JO, Scott JA, Lee SI. FDG PET-CT of gynecologic cancers: pearls and pitfalls. Abdom Imaging. 2015;40(7):2472-85. https://doi.org/10.1007/s00261-015-0362-7.

    Article  PubMed  Google Scholar 

  5. Lee SI, Atri M. 2018 FIGO Staging System for Uterine Cervical Cancer: Enter Cross-sectional Imaging. Radiology. 2019;292(1):15-24. https://doi.org/10.1148/radiol.2019190088.

    Article  PubMed  Google Scholar 

  6. Masch WR, Daye D, Lee SI. MR Imaging for Incidental Adnexal Mass Characterization. Magn Reson Imaging Clin N Am. 2017;25(3):521-43. https://doi.org/10.1016/j.mric.2017.03.001.

    Article  PubMed  Google Scholar 

  7. deSouza NM, Winfield JM, Waterton JC, Weller A, Papoutsaki MV, Doran SJ, et al. Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives. Eur Radiol. 2018;28(3):1118-31. https://doi.org/10.1007/s00330-017-4972-z.

    Article  CAS  PubMed  Google Scholar 

  8. Partridge SC, McDonald ES. Diffusion weighted magnetic resonance imaging of the breast: protocol optimization, interpretation, and clinical applications. Magn Reson Imaging Clin N Am. 2013;21(3):601-24. https://doi.org/10.1016/j.mric.2013.04.007.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Qayyum A. Diffusion-weighted imaging in the abdomen and pelvis: concepts and applications. Radiographics. 2009;29(6):1797-810. https://doi.org/10.1148/rg.296095521.

    Article  PubMed  Google Scholar 

  10. Moore WA, Khatri G, Madhuranthakam AJ, Sims RD, Pedrosa I. Added value of diffusion-weighted acquisitions in MRI of the abdomen and pelvis. AJR Am J Roentgenol. 2014;202(5):995-1006. https://doi.org/10.2214/ajr.12.9563.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Davarpanah AH, Kambadakone A, Holalkere NS, Guimaraes AR, Hahn PF, Lee SI. Diffusion MRI of uterine and ovarian masses: identifying the benign lesions. Abdom Radiol (NY). 2016;41(12):2466-75. https://doi.org/10.1007/s00261-016-0909-2.

    Article  PubMed  Google Scholar 

  12. Ghosh A, Singh T, Singla V, Bagga R, Khandelwal N. Comparison of Absolute Apparent Diffusion Coefficient (ADC) Values in ADC Maps Generated Across Different Postprocessing Software: Reproducibility in Endometrial Carcinoma. AJR Am J Roentgenol. 2017;209(6):1312-20. https://doi.org/10.2214/ajr.17.18002.

    Article  PubMed  Google Scholar 

  13. Pathak R, Ragheb H, Thacker NA, Morris DM, Amiri H, Kuijer J, et al. A data-driven statistical model that estimates measurement uncertainty improves interpretation of ADC reproducibility: a multi-site study of liver metastases. Sci Rep. 2017;7(1):14084. https://doi.org/10.1038/s41598-017-14625-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Jafar MM, Parsai A, Miquel ME. Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients, in-vitro and in-vivo reproducibility. World J Radiol. 2016;8(1):21-49. https://doi.org/10.4329/wjr.v8.i1.21.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Mitchell DG, Snyder B, Coakley F, Reinhold C, Thomas G, Amendola M, et al. Early invasive cervical cancer: tumor delineation by magnetic resonance imaging, computed tomography, and clinical examination, verified by pathologic results, in the ACRIN 6651/GOG 183 Intergroup Study. J Clin Oncol. 2006;24(36):5687-94. https://doi.org/10.1200/jco.2006.07.4799.

