Imaging characteristics and the value of 3 Tesla magnetic resonance imaging in malignant cervical lymphadenopathy

Tran Thi Me Tam1, Nguyen Van Dinh1, Le Duy Huynh1,
1 Da Nang Oncology Hospital

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Abstract

SUMMARY


Purposes: Describe imaging characteristics and assess value of 3 Tesla magnetic resonance imaging in differentiating benign and
malignant cervical nodes.
Materials and methods: There are 96 consecutive patients with cervical nodes were undergone a 3 Tesla magnetic resonance exam from 10/2016 to 9/2017 and compared with histopathological results.
Results: The average age is 55 years old, and male/female=2/1. Loss of the hilar fat, irregular margins, heterogeneous parenchyma on fat-suppressed T2-weighted images were found in malignant and benign lymph nodes were 74.5% and 4.44%, 72.5% and 4.44%, 88.2% and
4.44%. Diagnosis malignant lymph nodes based on the diameter has got the high valuation with p<0.001. Different size criteria for benign and
malignant lymph nodes found that a 11.5 mm size cutoff in the short axis diameter achieved Se 76.5%, Sp 95.6%, Acc 85.4%. In the 67 histologically proven malignant lymphadenopathies, the mean apparent
diffusion coefficient (ADC) value was 0.926 ± 0.133 mm2/sec. In the 29 pathologically confirmed benign lymph nodes, an average ADC value of 1.367 ± 0.165 mm2/sec was found. For differentiating between benign versus metastatic lymph nodes, morphological criteria displayed Se
80.0%, Sp 80.0%, Acc 85.4% whereas combined use of morphological criteria on nodal architecture and ADCs yielded Se 98%, Sp 82.2%, Acc 90.6%.
Conclusion: 3 Tesla magnetic resonance imaging is a non-invasive effective technique that can provide useful information in diagnosing benign and malignant nodes in the neck.

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References

TÀI LIỆU THAM KHẢO
1. Barchetti F. et al. (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
Research International, Volume 2014, Article ID 532095.
2. Bondt R.B.J., Nelemans P.J., Casselman J.W., Kremer B., Beets-Tan R.G.H. (2009), “Morphological MRI criteria improve the detection of lympho node metastases in head and neck squamous cell carcinoma: multivariate logistic regression analysis of MRI features of cervical lympho nodes”, Eur Radiol, 19:626-633.
3. Chong V. (2004), “Cervical lymphadenopathy: what radiologists need to know”, Cancer Imaging, 4:116-120.
4. Hoang J.K. et al. (2013), “Evaluation of cervical lymphonodes in head and neck cancer with CT and MRI: Tips, Traps, and a Systematic Approach”, American Journal of Roentgenology, 200(1): W17-W25.
5. Khan R. (2014), “Lymph node disease and advanced head and neck imaging: A review of the 2013 literature”, Current Radiology Reports, 2:58.
6. Lee M.C., Tsai H.Y., Chuang K.S., Liu C.K. and Chen M.K. (2013), “Prediction of nodal metastasis in head and neck cancer using a 3R MRI ADC map”, American journal of neuroradiology, 34:864-69.
7. Luciani A. et al. (2006), “Lympho node imaging: Basic principles”, European Journal of Radiology, 58:338-344.
8. Lugwig B.J. et al. (2012), “Imaging of cervical lymphadenopathy in children and young adults”, American
Journal of Roentgenology,199:1105-1113.
9. Mao Y. (2014), “Radiologic Assessment of lymph nodes in oncologic patients”, Current Radiology Reports, 2:36.
10. Moreno K.F., Cornelius R.S., Lucas F.V. et al. (2017), “Using 3 Tesla magnetic resonance imaging in the preoperative evaluation of tongue carcinoma”, The Journal of Laryngology & Otology, 1(8)1-8.
11. Sumi M. et al. (2006), “MR microimaging of benign and malignant nodes in the neck”, American Journal of Roentgenology, 186:749-757.
12. Taha Ali T.F. (2012), “Neck lymph nodes: Characterization with diffusion-weighted MRI”, The Egyptian Journal of Radiology and Nuclear Medicine, 43:173-181.