Skip to main content

Advertisement

SpringerLink
Log in

Synthetic MRI in differentiating benign from metastatic retropharyngeal lymph node: combination with diffusion-weighted imaging

  • Head and Neck
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

This study aimed to evaluate the synthetic MRI (syMRI), its combination with diffusion-weighted imaging (DWI), and morphological features for discriminating benign from metastatic retropharyngeal lymph nodes (RLNs).

Methods

Fifty-eight patients with a total of 63 RLNs (21 benign and 42 metastatic) were enrolled. The mean and standard deviation of syMRI-derived relaxometry parameters (T1, T2, PD; T1SD, T2SD, PDSD) were obtained from two different regions of interest (namely, partial-lesion and full-lesion ROI). The parameters derived from benign and metastatic RLNs were compared using Student’s t or chi-square tests. Logistic regression analysis was used to construct a multi-parameter model of syMRI, syMRI + DWI, and syMRI + DWI + morphological features. Areas under the curve (AUC) were compared using the DeLong test to determine the best diagnostic approach.

Results

Benign RLNs had significantly higher T1, T2, PD, and T1SD values compared with metastatic RLNs in both partial-lesion and full-lesion ROI (all p < 0.05). The T1SD obtained from full-lesion ROI showed the best diagnostic performance among all syMRI-derived single parameters. The AUC of combined syMRI multiple parameters (T1, T2, PD, T1SD) were higher than those of any single parameter from syMRI. The combination of synthetic MRI and DWI can improve the AUC regardless of ROI delineation. Furthermore, the combination of synthetic MRI, DWI-derived quantitative parameters, and morphological features can significantly improve the overall diagnostic performance.

Conclusions

The value of syMRI has been validated in differential diagnosis of benign and metastatic RLNs, and syMRI + DWI + morphological features can further improve the diagnostic efficiency for discriminating these two entities.

Key Points

• Synthetic MRI was useful in differential diagnosis of benign and metastatic RLNs.

• The combination of syMRI, DWI, and morphological features can significantly improve the diagnostic efficiency.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

Abbreviations

ADC:

Apparent diffusion coefficient

AUC:

Area under the curve

cMRI:

Conventional MRI

DWI:

Diffusion-weighted imaging

NPC:

Nasopharyngeal carcinoma

RLNs:

Retropharyngeal lymph nodes

ROI:

Regions of interest

syMRI:

Synthetic MRI

References

  1. Chen YP, Chan A, Le QT, Blanchard P, Sun Y, Ma J (2019) Nasopharyngeal carcinoma. Lancet 394:64–80

    Article  Google Scholar 

  2. Chen J, Luo J, He X, Zhu C (2020) Evaluation of contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) in the detection of retropharyngeal lymph node metastases in nasopharyngeal carcinoma patients. Cancer Manag Res 12:1733–1739

    Article  CAS  Google Scholar 

  3. King AD, Ahuja AT, Leung SF et al (2000) Neck node metastases from nasopharyngeal carcinoma: MR imaging of patterns of disease. Head Neck 22:275–281

    Article  CAS  Google Scholar 

  4. Huang L, Zhang Y, Liu Y et al (2019) Prognostic value of retropharyngeal lymph node metastasis laterality in nasopharyngeal carcinoma and a proposed modification to the UICC/AJCC N staging system. Radiother Oncol 140:90–97

    Article  Google Scholar 

  5. Lee AW, Ng WT, Pan JJ et al (2018) International guideline for the delineation of the clinical target volumes (CTV) for nasopharyngeal carcinoma. Radiother Oncol 126:25–36

    Article  Google Scholar 

  6. Lee AW, Ma BB, Ng WT, Chan AT (2015) Management of nasopharyngeal carcinoma: current practice and future perspective. J Clin Oncol 33:3356–3364

    Article  Google Scholar 

  7. Tang C, Komakula S, Chan C et al (2013) Radiologic assessment of retropharyngeal node involvement in oropharyngeal carcinomas stratified by HPV status. Radiother Oncol 109:293–296

