Dongyan Cai1,2, Size Wu1. 1. Department of Ultrasound, The First Affiliated Hospital of Hainan Medical University, Haikou, China. 2. Department of Medical Ultrasound, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China.
Abstract
OBJECTIVES: To investigate whether a multiparametric ultrasound (MPUS) diagnostic model improves differential diagnosis of benign and malignant cervical lymph nodes. METHODS: MPUS evaluation was performed on 87 lesions in 86 patients, and related characteristics and parameters of the patients and lesions were studied and logistic regression models based on the MPUS characteristics of cervical lymph nodes were built. A receiver operating characteristic curve and area under the curve (AUC) were built for the evaluation of diagnostic performances. RESULTS: Of the 87 lesions in 86 patients, there were 31 benign and 56 malignant lesions. Regression models for Duplex ultrasound and MPUS were established. The Duplex ultrasound regression model showed a sensitivity, specificity, positive predictive value and negative predictive value of 94.4, 61.3, 86.3 and 80.9%, respectively. The predictive accuracy was 82.4%, and the AUC was 0.861. The MPUS regression model showed a sensitivity, specificity, positive predictive value and negative predictive value of 98.1, 61.3, 81.5 and 95.0%, respectively. The predictive accuracy was 84.7%, and the AUC was 0.894. The differences in AUCs between the Duplex ultrasound model and MPUS model, ultrasound model and ultrasonic elastography (UE), and Duplex ultrasound and UE were not significant (all p > 0.05); the differences in AUCs between the MPUS model and Duplex ultrasound, Duplex ultrasound model and Duplex ultrasound, and MPUS model and UE were significant (all p < 0.05). CONCLUSIONS: The Duplex ultrasound and MPUS models achieve significantly higher diagnostic performance for differentiating between benign and malignant cervical lymph nodes.
OBJECTIVES: To investigate whether a multiparametric ultrasound (MPUS) diagnostic model improves differential diagnosis of benign and malignant cervical lymph nodes. METHODS: MPUS evaluation was performed on 87 lesions in 86 patients, and related characteristics and parameters of the patients and lesions were studied and logistic regression models based on the MPUS characteristics of cervical lymph nodes were built. A receiver operating characteristic curve and area under the curve (AUC) were built for the evaluation of diagnostic performances. RESULTS: Of the 87 lesions in 86 patients, there were 31 benign and 56 malignant lesions. Regression models for Duplex ultrasound and MPUS were established. The Duplex ultrasound regression model showed a sensitivity, specificity, positive predictive value and negative predictive value of 94.4, 61.3, 86.3 and 80.9%, respectively. The predictive accuracy was 82.4%, and the AUC was 0.861. The MPUS regression model showed a sensitivity, specificity, positive predictive value and negative predictive value of 98.1, 61.3, 81.5 and 95.0%, respectively. The predictive accuracy was 84.7%, and the AUC was 0.894. The differences in AUCs between the Duplex ultrasound model and MPUS model, ultrasound model and ultrasonic elastography (UE), and Duplex ultrasound and UE were not significant (all p > 0.05); the differences in AUCs between the MPUS model and Duplex ultrasound, Duplex ultrasound model and Duplex ultrasound, and MPUS model and UE were significant (all p < 0.05). CONCLUSIONS: The Duplex ultrasound and MPUS models achieve significantly higher diagnostic performance for differentiating between benign and malignant cervical lymph nodes.
Authors: Adrian Săftoiu; Odd Helge Gilja; Paul S Sidhu; Christoph F Dietrich; Vito Cantisani; Dominique Amy; Michael Bachmann-Nielsen; Flaviu Bob; Jörg Bojunga; Marko Brock; Fabrizio Calliada; Dirk André Clevert; Jean-Michel Correas; Mirko D'Onofrio; Caroline Ewertsen; André Farrokh; Daniela Fodor; Pietro Fusaroli; Roald Flesland Havre; Michael Hocke; André Ignee; Christian Jenssen; Andrea Sabine Klauser; Christian Kollmann; Maija Radzina; Kumar V Ramnarine; Luca Maria Sconfienza; Carolina Solomon; Ioan Sporea; Horia Ștefănescu; Mickael Tanter; Peter Vilmann Journal: Ultraschall Med Date: 2019-06-25 Impact factor: 6.548
Authors: Melissa A Pynnonen; M Boyd Gillespie; Benjamin Roman; Richard M Rosenfeld; David E Tunkel; Laura Bontempo; Itzhak Brook; Davoren Ann Chick; Maria Colandrea; Sandra A Finestone; Jason C Fowler; Christopher C Griffith; Zeb Henson; Corinna Levine; Vikas Mehta; Andrew Salama; Joseph Scharpf; Deborah R Shatzkes; Wendy B Stern; Jay S Youngerman; Maureen D Corrigan Journal: Otolaryngol Head Neck Surg Date: 2017-09 Impact factor: 3.497