Quantitative Assessment of Breast-Tumor Stiffness Using Shear-Wave Elastography Histograms

Purpose: Shear-wave elastography (SWE) measures tissue elasticity using ultrasound waves. This study proposes a histogram-based SWE analysis to improve breast malignancy detection. Methods: N = 22/32 (patients/tumors) benign and n = 51/64 malignant breast tumors with histological ground truth. Colored SWE heatmaps were adjusted to a 0–180 kPa scale. Normalized, 250-binned RGB histograms were used as image descriptors based on skewness and area under curve (AUC). The histogram method was compared to conventional SWE metrics, such as (1) the qualitative 5-point scale classification and (2) average stiffness (SWEavg)/maximal tumor stiffness (SWEmax) within the tumor B-mode boundaries. Results: The SWEavg and SWEmax did not discriminate malignant lesions in this database, p > 0.05, rank sum test. RGB histograms, however, differed between malignant and benign tumors, p < 0.001, Kolmogorov–Smirnoff test. The AUC analysis of histograms revealed the reduction of soft-tissue components as a significant SWE biomarker (p = 0.03, rank sum). The diagnostic accuracy of the suggested method is still low (Se = 0.30 for Se = 0.90) and a subject for improvement in future studies. Conclusions: Histogram-based SWE quantitation improved the diagnostic accuracy for malignancy compared to conventional average SWE metrics. The sensitivity is a subject for improvement in future studies.

[1]  M. C. Comes,et al.  A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patients , 2022, Scientific Reports.

[2]  R. Barr,et al.  Diagnostic Accuracy of Shear-Wave Elastography for Breast Lesion Characterization in Women: A Systematic Review and Meta-Analysis. , 2022, Journal of the American College of Radiology : JACR.

[3]  Ming-de Lu,et al.  RGB Three-Channel SWE-Based Ultrasomics Model: Improving the Efficiency in Differentiating Focal Liver Lesions , 2021, Frontiers in Oncology.

[4]  Arkadiusz Dudek,et al.  Shear Wave and Strain Elastography in Crohn’s Disease—A Systematic Review , 2021, Diagnostics.

[5]  M. Yamakawa,et al.  A review of physical and engineering factors potentially affecting shear wave elastography , 2021, Journal of Medical Ultrasonics.

[6]  Yanjun Xu,et al.  Role of “Stiff Rim” sign obtained by shear wave elastography in diagnosis and guiding therapy of breast cancer , 2021, International journal of medical sciences.

[7]  Max A. Viergever,et al.  Explainable artificial intelligence (XAI) in deep learning-based medical image analysis , 2021, Medical Image Anal..

[8]  Jinyi Bian,et al.  Diagnostic accuracy of ultrasound shear wave elastography combined with superb microvascular imaging for breast tumors , 2021, Medicine.

[9]  X. Cui,et al.  Management of breast lesions seen on US images: dual-model radiomics including shear-wave elastography may match performance of expert radiologists. , 2021, European journal of radiology.

[10]  S. Bonnema,et al.  Evaluation of thyroid nodules by shear wave elastography: a review of current knowledge , 2021, Journal of Endocrinological Investigation.

[11]  M. Chammas,et al.  Multiparametric Ultrasound Evaluation of the Thyroid: Elastography as a Key Tool in the Risk Prediction of Undetermined Nodules (Bethesda III and IV)-Histopathological Correlation. , 2021, Ultrasound in medicine & biology.

[12]  J. Bamber,et al.  Characterisation of Prostate Lesions Using Transrectal Shear Wave Elastography (SWE) Ultrasound Imaging: A Systematic Review , 2021, Cancers.

[13]  Bing Ou,et al.  Deep Learning-Based Radiomics of B-Mode Ultrasonography and Shear-Wave Elastography: Improved Performance in Breast Mass Classification , 2020, Frontiers in Oncology.

[14]  C. D. de Korte,et al.  Vascular Shear Wave Elastography in Atherosclerotic Arteries: A Systematic Review. , 2020, Ultrasound in medicine & biology.

[15]  Feiqian Wang,et al.  Comparative analysis of the quantitative parameter method and elasticity color mode method for real-time shear wave elastography in the diagnosis of benign and malignant solid breast lesions , 2019, Tumori.

[16]  G. Ferraioli Review of Liver Elastography Guidelines , 2018, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[17]  A. Preto,et al.  Ultrasound elastography: compression elastography and shear-wave elastography in the assessment of tendon injury , 2018, Insights into Imaging.