    Article  PubMed  Google Scholar 

  16. Dappa E, Elger T, Hasenburg A, Düber C, Battista MJ, Hötker AM. The value of advanced MRI techniques in the assessment of cervical cancer: a review. Insights Imaging. 2017;8(5):471-81. https://doi.org/10.1007/s13244-017-0567-0.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Pandharipande PV, Choy G, del Carmen MG, Gazelle GS, Russell AH, Lee SI. MRI and PET/CT for triaging stage IB clinically operable cervical cancer to appropriate therapy: decision analysis to assess patient outcomes. AJR Am J Roentgenol. 2009;192(3):802-14. https://doi.org/10.2214/ajr.08.1224.

    Article  PubMed  Google Scholar 

  18. Lee SI, Catalano OA, Dehdashti F. Evaluation of gynecologic cancer with MR imaging, 18F-FDG PET/CT, and PET/MR imaging. J Nucl Med. 2015;56(3):436-43. https://doi.org/10.2967/jnumed.114.145011.

    Article  PubMed  Google Scholar 

  19. Qu JR, Qin L, Li X, Luo JP, Li J, Zhang HK, et al. Predicting Parametrial Invasion in Cervical Carcinoma (Stages IB1, IB2, and IIA): Diagnostic Accuracy of T2-Weighted Imaging Combined With DWI at 3 T. AJR Am J Roentgenol. 2018;210(3):677-84. https://doi.org/10.2214/ajr.17.18104.

    Article  PubMed  Google Scholar 

  20. Park JJ, Kim CK, Park SY, Park BK. Parametrial invasion in cervical cancer: fused T2-weighted imaging and high-b-value diffusion-weighted imaging with background body signal suppression at 3 T. Radiology. 2015;274(3):734-41. https://doi.org/10.1148/radiol.14140920.

    Article  PubMed  Google Scholar 

  21. Nguyen NC, Beriwal S, Moon CH, D'Ardenne N, Mountz JM, Furlan A, et al. Diagnostic Value of FDG PET/MRI in Females With Pelvic Malignancy-A Systematic Review of the Literature. Front Oncol. 2020;10:519440. https://doi.org/10.3389/fonc.2020.519440.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Nakamura K, Joja I, Nagasaka T, Fukushima C, Kusumoto T, Seki N, et al. The mean apparent diffusion coefficient value (ADCmean) on primary cervical cancer is a predictive marker for disease recurrence. Gynecol Oncol. 2012;127(3):478-83. https://doi.org/10.1016/j.ygyno.2012.07.123.

    Article  PubMed  Google Scholar 

  23. Shih IL, Yen RF, Chen CA, Cheng WF, Chen BB, Chang YH, et al. PET/MRI in Cervical Cancer: Associations Between Imaging Biomarkers and Tumor Stage, Disease Progression, and Overall Survival. J Magn Reson Imaging. 2021;53(1):305-18. https://doi.org/10.1002/jmri.27311.

    Article  PubMed  Google Scholar 

  24. Thomeer MG, Vandecaveye V, Braun L, Mayer F, Franckena-Schouten M, de Boer P, et al. Evaluation of T2-W MR imaging and diffusion-weighted imaging for the early post-treatment local response assessment of patients treated conservatively for cervical cancer: a multicentre study. European radiology. 2019;29(1):309-18. https://doi.org/10.1007/s00330-018-5510-3.

    Article  PubMed  Google Scholar 

  25. Kilcoyne A, Chow DZ, Lee SI. FDG-PET for Assessment of Endometrial and Vulvar Cancer. Semin Nucl Med. 2019;49(6):471-83. https://doi.org/10.1053/j.semnuclmed.2019.06.011.

    Article  PubMed  Google Scholar 

  26. Moharamzad Y, Davarpanah AH, Yaghobi Joybari A, Shahbazi F, Esmaeilian Toosi L, Kooshkiforooshani M, et al. Diagnostic performance of apparent diffusion coefficient (ADC) for differentiating endometrial carcinoma from benign lesions: a systematic review and meta-analysis. Abdom Radiol (NY). 2021;46(3):1115-28. https://doi.org/10.1007/s00261-020-02734-w.

    Article  PubMed  Google Scholar 

  27. Shih IL, Yen RF, Chen CA, Chen BB, Wei SY, Chang WC, et al. Standardized uptake value and apparent diffusion coefficient of endometrial cancer evaluated with integrated whole-body PET/MR: Correlation with pathological prognostic factors. J Magn Reson Imaging. 2015;42(6):1723-32. https://doi.org/10.1002/jmri.24932.

