Pretreatment CT Identification of Extranodal Extension in Laryngeal and Hypopharyngeal Cancers Using Deep Learning.

Background Accurate preoperative identification of pathologic extranodal extension (ENE) at CT is essential for precise treatment decisions in laryngeal and hypopharyngeal squamous cell cancer (LHSCC). However, human interpretation of ENE is neither reliable nor reproducible. Purpose To develop and evaluate the diagnostic performance of a new deep learning tool, DeepENE, in detecting metastatic and ENE lymph nodes on preoperative CT scans in patients with LHSCC in a multicenter cohort. Materials and Methods In this retrospective study, patients with LHSCC from Zhongshan Hospital, Fudan University (April 2011-August 2022), were included in training, validation, and internal test sets to develop DeepENE. For the reference standard, lymph nodes were segmented on CT scans and labeled for metastasis and ENE status based on pathologic findings. DeepENE was tested using three external cohorts of patients with LHSCC (external test sets 1-3) and one external cohort of patients with oral squamous cell carcinoma. The primary diagnostic metric was the area under the receiver operating characteristic curve (AUC). The performance of DeepENE was compared with that of five board-certified head and neck cancer specialists using the DeLong method. Results Overall, 289 patients with LHSCC with 1954 pathologically confirmed lymph nodes were evaluated. DeepENE achieved an AUC of 0.93 for ENE diagnosis in the internal test set under fivefold cross-validation, and AUCs of 0.96, 0.87, and 0.90 in external test sets 1, 2, and 3, respectively. DeepENE outperformed the five experts, especially in early-stage ENE detection in external test set 2 (AUC of 0.87 for DeepENE vs mean AUC of 0.66 for readers; P < .001). In external test set 1, DeepENE maintained a high sensitivity of 97% at specificity of 90%, compared with experts' mean sensitivity of 77% (P = .003). In external test sets 2 and 3, DeepENE had sensitivity of 78% and 80%, compared with experts' mean sensitivity of 36% (P < .001) and 46% (P < .001), respectively. Conclusion DeepENE accurately detected ENE on preoperative CT scans in patients with LHSCC and outperformed head and neck cancer specialists. © RSNA, 2026 Supplemental material is available for this article.