Misa Sumi1, Takashi Nakamura. 1. Department of Radiology and Cancer Biology, Nagasaki University School of Dentistry, Nagasaki, Japan.
Abstract
PURPOSE: We evaluated dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the preoperative detection of extranodal spread (ENS) in metastatic nodes in the neck. MATERIALS AND METHODS: The time-signal intensity curve (TIC) profiles of 54 histologically proven metastatic nodes (26 ENS-positive and 28 ENS-negative) from 43 patients with head and neck squamous cell carcinoma (SCC) were retrospectively analyzed to determine the effective TIC criteria for ENS-positive nodes. The TICs were semiautomatically classified into four distinctive patterns (flat, slow uptake, rapid uptake with low washout ratio, and rapid uptake with high washout ratio) on a pixel-by-pixel basis. RESULTS: A number of the MRI findings were significantly correlated with ENS. However, multivariate logistic regression analysis revealed that only a short-axis diameter and an area with slow uptake TIC patterns were significantly and independently indicative of the presence of ENS. The combined MRI criteria of nodal size (>25 mm) or TIC profile (>44% nodal areas with slow-uptake TIC patterns) yielded the best results for differentiation between ENS-positive and ENS-negative nodes, providing 96% sensitivity, 100% specificity, 98% accuracy, and 100% positive, and 97% negative predictive values. CONCLUSION: When combined with size criteria, pixel-based MR factor analysis may be a promising tool for detecting ENS.
PURPOSE: We evaluated dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the preoperative detection of extranodal spread (ENS) in metastatic nodes in the neck. MATERIALS AND METHODS: The time-signal intensity curve (TIC) profiles of 54 histologically proven metastatic nodes (26 ENS-positive and 28 ENS-negative) from 43 patients with head and neck squamous cell carcinoma (SCC) were retrospectively analyzed to determine the effective TIC criteria for ENS-positive nodes. The TICs were semiautomatically classified into four distinctive patterns (flat, slow uptake, rapid uptake with low washout ratio, and rapid uptake with high washout ratio) on a pixel-by-pixel basis. RESULTS: A number of the MRI findings were significantly correlated with ENS. However, multivariate logistic regression analysis revealed that only a short-axis diameter and an area with slow uptake TIC patterns were significantly and independently indicative of the presence of ENS. The combined MRI criteria of nodal size (>25 mm) or TIC profile (>44% nodal areas with slow-uptake TIC patterns) yielded the best results for differentiation between ENS-positive and ENS-negative nodes, providing 96% sensitivity, 100% specificity, 98% accuracy, and 100% positive, and 97% negative predictive values. CONCLUSION: When combined with size criteria, pixel-based MR factor analysis may be a promising tool for detecting ENS.
Authors: Jing Yuan; Steven Kwok Keung Chow; Qinwei Zhang; David Ka Wai Yeung; Anil T Ahuja; Ann D King Journal: PLoS One Date: 2013-03-20 Impact factor: 3.240
Authors: Flora Yan; Hannah M Knochelmann; Patrick F Morgan; John M Kaczmar; David M Neskey; Evan M Graboyes; Shaun A Nguyen; Besim Ogretmen; Anand K Sharma; Terry A Day Journal: Cancers (Basel) Date: 2020-06-11 Impact factor: 6.639