Ultrasound viscoelastic imaging in differentiation of benign and malignant breast tumors

doi:10.16150/j.1671-2870.2025.02.011

Abstract

Abstract:

Objective To evaluate the application value of ultrasonic viscoelastic imaging technology in differentia-ting benign and malignant breast tumors. Methods A total of 717 patients with breast tumors confirmed by surgical patho-logy were consecutively enrolled at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine between February 2023 and August 2023, including 471 malignant and 246 benign cases. All patients underwent breast ultrasound examinations before treatment, including grayscale ultrasound, ultrasound strain elastography, ultrasound shear wave elastography, and ultrasound viscoelastic imaging. Ultrasound viscoelastic imaging technology included measuring four sets of parameters of the tumor and its surrounding tissues: viscosity coefficient, dispersion coefficient, shear wave elastic modulus, and strain ratio. Using the optimal predictive indicators from the four parameter groups, multiple prediction models were established, including single-variable models (viscosity coefficient, dispersion coefficient, shear wave, strain), a combined viscoelastic model (Shell/T-Vmean + Shell/T-Dmean), a Breast Imaging Reporting and Data System (BI-RADS) model, and a combined model integrating BI-RADS with viscoelastic parameters. The effectiveness of each model in differentiating benign and malignant breast tumors was evaluated. Results Parameters including viscosity coefficient, dispersion coefficient, elastic modulus, and strain ratio from ultrasound viscoelastic imaging could effectively distinguish benign and malignant breast tumors. Among them, the ratios of the tumor margin (2 mm region) to the tumor itself—Shell/T-Vmean, Shell/T-Dmean, Shell/T-Emean, and Strain Ratio A—were optimal predictive indicators, with areas under the curve (AUCs) of 0.742, 0.745, 0.726, and 0.705, respectively. The BI-RADS model for predicting benign and malignant breast tumors achieved an AUC of 0.822. When Shell/T-Vmean and Shell/T-Dmean were respectively combined with BI-RADS classification, the receiver operating characteristic (ROC) curve's AUC reached 0.895 (95% CI: 0.868–0.917), which was higher than that of BI-RADS alone. Conclusion Among the viscoelastic parameters of ultrasound viscoelastic imaging, the average ratios of viscosity coefficient, dispersion coefficient, and elastic modulus between the 2 mm tumor margin region and the tumor body are key diagnostic indicators. The combination of Shell/T-Vmean and Shell/T-Dmean with BI-RADS provides a new stra-tegy for noninvasive preoperative precision diagnosis.

Key words: Ultrasound viscoelastic imaging, Breast tumor, Benign and malignant differentiation, Viscosity coefficient, Dispersion coefficient

CLC Number:

R737.9

QIN Yu, LI Cheng, HUA Qing, ZHANG Huiting, JIA Wanru, DONG Yijie, ZHOU Jianqiao, XIA Shujun. Ultrasound viscoelastic imaging in differentiation of benign and malignant breast tumors[J]. Journal of Diagnostics Concepts & Practice, 2025, 24(02): 194-203.