    Article  PubMed  Google Scholar 

  28. Nougaret S, Reinhold C, Alsharif SS, Addley H, Arceneau J, Molinari N, et al. Endometrial Cancer: Combined MR Volumetry and Diffusion-weighted Imaging for Assessment of Myometrial and Lymphovascular Invasion and Tumor Grade. Radiology. 2015;276(3):797-808. https://doi.org/10.1148/radiol.15141212.

    Article  PubMed  Google Scholar 

  29. Reyes-Pérez JA, Villaseñor-Navarro Y, Jiménez de Los Santos ME, Pacheco-Bravo I, Calle-Loja M, Sollozo-Dupont I. The apparent diffusion coefficient (ADC) on 3-T MRI differentiates myometrial invasion depth and histological grade in patients with endometrial cancer. Acta Radiol. 2020;61(9):1277-86. https://doi.org/10.1177/0284185119898658.

    Article  PubMed  Google Scholar 

  30. Rechichi G, Galimberti S, Signorelli M, Franzesi CT, Perego P, Valsecchi MG, et al. Endometrial cancer: correlation of apparent diffusion coefficient with tumor grade, depth of myometrial invasion, and presence of lymph node metastases. AJR Am J Roentgenol. 2011;197(1):256-62. https://doi.org/10.2214/ajr.10.5584.

    Article  PubMed  Google Scholar 

  31. Atri M, Zhang Z, Dehdashti F, Lee SI, Ali S, Marques H, et al. Utility of PET-CT to evaluate retroperitoneal lymph node metastasis in advanced cervical cancer: Results of ACRIN6671/GOG0233 trial. Gynecol Oncol. 2016;142(3):413-9. https://doi.org/10.1016/j.ygyno.2016.05.002.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Atri M, Zhang Z, Dehdashti F, Lee SI, Marques H, Ali S, et al. Utility of PET/CT to Evaluate Retroperitoneal Lymph Node Metastasis in High-Risk Endometrial Cancer: Results of ACRIN 6671/GOG 0233 Trial. Radiology. 2017;283(2):450-9. https://doi.org/10.1148/radiol.2016160200.

    Article  PubMed  Google Scholar 

  33. Gee MS, Atri M, Bandos AI, Mannel RS, Gold MA, Lee SI. Identification of Distant Metastatic Disease in Uterine Cervical and Endometrial Cancers with FDG PET/CT: Analysis from the ACRIN 6671/GOG 0233 Multicenter Trial. Radiology. 2018;287(1):176-84. https://doi.org/10.1148/radiol.2017170963.

    Article  PubMed  Google Scholar 

  34. Nogami Y, Iida M, Banno K, Kisu I, Adachi M, Nakamura K, et al. Application of FDG-PET in cervical cancer and endometrial cancer: utility and future prospects. Anticancer Res. 2014;34(2):585-92.

    PubMed  Google Scholar 

  35. Lee LK, Kilcoyne A, Goldberg-Stein S, Chow DZ, Lee SI. FDG PET-CT of Genitourinary and Gynecologic Tumors: Overcoming the Challenges of Evaluating the Abdomen and Pelvis. Semin Roentgenol. 2016;51(1):2-11. https://doi.org/10.1053/j.ro.2015.12.007.

    Article  PubMed  Google Scholar 

  36. Fahey FH, Kinahan PE, Doot RK, Kocak M, Thurston H, Poussaint TY. Variability in PET quantitation within a multicenter consortium. Med Phys. 2010;37(7):3660-6. https://doi.org/10.1118/1.3455705.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Jacene HA, Leboulleux S, Baba S, Chatzifotiadis D, Goudarzi B, Teytelbaum O, et al. Assessment of interobserver reproducibility in quantitative 18F-FDG PET and CT measurements of tumor response to therapy. J Nucl Med. 2009;50(11):1760-9. https://doi.org/10.2967/jnumed.109.063321.

