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Breast elastography: diagnostic performance of computer-aided diagnosis software and interobserver agreement

Eduardo F. C. Fleury, Karem Marcomini
2020 Radiologia Brasileira  
Objective: To determine the best cutoff value for classifying breast masses by ultrasound elastography, using dedicated software for strain elastography, and to determine the level of interobserver agreement  ...  At a cutoff value of 75%, the interobserver agreement was excellent between R1 and R2, as well as between R1 and R3, and good between R2 and R3.  ...  Elastography is a tool that is complementary to ultrasound in the evaluation of breast masses. It should not be used, in isolation, to differentiate between benign and malignant lesions.  ... 
doi:10.1590/0100-3984.2019.0035 pmid:32313333 pmcid:PMC7159052 fatcat:yk4hc3xi2za3tfbniyhspshaiu

The Feasibility of Classifying Breast Masses Using a Computer-Assisted Diagnosis (CAD) System Based on Ultrasound Elastography and BI-RADS Lexicon

Eduardo F. C. Fleury, Ana Claudia Gianini, Karem Marcomini, Vilmar Oliveira
2018 Technology in Cancer Research and Treatment  
Methods: This prospective study was conducted between March 1, 2016, and May 30, 2016. A total of 83 breast masses subjected to percutaneous biopsy were included.  ...  Conclusion: The proposed computer-aided diagnostic system for strain elastography system has the potential to improve the diagnostic performance of radiologists in breast examination using ultrasound associated  ...  Among these tools, elastography is the most promising to date. 10 Ultrasound with elastography has been a promising tool in the diagnosis of breast lesions since its introduction in the fifth edition  ... 
doi:10.1177/1533033818763461 pmid:29551088 pmcid:PMC5882047 fatcat:uphpeuycyjfcncwglfcvakljym

Evaluation of a Computer-Aided Diagnosis System in the Classification of Lesions in Breast Strain Elastography Imaging

Karem Marcomini, Eduardo Fleury, Vilmar Oliveira, Antonio Carneiro, Homero Schiabel, Robert Nishikawa
2018 Bioengineering  
Purpose: Evaluation of the performance of a computer-aided diagnosis (CAD) system based on the quantified color distribution in strain elastography imaging to evaluate the malignancy of breast tumors.  ...  After six months with no eye contact on the breast images, the same radiologist and other two radiologists manually drew the contour of the lesions in B-mode ultrasound, which was masked in the elastography  ...  Acknowledgments: To FAPESP for the financial support. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/bioengineering5030062 pmid:30096868 fatcat:lrmoxqu5l5ggxcr4gdqbdb6bme

Which supplementary imaging modality should be used for breast ultrasonography? Comparison of the diagnostic performance of elastography and computer-aided diagnosis

Si Eun Lee, Ji Eun Moon, Yun Ho Rho, Eun-Kyung Kim, Jung Hyun Yoon
2017 Ultrasonography  
Methods: A total of 193 breast masses in 175 consecutive women (mean age, 46.4 years) from June to August 2015 were included. US and elastography images were obtained and recorded.  ...  A US-CAD system was applied to the grayscale sonograms, which were automatically analyzed and visualized in order to generate a final assessment.  ...  However, the US features used in BI-RADS contain an overlap between benign and malignant breast masses, particularly in category 4 lesions, as this category includes a broad spectrum of breast masses with  ... 
doi:10.14366/usg.16033 pmid:27764908 pmcid:PMC5381849 fatcat:vgdzshlu6ncu5cghwyxpez6c7a

Artificial intelligence in breast ultrasound

Ge-Ge Wu, Li-Qiang Zhou, Jian-Wei Xu, Jia-Yu Wang, Qi Wei, You-Bin Deng, Xin-Wu Cui, Christoph F Dietrich
2019 World Journal of Radiology  
AI can conduct a quantitative assessment by recognizing imaging information automatically and make more accurate and reproductive imaging diagnosis.  ...  Artificial intelligence (AI) is gaining extensive attention for its excellent performance in image-recognition tasks and increasingly applied in breast ultrasound.  ...  S-detect may be a feasible tool for the characterization of breast lesions and assist physicians in making clinical decisions.  ... 
doi:10.4329/wjr.v11.i2.19 pmid:30858931 pmcid:PMC6403465 fatcat:lkn2m2h4nzdzbfvfdyam5r2czm

