Nuclear medicine communications · 2026
A scoring model based on lymph node-to-primary tumor standardized uptake value ratio aids in classifying neck nodal metastasis risk in patients with head and neck cancer treated by surgery.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Chi Shuang-Shuang, Chan Sheng-Chieh, Shih Yu-Tai, Chen Peir-Rong, Ng Shu-Hang
Аннотация
OBJECTIVE: Accurate detection of cervical lymph node metastasis in head and neck cancer (HNC) is essential for guiding neck dissection. The lymph node-to-primary tumor maximum standardized uptake value (SUVmax) ratio (NTR), derived from [18F]fluorodeoxyglucose PET/computed tomography ([18F]FDG PET/CT), has emerged as a robust and reproducible imaging biomarker. This study aimed to evaluate the diagnostic value of NTR for predicting cervical nodal metastasis in patients with HNC.
METHODS: This retrospective study included 167 patients with surgically treated HNC who underwent neck dissection. All patients received contrast-enhanced CT/MRI and [18F]FDG PET/CT before treatment. The diagnostic performance was evaluated using histopathology as the reference standard. Clinical and imaging factors were analyzed, and a scoring model was constructed.
RESULTS: On visual interpretation, [18F]FDG PET/CT outperformed CT/MRI, showing higher sensitivity (87.5 vs. 77.4%) and specificity (75.7 vs. 68.6%), but its positive predictive value (PPV) remained suboptimal (69.1%). Multivariate analysis identified SUVmax of cervical lymph nodes (P = 0.049) and NTR (P = 0.038) as independent predictors. A scoring model incorporating these predictors was developed. When visual interpretation was combined with the scoring model, visually positive nodes were stratified into high-risk (PPV: 86.8%), intermediate-risk (PPV: 41.1%), and low-risk (PPV: 36.3%) for refined discrimination of metastatic potential.
CONCLUSION: Integration of visual assessment with an NTR-based scoring model enhances the diagnostic accuracy of [18F]FDG PET/CT in evaluating cervical lymph node metastasis in HNC. This combined approach may improve diagnostic confidence and help minimize unnecessary neck dissections.
METHODS: This retrospective study included 167 patients with surgically treated HNC who underwent neck dissection. All patients received contrast-enhanced CT/MRI and [18F]FDG PET/CT before treatment. The diagnostic performance was evaluated using histopathology as the reference standard. Clinical and imaging factors were analyzed, and a scoring model was constructed.
RESULTS: On visual interpretation, [18F]FDG PET/CT outperformed CT/MRI, showing higher sensitivity (87.5 vs. 77.4%) and specificity (75.7 vs. 68.6%), but its positive predictive value (PPV) remained suboptimal (69.1%). Multivariate analysis identified SUVmax of cervical lymph nodes (P = 0.049) and NTR (P = 0.038) as independent predictors. A scoring model incorporating these predictors was developed. When visual interpretation was combined with the scoring model, visually positive nodes were stratified into high-risk (PPV: 86.8%), intermediate-risk (PPV: 41.1%), and low-risk (PPV: 36.3%) for refined discrimination of metastatic potential.
CONCLUSION: Integration of visual assessment with an NTR-based scoring model enhances the diagnostic accuracy of [18F]FDG PET/CT in evaluating cervical lymph node metastasis in HNC. This combined approach may improve diagnostic confidence and help minimize unnecessary neck dissections.