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

Jun Mei Xu, Xiao Hong Xu, Hui Xiong Xu, Yi Feng Zhang, Le Hang Guo, Lin Na Liu, Chang Liu, Xiao Wan Bo, Shen Qu, Michael Mingzhao Xing, Xiao Long Li

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
JournalEuropean Radiology
DOIs
StateAccepted/In press - Nov 11 2015

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Elasticity Imaging Techniques
Acoustics
Lymph Nodes
Touch
Radiation
Neoplasm Metastasis
Capsules
Multivariate Analysis
Calcinosis
Factor IX
ROC Curve
Papillary Thyroid cancer
Sensitivity and Specificity

Keywords

  • Acoustic radiation force impulse
  • Conventional ultrasound
  • Thyroid cancer
  • Thyroid nodule
  • Virtual touch tissue imaging

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

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. / Xu, Jun Mei; Xu, Xiao Hong; Xu, Hui Xiong; Zhang, Yi Feng; Guo, Le Hang; Liu, Lin Na; Liu, Chang; Bo, Xiao Wan; Qu, Shen; Xing, Michael Mingzhao; Li, Xiao Long.

In: European Radiology, 11.11.2015.

Research output: Contribution to journalArticle

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title = "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",
abstract = "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.",
keywords = "Acoustic radiation force impulse, Conventional ultrasound, Thyroid cancer, Thyroid nodule, Virtual touch tissue imaging",
author = "Xu, {Jun Mei} and Xu, {Xiao Hong} and Xu, {Hui Xiong} and Zhang, {Yi Feng} and Guo, {Le Hang} and Liu, {Lin Na} and Chang Liu and Bo, {Xiao Wan} and Shen Qu and Xing, {Michael Mingzhao} and Li, {Xiao Long}",
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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, Michael Mingzhao

AU - Li, Xiao Long

PY - 2015/11/11

Y1 - 2015/11/11

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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