Imaging-based nodal classification for evaluation of neck metastatic adenopathy

Abstract

Objective: This study was undertaken to create an imaging-based classification for the lymph nodes of the neck that will be readily accepted by clinicians, result in consistent nodal classification, and be easily used by radiologists.

Subjects and methods: Over an 18-month period, the necks of 50 patients with cervical lymphadenopathy were scanned with CT, MR imaging, or both. Imaging anatomic landmarks were sought that would create a nodal classification of these necks similar to the clinically based nodal classifications of the American Joint Committee on Cancer and the American Academy of Otolaryngology-Head and Neck Surgery. Each nodal level was defined to ensure consistent nodal classification and eliminate areas of confusion existing in the clinically based classifications.

Results: Necks were classified using the imaging-based classification and then compared with the classification of the same necks using the most common clinically based classifications. The imaging-based nodal classifications of the superficial nodes were the same as the clinically based classifications; however, the deep nodes of eight patients were found only by imaging. The anatomic precision and the level definition afforded by sectional imaging allowed the radiologists to use the imaging-based classification in a consistent manner.

Conclusion: This imaging-based classification has been endorsed by clinicians who specialize in head and neck cancer. The boundaries of the nodal levels were easily discerned by radiologists and yielded consistent nodal classifications. The reproducibility of this classification will allow it to become an essential component of future classifications of metastatic neck disease.