title: An imaging-based classification for the cervical nodes designed as an adjunct to recent clinically based nodal classifications.
abstract: Over the past 18 years, numerous classifications have been proposed to distinguish among the diverse nodal levels. Some classifications have used surgical landmarks, others physical assessment criteria. These classifications do not agree precisely and exhibit sufficient variation that competent physicians could arrive at slightly different staging of the patient's nodal disease. In the past 2 decades, computed tomography and magnetic resonance imaging have offered progressively more refined anatomical precision, reproducibility, and visualization of deep, clinically inaccessible structures. Because the majority of patients with head and neck malignancies presently undergo sectional imaging prior to treatment planning, we felt a need to integrate anatomical imaging criteria with the 2 most commonly used nodal classifications: those of the American Joint Committee on Cancer and those of the American Academy of Otolaryngology-Head and Neck Surgery. The imaging-based nodal classification proposed herein has been developed in consultation with surgeons interested in such classifications in the hope that the resultant classification would find ready acceptance by both clinicians and imagers. It is our desire that the best attributes of imaging, combined with those of the physical assessment, can result in a better and more consistently reproducible nodal staging than is possible by either
authors: Department of Radiology, Mount Sinai School of Medicine, City University of New York, NY, USA.
authors: P M
authors: PM
authors: Som
authors: H D
authors: HD
authors: Curtin
authors: A A
authors: AA
authors: Mancuso
mesh_terms: D006258:Head and Neck Neoplasms / Q000145:classification* / Q000000981:diagnostic imaging*; D006801:Humans; D008198:Lymph Nodes / Q000000981:diagnostic imaging* / Q000473:pathology; D008207:Lymphatic Metastasis / Q000175:diagnosis / Q000000981:diagnostic imaging*; D008279:Magnetic Resonance Imaging; D014057:Tomography, X-Ray Computed