Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on sleep in brain health

LIVE: Thursday 2nd May 2024, 18:00-19:30 (CEST)

Quality sleep is essential for health. But what happens to our brains when sleep patterns are disturbed? Join our experts to explore the interplay between sleep disruption and neurological diseases, and the questions that you need to be asking your patients to help you prevent the harmful effects of sleep deprivation.
ADVANCED SEARCH
Log in
Top
BMC Medical Imaging
Published in: BMC Medical Imaging 1/2018

Open Access 01-12-2018 | Research article

In silico simulation of liver crack detection using ultrasonic shear wave imaging

Authors: Erwei Nie, Jiao Yu, Debaditya Dutta, Yanying Zhu

Published in: BMC Medical Imaging | Issue 1/2018

Login to get access

Abstract

Background

Liver trauma is an important source of morbidity and mortality worldwide. A timely detection and precise evaluation of traumatic liver injury and the bleeding site is necessary. There is a need to develop better imaging modalities of hepatic injuries to increase the sensitivity of ultrasonic imaging techniques for sites of hemorrhage caused by cracks. In this study, we conduct an in silico simulation of liver crack detection and delineation using an ultrasonic shear wave imaging (USWI) based method.

Methods

We simulate the generation and propagation of the shear wave in a liver tissue medium having a crack using COMSOL. Ultrasound radio frequency (RF) signal synthesis and the two-dimensional speckle tracking algorithm are applied to simulate USWI in a medium with randomly distributed scatterers. Crack detection is performed using the directional filter and the edge detection algorithm rather than the conventional inversion algorithm. Cracks with varied sizes and locations are studied with our method and the crack localization results are compared with the given crack.

Results

Our pilot simulation study shows that, by using USWI combined with a directional filter cum edge detection technique, the near-end edge of the crack can be detected in all the three cracks that we studied. The detection errors are within 5%. For a crack of 1.6 mm thickness, little shear wave can pass through it and the far-end edge of the crack cannot be detected. The detected crack lengths using USWI are all slightly shorter than the actual crack length. The robustness of our method in detecting a straight crack, a curved crack and a subtle crack of 0.5 mm thickness is demonstrated.

