Diffusion Weighted MRI in Differentiating Benign from Malignant Cervical Lymph Nodes

— Background: The evaluation of cervical lymph nodes is essential for the diagnosis and staging of malignancies, as well as for treatment planning and monitoring. While ultrasound imaging, contrast-enhanced computed tomography, and contrast-enhanced MRI facilitate the identification of enlarged cervical lymphadenopathies, none of these modalities achieves optimal accuracy. Objectives: To evaluate the diagnostic efficacy of DWI in the assessment of cervical lymph nodes in a cohort of Iraqi patients, some of whom had head and neck cancer. Methods: A prospective study conducted at the Oncology Teaching Hospital, Medical City, involved a total of 39 patients with enlarged cervical lymph nodes. They were examined utilizing 1.5 T MRI. DWI was conducted with b values of 0 and 1,000 s/mm². The short axis diameter and ADC values (minimum, maximum, and mean) were assessed for benign and malignant neck lymph nodes, and the results were compared with histological findings obtained through either fine needle aspiration or excisional biopsy. The optimal ADC thresholds were assessed using receiver operating characteristic (ROC) curves to distinguish between cancer and benign neck lymph nodes. Result: The histopathological analysis of included cervical lymph nodes indicated that 56.4% (n=22) were benign, whereas 55% (n=44) were malignant neck lymph nodes, respectively. The ADC values of malignant cervical lymph nodes were significantly lower than those of benign cervical lymph nodes (p < 0.001); 0.6771 ± 0.145 × 10^- 3 mm²/s compared to 1.067 ± 0.257 × 10^-3 mm²/s (mean ADC). The ideal mean ADC threshold was 0.965 x 10^-3 for differentiating cancer from benign cervical lymph nodes, exhibiting a sensitivity of 95.5% and a specificity of 88.2%. Conclusion: MR diffusion imaging and ADC values serve as a non-invasive modality that significantly aids in the evaluation of cervical lymph nodes in head and neck cancer, exhibiting high sensitivity, specificity, and accuracy.