Tissues exhibiting quasi-periodic structures can be modeled as a collection of diffuse scatterers and coherent scatterers. The mean scatterer spacing (MSS) of coherent and quasi-periodic components is directly related to tissue microstructure and has become an important quantitative ultrasound (QUS) parameter in the characterization of quasi-periodic tissues. In this paper, a review of the literature on the development of MSS as a QUS parameter was conducted. First, a unified theoretical background of MSS estimates was provided. Then, the application of MSS estimates was summarized with respect to liver, spleen, breast, bone, muscle, and other tissues. MSS estimation techniques were applied to (a) the diagnosis of hepatitis, liver fibrosis and cirrhosis, and lesions in tissues such as liver, breast, and spleen; (b) the differentiation between benign and malignant breast tumors, and the grading of breast cancer; (c) the detection of cancellous bone; and (d) the monitoring of the efficacy of treatments such as thermal ablation, with various levels of success. Future developments were also discussed in terms of real-time implementation of MSS estimates, local MSS estimation, relationship of MSS to other QUS parameters, combination of MSS with other QUS parameters, in vivo validation of MSS estimates, MSS parametric imaging, and three-dimensional ultrasound tissue characterization.
InsanaMFWagnerRFBrownDGHallTJ. Describing small-scale structure in random media using pulse-echo ultrasound. J Acoust Soc Am. 1990;87:179-92.
2.
NobleJA. Ultrasound image segmentation and tissue characterization. Proc Inst Mech Eng H. 2010;224:307-16.
3.
OelzeMLMamouJ. Review of quantitative ultrasound: envelope statistics and backscatter coefficient imaging and contributions to diagnostic ultrasound. IEEE Trans Ultrason Ferroelectr Freq Control. 2016;63:336-51.
4.
MamouJOelzeML. Quantitative Ultrasound in Soft Tissues. Heidelberg: Springer; 2013.
5.
InsanaMFHallTJ. Parametric ultrasound imaging from backscatter coefficient measurements: image formation and interpretation. Ultrason Imaging. 1990;12:245-67.
6.
SamimiKVargheseT. Lower bound on estimation variance of the ultrasonic attenuation coefficient using the spectral-difference reference phantom method. Ultrason Imaging. Published electronically 20October2016. Available from http://journals.sagepub.com/doi/abs/10.1177/0161734616674329
7.
NamKZagzebskiJAHallTJ. Quantitative assessment of in vivo breast masses using ultrasound attenuation and backscatter. Ultrason Imaging. 2013;35:146-61.
8.
SakMDuricNLittrupPBey-KnightLAliHVallieresPet al. Using speed of sound imaging to characterize breast density. Ultrasound Med Biol. 2017;43:91-103.
9.
IrieSInoueKYoshidaKMamouJKobayashiKMaruyamaHet al. Speed of sound in diseased liver observed by scanning acoustic microscopy with 80 MHz and 250 MHz. J Acoust Soc Am. 2016;139:512-9.
10.
TsuiPHTsaiYW. Artifact reduction of ultrasound Nakagami imaging by combining multifocus image reconstruction and the noise-assisted correlation algorithm. Ultrason Imaging. 2015;37:53-69.
11.
ZhouZWuSWangCYMaHYLinCCTsuiPH. Monitoring radiofrequency ablation using real-time ultrasound Nakagami imaging combined with frequency and temporal compounding techniques. PLoS ONE. 2015;10:e0118030.
12.
ByraMNowickiAWroblewska-PiotrzkowskaHDobruch-SobczakK. Classification of breast lesions using segmented quantitative ultrasound maps of homodyned K distribution parameters. Med Phys. 2016;43:5561-9.
13.
OelzeMLO’BrienWDJrBlueJPZacharyJF. Differentiation and characterization of rat mammary fibroadenomas and 4T1 mouse carcinomas using quantitative ultrasound imaging. IEEE Trans Med Imaging. 2004;23:764-71.
14.
TadayyonHSadeghi-NainiAWirtzfeldLWrightFCCzarnotaG. Quantitative ultrasound characterization of locally advanced breast cancer by estimation of its scatterer properties. Med Phys. 2014;41:012903.
15.
GerigALVargheseTZagzebskiJA. Improved parametric imaging of scatterer size estimates using angular compounding. IEEE Trans Ultrason Ferroelectr Freq Control. 2004;51:708-15.
16.
