Differentiation of lymphomatous, metastatic, and non-malignant lymphadenopathy in the neck with quantitative diffusion-weighted imaging: systematic review and meta-analysis
To perform a systematic review and meta-analysis of literature comparing average apparent diffusion coefficient (ADC) for differentiating lymphomatous, metastatic, and non-malignant cervical lymphadenopathy.
We performed a comprehensive literature search of Ovid MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Web of Science Core Collection. Studies comparing average ADC of lymphomatous, metastatic, and non-malignant neck lymph nodes were included. The standardized mean difference and 95% confidence interval (CI) was calculated using random-effects models. In subgroup analysis of those studies applying ADC threshold for differentiation of cervical lymphadenopathy, pooled diagnostic odds ratio (DOR) and summary receiver operating characteristics (sROC) area under the curve (AUC) were determined.
A total of 27 studies with 1165 patients were included, pooling data from 225 lymphomatous, 1162 metastatic, and 1333 non-malignant cervical lymph nodes. The average ADC values were lower in lymphomatous compared to metastatic nodes, and in metastatic compared to non-malignant nodes with a standardized mean difference of − 1.36 (95% CI: − 1.71 to − 1.01, p < 0.0001) and − 1.61 (95% CI: − 2.19 to − 1.04, p < 0.0001), respectively. In subgroup analysis, applying ADC threshold could differentiate lymphomatous from metastatic lymphadenopathy with DOR of 52.07 (95% CI 25.45–106.54) and sROC AUC of 0.936 (95% CI 0.896–0.979) and differentiate metastatic from non-malignant nodes with DOR of 39.45 (95% CI 16.92–92.18) and sROC AUC of 0.929 (95% CI 0.873–0.966).
Quantitative assessment of ADC can help with differentiation of suspicious cervical lymph nodes, particularly in those patients without prior history of malignancy or unknown primary cancer site.
KeywordsApparent diffusion coefficient Metastasis Lymphoma Cervical lymphadenopathy
No funding was received for this study. RF is a clinical research scholar supported by the FRQS (Fonds de recherche en santé du Québec).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest with regard to present study. RF has, however, acted as consultant and speaker for GE Healthcare and is a founding partner and stockholder of 4Intel Inc.
All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Informed consent was not required for the study, given the retrospective review of literature.
- 1.Lydiatt W, O'Sullivan B, Patel S (2018) Major changes in head and neck staging for 2018. In: Am Soc Clin Oncol Educ Book, pp 505–514Google Scholar
- 2.Glastonbury CM, Mukherji SK, O'Sullivan B, Lydiatt WM (2017) Setting the stage for 2018: how the changes in the American joint committee on cancer/Union for International Cancer Control cancer staging manual eighth edition impact radiologists. AJNR Am J Neuroradiol 38:2231–2237CrossRefGoogle Scholar
- 9.Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, Clarke M, Devereaux PJ, Kleijnen J, Moher D (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med 151:W65–W94CrossRefGoogle Scholar
- 15.Barchetti F, Pranno N, Giraldi G, Sartori A, Gigli S, Barchetti G, Lo Mele L, Marsella LT (2014) The role of 3 tesla diffusion-weighted imaging in the differential diagnosis of benign versus malignant cervical lymph nodes in patients with head and neck squamous cell carcinoma. Biomed Res Int 2014:532095Google Scholar