    Article  Google Scholar 

  8. Kato H, Kanematsu M, Watanabe H, Mizuta K, Aoki M (2014) Metastatic retropharyngeal lymph nodes: comparison of CT and MR imaging for diagnostic accuracy. Eur J Radiol 83:1157–1162

    Article  Google Scholar 

  9. Zhang GY, Liu LZ, Wei WH, Deng YM, Li YZ, Liu XW (2010) Radiologic criteria of retropharyngeal lymph node metastasis in nasopharyngeal carcinoma treated with radiation therapy. Radiology 255:605–612

    Article  Google Scholar 

  10. Abdel RA, Soliman NY, Elkhamary S, Alsharaway MK, Tawfik A (2006) Role of diffusion-weighted MR imaging in cervical lymphadenopathy. Eur Radiol 16:1468–1477

    Article  Google Scholar 

  11. Jin GQ, Yang J, Liu LD et al (2016) The diagnostic value of 1.5-T diffusion-weighted MR imaging in detecting 5 to 10 mm metastatic cervical lymph nodes of nasopharyngeal carcinoma. Medicine (Baltimore) 95:e4286

    Article  CAS  Google Scholar 

  12. Chen C, Lin Z, Xiao Y et al (2018) Role of diffusion-weighted imaging in the discrimination of benign and metastatic parotid area lymph nodes in patients with nasopharyngeal carcinoma. Sci Rep 8:281

    Article  Google Scholar 

  13. Li H, Liu XW, Geng ZJ, Wang DL, Xie CM (2015) Diffusion-weighted imaging to differentiate metastatic from non-metastatic retropharyngeal lymph nodes in nasopharyngeal carcinoma. Dentomaxillofac Radiol 44:20140126

    Article  CAS  Google Scholar 

  14. Pekcevik Y, Cukurova I, Arslan IB (2015) Apparent diffusion coefficient for discriminating metastatic lymph nodes in patients with squamous cell carcinoma of the head and neck. Diagn Interv Radiol 21:397–402

    Article  Google Scholar 

  15. Warntjes JB, Dahlqvist O, Lundberg P (2007) Novel method for rapid, simultaneous T1, T2*, and proton density quantification. Magn Reson Med 57:528–537

    Article  CAS  Google Scholar 

  16. Warntjes JB, Leinhard OD, West J, Lundberg P (2008) Rapid magnetic resonance quantification on the brain: optimization for clinical usage. Magn Reson Med 60:320–329

    Article  CAS  Google Scholar 

  17. Jung Y, Gho SM, Back SN, Ha T, Kang DK, Kim TH (2018) The feasibility of synthetic MRI in breast cancer patients: comparison of T2 relaxation time with multiecho spin echo T2 mapping method. Br J Radiol:20180479

  18. Hagiwara A, Hori M, Cohen-Adad J et al (2019) Linearity, bias, intrascanner repeatability, and interscanner reproducibility of quantitative multidynamic multiecho sequence for rapid simultaneous relaxometry at 3 T: a validation study with a standardized phantom and healthy controls. Invest Radiol 54:39–47

    Article  Google Scholar 

  19. Gao W, Zhang S, Guo J et al (2021) Investigation of synthetic relaxometry and diffusion measures in the differentiation of benign and malignant breast lesions as compared to BI-RADS. J Magn Reson Imaging 53:1118–1127

    Article  Google Scholar 

  20. Cai Q, Wen Z, Huang Y et al (2021) Investigation of synthetic magnetic resonance imaging applied in the evaluation of the tumor grade of bladder cancer. J Magn Reson Imaging 54:1989–1997

    Article  Google Scholar 

  21. Meng T, He H, Liu H et al (2021) Investigation of the feasibility of synthetic MRI in the differential diagnosis of non-keratinising nasopharyngeal carcinoma and benign hyperplasia using different contoured methods for delineation of the region of interest. Clin Radiol 76:238–239

