Shear wave elastography combining with conventional grey scale ultrasound improves the diagnostic accuracy in differentiating benign and malignant thyroid nodules

Faisal N. Baig, Shirley Y.W. Liu, Hoi Chun Lam, Shea Ping Yip, Helen K.W. Law, Tin Cheung Ying

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)


Shear wave elastography provides information about the stiffness of thyroid nodules that could be a new indicator of malignancy. The current study aimed to investigate the feasibility of using shear wave elastography (SWE) alone and in conjunction with grey scale ultrasound (GSU) to predict malignancy in 111 solitary thyroid nodules. Malignant thyroid nodules tended to have microcalcification, hypoechogenicity, tall to width ratio > 1, and irregular borders (p < 0.05). SWE indices (Emaximumand Emean) of malignant nodules (median ± standard error: 85.2 ± 8.1 kPa and 26.6 ± 2.5 kPa) were significantly higher than those of benign nodules (median ± standard error: 50.3 ± 3.1 kPa and 20.2 ± 1 kPa) (p < 0.05). The optimal cut-off of Emaximumand Emeanfor distinguishing benign and malignant nodules was 67.3 kPa and 23.1 kPa, respectively. Diagnostic performances for GSU + Emaximum, GSU + Emean, GSU, Emaximumand Emeanwere: 70.4%, 74.1%, 96.3%, 70.4% and 74.1% for sensitivity, 83.3%, 79.8%, 46.4%, 70.2%, and 66.7% for specificity, and 80.2%, 78.4%, 58.5%, 70.3%, and 68.5% for accuracy, respectively. Our results suggested that combining GSU with SWE (using Emaximumor Emean) increased the overall diagnostic accuracy in distinguishing benign and malignant thyroid nodules.
Original languageEnglish
Article number1103
JournalApplied Sciences (Switzerland)
Issue number11
Publication statusPublished - 25 Oct 2017


  • Shear wave elastography
  • Thyroid cancer
  • Ultrasound

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

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