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References 26

[1]	SUNG H, FERLAY J, SIEGEL R L, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249.
[2]	CHEN W, ZHENG R, BAADE P D, et al. Cancer statistics in China, 2015[J]. CA Cancer J Clin, 2016, 66(2): 115-132.
[3]	FELDMANN A, LANGLOIS C, DEWAILLY M, et al. Shear wave elastography (SWE): an analysis of breast lesion characterization in 83 breast lesions[J]. Ultrasound Med Biol, 2015, 41(10): 2594-2604. doi: 10.1016/j.ultrasmedbio.2015.05.019 pmid: 26159068
[4]	RICCI P, MAGGINI E, MANCUSO E, et al. Clinical application of breast elastography: state of the art[J]. Eur J Radiol,2014, 83(3): 429-37. doi: 10.1016/j.ejrad.2013.05.007 pmid: 23787274
[5]	SIGRIST R M S, LIAU J, KAFFAS A E, et al. Ultrasound elastography: review of techniques and clinical applications[J]. Theranostics, 2017, 7(5): 1303-1329. doi: 10.7150/thno.18650 pmid: 28435467
[6]	SHIINA T, NIGHTINGALE K R, PALMERI M L, et al. WFUMB guidelines and recommendations for clinical use of ultrasound elastography: Part 1: basic principles and terminology[J]. Ultrasound Med Biol,2015,41(5):1126-1147. doi: 10.1016/j.ultrasmedbio.2015.03.009 pmid: 25805059
[7]	KUMAR V, DENIS M, GREGORY A, et al. Viscoelastic parameters as discriminators of breast masses: Initial human study results[J]. PLoS One, 2018,13(10): e0205717.
[8]	LI W, JIANG J, CAO J, et al. The value of ultrasound viscosity imaging in preoperative differential diagnosis between malignant and benign breast lesions: Preliminary clinical applications[J]. Clin Hemorheol Microcirc,2025,89(1):111-122. doi: 10.3233/CH-242405 pmid: 39911120
[9]	American College of Radiology. ACR BI-RADS atlas: breast imaging reporting and data system[M].5th ed, Reston, Virginia, 2013.
[10]	JIA W, XIA S, JIA X, et al. Ultrasound Viscosity Imaging in Breast Lesions: A Multicenter Prospective Study[J]. Acad Radiol, 2024, 31(9): 3499-510. doi: 10.1016/j.acra.2024.03.017 pmid: 38582684
[11]	MANDUCA A, BAYLY P J, EHMAN R L, et al. MR elastography: Principles, guidelines, and terminology[J]. Magn Reson Med, 2021, 85(5): 2377-2390. doi: 10.1002/mrm.28627 pmid: 33296103
[12]	SHI Y, QI Y F, LAN G Y, et al. Three-dimensional MR elastography depicts liver inflammation, fibrosis, and portal hypertension in chronic hepatitis B or C[J]. Radio-logy, 2021, 301(1): 154-162.
[13]	TAPPER E B, LOOMBA R. Noninvasive imaging biomarker assessment of liver fibrosis by elastography in NAFLD[J]. Nat Rev Gastroenterol Hepatol,2018,15(5): 274-282. doi: 10.1038/nrgastro.2018.10 pmid: 29463906
[14]	PATEL B K, SAMREEN N, ZHOU Y, et al. MR elastography of the breast: evolution of technique, case examples, and future directions[J]. Clin Breast Cancer, 2021,21(1): e102-e111. doi: 10.1016/j.clbc.2020.08.005 pmid: 32900617
[15]	CHEN S, SANCHEZ W, CALLSTROM M R, et al. Assessment of liver viscoelasticity by using shear waves induced by ultrasound radiation force[J]. Radiology, 2013, 266(3): 964-970. doi: 10.1148/radiol.12120837 pmid: 23220900
[16]	SUGIMOTO K, MORIYASU F, OSHIRO H, et al. The role of multiparametric US of the liver for the evaluation of nonalcoholic steatohepatitis[J]. Radiology,2020, 296(3): 532-540. doi: 10.1148/radiol.2020192665 pmid: 32573385
[17]	LEE D H, LEE J Y, BAE J S, et al. Shear-wave dispersion slope from US shear-wave elastography: detection of allograft damage after liver transplantation[J]. Radiology, 2019,293(2): 327-333. doi: 10.1148/radiol.2019190064 pmid: 31502939
[18]	HOSSAIN M M, SELZO M R, HINSON R M, et al. Evaluating renal transplant status using viscoelastic response (VisR) Ultrasound[J]. Utrasound Med Biol, 2018, 44(8): 1573-1584.
[19]	SADIGH G, CARLOS R C, NEAL C H, et al. Accuracy of quantitative ultrasound elastography for differentiation of malignant and benign breast abnormalities: a meta-analysis[J]. Breast Cancer Res Treat,2012,134(3): 923-931.
[20]	BERG W A, COSGROVE D O, DORé C J, et al. Shear-wave elastography improves the specificity of breast US: the BE1 multinational study of 939 masses [J]. Radiology, 2012, 262(2): 435-449. doi: 10.1148/radiol.11110640 pmid: 22282182
[21]	ZHANG H, GUO Y, ZHOU Y, et al. Fluidity and elasticity form a concise set of viscoelastic biomarkers for breast cancer diagnosis based on Kelvin-Voigt fractional derivative modeling[J]. Biomech Model Mechanobiol,2020,19(6): 2163-2177.
[22]	MIERKE C T. Viscoelasticity acts as a marker for tumor extracellular matrix characteristics[J]. Front Cell Dev Biol, 2021, 9: 785138.
[23]	ZHOU J, ZHAN W, CHANG C, et al. Breast lesions: evaluation with shear wave elastography, with special emphasis on the "stiff rim" sign[J]. Radiology,2014,272(1): 63-72. doi: 10.1148/radiol.14130818 pmid: 24661245
[24]	PARK H S, SHIN H J, SHIN K C, et al. Comparison of peritumoral stromal tissue stiffness obtained by shear wave elastography between benign and malignant breast lesions[J]. Acta Radiol,2018,59(10): 1168-1175. doi: 10.1177/0284185117753728 pmid: 29359949
[25]	王艳萍, 唐笛娇, 努尔比耶·买买提依力, 等. 血清抗着丝粒蛋白F抗体在乳腺癌中的临床价值探讨 [J]. 重庆医科大学学报, 2024, 49 (9): 1188-1192.
	WANG Y P, TANG D J, NUERBIYE·M, et al. Clinical value of serum anti-centromere protein F antibody in breast cancer[J]. J Chongqing Med Univ,2024,49(9): 1188-1192.
[26]	SRIDHAR M, INSANA M F. Ultrasonic measurements of breast viscoelasticity[J]. Med Phys,2007,34(12): 4757-4767. pmid: 18196803