    Article  Google Scholar 

  22. Han X, Suo S, Sun Y et al (2017) Apparent diffusion coefficient measurement in glioma: influence of region-of-interest determination methods on apparent diffusion coefficient values, interobserver variability, time efficiency, and diagnostic ability. J Magn Reson Imaging 45:722–730

    Article  Google Scholar 

  23. So TY, Ai QH, Lam W et al (2020) Intravoxel incoherent motion diffusion-weighted imaging for discrimination of benign and malignant retropharyngeal nodes. Neuroradiology 62:1667–1676

    Article  Google Scholar 

  24. DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845

    Article  CAS  Google Scholar 

  25. Zhao L, Liang M, Xie L, Yang Y, Zhang H, Zhao X (2021) Prediction of pathological prognostic factors of rectal cancer by relaxation maps from synthetic magnetic resonance imaging. Eur J Radiol 138:109658

    Article  Google Scholar 

  26. Spieker M, Katsianos E, Gastl M et al (2018) T2 mapping cardiovascular magnetic resonance identifies the presence of myocardial inflammation in patients with dilated cardiomyopathy as compared to endomyocardial biopsy. Eur Heart J Cardiovasc Imaging 19:574–582

    Article  CAS  Google Scholar 

  27. Cui Y, Han S, Liu M et al (2020) Diagnosis and grading of prostate cancer by relaxation maps from synthetic MRI. J Magn Reson Imaging 52:552–564

    Article  Google Scholar 

  28. Ge YX, Hu SD, Wang Z et al (2021) Feasibility and reproducibility of T2 mapping and DWI for identifying malignant lymph nodes in rectal cancer. Eur Radiol 31:3347–3354

    Article  Google Scholar 

  29. Matsuda M, Tsuda T, Ebihara R et al (2021) Enhanced masses on contrast-enhanced breast: differentiation using a combination of dynamic contrast-enhanced MRI and quantitative evaluation with synthetic MRI. J Magn Reson Imaging 53:381–391

    Article  Google Scholar 

  30. Meng T, He N, He H et al (2020) The diagnostic performance of quantitative mapping in breast cancer patients: a preliminary study using synthetic MRI. Cancer Imaging 20:88

    Article  Google Scholar 

  31. Gracien RM, Reitz SC, Hof SM et al (2016) Changes and variability of proton density and T1 relaxation times in early multiple sclerosis: MRI markers of neuronal damage in the cerebral cortex. Eur Radiol 26:2578–2586

    Article  Google Scholar 

  32. Jovic A, Fila J, Grsic K, Ivkic M, Ozretic D (2020) Diffusion-weighted MRI: impact of the size of the ROI in detecting metastases in subcentimeter lymph nodes in head and neck squamous cell carcinoma. Neuroradiology 62:987–994

    Article  Google Scholar 

  33. Suh CH, Choi YJ, Baek JH, Lee JH (2018) The diagnostic value of diffusion-weighted imaging in differentiating metastatic lymph nodes of head and neck squamous cell carcinoma: a systematic review and meta-analysis. AJNR Am J Neuroradiol 39:1889–1895

    Article  CAS  Google Scholar 

  34. Connolly M, Srinivasan A (2018) Diffusion-weighted imaging in head and neck cancer: technique, limitations, and applications. Magn Reson Imaging Clin N Am 26:121–133

    Article  Google Scholar 

  35. Payabvash S (2018) Quantitative diffusion magnetic resonance imaging in head and neck tumors. Quant Imaging Med Surg 8:1052–1065

    Article  Google Scholar 

  36. Yamada I, Yoshino N, Hikishima K et al (2017) Colorectal carcinoma: ex vivo evaluation using 3-T high-spatial-resolution quantitative T2 mapping and its correlation with histopathologic findings. Magn Reson Imaging 38:174–181

