DOI: 10.4103/jhnps.jhnps_20_26 ISSN: 2347-8128

Ipsilateral Neck Node Irradiation in Mucoepidermoid Carcinoma of the Parotid Gland: A Case Series and Decision Algorithm

Ahmed Sohaib, Ahmed Beddah, Mohamed Alhefny

Background:

Mucoepidermoid carcinoma (MEC) is the leading malignant salivary gland tumor, with ambiguous neck management for clinically node-negative (cN0) patients. The effectiveness of ipsilateral neck node irradiation (INNI) following surgery and adjuvant radiotherapy is not clearly established due to varying risk factors.

Objective:

This preliminary study presents a series of parotid MEC patients treated surgically with adjuvant radiotherapy, highlighting a two-step algorithm for INNI based on clinical, radiological, and pathological evaluations. We assess outcomes, toxicity, and the rationale for INNI in accordance with established guidelines.

Methods:

Ten patients underwent surgical procedures and received adjuvant radiotherapy (60 Gy). INNI was implemented via a two-step approach: (1) initial clinical and radiological evaluation, followed by (2) postsurgical pathological assessment. INNI was omitted in cN0/pN0 cases, applied in cN0/pN + cases, and considered in cN0 without neck dissection when high-risk features were present. cN + patients were treated based on pathological findings and a multidisciplinary approach. One-year outcomes were evaluated.

Results:

All patients remained alive and disease-free after 1 year, with no recurrences observed. INNI was utilized for four patients (two cN0/pN + and two cN0 with high-risk features). No significant acute or late grade ≥3 toxicity was reported. The decision algorithm facilitated personalized neck management, minimizing unnecessary irradiation.

Conclusion:

The proposed risk-adapted algorithm for INNI in parotid MEC appears feasible and is associated with acceptable short-term toxicity. These findings are exploratory and hypothesis-generating only, given the very small sample size and limited follow-up. Selective INNI for high-risk patients can be easily applied with the proposed algorithm.

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