- To describe the basics of the Neck Imaging Reporting and Data System (NI-RADS) classification. - To learn common pitfalls that lead to wrong classification and management plan of patients with head and neck cancers (HNC). - To learn some tips and tricks to optimize NI-RADS classification.

NI-RADS was developed for follow-up imaging evaluation in patients with treated HNC. It aims to provide numerical levels of suspicion for residual tumor or recurrence, generate data-mineable reports and standardize approach with linked management recommendations. Nevertheless, accurate knowledge of common pitfalls is mandatory to avoid patient’s management errors.

Findings and procedure details: NI-RADS classification is based on the combination of morphological (CT, MRI) and molecular (F-18-FDG PET) imaging. In this poster, along with the description of the four NI-RADS categories, we present the most frequently made but avoidable pitfalls. Errors in NI-RADS classification can be divided into those related to technical aspects (metal or motion artifacts, PET resolution, scan timing, single imaging method), normal (physiological F-18-FDG uptake) or tumor (low baseline F-18-FDG uptake, necrosis) conditions and those related to treatment induced changes (inflammatory...

Accurate knowledge of typical post-treatment imaging patterns as well as of common pitfalls is mandatory to expend the use of NI-RADS, thus allowing standardization of patients’ imaging report and care.

ADDIN EN.REFLIST [1] A.H. Aiken, T.J. Rath, Y. Anzai, B.F. Branstetter, J.K. Hoang, R.H. Wiggins, A.F. Juliano, C. Glastonbury, C.D. Phillips, R. Brown, P.A. Hudgins, ACR Neck Imaging Reporting and Data Systems (NI-RADS): A White Paper of the ACR NI-RADS Committee, J Am Coll Radiol 15(8) (2018) 1097-1108. [2] D.A. Krieger, P.A. Hudgins, G.K. Nayak, K.L. Baugnon, A.S. Corey, M.R. Patel, J.J. Beitler, N.F. Saba, Y. Liu, A.H. Aiken, Initial Performance of NI-RADS to Predict Residual or Recurrent Head and Neck Squamous Cell Carcinoma, AJNR...