PURPOSE
Pre- and post-operative contrast-enhanced neck CT scans were used to quantify lymphatic tissue volume in individuals with invasive tonsillar and tongue base malignancies undergoing dissection of nodal levels 2–4 for the purpose of developing a pre-operative tool to estimate lymph node yield.

INTRODUCTION
Head and neck malignancies account for approximately 550,000 incident cases and 380,000 deaths worldwide annually. In the setting of invasive head and neck malignancies, the resection of lymphatic tissue from the neck (neck dissection) has important implications for staging and treatment. Lymph node yield (number of lymph nodes in a neck dissection specimen) and lymph node ratio (number of cancerous nodes divided by lymph node yield) have been shown to have prognostic significance. However, because lymph node yield and lymph node ratio are highly variable across the population, it may be difficult for surgeons to determine whether an adequate tissue sample has been obtained intra-operatively and for pathologists to anticipate the number of lymph nodes a specimen will contain. Currently, there are no validated tools to estimate adequacy of lymph node dissection based on pre-operative data, which potentially has important implications for lymph node yield and ratio.

MATERIALS AND METHODS
The cohort was composed of 15 individuals with invasive malignancies of the tonsil or tongue base who underwent dissection of nodal levels 2–4 in 2018. Patients who had prior radiation therapy were excluded from the study. All neck dissections were performed by a single head and neck surgeon. Neck lymphatic tissue volumes were quantified from pre- and post-operative contrast-enhanced CT scans using the imaging segmentation software Mimics. A volumetric model of the fat (fat mask) was generated based on Hounsfield units. A second mask composed of nodal levels 2–4 was generated (interpolation mask). The two masks were intersected to create a volumetric model of the fat within nodal levels 2– 4 (intersection mask). This third mask was edited manually to ensure it included nodal tissue and excluded vessels (final mask). Lymph node yield was obtained from the surgical pathology report prepared at the time of neck dissection. Linear regression models were used to correlate reported lymph node yields to the calculated lymphatic volumes on pre- and post-operative CT scans.

RESULTS
A significant correlation (r = 0.94, p < 0.0001) was found between the pre-operative lymphatic tissue volume as measured on CT and the volume of lymphatic tissue resected as estimated by CT. There was also a significant correlation (r = 0.89, p < 0.0001) between the volume of tissue resected as estimated by CT and the volume of tissue resected as determined by gross pathology. A significant correlation (r = 0.82, p = 0.0002) was found between the pre-operative lymphatic tissue volume as measured on CT and the volume of tissue resected as determined by gross pathology. Lastly, the lymph node density by CT and gross pathology showed a significant correlation (r = 0.77, p = 0.0008).

CONCLUSION
Preliminary results in 15 patients demonstrate that CT-derived lymphatic tissue volumes can potentially serve as a useful pre-operative tool in guiding head and neck surgeons on the adequacy of a lymph node dissection in patients with invasive cancers of the tonsil and tongue base.

Utility of CT as a Predictive Tool for Estimating Lymph Node Yield in Patients Affected by Head and Neck Malignancies

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