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Head and neck cancers accounts for maximum number of cancer cases in Indian hospital settings. Involvement of neck nodes is a very important prognostic factor of its outcome. Differentiation between benign and metastatic lymphadenopathy often presents a diagnostic challenge with conventional imaging techniques. Diffusion-weighted imaging (DWI) has emerged as a powerful non-invasive imaging technique that is capable of characterisation of these lesions as benign or malignant with the help of apparent diffusion coefficient (ADC) maps. Aim: The aim of this cross-sectional study was to determine the diagnostic accuracy of DWI to differentiate benign from malignant cervical lymph nodes in head and neck tumours, subsequently confirming the results using histopathology as the reference standard. Materials and Methods: The cross-sectional study was conducted on 60 patients of either age or sex with enlarged neck lymph nodes over a period of 2 years, subsequently these patients underwent DW MRI imaging followed by histopathology of either neck dissection specimen or core biopsy or US guided FNAC as a part of the study. Results: Out of 60 patients, 41(68.33 percent) cases came out as malignant and 19 (31.67 percent) cases came out as benign. The results obtained were 36 true positives, 4 false positives, 15 true negatives and 5 false negatives. The overall sensitivity of DWI for differentiating malignant from benign cervical lymphadenopathy was 87.80% with specificity of 78.95%. The positive predictive value and negative predictive value were 90.00% and 75.00% respectively. The best ADC threshold value for distinguishing benign and malignant nodes was 1.005 × 10-3 mm2/sec. Conclusion: DWI is an important tool to differentiate benign vs malignant lymphadenopathy and helps in guiding the clinician to treat these nodes accordingly.

Head and neck cancers accounts for maximum number of cancer cases in Indian hospital settings. Involvement of neck nodes is a very important prognostic factor of its outcome. Differentiation between benign and metastatic lymphadenopathy often presents a diagnostic challenge with conventional imaging techniques. Diffusion-weighted imaging (DWI) has emerged as a powerful non-invasive imaging technique that is capable of characterisation of these lesions as benign or malignant with the help of apparent diffusion coefficient (ADC) maps. Aim: The aim of this cross-sectional study was to determine the diagnostic accuracy of DWI to differentiate benign from malignant cervical lymph nodes in head and neck tumours, subsequently confirming the results using histopathology as the reference standard. Materials and Methods: The cross-sectional study was conducted on 60 patients of either age or sex with enlarged neck lymph nodes over a period of 2 years, subsequently these patients underwent DW MRI imaging followed by histopathology of either neck dissection specimen or core biopsy or US guided FNAC as a part of the study. Results: Out of 60 patients, 41(68.33 percent) cases came out as malignant and 19 (31.67 percent) cases came out as benign. The results obtained were 36 true positives, 4 false positives, 15 true negatives and 5 false negatives. The overall sensitivity of DWI for differentiating malignant from benign cervical lymphadenopathy was 87.80% with specificity of 78.95%. The positive predictive value and negative predictive value were 90.00% and 75.00% respectively. The best ADC threshold value for distinguishing benign and malignant nodes was 1.005 × 10-3 mm2/sec. Conclusion: DWI is an important tool to differentiate benign vs malignant lymphadenopathy and helps in guiding the clinician to treat these nodes accordingly.