Munetaka Matoba1, Hiroyuki Tsuji2, Yuzo Shimode2, Hiroji Nagata3, Hisao Tonami1. 1. 1 Department of Radiology, Kanazawa Medical University, Daigaku 1-1, Uchinada, Kahoku, Ishikawa 920-0293, Japan. 2. 2 Department of Head and Neck Surgery, Kanazawa Medical University, Kahoku, Ishikawa, Japan. 3. 3 Department of Medical Technology, Kanazawa Medical University, Kahoku, Ishikawa, Japan.
Abstract
OBJECTIVE: The purpose of this study was to investigate the diagnostic performance of adaptive 4D volume perfusion CT covering the entire neck for detecting metastatic nodes in patients with head and neck squamous cell carcinoma. SUBJECTS AND METHODS: Thirty patients with histologically confirmed disease were enrolled. The relation between perfusion parameters and nodal size was analyzed, and perfusion parameters were compared between metastatic and benign nodes. The diagnostic capability for detecting metastatic nodes was evaluated. RESULTS: Significant inverse correlations with nodal size were found for blood flow (r = -0.40, p = 0.002), blood volume (r = -0.32, p = 0.02), and permeability surface product (r = -0.27, p = 0.04) of the metastatic nodes. All three parameters had significantly higher values in association with nodal maximum diameter < 10 mm compared with diameter ≥ 10 mm (blood flow, p = 0.004; blood volume, p = 0.01; permeability surface product, p = 0.02). Among the nodes with maximum diameter < 10 mm, blood flow of the metastatic nodes was significantly higher than that of the benign nodes (p = 0.02), whereas among the nodes ≥ 10 mm in diameter, the mean transit time of the metastatic nodes was significantly lower than that of the benign nodes (p = 0.04). In multivariate analysis, blood flow in nodes with maximum diameter < 10 mm had a significant association with the detection of metastatic nodes. The sensitivity and specificity of blood flow for differentiating metastatic from benign nodes were 73.3% and 70.8%. CONCLUSION: Findings from 4D volume perfusion CT covering the entire neck may be informative for characterization of cervical nodes. It is worthwhile to include the examination in nodal staging of head and neck squamous cell carcinoma.
OBJECTIVE: The purpose of this study was to investigate the diagnostic performance of adaptive 4D volume perfusion CT covering the entire neck for detecting metastatic nodes in patients with head and neck squamous cell carcinoma. SUBJECTS AND METHODS: Thirty patients with histologically confirmed disease were enrolled. The relation between perfusion parameters and nodal size was analyzed, and perfusion parameters were compared between metastatic and benign nodes. The diagnostic capability for detecting metastatic nodes was evaluated. RESULTS: Significant inverse correlations with nodal size were found for blood flow (r = -0.40, p = 0.002), blood volume (r = -0.32, p = 0.02), and permeability surface product (r = -0.27, p = 0.04) of the metastatic nodes. All three parameters had significantly higher values in association with nodal maximum diameter < 10 mm compared with diameter ≥ 10 mm (blood flow, p = 0.004; blood volume, p = 0.01; permeability surface product, p = 0.02). Among the nodes with maximum diameter < 10 mm, blood flow of the metastatic nodes was significantly higher than that of the benign nodes (p = 0.02), whereas among the nodes ≥ 10 mm in diameter, the mean transit time of the metastatic nodes was significantly lower than that of the benign nodes (p = 0.04). In multivariate analysis, blood flow in nodes with maximum diameter < 10 mm had a significant association with the detection of metastatic nodes. The sensitivity and specificity of blood flow for differentiating metastatic from benign nodes were 73.3% and 70.8%. CONCLUSION: Findings from 4D volume perfusion CT covering the entire neck may be informative for characterization of cervical nodes. It is worthwhile to include the examination in nodal staging of head and neck squamous cell carcinoma.
Authors: Reza Assadsangabi; Rosa Babaei; Catherine Songco; Vladimir Ivanovic; Matthew Bobinski; Yin J Chen; Seyed Ali Nabavizadeh Journal: Radiol Med Date: 2021-05-16 Impact factor: 3.469