Conclusions

In this paper, we simulate the use of a USWI based method for the detection and delineation of the crack in liver. The in silico simulation helps to improve understanding and interpretation of USWI measurements in a physical scattered liver medium with a crack. This pilot study provides a basis for improved insights in future crack detection studies in a tissue phantom or liver.
Literature
1.
2.
Chien LC, Lo SS, Yeh SY. Incidence of liver trauma and relative risk factors for mortality: a population-based study. J Chin Med Assoc. 2013;76:576–82.CrossRefPubMed
3.
4.
5.
6.
Ophir J, Céspedes I, Ponnekanti H, Yazdi Y, Elastography LX. A quantitative method for imaging the elasticity of biological tissues. Ultrason Imaging. 1991;13:111–34.CrossRefPubMed
7.
Sarvazyan AP, Skovoroda AR. The new approaches in ultrasonic visualization of cancers and their qualitative mechanical characterization for the differential diagnostics. In: Abstract of the all-union conference “the actual problems of the cancer ultrasonic diagnostics,” Moscow; 1990.
8.
Natarajan B, Gupta PK, Cemaj S, Sorensen M, Hatzoudis GI, Forse RAFAST. Scan: is it worth doing in hemodynamically stable blunt trauma patients? Surgery. 2010;148:695–701.CrossRefPubMed
9.
He L, Guo Y, Lee WN. Systematic performance evaluation of a cross-correlation-based ultrasound strain imaging method. Ultrasound Med Biol. 2016;42:2436–56.CrossRef
10.
Chen S, Urban MW, Greenleaf JF, Zheng Y, Yao A. Quantification of liver stiffness and viscosity with SDUV: in vivo animal study. In: 2008 IEEE Ultrasonics symposium (IUS); 2008. p. 654–7.CrossRef
11.
Wang MH, Palmeri ML, Rotemberg VM, Rouze NC, Nightingale KR. Improving the robustness of time-of-flight based shear wave speed reconstruction methods using RANSAC in human liver in vivo. Ultrasound Med Biol. 2010;36:802–13.CrossRefPubMedPubMedCentral
12.
Palmeri ML, Wang MH, Dahl JJ, Frinkley KD, Nightingale KR. Quantifying hepatic shear modulus in vivo using acoustic radiation force. Ultrasound Med Biol. 2008;34:546–58.CrossRefPubMedPubMedCentral
13.
14.
Xu J, Tripathy S, Rubin JM, Stidham RW, Johnson LA, Higgins PDR, Kim K. A new nonlinear parameter in the developed strain-to-applied strain of the soft tissues and its application in ultrasound elasticity imaging. Ultrasound Med Biol. 2012;38:511–23.CrossRefPubMedPubMedCentral
15.
Maurice RL, Bertrand M. Speckle-motion artifact under tissue shearing. IEEE Trans Ultrason Ferroelectr Freq Control. 1999;46:584–94.CrossRefPubMed
16.
Shao J, Wang J, Zhang Y, Cui L, Liu K, Bai J. Subtraction elastography for the evaluation of ablation-induced lesions: a feasibility study. IEEE Trans Ultrason Ferroelectr Freq Control. 2009;56:44–54.CrossRefPubMed
17.
Wagner RF, Smith SW, Sandrik JM, Lopez H. Statistics of speckle in ultrasound B-scans. IEEE Trans Sonics Ultrason. 1983;30:156–63.CrossRef
18.
Mcaleavey SA, Osapoetra LO, Langdon J. Shear wave arrival time estimates correlate with local speckle pattern. IEEE Trans Ultrason Ferroelectr Freq Control. 2015;62:2054–67.CrossRefPubMedPubMedCentral
19.
20.
Lubinski MA, Emelianov SY, O'Donnell M. Speckle tracking methods for ultrasonic elasticity imaging using short-time correlation. IEEE Trans Ultrason Ferroelectr Freq Control. 1999;46:82–96.CrossRefPubMed
21.
Kim K, Johnson LA, Jia C, Joyce JC, Rangwalla S, Higgins PDR, Rubin JM. Noninvasive ultrasound elasticity imaging (UEI) of Crohn's disease: animal model. Ultrasound Med Biol. 2008;34:902–12.CrossRefPubMedPubMedCentral
22.
Manduca A, Lake DS, Kruse SA, Ehman RL. Spatio-temporal directional filtering for improved inversion of MR elastography images. Med Image Anal. 2002;7:465–73.CrossRef
23.