    Article  PubMed  Google Scholar 

  38. Huang YE, Chen CF, Huang YJ, Konda SD, Appelbaum DE, Pu Y. Interobserver variability among measurements of the maximum and mean standardized uptake values on (18)F-FDG PET/CT and measurements of tumor size on diagnostic CT in patients with pulmonary tumors. Acta Radiol. 2010;51(7):782-8. https://doi.org/10.3109/02841851.2010.497772.

    Article  PubMed  Google Scholar 

  39. Benz MR, Evilevitch V, Allen-Auerbach MS, Eilber FC, Phelps ME, Czernin J, et al. Treatment monitoring by 18F-FDG PET/CT in patients with sarcomas: interobserver variability of quantitative parameters in treatment-induced changes in histopathologically responding and nonresponding tumors. J Nucl Med. 2008;49(7):1038-46. https://doi.org/10.2967/jnumed.107.050187.

    Article  PubMed  Google Scholar 

  40. Shankar LK, Hoffman JM, Bacharach S, Graham MM, Karp J, Lammertsma AA, et al. Consensus recommendations for the use of 18F-FDG PET as an indicator of therapeutic response in patients in National Cancer Institute Trials. J Nucl Med. 2006;47(6):1059-66.

    CAS  PubMed  Google Scholar 

  41. Gandy N, Arshad MA, Park WE, Rockall AG, Barwick TD. FDG-PET Imaging in Cervical Cancer. Semin Nucl Med. 2019;49(6):461-70. https://doi.org/10.1053/j.semnuclmed.2019.06.007.

    Article  PubMed  Google Scholar 

  42. Choi HJ, Ju W, Myung SK, Kim Y. Diagnostic performance of computer tomography, magnetic resonance imaging, and positron emission tomography or positron emission tomography/computer tomography for detection of metastatic lymph nodes in patients with cervical cancer: meta-analysis. Cancer Sci. 2010;101(6):1471-9. https://doi.org/10.1111/j.1349-7006.2010.01532.x.

    Article  CAS  PubMed  Google Scholar 

  43. Signorelli M, Guerra L, Montanelli L, Crivellaro C, Buda A, Dell'Anna T, et al. Preoperative staging of cervical cancer: is 18-FDG-PET/CT really effective in patients with early stage disease? Gynecol Oncol. 2011;123(2):236-40. https://doi.org/10.1016/j.ygyno.2011.07.096.

    Article  PubMed  Google Scholar 

  44. Kidd EA, Siegel BA, Dehdashti F, Rader JS, Mutch DG, Powell MA, et al. Lymph node staging by positron emission tomography in cervical cancer: relationship to prognosis. J Clin Oncol. 2010;28(12):2108-13. https://doi.org/10.1200/jco.2009.25.4151.

    Article  PubMed  Google Scholar 

  45. Sun Y, Lu P, Yu L. The Volume-metabolic Combined Parameters from (18)F-FDG PET/CT May Help Predict the Outcomes of Cervical Carcinoma. Acad Radiol. 2016;23(5):605-10. https://doi.org/10.1016/j.acra.2016.01.001.

    Article  PubMed  Google Scholar 

  46. Kidd EA, El Naqa I, Siegel BA, Dehdashti F, Grigsby PW. FDG-PET-based prognostic nomograms for locally advanced cervical cancer. Gynecol Oncol. 2012;127(1):136-40. https://doi.org/10.1016/j.ygyno.2012.06.027.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Bollineni VR, Ytre-Hauge S, Gulati A, Halle MK, Woie K, Salvesen Ø, et al. The prognostic value of preoperative FDG-PET/CT metabolic parameters in cervical cancer patients. European Journal of Hybrid Imaging. 2018;2(1):24. https://doi.org/10.1186/s41824-018-0042-2.

    Article  Google Scholar 

  48. Grigsby PW, Siegel BA, Dehdashti F, Rader J, Zoberi I. Posttherapy [18F] fluorodeoxyglucose positron emission tomography in carcinoma of the cervix: response and outcome. J Clin Oncol. 2004;22(11):2167-71. https://doi.org/10.1200/jco.2004.09.035.

