Diagnostic Accuracy of Multislice CT Scan in the Detection of Cervical Lymph Node Metastasis in Head and Neck Cancers

Abstract

Objectives: To determine the diagnostic accuracy of multislice CT scan in the detection of cervical lymph node metastasis in head and neck cancers, taking histopathology as gold standard.

Study design: Descriptive, cross-sectional study.

Settings: Department of Radiology, Jinnah Hospital, Lahore

Study duration: 8^th January 2018 to 7^th July 2018

Materials & Methods: Total 95patients with squamous cell carcinoma of head and neck, 15-55 years of age of both genders were selected. All the patients with prior radiation to head and neck, already proven histopathology, CRF and claustrophobic patients were excluded. Multislice computed tomography of neck was performed on Toshiba Aquilion Multislice CT scanner before and after intravenous contrast administration. Each multislice CT scan findings were looked for malignant cervical lymph nodes. Multislice CT scan findings were compared with histopathology findings.

Results: Mean age was 43.21 ± 8.16 years. Out of these 95 patients, 54 (56.84%) were males and 41 (43.16%) were females with ratio of 1.3:1.All the patients were subjected to CT of neck and found that 48 were True Positive and 04 were False Positive. Among 43, CT negative patients, 04 (False Negative) had malignant cervical nodes on histopathology whereas 39 (True Negative) had benign cervical nodes on histopathology (p=0.0001). Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of multislice CT scan in the detection of cervical lymph node metastasis in head and neck cancers, taking histopathology as gold standard was 92.31%, 90.70%, 92.31%, 90.70% and 91.58% respectively.

Conclusion: This study concluded that multislice CT scan is a highly sensitive and accurate non-invasive modality for detecting cervical lymph node metastasis in head and neck cancers.

Keywords: Head and Neck Cancers, Cervical Lymph Node Metastasis, Computed Tomography.