1
|
Mutala TM, Mwango GN, Aywak A, Cioni D, Neri E. Determining the elastography strain ratio cut off value for differentiating benign from malignant breast lesions: systematic review and meta-analysis. Cancer Imaging 2022; 22:12. [PMID: 35151365 PMCID: PMC8841096 DOI: 10.1186/s40644-022-00447-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 01/10/2022] [Indexed: 12/15/2022] Open
Abstract
Background Elastography is an addition to grey-scale ultrasonic examination that has gained substantial traction within the last decade. Strain ratio (SR) has been incorporated as a semiquantitative measure within strain elastography, thus a potential imaging biomarker. The World Federation for Ultrasound in Medicine and Biology (WFUMB) published guidelines in 2015 for breast elastography. These guidelines acknowledge the marked variance in SR cut-off values used in differentiating benign from malignant lesions. The objective of this review was to include more recent evidence and seek to determine the optimal strain ratio cut off value for differentiating between benign and malignant breast lesions. Methods Comprehensive search of MEDLINE and Web of Science electronic databases with additional searches via Google Scholar and handsearching set from January 2000 to May 2020 was carried out. For retrieved studies, screening for eligibility, data extraction and analysis was done as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Diagnostic Test Accuracy (PRISMA-DTA) Statement guidelines of 2018. Quality and risk of bias assessment of the studies were performed using the revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Results A total of 424 articles, 412 from electronic database and 12 additional searches were retrieved and 65 studies were included in the narrative synthesis and subgroup analysis. The overall threshold effect indicated significant heterogeneity among the studies with Spearman correlation coefficient of Logit (TPR) vs Logit (FPR) at − 0.301, p-value = 0.015. A subgroup under machine model consisting seven studies with 783 patients and 844 lesions showed a favourable threshold, Spearman’s correlation coefficient,0.786 (p = 0.036). Conclusion From our review, currently the optimal breast SR cut-off point or value remains unresolved despite the WFUMB guidelines of 2015. Machine model as a possible contributor to cut-off value determination was suggested from this review which can be subjected to more industry and multi-center research determination. Supplementary Information The online version contains supplementary material available at 10.1186/s40644-022-00447-5.
Collapse
|
2
|
Rosen D, Jiang J. Modeling Uncertainty of Strain Ratio Measurements in Ultrasound Breast Strain Elastography: A Factorial Experiment. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2020; 67:258-268. [PMID: 31545719 PMCID: PMC8011866 DOI: 10.1109/tuffc.2019.2942821] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Strain elastography (SE) is a technique in which images of localized tissue strains are used to detect the relative stiffness of tissues. The application of SE in differentiating malignant breast lesions from benign ones has been broadly investigated. The strain ratio (SR) between the background and the breast tumor has been used and its results have been mixed. Due to the complex nature of tissue elasticity and how it relates to the strain fields measured in SE, the exact reason is not known. In this study, we apply a novel design-of-experiments-based metamodeling approach to mechanical simulation of SE in the human breast. To our knowledge, such a study has not been reported in the ultrasound SE literature. More specifically, we first conduct a screening study to identify the biomechanical factors/simulation inputs that most strongly determine SR. We then apply a response surface experimental design to these factors to produce a metamodel of SR as a function of said factors. Results from the screening study suggest that the SR measurements are primarily influenced by three factors: the initial shear modulus of the lesion, the elastic nonlinearity of the lesion, and the precompression applied during acquisition. In order to investigate the implications of these results, stochastic inputs for these three factors associated with the malignant and benign cases were applied to the resulting response surface. The resulting optimal cutoffs, sensitivity, and specificity were generally in line with a majority (>60%) of 19 clinical trials in the literature.