    Article  Google Scholar 

  37. Ren JL, Yuan Y, Li XX, Shi YQ, Tao XF (2018) Histogram analysis of apparent diffusion coefficient maps in the prognosis of patients with locally advanced head and neck squamous cell carcinoma: comparison of different region of interest selection methods. Eur J Radiol 106:7–13

    Article  Google Scholar 

  38. Sun SY, Ding Y, Li Z et al (2021) Multiparameter MRI model with DCE-MRI, DWI, and synthetic MRI improves the diagnostic performance of BI-RADS 4 lesions. Front Oncol 11:699127

    Article  Google Scholar 

  39. Ge X, Wang M, Ma H et al (2022) Investigated diagnostic value of synthetic relaxometry, three-dimensional pseudo-continuous arterial spin labelling and diffusion-weighted imaging in the grading of glioma. Magn Reson Imaging 86:20–27

    Article  Google Scholar 

  40. Li S, Zhang Z, Liu J et al (2021) The feasibility of a radial turbo-spin-echo T2 mapping for preoperative prediction of the histological grade and lymphovascular space invasion of cervical squamous cell carcinoma. Eur J Radiol 139:109684

    Article  Google Scholar 

  41. Abudureheman Y, Wang J, Liu W (2017) Comparison of intravoxel incoherent motion diffusion-weighted magnetic resonance (MR) imaging to T1 mapping in characterization of hepatic alveolar echinococcosis. Med Sci Monit 23:6019–6025

    Article  CAS  Google Scholar 

  42. Fujima N, Homma A, Harada T et al (2019) The utility of MRI histogram and texture analysis for the prediction of histological diagnosis in head and neck malignancies. Cancer Imaging 19:5

    Article  Google Scholar 

  43. Cai PQ, Li YZ, Zeng RF et al (2013) Nasopharyngeal tuberculosis: CT and MRI findings in thirty-six patients. Eur J Radiol 82:e448–e454

    Article  Google Scholar 

  44. Yang L, Li H, Wang H et al (2016) Nasopharyngeal granulomatous mass after radiotherapy for nasopharyngeal carcinoma. Auris Nasus Larynx 43:330–335

    Article  Google Scholar 

  45. Akin S, Akin S, Karadag O, Kalyoncu U, Balci S, Ozgen B (2012) Nasopharyngeal sarcoidosis: a rare involvement. Rheumatol Int 32:1407–1409

    Article  Google Scholar 

Download references

Funding

None

Author information

Authors and Affiliations

  1. Department of Radiology, Affiliated Hospital of Jiangnan University, 1000 Hefeng Road, Wuxi, 214122, People’s Republic of China

    Peng Wang, Shudong Hu, Xiuyu Wang, Yuxi Ge, Jing Zhao, Hongyan Qiao, Jun Chang & Heng Zhang

  2. GE Healthcare, MR Research China, Beijing, 100176, People’s Republic of China

    Weiqiang Dou

Authors
  1. Peng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shudong Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiuyu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuxi Ge
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jing Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hongyan Qiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jun Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Weiqiang Dou
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Heng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Heng Zhang.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Prof. Heng Zhang, MD, Affiliated Hospital of Jiangnan University.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic study

• performed at one institution

Additional information

Publisher’s note

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

Peng Wang, Shudong Hu, and Xiuyu Wang are Co-first authors.

Supplementary Information

ESM 1

ROC curves for differentiating benign from metastatic retropharyngeal lymph node for partial-lesion ROIs delineation. The AUC of synthetic MRI +DWI+morphological features (size) was significantly higher than those of combined (P), DWI or morphological features (size) alone (both p <0.05). Synthetic MRI: combined syMRI derived quantitative parameters (T1, T2, PD, T1SD). (DOCX 115 kb)

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, P., Hu, S., Wang, X. et al. Synthetic MRI in differentiating benign from metastatic retropharyngeal lymph node: combination with diffusion-weighted imaging. Eur Radiol 33, 152–161 (2023). https://doi.org/10.1007/s00330-022-09027-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-022-09027-4

Keywords

Search

Navigation