Deffieux T, Gennisson JL, Bercoff J, Tanter M. On the effects of reflected waves in transient shear wave elastography. IEEE Trans Ultrason Ferroelectr Freq Control. 2011;58:2032–5.CrossRefPubMed
24.
Deffieux T, Gennisson JL, Larrat B, Fink M, Tanter M. The variance of quantitative estimates in shear wave imaging: theory and experiments. IEEE Trans Ultrason Ferroelectr Freq Control. 2012;59:2390–410.CrossRefPubMed
25.
Mercado KP, Langdon J, Helguera M, McAleavey SA, Hocking DC, Dalecki D. Scholte wave generation during single tracking location shear wave elasticity imaging of engineered tissues. J Acoust Soc Am. 2015;138:138–44.CrossRef
26.
Coccolini F, Montori G, Catena F, Di Saverio S, Biffl W, Moore EE, Peitzman AB, Rizoli S, Tugnoli G, Sartelli M, Manfredi R, Ansaloni L. Liver trauma: WSES position paper. World J Emerg Surg. 2015;10:39.CrossRefPubMedPubMedCentral
27.
Savatmongkorngul S, Wongwaisayawan S, Kaewlai R. Focused assessment with sonography for trauma: current perspectives. Open Access Emerg Med. 2017;9:57–62.CrossRefPubMedPubMedCentral
28.
McGahan JP, Wang L, Richards JR. From the RSNA refresher courses: focused abdominal US for trauma. Radiographics. 2001;21(Spec Issue):S191–9.CrossRefPubMed
29.
30.
Rudenko OV, Sarvazyan AP, Emelianov SY. Acoustic radiation force and streaming induced by focused nonlinear ultrasound in a dissipative medium. J Acoust Soc Am. 1996;99:2791–8.CrossRef
31.
Sarvazyan AP, Rudenko OV, Swanson SD, Fowlkes JB, Emelianov SY. Shear wave elasticity imaging: a new ultrasonic technology of medical diagnostics. Ultrasound Med Biol. 1998;24:1419–35.CrossRefPubMed
32.
Athanasiou A, Tardivon A, Tanter M, Sigal-Zafrani B, Bercoff J, Deffieux T, Gennisson JL, Fink M, Neuenschwander S. Breast lesions: quantitative elastography with supersonic shear imaging—preliminary results. Radiology. 2010;256:297–303.CrossRefPubMed
33.
Bavu E, Gennisson JL, Mallet V. Supersonic shear imaging is a new potent morphological non-invasive technique to assess liver fibrosis. Part 1: technical feasibility. Hepatology. 2010;52(Suppl):S166.
34.
Wu R, Luo Y, Lv F, Tang J, Liu Q, Jiao Z. Evaluation of liver trauma after haemostatic injection by shear wave elastography: an experimental study. Chin J Med Ultrasound. 2011;8:1914–21.
35.
Wu R, Luo Y, Lv F, Tang J, Liu Q, Jiao Z. An animal experiment of real-time shear wave elastography in diagnosing acute liver trauma. Chin J Med Ultrasound. 2012;20:294–7.
36.
Baghani A, Salcudean S, Rohling R. Theoretical limitations of the elastic wave equation inversion for tissue elastography. J Acoust Soc Am. 2009;126:1541–51.CrossRefPubMed
37.
Deffieux T, Montaldo G, Tanter M, Fink M. Shear wave spectroscopy for in vivo quantification of human soft tissues visco-elasticity. IEEE Trans Med Imaging. 2009;28:313–22.CrossRefPubMed
38.
Sigrist RMS, Liau J, Kaffas AE, Chammas MC, Willmann JK. Ultrasound elastography: review of techniques and clinical applications. Theranostics. 2017;7:1303–29.CrossRefPubMedPubMedCentral
39.
Shiina T, Nightingale KR, Palmeri ML, Hall TJ, Bamber JC, Barr RG, et al. WFUMB guidelines and recommendations for clinical use of ultrasound elastography: part 1: basic principles and terminology. Ultrasound Med Biol. 2015;41:1126–47.CrossRefPubMed
40.
Park E. Finite element formulation for shear modulus reconstruction in transient elastography. Inverse Probl Sci En. 2009;17:605–26.CrossRef
41.
Lubinski MA, Emelianov SY, Raghavan KR, Yagle AE, Skovoroda AR, O’Donnell M. Lateral displacement estimation using tissue incompressibility. IEEE Trans Ultrason Ferroelectr Freq Control. 1996;43:247–56.CrossRef
42.
Konofagou E, Ophir JA. New elastographic method for estimation and imaging of lateral displacements, lateral strains, corrected axial strains and Poisson's ratios in tissues. Ultrasound Med Biol. 1998;24:1183–99.CrossRefPubMed