LiuWZagzebskiJA. Trade-offs in data acquisition and processing parameters for backscatter and scatterer size estimations. IEEE Trans Ultrason Ferroelectr Freq Control. 2010;57:340-52.
17.
ParkerKJDoyleyMMRubensDJ. Imaging the elastic properties of tissue: the 20 year perspective. Phys Med Biol. 2011;56:R1-R29.
18.
SarvazyanAHallTJUrbanMWFatemiMAglyamovSRGarraBS. An overview of elastography—an emerging branch of medical imaging. Curr Med Imaging Rev. 2011;7:255-82.
19.
OphirJCespedesIPonnekantiHYazdiYLiX. Elastography: a quantitative method for imaging the elasticity of biological tissues. Ultrason Imaging. 1991;13:111-34.
20.
OphirJAlamSKGarraBKallelFKonofagouEKrouskopTet al. Elastography: ultrasonic estimation and imaging of the elastic properties of tissues. Proc Inst Mech Eng H. 1999;213:203-33.
21.
VargheseTDonohueKD. Estimating mean scatterer spacing with the frequency-smoothed spectral autocorrelation function. IEEE Trans Ultrason Ferroelectr Freq Control. 1995;42:451-63.
22.
InsanaMFWagnerRFGarraBSBrownDGShawkerTH. Analysis of ultrasound image texture via generalized Rician statistics. Opt Eng. 1986;25:743-8.
23.
GarraBSInsanaMFSesterhennIAHallTJWagnerRFRotellarCet al. Quantitative ultrasonic detection of parenchymal structural change in diffuse renal disease. Invest Radiol. 1994;29:134-40.
24.
GarraBSInsanaMFShawkerTHWagnerRFBradfordMRussellM. Quantitative ultrasonic detection and classification of diffuse liver disease. Comparison with human observer performance. Invest Radiol. 1989;24:196-203.
25.
WagnerRFInsanaMFSmithSW. Fundamental correlation lengths of coherent speckle in medical ultrasonic images. IEEE Trans Ultrason Ferroelectr Freq Control. 1988;35:34-44.
26.
WagnerRFInsanaMFBrownDG. Statistical properties of radio-frequency and envelope-detected signals with applications to medical ultrasound. J Opt Soc Am A. 1987;4:910-22.
27.
WagnerRFInsanaMFBrownDG. Unified approach to the detection and classification of speckle texture in diagnostic ultrasound. Opt Eng. 1986;25:738-42.
28.
HuangKTaDWangWLeLH. Simplified inverse filter tracking algorithm for estimating the mean trabecular bone spacing. IEEE Trans Ultrason Ferroelectr Freq Control. 2008;55:1453-64.
29.
AbeyratneURPetropuluAPReidJM. On modeling the tissue response from ultrasonic B-scan images. IEEE Trans Med Imaging. 1996;15:479-90.
30.
SommerFGHoppeRTFellinghamLCarrollBASolomonHYousemS. Spleen structure in Hodgkin disease: ultrasonic characterization. Radiology. 1984;153:219-22.
31.
FellinghamLLSommerFG. Ultrasonic characterization of tissue structure in the in vivo human liver and spleen. IEEE Trans Son Ultrason. 1984;31:418-28.
32.
SommerFGGregoryPBFellinghamLLSternRANassiMWeissbergJet al. Measurement of attenuation and scatterer spacing in human liver tissue: preliminary results. J Ultrasound Med. 1984;3:557-61.
33.
SommerFGJoyntLFHayesDLMacovskiA. Stochastic frequency-domain tissue characterization: application to human spleens “in vivo.”Ultrasonics. 1982;20:82-86.
34.
SommerFGJoyntLFCarrollBAMacovskiA. Ultrasonic characterization of abdominal tissues via digital analysis of backscattered waveforms. Radiology. 1981;141:811-7.
35.
FellinghamLL. A stochastic approach to ultrasonic tissue characterization. PhD dissertation, Stanford University, Stanford, CA, 1979.
36.
DonohueKDHuangLBurksTForsbergFPiccoliCW. Tissue classification with generalized spectrum parameters. Ultrasound Med Biol. 2001;27:1505-14.
DonohueKDBresslerJMVargheseTBilgutayNM. Spectral correlation in ultrasonic pulse echo signal processing. IEEE Trans Ultrason Ferroelectr Freq Control. 1993;40:330-7.
39.
VargheseTDonohueKD. Characterization of tissue microstructure scatterer distribution with spectral correlation. Ultrason Imaging. 1993;15:238-54.