Item	Number (%)
Benign/Malignant
Malignant	471	(65.69)
Benign	246	(34.31)
Pathological type
Adenosis	64	(8.93)
Fibroadenoma	93	(12.97)
Intraductal papilloma	52	(7.25)
Other benign lesions	33	（4.60)
Borderline tumor	6	（0.84)
Ductal carcinoma in situ	55	(7.67)
Lobular carcinoma in situ	8	(1.12)
Invasive papillary carcinoma	17	(2.37)
Invasive ductal carcinoma	334	(46.58)
Invasive lobular carcinoma	15	(2.09)
Neuroendocrine tumor	2	(0.28)
Mucinous carcinoma	13	(1.81)
Mucinous carcinoma	25	(3.49)

Item	Total (N = 717)	Benign(n= 246)	Malignant(n= 471)	P-value
Age	52.49±14.05	45.00 ± 13.17	56.40 ± 12.86	<0.001
BI-RADS				<0.001
4B and above	516(71.97%)	73(29.67%)	443(94.06%)
Below 4B	201(28.03%)	173(70.33%)	28(5.94%)
T-Emean	25.93±14.65	23.12±13.30	27.40±15.12	<0.001
T-Emax	126.63±84.63	90.34± 64.77	145.58±87.61	<0.001
T-Esd	16.83 ± 11.33	12.83 ± 8.56	18.92 ±12.02	<0.001
Shell-Emean	30.25 ±16.93	23.36 ±13.24	33.85 ± 17.53	<0.001
Shell-Emax	139.84±85.38	98.11± 66.43	161.63±86.12	<0.001
Shell-Esd	21.26 ± 13.57	15.18± 10.11	24.44 ± 14.06	<0.001
A-Emean	27.74 ± 14.78	23.41± 12.85	30.00 ± 15.22	<0.001
A-Emax	151.54±90.95	107.56±72.52	174.50±91.20	<0.001
A-Esd	19.58 ± 12.02	14.56 ± 9.28	22.20 ± 12.46	<0.001
Shell/T-Emean	1.21 ± 0.33	1.05 ± 0.27	1.29 ± 0.33	<0.001
Shell/T-Emax	1.24 ± 0.59	1.22 ± 0.64	1.24 ± 0.56	0.400
Shell/T-Esd	1.37 ± 0.53	1.27 ± 0.55	1.42 ± 0.52	<0.001
T-Vmean	1.74 ± 0.89	1.77 ± 0.87	1.72 ± 0.90	0.400
T-Vmax	8.15 ± 4.78	6.60 ± 3.92	8.95 ± 4.99	<0.001
T-Vsd	1.15±0.71	1.02 ± 0.61	1.22 ± 0.75	<0.001
Shell-Vmean	2.07±1.00	1.80 ± 0.85	2.21 ± 1.04	<0.001
Shell-Vmax	8.97±4.77	7.10 ± 4.00	9.95 ± 4.85	<0.001
Shell-Vsd	1.46±0.85	1.18 ± 0.69	1.60 ± 0.90	<0.001

Model	AIC	AUC	95%CI
Shell/T-Vmean+ Shell/T-Dmean Combined model	788.58	0.755	0.718-0.789
Shell/T-Vmean Univariate model	804.32	0.742	0.704-0.775
Shell/T-Dmean Univariate model	800.82	0.745	0.707-0.780

Model	AIC	AUC	95%CI
BI-RADS combined with viscoelastic model	546.862	0.895	0.868-0.917
BI-RADS model	586.959	0.822	0.790-0.853
Viscoelastic combined model	788.584	0.755	0.718-0.789
Shear wave univariate model	830.377	0.726	0.685-0.764
Strain univariate model	848.274	0.705	0.663-0.744