Response Evaluation and Surveillance of Head and Neck Tumours Using the NI-RADS Algorithm

Area of Science:

• Radiology
• Oncology
• Medical Imaging

Background:

• Head and neck neoplasms pose significant challenges in post-treatment surveillance.
• Accurate evaluation of treatment response is crucial for effective patient management and prognosis.
• The American College of Radiology (ACR) developed the Neck Imaging Reporting and Data System (NI-RADS) to standardize reporting.

Purpose of the Study:

• To assess the effectiveness of the ACR NI-RADS system in evaluating treatment response for head and neck neoplasms.
• To determine the diagnostic accuracy of NI-RADS in identifying recurrence after therapy using CT or MRI.
• To evaluate the risk stratification capabilities of NI-RADS for post-treatment head and neck cancer surveillance.

Main Methods:

• A descriptive study involving 70 patients with head and neck cancer post-treatment.
• Contrast-enhanced CT or MRI scans were analyzed using the NI-RADS lexicon and categorization.
• Diagnostic accuracy was determined by comparing NI-RADS findings with histopathology, clinical follow-up, and PET scans.

Main Results:

• The overall accuracy of NI-RADS categorization for primary tumor sites was 82.86%.
• For neck lesions, NI-RADS demonstrated 80% sensitivity, 100% specificity, and 98.59% overall accuracy.
• Negative predictive value was 92% for NI-RADS 1 and 76.92% for NI-RADS 2; Positive predictive value was 69.23% for NI-RADS 3 and 100% for NI-RADS 4.

Conclusions:

• The ACR NI-RADS system exhibits high diagnostic accuracy for post-treatment surveillance of head and neck cancer.
• NI-RADS provides reliable risk stratification, assisting in clinical decision-making.
• The structured reporting format of NI-RADS ensures consistent evaluation of head and neck neoplasms.