    Article  PubMed  Google Scholar 

  49. Kidd EA, Siegel BA, Dehdashti F, Grigsby PW. The standardized uptake value for F-18 fluorodeoxyglucose is a sensitive predictive biomarker for cervical cancer treatment response and survival. Cancer. 2007;110(8):1738-44. https://doi.org/10.1002/cncr.22974.

    Article  PubMed  Google Scholar 

  50. Xue F, Lin LL, Dehdashti F, Miller TR, Siegel BA, Grigsby PW. F-18 fluorodeoxyglucose uptake in primary cervical cancer as an indicator of prognosis after radiation therapy. Gynecol Oncol. 2006;101(1):147-51. https://doi.org/10.1016/j.ygyno.2005.10.005.

    Article  CAS  PubMed  Google Scholar 

  51. St Laurent JD, Davis MR, Feltmate CM, Goodman A, Del Carmen MG, Horowitz NE, et al. Prognostic Value of Preoperative Imaging: Comparing 18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography to Computed Tomography Alone for Preoperative Planning in High-risk Histology Endometrial Carcinoma. Am J Clin Oncol. 2020;43(10):714-9. https://doi.org/10.1097/coc.0000000000000735.

    Article  CAS  PubMed  Google Scholar 

  52. Kitajima K, Murakami K, Yamasaki E, Fukasawa I, Inaba N, Kaji Y, et al. Accuracy of 18F-FDG PET/CT in detecting pelvic and paraaortic lymph node metastasis in patients with endometrial cancer. AJR Am J Roentgenol. 2008;190(6):1652-8. https://doi.org/10.2214/ajr.07.3372.

    Article  PubMed  Google Scholar 

  53. Nakamura K, Kodama J, Okumura Y, Hongo A, Kanazawa S, Hiramatsu Y. The SUVmax of 18F-FDG PET correlates with histological grade in endometrial cancer. Int J Gynecol Cancer. 2010;20(1):110-5. https://doi.org/10.1111/IGC.0b013e3181c3a288.

    Article  PubMed  Google Scholar 

  54. Chung HH, Kim JW, Kang KW, Park NH, Song YS, Chung JK, et al. Post-treatment [18F]FDG maximum standardized uptake value as a prognostic marker of recurrence in endometrial carcinoma. Eur J Nucl Med Mol Imaging. 2011;38(1):74-80. https://doi.org/10.1007/s00259-010-1614-y.

    Article  PubMed  Google Scholar 

  55. Catalano OA, Daye D, Signore A, Iannace C, Vangel M, Luongo A, et al. Staging performance of whole-body DWI, PET/CT and PET/MRI in invasive ductal carcinoma of the breast. Int J Oncol. 2017;51(1):281-8. https://doi.org/10.3892/ijo.2017.4012.

    Article  CAS  PubMed  Google Scholar 

  56. Catalano OA, Nicolai E, Rosen BR, Luongo A, Catalano M, Iannace C, et al. Comparison of CE-FDG-PET/CT with CE-FDG-PET/MR in the evaluation of osseous metastases in breast cancer patients. Br J Cancer. 2015;112(9):1452-60. https://doi.org/10.1038/bjc.2015.112.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Catalano OA, Lee SI, Parente C, Cauley C, Furtado FS, Striar R, et al. Improving staging of rectal cancer in the pelvis: the role of PET/MRI. Eur J Nucl Med Mol Imaging. 2021;48(4):1235-45. https://doi.org/10.1007/s00259-020-05036-x.

    Article  PubMed  Google Scholar 

  58. Grueneisen J, Beiderwellen K, Heusch P, Gratz M, Schulze-Hagen A, Heubner M, et al. Simultaneous positron emission tomography/magnetic resonance imaging for whole-body staging in patients with recurrent gynecological malignancies of the pelvis: a comparison to whole-body magnetic resonance imaging alone. Invest Radiol. 2014;49(12):808-15. https://doi.org/10.1097/rli.0000000000000086.

