Abstract
Accurate and consistent characterization of metastatic cervical adenopathy is essential for the initial staging, treatment planning and surveillance of head and neck cancer patients. While enlarged superficial nodes may be clinically palpated, imaging allows identification of deeper adenopathy as well as clinically unsuspected pathology and thus imaging has become an integral part of the evaluation of most head and neck cancers patients. This review will focus on the evaluation of cervical adenopathy, summarizing the currently used nomenclature and imaging approach for determining cervical lymph node metastases in head and neck malignancies. The imaging-based classification, which has also been adopted by the American Joint Committee on Cancer, will be presented, the morphologic characteristics used to identify metastatic nodes will be reviewed and the typical nodal spread patterns of the major mucosal cancers of the head and neck will be examined.
Acknowledgements
The authors would like to thank V Glyudza for assistance with figure preparation and I Gliudza for preparation of illustrations.
Financial & competing interests disclosure
R Forghani and M Levental have acted as a consultant for Biogen Idec for the event ‘Neuroradiology Scientific Exchange Program – focus on the role of MRI in the detection, diagnosis and monitoring of natalizumab-associated progressive multifocal leukoencephalopathy (PML) in patients with multiple sclerosis’. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending or royalties.
No writing assistance was utilized in the production of this manuscript.
Determination of node location can be reliably performed using the imaging classification which has had widespread acceptance and is used by the American Joint Committee on Cancer for head and neck cancer nodal staging.
Determination of presence of nodal metastases is best performed via a multiparametric approach combining multiple anatomic/morphologic criteria, information from functional imaging such as PET when available and key clinical information. However, the neck may still be treated based on tumor size and primary site, even when imaging is negative for nodal disease, because imaging is not sensitive enough to detect all clinically important micrometastases.
The anatomic/morphologic criteria used for evaluation of cervical nodes can be remembered by the acronym CRISPS (clustering, rounded shape, inhomogeneity, size, periphery, sentinel location) and when combined can identify metastatic nodes >8–10 mm with relatively high reliability.
Incorporation of key clinical information is essential for optimal evaluation: while an enlarged or inhomogenous node in a patient with biopsy proven head and neck cancer can be reliably characterized as metastatic, a similar node in a young patient presenting with acute infectious symptoms is likely to represent infectious lymphadenitis.
For borderline or indeterminate nodes, ultrasound-guided fine-needle aspiration can be very useful for determination of metastatic lymphadenopathy.
Notes
†In practice, some will report both levels, separated by a hyphen (e.g., level II–III node). This is not the way node assignment is described in the official imaging classification, although in practice relays the necessary anatomic information accurately.
†Minimal axial diameter or dimension corresponds to the widest diameter of the node in the axial plane that is perpendicular to the maximum axial diameter.
‡Nodal clustering or grouping is defined as the presence of three or more borderline lymph nodes in the first or second lymph node drainage region of a primary tumor site. When present, the size threshold for metastatic lymphadenopathy for clustered nodes can be decreased by 1–2 mm, increasing sensitivity, without significantly affecting specificity.