[18]  Cheng Li,et al.  A Radiomics Approach With CNN for Shear-Wave Elastography Breast Tumor Classification , 2018, IEEE Transactions on Biomedical Engineering.

[19]  J. Park,et al.  Impact of region of interest (ROI) size on the diagnostic performance of shear wave elastography in differentiating solid breast lesions , 2018, Acta radiologica.

[20]  Triantafyllos Stylianopoulos,et al.  Cell Adhesion and Matrix Stiffness: Coordinating Cancer Cell Invasion and Metastasis , 2018, Front. Oncol..

[21]  Cai Chang,et al.  Ultrasound shear wave elastography of breast lesions: correlation of anisotropy with clinical and histopathological findings , 2018, Cancer Imaging.

[22]  Y. Cho,et al.  The diagnostic performance of shear-wave elastography for liver fibrosis in children and adolescents: A systematic review and diagnostic meta-analysis , 2018, European Radiology.

[23]  Yang Xiao,et al.  Breast lesion classification based on supersonic shear-wave elastography and automated lesion segmentation from B-mode ultrasound images , 2018, Comput. Biol. Medicine.

[24]  J. Carlsen,et al.  Strain histograms are equal to strain ratios in predicting malignancy in breast tumours , 2017, PloS one.

[25]  A. Farrokh,et al.  Strain Elastography - How To Do It? , 2017, Ultrasound International Open.

[26]  M. Chammas,et al.  Ultrasound Elastography: Review of Techniques and Clinical Applications , 2017, Theranostics.

[27]  J. Antaki,et al.  Breast Lesion Elastography Region of Interest Selection and Quantitative Heterogeneity: A Systematic Review and Meta-Analysis. , 2017, Ultrasound in medicine & biology.

[28]  Jing Li,et al.  A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation. , 2017, European journal of radiology.

[29]  Y. Bae,et al.  Clinical application of a color map pattern on shear-wave elastography for invasive breast cancer. , 2016, Surgical oncology.

[30]  B. Seo,et al.  Diagnostic performance and color overlay pattern in shear wave elastography (SWE) for palpable breast mass. , 2015, European journal of radiology.

[31]  D. Cosgrove,et al.  Ultrasound Elastography in Breast Cancer Diagnosis , 2015, Ultraschall in der Medizin.

[32]  Congzhi Wang,et al.  Quantification of elastic heterogeneity using contourlet-based texture analysis in shear-wave elastography for breast tumor classification. , 2015, Ultrasound in medicine & biology.

[33]  Hadas Moshonov,et al.  Diagnostic performance of quantitative shear wave elastography in the evaluation of solid breast masses: determination of the most discriminatory parameter. , 2014, AJR. American journal of roentgenology.

[34]  Hyoung-Ki Lee,et al.  Principles and clinical application of ultrasound elastography for diffuse liver disease , 2014, Ultrasonography.

[35]  Cai Chang,et al.  Breast lesions: evaluation with shear wave elastography, with special emphasis on the "stiff rim" sign. , 2014, Radiology.

[36]  J. H. Yoon,et al.  Qualitative pattern classification of shear wave elastography for breast masses: how it correlates to quantitative measurements. , 2013, European journal of radiology.

[37]  Woo Kyung Moon,et al.  Comparison of shear-wave and strain ultrasound elastography in the differentiation of benign and malignant breast lesions. , 2013, AJR. American journal of roentgenology.

[38]  M. Fink,et al.  Ultrasound elastography: principles and techniques. , 2013, Diagnostic and interventional imaging.

[39]  J. Youk,et al.  Visually assessed colour overlay features in shear-wave elastography for breast masses: quantification and diagnostic performance , 2013, European Radiology.

[40]  Dihua Yu,et al.  Cancer cell stiffness: integrated roles of three-dimensional matrix stiffness and transforming potential. , 2010, Biophysical journal.

[41]  T. Matsumura,et al.  Breast disease: clinical application of US elastography for diagnosis. , 2006, Radiology.

[42]  Ruey-Feng Chang,et al.  Computer-Aided tumor diagnosis in 3-D breast elastography , 2018, Comput. Methods Programs Biomed..

[43]  Tsuyoshi Shiina,et al.  WFUMB guidelines and recommendations for clinical use of ultrasound elastography: Part 2: breast. , 2015, Ultrasound in medicine & biology.

[44]  Devanshi Characterisation of BE , 2008 .