- 17.de Bondt RB, Hoeberigs MC, Nelemans PJ, Deserno WM, Peutz-Kootstra C, Kremer B, Beets-Tan RG (2009) Diagnostic accuracy and additional value of diffusion-weighted imaging for discrimination of malignant cervical lymph nodes in head and neck squamous cell carcinoma. Neuroradiology 51:183–192CrossRefGoogle Scholar
- 18.Goel V, Parihar PS, Parihar A, Goel AK, Waghwani K, Gupta R, Bhutekar U (2016) Accuracy of MRI in prediction of tumour thickness and nodal stage in oral tongue and gingivobuccal cancer with clinical correlation and staging. J Clin Diagn Res 10:TC01–TTC5Google Scholar
- 28.Sumi M, Sakihama N, Sumi T, Morikawa M, Uetani M, Kabasawa H, Shigeno K, Hayashi K, Takahashi H, Nakamura T (2003) Discrimination of metastatic cervical lymph nodes with diffusion-weighted MR imaging in patients with head and neck cancer. AJNR Am J Neuroradiol 24:1627–1634Google Scholar
- 33.Vidiri A, Minosse S, Piludu F, Pellini R, Cristalli G, Kayal R, Carlino G, Renzi D, Covello R, Marzi S (2019) Cervical lymphadenopathy: can the histogram analysis of apparent diffusion coefficient help to differentiate between lymphoma and squamous cell carcinoma in patients with unknown clinical primary tumor. Radiol Med 124:19–26CrossRefGoogle Scholar
- 35.Wendl CM, Muller S, Eiglsperger J, Fellner C, Jung EM, Meier JK (2016) Diffusion-weighted imaging in oral squamous cell carcinoma using 3 Tesla MRI: is there a chance for preoperative discrimination between benign and malignant lymph nodes in daily clinical routine. Acta Radiol 57:939–946CrossRefGoogle Scholar
- 36.Yamada I, Yoshino N, Hikishima K, Sakamoto J, Yokokawa M, Oikawa Y, Harada H, Kurabayashi T, Saida Y, Tateishi U, Yukimori A, Izumo T, Asahina S (2018) Oral carcinoma: clinical evaluation using diffusion kurtosis imaging and its correlation with histopathologic findings. Magn Reson Imaging 51:69–78CrossRefGoogle Scholar
- 38.Zhang S-C, Zhou S-H, Shang D-S, Bao Y-Y, Ruan L-X, Wu T-T (2018) The diagnostic role of diffusion-weighted magnetic resonance imaging in hypopharyngeal carcinoma. Oncol Lett 15:5533–5544Google Scholar
- 39.Zhong J, Lu Z, Xu L, Dong L, Qiao H, Hua R, Gong Y, Liu Z, Hao C, Liu X, Zong C, He L, Liu J (2014) The diagnostic value of cervical lymph node metastasis in head and neck squamous carcinoma by using diffusion-weighted magnetic resonance imaging and computed tomography perfusion. Biomed Res Int 2014:260859Google Scholar
- 51.Stecco A, Buemi F, Cassara A, Matheoud R, Sacchetti GM, Arnulfo A, Brambilla M, Carriero A (2016) Comparison of retrospective PET and MRI-DWI (PET/MRI-DWI) image fusion with PET/CT and MRI-DWI in detection of cervical and endometrial cancer lymph node metastases. Radiol Med 121:537–545CrossRefGoogle Scholar
- 52.Kolff-Gart AS, Pouwels PJ, Noij DP, Ljumanovic R, Vandecaveye V, de Keyzer F, de Bree R, de Graaf P, Knol DL, Castelijns JA (2015) Diffusion-weighted imaging of the head and neck in healthy subjects: reproducibility of ADC values in different MRI systems and repeat sessions. AJNR Am J Neuroradiol 36:384–390CrossRefGoogle Scholar
- 53.Paudyal R, Konar AS, Obuchowski NA, Hatzoglou V, Chenevert TL, Malyarenko DI, Swanson SD, LoCastro E, Jambawalikar S, Liu MZ, Schwartz LH, Tuttle RM, Lee N, Shukla-Dave A (2019) Repeatability of quantitative diffusion-weighted imaging metrics in phantoms, head-and-neck and thyroid cancers: preliminary findings. Tomography 5:15–25CrossRefGoogle Scholar
- 54.Shukla-Dave A, Obuchowski NA, Chenevert TL, Jambawalikar S, Schwartz LH, Malyarenko D, Huang W, Noworolski SM, Young RJ, Shiroishi MS, Kim H, Coolens C, Laue H, Chung C, Rosen M, Boss M, Jackson EF (2018) Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials. J Magn Reson ImagingGoogle Scholar