Collapse
|
4
|
Kim HJ, Kim SM, Kim B, La Yun B, Jang M, Ko Y, Lee SH, Jeong H, Chang JM, Cho N. Comparison of strain and shear wave elastography for qualitative and quantitative assessment of breast masses in the same population. Sci Rep 2018; 8:6197. [PMID: 29670125 PMCID: PMC5906688 DOI: 10.1038/s41598-018-24377-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Accepted: 03/29/2018] [Indexed: 12/21/2022] Open
Abstract
We investigated addition of strain and shear wave elastography to conventional ultrasonography for the qualitative and quantitative assessment of breast masses; cut-off points were determined for strain ratio, elasticity ratio, and visual score for differentiating between benign and malignant masses. In all, 108 masses from 94 patients were evaluated with strain and shear wave elastography and scored for suspicion of malignancy, visual score, strain ratio, and elasticity ratio. The diagnostic performance between ultrasonography alone and ultrasonography combined with either type of elastography was compared; cut-off points were determined for strain ratio, elasticity ratio, and visual score. Of the 108 masses, 44 were malignant and 64 were benign. The areas under the curves were significantly higher for strain and shear wave elastography-supplemented ultrasonography (0.839 and 0.826, respectively; P = 0.656) than for ultrasonography alone (0.764; P = 0.018 and 0.035, respectively). The diagnostic performances of strain and elasticity ratios were similar when differentiating benign from malignant masses. Cut-off values for strain ratio, elasticity ratio, and visual scores for strain and shear wave elastography were 2.93, 4, 3, and 2, respectively. Both forms of elastography similarly improved the diagnostic performance of conventional ultrasonography in the qualitative and quantitative assessment of breast masses.
Collapse
Affiliation(s)
- Hyo Jin Kim
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea
| | - Sun Mi Kim
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea.
| | - Bohyoung Kim
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Oedae-ro 81, Mohyeon-myeon, Cheoin-gu, Yongin-si, Gyeonggi-do, Korea
| | - Bo La Yun
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea
| | - Mijung Jang
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea
| | - Yousun Ko
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea
| | - Soo Hyun Lee
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea.,Department of Radiology, College of Medicine, Chungbuk National University, 776 1sunhwan-ro, Seowon-gu, Cheongju, Korea
| | - Heeyeong Jeong
- Department of Health Promotion, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea
| | - Jung Min Chang
- Department of Radiology, Seoul National University College of Medicine, 101 Daehakro, Jongno-gu, Seoul, Korea
| | - Nariya Cho
- Department of Radiology, Seoul National University College of Medicine, 101 Daehakro, Jongno-gu, Seoul, Korea
| |
Collapse
|
5
|
Guo R, Lu G, Qin B, Fei B. Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Review. ULTRASOUND IN MEDICINE & BIOLOGY 2018; 44:37-70. [PMID: 29107353 PMCID: PMC6169997 DOI: 10.1016/j.ultrasmedbio.2017.09.012] [Citation(s) in RCA: 184] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 09/12/2017] [Accepted: 09/13/2017] [Indexed: 05/25/2023]
Abstract
Ultrasound imaging is a commonly used modality for breast cancer detection and diagnosis. In this review, we summarize ultrasound imaging technologies and their clinical applications for the management of breast cancer patients. The technologies include ultrasound elastography, contrast-enhanced ultrasound, 3-D ultrasound, automatic breast ultrasound and computer-aided detection of breast ultrasound. We summarize the study results seen in the literature and discuss their future directions. We also provide a review of ultrasound-guided, breast biopsy and the fusion of ultrasound with other imaging modalities, especially magnetic resonance imaging (MRI). For comparison, we also discuss the diagnostic performance of mammography, MRI, positron emission tomography and computed tomography for breast cancer diagnosis at the end of this review. New ultrasound imaging techniques, ultrasound-guided biopsy and the fusion of ultrasound with other modalities provide important tools for the management of breast patients.
Collapse
Affiliation(s)
- Rongrong Guo
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA; Department of Ultrasound, Shanxi Provincial Cancer Hospital, Taiyuan, Shanxi, China
| | - Guolan Lu
- The Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Binjie Qin
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Baowei Fei
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA; The Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia, USA; Department of Mathematics and Computer Science, Emory College of Emory University, Atlanta, Georgia, USA; Winship Cancer Institute of Emory University, Atlanta, Georgia, USA.
| |
Collapse
|
6
|
Zhang Q, Xiao Y, Suo J, Shi J, Yu J, Guo Y, Wang Y, Zheng H. Sonoelastomics for Breast Tumor Classification: A Radiomics Approach with Clustering-Based Feature Selection on Sonoelastography. ULTRASOUND IN MEDICINE & BIOLOGY 2017; 43:1058-1069. [PMID: 28233619 DOI: 10.1016/j.ultrasmedbio.2016.12.016] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2016] [Revised: 12/09/2016] [Accepted: 12/24/2016] [Indexed: 06/06/2023]
Abstract
A radiomics approach to sonoelastography, called "sonoelastomics," is proposed for classification of benign and malignant breast tumors. From sonoelastograms of breast tumors, a high-throughput 364-dimensional feature set was calculated consisting of shape features, intensity statistics, gray-level co-occurrence matrix texture features and contourlet texture features, which quantified the shape, hardness and hardness heterogeneity of a tumor. The high-throughput features were then selected for feature reduction using hierarchical clustering and three-feature selection metrics. For a data set containing 42 malignant and 75 benign tumors from 117 patients, seven selected sonoelastomic features achieved an area under the receiver operating characteristic curve of 0.917, an accuracy of 88.0%, a sensitivity of 85.7% and a specificity of 89.3% in a validation set via the leave-one-out cross-validation, revealing superiority over the principal component analysis, deep polynomial networks and manually selected features. The sonoelastomic features are valuable in breast tumor differentiation.
Collapse
Affiliation(s)
- Qi Zhang
- Institute of Biomedical Engineering, Shanghai University, Shanghai, China.
| | - Yang Xiao
- Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jingfeng Suo
- Institute of Biomedical Engineering, Shanghai University, Shanghai, China
| | - Jun Shi
- Institute of Biomedical Engineering, Shanghai University, Shanghai, China
| | - Jinhua Yu
- Department of Electronic Engineering, Fudan University, Shanghai, China
| | - Yi Guo
- Department of Electronic Engineering, Fudan University, Shanghai, China
| | - Yuanyuan Wang
- Department of Electronic Engineering, Fudan University, Shanghai, China
| | - Hairong Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| |
Collapse
|
7
|
Can strain elastography combined with ultrasound breast imaging reporting and data system be a more effective method in the differentiation of benign and malignant breast lesions? J Med Ultrason (2001) 2017; 44:289-296. [PMID: 28154989 DOI: 10.1007/s10396-017-0772-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Accepted: 01/05/2017] [Indexed: 12/21/2022]
Abstract
PURPOSE To investigate whether a novel method that combines breast imaging reporting and data system (BI-RADS) with strain elastography contributes to diagnostic performance in differentiation of malignant and benign breast lesions. METHODS In 81 patients, 81 breast lesions were prospectively investigated. Breast lesions were separately evaluated with ultrasonography and strain elastography. While evaluations with ultrasonography were based on 2003 BI-RADS-US, strain elastography evaluations were based on a 5-point scale and strain ratio. Diagnostic performances of ultrasonography, strain elastography, and the combined method were compared. RESULTS Among 81 lesions, 43 (53.1%) were benign and 38 (46.9%) were malignant. When a cutoff point of category 3 was used, sensitivity, specificity, positive and negative predictive values, and accuracy for BI-RADS were 100, 11.6, 50, 100, and 53%, respectively. When BI-RADS and strain ratio were combined, sensitivity, specificity, positive and negative predictive values, and accuracy were 89.5, 93, 91.9, 90.9, and 91.3%, respectively. When BI-RADS and elastography scores were combined, sensitivity, specificity, positive and negative predictive values, and accuracy were 86.8, 97.7, 97.1, 89.4, and 92.5%, respectively. CONCLUSIONS The combination of strain elastography and BI-RADS was found to have better diagnostic performances to diagnose breast lesions than BI-RADS alone.
Collapse
|