40.
KaddourABouhadefBBelbachirMFRouvaenJM. High-order statistic for mean scatterer spacing estimation for human tissues characterization. Acoust Sci Technol. 2011;32:1-7.
41.
LizziFFeleppaEJaremkoN. Liver-tissue characterization by digital spectrum and cepstrum analysis. In: IEEE Ultrasonics Symposium, Chicago, IL, USA, 14-16 October, 1981, pp. 575-8.
42.
WearKAWagnerRFInsanaMFHallTJ. Application of autoregressive spectral analysis to cepstral estimation of mean scatterer spacing. IEEE Trans Ultrason Ferroelectr Freq Control. 1993;40:50-58.
43.
MiaRSLoewMHWearKAWagnerRF. Quantitative estimation of scatterer spacing from backscattered ultrasound signals using the complex cepstrum. Inf Process Med Imaging. 1997;1230:513-8.
44.
WengLReidJMShankarPMSoetantoKLuXM. Nonuniform phase distribution in ultrasound speckle analysis. I. Background and experimental demonstration. IEEE Trans Ultrason Ferroelectr Freq Control. 1992;39:352-9.
45.
WengLReidJMShankarPMSoetanoKLuXM. Nonuniform phase distribution in ultrasound speckle analysis. II. Parametric expression and a frequency sweeping technique to measure mean scatterer spacing. IEEE Trans Ultrason Ferroelectr Freq Control. 1992;39:360-5.
46.
MolthenRCNarayananVMShankarPMReidJMGenisVForsbergFet al. Using phase information in ultrasonic backscatter for in vivo liver analysis. Ultrasound Med Biol. 1998;24:79-91.
47.
NarayananVMMolthenRCShankarPMVergaraLReidJM. Studies on ultrasonic scattering from quasi-periodic structures. IEEE Trans Ultrason Ferroelectr Freq Control. 1997;44:114-24.
48.
SimonCShenJSeipREbbiniES. A robust and computationally efficient algorithm for mean scatterer spacing estimation. IEEE Trans Ultrason Ferroelectr Freq Control. 1997;44:882-94.
49.
MachadoCBPereiraWCAMeziriMLaugierP. Characterization of in vitro healthy and pathological human liver tissue periodicity using backscattered ultrasound signals. Ultrasound Med Biol. 2006;32:649-57.
50.
CohenFSGeorgiouGHalpernEJ. WOLD decomposition of the backscatter echo in ultrasound images of soft tissue organs. IEEE Trans Ultrason Ferroelectr Freq Control. 1997;44:460-72.
51.
PereiraWCAMacielCD. Performance of ultrasound echo decomposition using singular spectrum analysis. Ultrasound Med Biol. 2001;27:1231-8.
52.
MamouJFeleppaEJ. Singular spectrum analysis applied to ultrasonic detection and imaging of brachytherapy seeds. J Acoust Soc Am. 2007;121:1790-801.
53.
GeorgiouGCohenFS. Tissue characterization using the continuous wavelet transform. Part I: decomposition method. IEEE Trans Ultrason Ferroelectr Freq Control. 2001;48:355-63.
54.
TangXYAbeyratneUR. Wavelet transforms in estimating scatterer spacing from ultrasound echoes. Ultrasonics. 2000;38:688-92.
55.
ZhouZShengLWuSYangCZengY. Ultrasonic evaluation of microwave-induced thermal lesions based on wavelet analysis of mean scatterer spacing. Ultrasonics. 2013;53:1325-31.
56.
KaySM. Modern Spectral Estimation: Theory and Application. Englewood Cliffs, NJ: Prentice Hall;1988.
57.
MuzyJ-FBacryEArneodoA. Multifractal formalism for fractal signals: the structure-function approach versus the wavelet-transform modulus-maxima method. Phys Rev E. 1993;47:875-84.
58.
KucRHaghkerdarKO’DonnellM. Presence of cepstral peak in random reflected ultrasound signals. Ultrason Imaging. 1986;8:196-212.
59.
VargheseTDonohueKDGenisVIHalpernEJ. Order selection criteria for detecting mean scatterer spacings with the AR model. IEEE Trans Ultrason Ferroelectr Freq Control. 1996;43:979-84.
PanWLShenYLiuTWangY. Golay improvement of the robustness of mean scatterer spacing measurement with ultrasonic backscattering. Biomed Mater Eng. 2015;26:S455-65.
62.
HuangLDonohueKDGenisVForsbergF. Duct detection and wall spacing estimation in breast tissue. Ultrason Imaging. 2000;22:137-52.
63.
PereiraWCAAbdelwahabABridalSLLaugierP. Singular spectrum analysis applied to 20MHz backscattered ultrasound signals from periodic and quasi-periodic phantoms. Acoust Imaging. 2002;26:239-46.
64.
Rosado-MendezIMCarlsonLCHallTJZagzebskiJA. A multitaper generalized spectrum technique for detection of periodic structures in tissue: comparison with conventional methods. In: IEEE International Ultrasonics Symposium, Prague, Czech Republic, 21-25 July 2013, pp. 433-6.
65.
NasrRFalouOWirtzfeldLBerndlEKoliosM. Mean scatterer spacing estimation from pellets using cepstral analysis: a preliminary study. In: International Conference on Advances in Biomedical Engineering, Beirut, Lebanon, 16-18 September 2015, pp. 305-8.
66.
TsaoJJiangGS. Mean scatterer spacing estimation using wavelet spectrum. Proc IEEE Ultrason Symp. 2004;3:2090-3.
67.
SuzukiKHayashiNSasakiYKonoMImaiYFusamotoHet al. Ultrasonic tissue characterization of chronic liver disease using cepstral analysis. Gastroenterology. 1991;101:1325-31.
68.
BouzitouneRMeziriMMachadoCBPadillaFPereiraWCA. Can early hepatic fibrosis stages be discriminated by combining ultrasonic parameters?Ultrasonics. 2016;68:120-6.
69.
AbeyratneURTangXY. Ultrasound scatter-spacing based diagnosis of focal diseases of the liver. Biomed Signal Process Control. 2007;2:9-15.
70.
GeorgiouGCohenFS. Is early detection of liver and breast cancers from ultrasound scans possible?Pattern Recogn Lett. 2003;24:729-39.
71.
ShengLWangGLiFLuoJLiuJ. Ultrasound signal wavelet analysis to quantify the microstructures of normal and frozen tissues in vitro. Cryobiology. 2014;68:29-34.
72.
RubertNVargheseT. Mean scatterer spacing estimation using multi-taper coherence. IEEE Trans Ultrason Ferroelectr Freq Control. 2013;60:1061-73.
73.
RubertNVargheseT. Mean scatterer spacing estimation in normal and thermally coagulated ex vivo bovine liver. Ultrason Imaging. 2014;36:79-97.
74.
DonohueKDForsbergFPiccoliCVGoldbergBB. Analysis and classification of tissue with scatterer structure templates. IEEE Trans Ultrason Ferroelectr Freq Control. 1999;46:300-10.
75.
GeorgiouGCohenFSPiccoliCWForsbergFGoldbergBB. Tissue characterization using the continuous wavelet transform. Part II: application on breast RF data. IEEE Trans Ultrason Ferroelectr Freq Control. 2001;48:364-73.
76.
BigeYZuoHFWangR. Analysis of microstructural alterations of normal and pathological breast tissue in vivo using the AR cepstrum. Ultrasonics. 2006;44:211-5.
77.
WearKA. Autocorrelation and cepstral methods for measurement of tibial cortical thickness. IEEE Trans Ultrason Ferroelectr Freq Control. 2003;50:655-60.
78.
PereiraWCABridalSLCoronALaugierP. Singular spectrum analysis applied to backscattered ultrasound signals from in vitro human cancellous bone specimens. IEEE Trans Ultrason Ferroelectr Freq Control. 2004;51:302-12.
79.
SeipREbbiniES. Noninvasive estimation of tissue temperature response to heating fields using diagnostic ultrasound. IEEE Trans Biomed Eng. 1995;42:828-39.
80.
AminiANEbbiniESGeorgiouTT. Noninvasive estimation of tissue temperature via high-resolution spectral analysis techniques. IEEE Trans Biomed Eng. 2005;52:221-8.
81.
CortelaGAVon KrügerMAMachadoCBNegreiraCAPereiraWCA. Influence of temperature on mean scattering spacing estimation of in vitro bovine muscle. In: Pan American Health Care Exchanges, Rio de Janeiro, Brazil, 28 March-1 April 2011, pp. 415-20.
82.
AboofazeliMAbolmaesumiPFichtingerGMousaviP. Tissue characterization using multiscale products of wavelet transform of ultrasound radio frequency echoes. Conf Proc IEEE Eng Med Biol Soc. 2009;1:479-82.