    Article  PubMed  Google Scholar 

  59. Ward RD, Amorim B, Li W, King J, Umutlu L, Groshar D, et al. Abdominal and pelvic (18)F-FDG PET/MR: a review of current and emerging oncologic applications. Abdom Radiol (NY). 2021;46(3):1236-48. https://doi.org/10.1007/s00261-020-02766-2.

    Article  PubMed  Google Scholar 

  60. Choi BB, Kim SH, Kang BJ, Lee JH, Song BJ, Jeong SH, et al. Diffusion-weighted imaging and FDG PET/CT: predicting the prognoses with apparent diffusion coefficient values and maximum standardized uptake values in patients with invasive ductal carcinoma. World J Surg Oncol. 2012;10:126. https://doi.org/10.1186/1477-7819-10-126.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Brandmaier P, Purz S, Bremicker K, Höckel M, Barthel H, Kluge R, et al. Simultaneous [18F]FDG-PET/MRI: Correlation of Apparent Diffusion Coefficient (ADC) and Standardized Uptake Value (SUV) in Primary and Recurrent Cervical Cancer. PLoS One. 2015;10(11):e0141684. https://doi.org/10.1371/journal.pone.0141684.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Floberg JM, Fowler KJ, Fuser D, DeWees TA, Dehdashti F, Siegel BA, et al. Spatial relationship of 2-deoxy-2-[(18)F]-fluoro-D-glucose positron emission tomography and magnetic resonance diffusion imaging metrics in cervical cancer. EJNMMI Res. 2018;8(1):52. https://doi.org/10.1186/s13550-018-0403-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Surov A, Meyer HJ, Schob S, Höhn AK, Bremicker K, Exner M, et al. Parameters of simultaneous 18F-FDG-PET/MRI predict tumor stage and several histopathological features in uterine cervical cancer. Oncotarget. 2017;8(17):28285-96. https://doi.org/10.18632/oncotarget.16043.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Rakheja R, Chandarana H, DeMello L, Jackson K, Geppert C, Faul D, et al. Correlation between standardized uptake value and apparent diffusion coefficient of neoplastic lesions evaluated with whole-body simultaneous hybrid PET/MRI. AJR Am J Roentgenol. 2013;201(5):1115-9. https://doi.org/10.2214/ajr.13.11304.

    Article  PubMed  Google Scholar 

  65. Fraum TJ, Fowler KJ, Crandall JP, Laforest RA, Salter A, An H, et al. Measurement Repeatability of (18)F-FDG PET/CT Versus (18)F-FDG PET/MRI in Solid Tumors of the Pelvis. J Nucl Med. 2019;60(8):1080-6. https://doi.org/10.2967/jnumed.118.218735.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Catana C. Attenuation correction for human PET/MRI studies. Phys Med Biol. 2020;65(23):23tr02. https://doi.org/10.1088/1361-6560/abb0f8.

    Article  Google Scholar 

  67. Bezrukov I, Schmidt H, Mantlik F, Schwenzer N, Brendle C, Schölkopf B, et al. MR-based attenuation correction methods for improved PET quantification in lesions within bone and susceptibility artifact regions. J Nucl Med. 2013;54(10):1768-74. https://doi.org/10.2967/jnumed.112.113209.

    Article  PubMed  Google Scholar 

  68. Fuin N, Catalano OA, Scipioni M, Canjels LPW, Izquierdo-Garcia D, Pedemonte S, et al. Concurrent Respiratory Motion Correction of Abdominal PET and Dynamic Contrast-Enhanced-MRI Using a Compressed Sensing Approach. J Nucl Med. 2018;59(9):1474-9. https://doi.org/10.2967/jnumed.117.203943.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Madeleine Sertic.

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

Sertic, M., Kilcoyne, A., Catalano, O.A. et al. Quantitative imaging of uterine cancers with diffusion-weighted MRI and 18-fluorodeoxyglucose PET/CT. Abdom Radiol 47, 3174–3188 (2022). https://doi.org/10.1007/s00261-021-03218-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-021-03218-1

Keywords

Navigation