TY - JOUR
T1 - Prediction of cervical lymph node metastasis in patients with papillary thyroid cancer using combined conventional ultrasound, strain elastography, and acoustic radiation force impulse (ARFI) elastography
AU - Xu, Jun Mei
AU - Xu, Xiao Hong
AU - Xu, Hui Xiong
AU - Zhang, Yi Feng
AU - Guo, Le Hang
AU - Liu, Lin Na
AU - Liu, Chang
AU - Bo, Xiao Wan
AU - Qu, Shen
AU - Xing, Mingzhao
AU - Li, Xiao Long
N1 - Funding Information:
The scientific guarantor of this publication is Hui-Xiong Xu, head of the Department of Medical Ultrasound, Shanghai Tenth People’s Hospital, Ultrasound Research and Education Institute, Tongji University School of Medicine. This study was funded by a grant SHDC12014229 from the Shanghai Hospital Development Center, grants 14441900900 and 15411969000 from the Science and Technology Commission of Shanghai Municipality, a grant 2012045 from the Shanghai Municipal Human Resources and Social Security Bureau, and grants 81501475, 81401417 and 81472579 from the National Natural Science Foundation of China.The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. No complex statistical methods were necessary for this paper. Institutional review board approval was obtained. Informed consent was obtained from all subjects (patients) to include their data for analysis in this study. Some malignant nodules (N = 57) in this study have been reported in two previously published articles: Xu JM, Xu XH, Xu HX, et al (2014) Conventional US, US elasticity imaging, and acoustic radiation force impulse imaging for prediction of malignancy in thyroid nodules. Radiology, 272(2): 577–586 and Zhang YF, Liu C, Xu HX, et al (2014) Acoustic radiation force impulse imaging: a new tool for the diagnosis of papillary thyroid microcarcinoma. Biomed Res Int, 2014: 416969.
Publisher Copyright:
© 2015, European Society of Radiology.
PY - 2016/8/1
Y1 - 2016/8/1
N2 - Objectives: To investigate the value of combined conventional ultrasound (US), strain elastography (SE) and acoustic radiation force impulse (ARFI) elastography for prediction of cervical lymph node metastasis (CLNM) in papillary thyroid cancer (PTC). Methods: A consecutive series of 203 patients with 222 PTCs were preoperatively evaluated by US, SE, and ARFI including virtual touch tissue imaging (VTI) and virtual touch tissue quantification (VTQ). A multivariate analysis was performed to predict CLNM by 22 independent variables. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance. Results: Multivariate analysis demonstrated that VTI area ratio (VAR) > 1 was the best predictor for CLNM, followed by abnormal cervical lymph node (ACLN), capsule contact, microcalcification, capsule involvement, and multiple nodules (all P < 0.05). ROC analyses of these characteristics showed the areas under the curve (Az), sensitivity, and specificity were 0.600–0.630, 47.7 %–93.2 %, and 26.9 %–78.4 % for US, respectively; and they were 0.784, 83.0 %, and 73.9 %, respectively, for VAR > 1. As combination of US characteristics with and without VAR, the Az, sensitivity, and specificity were 0.803 and 0.556, 83.0 % and 100.0 %, and 77.6 % and 11.2 %, respectively (P < 0.001). Conclusions: ARFI elastography shows superior performance over conventional US, particularly when combined with US, in predicting CLNM in PTC patients. Key Points: • Conventional ultrasound is useful in predicting cervical lymph node metastasis preoperatively. • Virtual touch tissue imaging area ratio is the strongest predicting factor. • Predictive performance is markedly improved by combining ultrasound characteristics with VAR. • Acoustic radiation force impulse elastography may be a promising complementary tool.
AB - Objectives: To investigate the value of combined conventional ultrasound (US), strain elastography (SE) and acoustic radiation force impulse (ARFI) elastography for prediction of cervical lymph node metastasis (CLNM) in papillary thyroid cancer (PTC). Methods: A consecutive series of 203 patients with 222 PTCs were preoperatively evaluated by US, SE, and ARFI including virtual touch tissue imaging (VTI) and virtual touch tissue quantification (VTQ). A multivariate analysis was performed to predict CLNM by 22 independent variables. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance. Results: Multivariate analysis demonstrated that VTI area ratio (VAR) > 1 was the best predictor for CLNM, followed by abnormal cervical lymph node (ACLN), capsule contact, microcalcification, capsule involvement, and multiple nodules (all P < 0.05). ROC analyses of these characteristics showed the areas under the curve (Az), sensitivity, and specificity were 0.600–0.630, 47.7 %–93.2 %, and 26.9 %–78.4 % for US, respectively; and they were 0.784, 83.0 %, and 73.9 %, respectively, for VAR > 1. As combination of US characteristics with and without VAR, the Az, sensitivity, and specificity were 0.803 and 0.556, 83.0 % and 100.0 %, and 77.6 % and 11.2 %, respectively (P < 0.001). Conclusions: ARFI elastography shows superior performance over conventional US, particularly when combined with US, in predicting CLNM in PTC patients. Key Points: • Conventional ultrasound is useful in predicting cervical lymph node metastasis preoperatively. • Virtual touch tissue imaging area ratio is the strongest predicting factor. • Predictive performance is markedly improved by combining ultrasound characteristics with VAR. • Acoustic radiation force impulse elastography may be a promising complementary tool.
KW - Acoustic radiation force impulse
KW - Conventional ultrasound
KW - Thyroid cancer
KW - Thyroid nodule
KW - Virtual touch tissue imaging
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U2 - 10.1007/s00330-015-4088-2
DO - 10.1007/s00330-015-4088-2
M3 - Article
C2 - 26560715
AN - SCOPUS:84946781264
VL - 26
SP - 2611
EP - 2622
JO - European Radiology
JF - European Radiology
SN - 0938-7994
IS - 8
ER -