Next Article in Journal
Robotic Peg-in-Hole Assembly Strategy Research Based on Reinforcement Learning Algorithm
Previous Article in Journal
Quality Evaluation of Plant Oil Blends Interesterified by Using Immobilized Rhizomucor miehei Lipase
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Strain Versus 2D Shear-Wave Elastography Parameters—Which Score Better in Predicting Thyroid Cancer?

1
2nd Department of Internal Medicine, Victor Babes University of Medicine and Pharmacy, 300041 Timisoara, Romania
2
Ultrasound Center Dr. D Medical, 300029 Timisoara, Romania
3
Emergency County Hospital No1, 300723 Timisoara, Romania
4
Center for Advanced Hepatology Research of the Academy of Medical Sciences, Faculty of Medicine, University of Medicine and Pharmacy “Victor Babes” Timisoara, E. Murgu Square, Nr. 2, 300041 Timisoara, Romania
5
Center of Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, University of Medicine and Pharmacy “Victor Babes” Timisoara, E. Murgu Square, Nr. 2, 300041 Timisoara, Romania
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(21), 11147; https://doi.org/10.3390/app122111147
Submission received: 8 August 2022 / Revised: 28 October 2022 / Accepted: 29 October 2022 / Published: 3 November 2022
(This article belongs to the Section Biomedical Engineering)

Abstract

The aim of this study is to assess the diagnostic performance of strain elastography (SE) versus 2D shear-wave elastography (2D-SWE) by providing a head-to-head comparison of the two methods. Ninety-four thyroid nodules were evaluated using conventional ultrasound (B-mode) and SE, namely, real-time elastography (RTE) with a Hitachi Preirus machine (Hitachi Inc., Tokyo, Japan) and consecutively, 2D-SWE with SuperSonic Mach30 equipment (Supersonic Imagine, Aix-en-Provence, France). The results were compared in all cases to the pathology reports. Out of the 94 nodules, 29 (30.9%) were malignant. Both SE and 2D-SWE parameters proved to have excellent diagnostic quality, with comparable results. The mean elasticity index was the best parameter for the 2D-SWE (AUC 0.912); for a cut-off value of 30.5 kPa, it predicts thyroid malignancy with a sensitivity of 79.3%, specificity of 95.38%, NPV of 91.2% and PPV of 88.5%. The best parameter for SE was the strain ratio (cutoff > 3.9; sensitivity 82.7%; specificity 92.3%; AUC 0.905). When integrated in the ultrasound risk algorithm, both elastography methods improved the diagnostic performance: AUC 0.764 vs. 0.886 vs. 0.861 for B-modes: B-mode + 2D-SWE vs. B-mode + SE. We concluded that elastography adds diagnostic value in predicting malignancy, both when Hitachi RTE and SuperSonic 2D-SWE were used.
Keywords: risk stratification; thyroid cancer; strain; 2D shear wave; SWE; thyroid elastography risk stratification; thyroid cancer; strain; 2D shear wave; SWE; thyroid elastography

Share and Cite

MDPI and ACS Style

Borlea, A.; Sporea, I.; Popa, A.; Derban, M.; Taban, L.; Stoian, D. Strain Versus 2D Shear-Wave Elastography Parameters—Which Score Better in Predicting Thyroid Cancer? Appl. Sci. 2022, 12, 11147. https://doi.org/10.3390/app122111147

AMA Style

Borlea A, Sporea I, Popa A, Derban M, Taban L, Stoian D. Strain Versus 2D Shear-Wave Elastography Parameters—Which Score Better in Predicting Thyroid Cancer? Applied Sciences. 2022; 12(21):11147. https://doi.org/10.3390/app122111147

Chicago/Turabian Style

Borlea, Andreea, Ioan Sporea, Alexandru Popa, Mihnea Derban, Laura Taban, and Dana Stoian. 2022. "Strain Versus 2D Shear-Wave Elastography Parameters—Which Score Better in Predicting Thyroid Cancer?" Applied Sciences 12, no. 21: 11147. https://doi.org/10.3390/app122111147

APA Style

Borlea, A., Sporea, I., Popa, A., Derban, M., Taban, L., & Stoian, D. (2022). Strain Versus 2D Shear-Wave Elastography Parameters—Which Score Better in Predicting Thyroid Cancer? Applied Sciences, 12(21), 11147. https://doi.org/10.3390/app122111147

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop