Quantitative Assessment of In Vivo Breast Masses Using Ultrasound Attenuation and Backscatter

Clinical analysis of breast ultrasound imaging is done qualitatively, facilitated with the ultrasound breast imaging–reporting and data system (US BI-RADS) lexicon, which helps to standardize imaging assessments. Two descriptors in that lexicon, “posterior acoustic features” and the “echo pattern” within a mass, are directly related to quantitative ultrasound (QUS) parameters, namely, ultrasound attenuation and the average backscatter coefficient (BSC). The purpose of this study was to quantify ultrasound attenuation and backscatter in breast masses and to investigate these QUS properties as potential differential diagnostic markers. Radio frequency (RF) echo signals were from patients with breast masses during a special ultrasound imaging session prior to core biopsy. Data were also obtained from a well characterized phantom using identical system settings. Masses include 14 fibroadenomas and 10 carcinomas. Attenuation for the acoustic path lying proximal to the tumor was estimated offline using a least squares method with constraints. BSCs were estimated using a reference phantom method (RPM). The attenuation coefficient within each mass was assessed using both the RPM and a hybrid method, and effective scatterer diameters (ESDs) were estimated using a Gaussian form factor model. Attenuation estimates obtained with the RPM were consistent with estimates done using the hybrid method in all cases except for two masses. The mean slope of the attenuation coefficient versus frequency for carcinomas was 20% greater than the mean slope value for the fibroadenomas. The product of the attenuation coefficient and anteroposterior dimension of the mass was computed to estimate the total attenuation for each mass. That value correlated well with the BI-RADS assessment of “posterior acoustic features” judged qualitatively from gray scale images. Nearly all masses were described as “hypoechoic,” so no strong statements could be made about the correlation of echo pattern findings in BI-RADS with the averaged BSC values. However, most carcinomas exhibited lower values for the frequency-average BSC than fibroadenomas. The mean ESD alone did not differentiate the mass type, but fibroadenomas had greater variability in ESDs within the ROI than that found for invasive ductal carcinomas. This study demonstrates the potential to use attenuation and QUS parameters associated with the BSC as quantitative descriptors.

[1]  L. X. Yao,et al.  Backscatter Coefficient Measurements Using a Reference Phantom to Extract Depth-Dependent Instrumentation Factors , 1990, Ultrasonic imaging.

[2]  T J Hall,et al.  Parametric Ultrasound Imaging from Backscatter Coefficient Measurements: Image Formation and Interpretation , 1990, Ultrasonic imaging.

[3]  C W Piccoli,et al.  Tissue classification with generalized spectrum parameters. , 2001, Ultrasound in medicine & biology.

[4]  Tomy Varghese,et al.  Stability of heterogeneous elastography phantoms made from oil dispersions in aqueous gels. , 2006, Ultrasound in medicine & biology.

[5]  D. Nicholas,et al.  EVALUATION OF BACKSCATTERING COEFFICIENTS FOR EXCISED HUMAN TISSUES: RESULTS, INTERPRETATION AND ASSOCIATED MEASUREMENTS , 1982 .

[6]  Pascal Laugier,et al.  Three-dimensional high-frequency characterization of cancerous lymph nodes. , 2010, Ultrasound in medicine & biology.

[7]  H. Ermert,et al.  An ultrasound research interface for a clinical system , 2006, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[8]  S. Urban,et al.  Advanced ultrasonic imaging of the prostate for guiding biopsies and for planning and monitoring therapy , 2000, 2000 IEEE Ultrasonics Symposium. Proceedings. An International Symposium (Cat. No.00CH37121).

[9]  V. Jackson Management of solid breast nodules: what is the role of sonography? , 1995, Radiology.

[10]  G G Cox,et al.  Ultrasonic measurement of glomerular diameters in normal adult humans. , 1996, Ultrasound in medicine & biology.

[11]  Kouichi Itoh,et al.  A New Method for Attenuation Coefficient Measurement in the Liver , 2002, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[12]  T. Hall,et al.  Renal Ultrasound Using Parametric Imaging Techniques to Detect Changes in Microstructure and Function , 1993, Investigative radiology.

[13]  Timothy J. Hall,et al.  Ultrasound Attenuation Measurements Using a Reference Phantom with Sound Speed Mismatch , 2011, Ultrasonic imaging.

[14]  E. Madsen,et al.  Tests of backscatter coefficient measurement using broadband pulses , 1993, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[15]  William D O'Brien,et al.  Method of improved scatterer size estimation and application to parametric imaging using ultrasound. , 2002, The Journal of the Acoustical Society of America.

[16]  R. R. Paulinelli,et al.  Risk of Malignancy in Solid Breast Nodules According to Their Sonographic Features , 2005, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[17]  R. Kuc,et al.  Estimating the Acoustic Attenuation Coefficient Slope for Liver from Reflected Ultrasound Signals , 1979, IEEE Transactions on Sonics and Ultrasonics.

[18]  Tomy Varghese,et al.  Initial Clinical Experience Imaging Scatterer Size and Strain in Thyroid Nodules , 2006, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[19]  Ernest J. Feleppa,et al.  Differentiation of metastatic from benign lymph nodes by spectrum analysis in vitro , 1997, 1997 IEEE Ultrasonics Symposium Proceedings. An International Symposium (Cat. No.97CH36118).

[20]  T. J. Hall,et al.  Performance of various spectral estimation methods on acoustic backscatter coefficient estimation under data size limitations , 2011, 2011 IEEE International Ultrasonics Symposium.

[21]  L. Liberman,et al.  The breast imaging reporting and data system: positive predictive value of mammographic features and final assessment categories. , 1998, AJR. American journal of roentgenology.

[22]  F. Foster,et al.  Frequency dependence of ultrasound attenuation and backscatter in breast tissue. , 1986, Ultrasound in medicine & biology.

[23]  Helmut Madjar,et al.  The Practice of Breast Ultrasound: Techniques, Findings, Differential Diagnosis , 2000 .

[24]  J. Baker,et al.  BI-RADS for sonography: positive and negative predictive values of sonographic features. , 2005, AJR. American journal of roentgenology.

[25]  P. Welch The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms , 1967 .

[26]  T. Varghese,et al.  WE‐D‐L100J‐06: Ultrasonic Scatterer Size Estimations in Liver Tumor Differentiation , 2007 .

[27]  Pascal Laugier,et al.  Measurement of integrated backscatter coefficient of trabecular bone , 1996, 1996 IEEE Ultrasonics Symposium. Proceedings.

[28]  Adam C. Luchies,et al.  Quantitative ultrasonic characterization of diffuse scatterers in the presence of structures that produce coherent echoes , 2012, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[29]  C. S. Spalding,et al.  In vivo real-time freehand palpation imaging. , 2003, Ultrasound in medicine & biology.

[30]  Abd-elrahma Hassan,et al.  Benign Versus Malignant Solid Breast Masses: US Differentiation , 2015 .

[31]  William D. O'Brien,et al.  Differentiation and characterization of rat mammary fibroadenomas and 4T1 mouse carcinomas using quantitative ultrasound imaging , 2004, IEEE Transactions on Medical Imaging.

[32]  Tian Liu,et al.  Ultrasonic tissue characterization using 2-D spectrum analysis and its application in ocular tumor diagnosis. , 2004, Medical physics.

[33]  Timothy J Hall,et al.  Simultaneous backscatter and attenuation estimation using a least squares method with constraints. , 2011, Ultrasound in medicine & biology.

[34]  E J Feleppa,et al.  Differentiation of breast tumors by ultrasonic tissue characterization , 1993, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[35]  Handel E. Reynolds,et al.  Sonography of the breast. , 1996, Seminars in ultrasound, CT, and MR.

[36]  M. Sasso,et al.  Dependence of ultrasonic attenuation on bone mass and microstructure in bovine cortical bone. , 2008, Journal of biomechanics.

[37]  L. Rabiner,et al.  The chirp z-transform algorithm , 1969 .

[38]  C R Hill,et al.  The use of angular acoustic scattering measurements to estimate structural parameters of human and animal tissues. , 1986, The Journal of the Acoustical Society of America.

[39]  P. Porter,et al.  Breast density as a predictor of mammographic detection: comparison of interval- and screen-detected cancers. , 2000, Journal of the National Cancer Institute.

[40]  J. Ophir,et al.  On the Frequency Dependence of Attenuation in Normal and Fatty Liver , 1983, IEEE Transactions on Sonics and Ultrasonics.

[41]  K. Wear,et al.  Characterization of trabecular bone using the backscattered spectral centroid shift , 2003, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[42]  E. Madsen,et al.  Interlaboratory Comparison of Ultrasonic Backscatter Coefficient Measurements From 2 to 9 MHz , 2005, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[43]  R. F. Wagner,et al.  Describing small-scale structure in random media using pulse-echo ultrasound. , 1990, The Journal of the Acoustical Society of America.

[44]  Tomy Varghese,et al.  Hybrid spectral domain method for attenuation slope estimation. , 2008, Ultrasound in medicine & biology.

[45]  A. Stavros,et al.  Solid breast nodules: use of sonography to distinguish between benign and malignant lesions. , 1995, Radiology.

[46]  E. Conant,et al.  A Review of Breast Ultrasound , 2006, Journal of Mammary Gland Biology and Neoplasia.

[47]  Pai-Chi Li,et al.  Ultrasonic computed tomography reconstruction of the attenuation coefficient using a linear array , 2005, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[48]  R. Freitas-Junior,et al.  Sonobreast: Predicting Individualized Probabilities of Malignancy in Solid Breast Masses with Echographic Expression , 2011, The breast journal.

[49]  E. Conant,et al.  Interreader variability and predictive value of US descriptions of solid breast masses: pilot study. , 2001, Academic radiology.