43.
Chaturvedi P, Insana MF, Hall TJ. 2-D companding for noise reduction in strain imaging. IEEE Trans Ultrason Ferroelectr Freq Control. 1998;45:179–91.CrossRefPubMed
44.
Nishi T, Funabashi N, Ozawa K, Takahara M, Fujimoto Y, Kamata T, Kobayashi Y. Resting multilayer 2D speckle-tracking transthoracic echocardiography for the detection of clinically stable myocardial ischemic segments confirmed by invasive fractional flow reserve. Part 1: vessel-by-vessel analysis. Int J Cardiol. 2016;218:324–32.CrossRefPubMed
45.
Palmeri ML, Sharma AC, Bouchard RR, Nightingale RW, Nightingale KRA. Finite-element method model of soft tissue response to impulsive acoustic radiation force. IEEE Trans Ultrason Ferroelectr Freq Control. 2005;52:1699–712.CrossRefPubMedPubMedCentral
46.
Mcaleavey SA, Nightingale KR, Trahey GE. Estimates of echo correlation and measurement bias in acoustic radiation force impulse imaging. IEEE Trans Ultrason Ferroelectr Freq Control. 2003;50:631–41.CrossRefPubMed
47.
Wang Y, Zhang Q, Luo S. Image tracking method based on fractal-geometry edge extraction. J Appl Optics. 2005;34:S258.
48.
49.
Adedipe AA, Backlund BH, Basler E, Shah S. Accuracy of the fast exam: a retrospective analysis of blunt abdominal trauma patients. Open Access Emerg Med. 2016;06:1000308.CrossRef
50.
Bruce M, Kolokythas O, Ferraioli G, Filice C, Limitations O’DM. Artifacts in shear-wave elastography of the liver. Biomed Eng Lett. 2017;7:1–9.CrossRef
51.
Wang C, Zheng J, Huang Z, Xiao Y, Song D, Zeng J, Zheng H, Zheng R. Influence of measurement depth on the stiffness assessment of healthy liver with real-time shear wave elastography. Ultrasound Med Biol. 2014;40:461–9.CrossRefPubMed
52.
Ferraioli G, Tinelli C, Zicchetti M, Above E, Poma G, Gregorio MD, Filice C. Reproducibility of real-time shear wave elastography in the evaluation of liver elasticity. Eur J Radiol. 2012;81:3102–6.CrossRefPubMed
53.
He XN, Diao XF, Lin HM, Zhang XY, Shen YY, Chen SP, Qin ZD, Chen X. Improved shear wave motion detection using coded excitation for transient elastography. Sci Rep. 2017;7:44483.CrossRefPubMedPubMedCentral
54.
Giachetti A, Zanetti G. Vascular modeling from volumetric diagnostic data: a review. Curr Med Imaging Rev. 2006;2:415–23.CrossRef
55.
Ros SJ, Andarawis-Puri N, Flatow EL. Tendon extracellular matrix damage detection and quantification using automated edge detection analysis. J Biomech. 2013;46:2844–7.CrossRefPubMed
Metadata
Title
In silico simulation of liver crack detection using ultrasonic shear wave imaging
Authors
Erwei Nie
Jiao Yu
Debaditya Dutta
Yanying Zhu
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Medical Imaging / Issue 1/2018
Electronic ISSN: 1471-2342
DOI
https://doi.org/10.1186/s12880-018-0249-5

Other articles of this Issue 1/2018

BMC Medical Imaging 1/2018 Go to the issue

Research article

High-definition neural visualization of rodent brain using micro-CT scanning and non-local-means processing

Case report

Incidental finding of cardiac hydatid cysts, report of two cases

Research article

Comparison of two different measurement methods in evaluating basilar atherosclerotic plaque using high-resolution MRI at 3 tesla

Research article

Automatic differentiation of Glaucoma visual field from non-glaucoma visual filed using deep convolutional neural network

Research article

MRI assessment of aortic flow in patients with pulmonary arterial hypertension in response to exercise

Research article

An automated algorithm for the detection of cortical interruptions and its underlying loss of trabecular bone; a reproducibility study