Feasibility of computer-assisted diagnosis for breast ultrasound: the results of the diagnostic performance of S-detect from a single center in China

Chenyang Zhao, Mengsu Xiao, Yuxin Jiang, He Liu, Ming Wang, Hongyan Wang, Qiang Sun, Qingli Zhu
2019 Cancer Management and Research  
S-detect classified the lesions automatically in a dichotomous form. An in-training resident who was blind to both the US diagnostic results and histological results reviewed the images afterward.  ...  The diagnostic performances and interrater agreements were analyzed. A total of 266 focal breast lesions (161 benign lesions and 105 malignant lesions) were assessed in this study.  ...  a second reader to assist radiologists in diagnosis.  ... 
doi:10.2147/cmar.s190966 pmid:30774422 pmcid:PMC6350640 fatcat:7ty4epzbgfbmjcj4r4dqzo37ya

Enhancing Performance of Breast Ultrasound in Opportunistic Screening Women by a Deep Learning-Based System: A Multicenter Prospective Study

Chenyang Zhao, Mengsu Xiao, Li Ma, Xinhua Ye, Jing Deng, Ligang Cui, Fajin Guo, Min Wu, Baoming Luo, Qin Chen, Wu Chen, Jun Guo (+5 others)
2022 Frontiers in Oncology  
The final pathological results are referred to as the gold standard for classifying breast mass.  ...  In comparison to that of S-Detect alone, the AUC value significantly was enhanced after combining elastography and S-Detect (0.87 [0.84–0.90]), without compromising specificity (73.93% [68.60%–78.78%])  ...  Automated Classification of Focal Breast Lesions According to S-Detect: Validation and Role as a Clinical and Teaching Tool.  ... 
doi:10.3389/fonc.2022.804632 pmid:35223484 pmcid:PMC8867611 fatcat:2jabrn7npzashgtcdrk7vev5qy

Reducing the number of unnecessary biopsies of US-BI-RADS 4a lesions through a deep learning method for residents-in-training: a cross-sectional study

Chenyang Zhao, Mengsu Xiao, He Liu, Ming Wang, Hongyan Wang, Jing Zhang, Yuxin Jiang, Qingli Zhu
2020 BMJ Open  
The ultrasonic images of the lesions were retrospectively assessed by five residents-in-training according to the Breast Imaging Report and Data System (BI-RADS) lexicon, and a dichotomic classification  ...  ObjectiveThe aim of the study is to explore the potential value of S-Detect for residents-in-training, a computer-assisted diagnosis system based on deep learning (DL) algorithm.MethodsThe study was designed  ...  [17] [18] [19] [20] [21] S-Detect for Breast is a cutting-edge CAD system that acts as adjunctive tool for US imaging diagnosis of breast lesions.  ... 
doi:10.1136/bmjopen-2019-035757 pmid:32513885 fatcat:b4zfqkgtvjcw7gzi4qhcr2inde

Clinical application of S-Detect to breast masses on ultrasonography: a study evaluating the diagnostic performance and agreement with a dedicated breast radiologist

Kiwook Kim, Mi Kyung Song, Eun-Kyung Kim, Jung Hyun Yoon
2017 Ultrasonography  
US features of the breast masses were retrospectively analyzed by a radiologist who specializes in breast imaging and S-Detect, according to the fourth edition of the American College of Radiology Breast  ...  Moderate agreement (k=0.58) was seen in the final assessment between the radiologist and S-Detect.  ...  As a way to overcome the complexity of applying US descriptors and the interobserver variability of breast US, a recent study has applied computer-aided diagnosis to breast US for assistance in either  ... 
doi:10.14366/usg.16012 pmid:27184656 pmcid:PMC5207353 fatcat:eu3wh5evorhofpqy4jvajnl5qm

Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography

Ji Soo Choi, Boo-Kyung Han, Eun Sook Ko, Jung Min Bae, Eun Young Ko, So Hee Song, Mi-ri Kwon, Jung Hee Shin, Soo Yeon Hahn
2019 Korean Journal of Radiology  
To investigate whether a computer-aided diagnosis (CAD) system based on a deep learning framework (deep learning-based CAD) improves the diagnostic performance of radiologists in differentiating between  ...  malignant and benign masses on breast ultrasound (US).  ...  Acknowledgments The authors are grateful to Insuk Sohn, Ph.D., Biostatics and Clinical Epidemiology Center, Samsung Medical Center, for help in the statistical analyses. ORCID iDs  ... 
doi:10.3348/kjr.2018.0530 pmid:30993926 pmcid:PMC6470083 fatcat:dujdt5tdavc37h4h3e674pxkha

Distinction between phyllodes tumor and fibroadenoma in breast ultrasound using deep learning image analysis

Elina Stoffel, Anton S. Becker, Moritz C. Wurnig, Magda Marcon, Soleen Ghafoor, Nicole Berger, Andreas Boss
2018 European Journal of Radiology Open  
To evaluate the accuracy of a deep learning software (DLS) in the discrimination between phyllodes tumors (PT) and fibroadenomas (FA).  ...  In this IRB-approved, retrospective, single-center study, we collected all ultrasound images of histologically secured PT (n = 11, 36 images) and a random control group with FA (n = 15, 50 images).  ...  The authors of this manuscript declare no relevant conflicts of interest, and no relationships with any companies, whose products or services may be related to the subject matter of the article.  ... 
doi:10.1016/j.ejro.2018.09.002 pmid:30258856 pmcid:PMC6154513 fatcat:chy62t4mgzektfk24dor7wytoe

Artificial Intelligence in Medical Imaging of the Breast

Yu-Meng Lei, Miao Yin, Mei-Hui Yu, Jing Yu, Shu-E Zeng, Wen-Zhi Lv, Jun Li, Hua-Rong Ye, Xin-Wu Cui, Christoph F. Dietrich
2021 Frontiers in Oncology  
This paper introduces the background of AI and its application in breast medical imaging (mammography, ultrasound and MRI), such as in the identification, segmentation and classification of lesions; breast  ...  AI has shown excellent performance in image recognition tasks and has been widely studied in breast cancer screening.  ...  ACKNOWLEDGMENTS I would like to extend my sincere gratitude to my colleagues for their help in the completion of this article and the reviewers for reviewing my article.  ... 
doi:10.3389/fonc.2021.600557 fatcat:5tphtisnhnd33c3e5oycvywnee

Study Processes and Applications of Ultrasomics in Precision Medicine

Rui Yin, Meng Jiang, Wen-Zhi Lv, Fan Jiang, Jun Li, Bing Hu, Xin-Wu Cui, Christoph F. Dietrich
2020 Frontiers in Oncology  
Ultrasomics is a powerful tool in oncology but can also be applied to other medical problems for which a disease is imaged. To date there is no comprehensive review focusing on ultrasomics.  ...  Here, we describe how ultrasomics works and its capability in diagnosing disease in different organs, including breast, liver, and thyroid.  ...  All authors discussed the statement and conclusions and approved the final version to be published.  ... 
doi:10.3389/fonc.2020.01736 pmid:33014858 pmcid:PMC7494734 fatcat:exhi72oysbht7inaudmq6lrm2m

Comparison of Automated Breast Ultrasound and Hand-Held Breast Ultrasound in the Screening of Dense Breasts
Comparação entre a ultrassonografia automatizada e a ultrassonografia convencional no rastreio de mamas densas

Fernanda Philadelpho, Maria Julia Gregorio Calas, Gracy de Almeida Coutinho Carneiro, Isabela Cunha Silveira, Andréia Brandão Ribeiro Vaz, Adriana Maria Coelho Nogueira, Anke Bergmann, Flávia Paiva Proença Lobo Lopes
2021 Revista Brasileira de Ginecologia e Obstetrícia  
Objective To compare hand-held breast ultrasound (HHBUS) and automated breast ultrasound (ABUS) as screening tool for cancer.  ...  We evaluated the Breast Imaging Reporting and Data System (BI-RADS) classification of the exam and of the lesion, as well as the amount of time required to perform and read each exam.  ...  We thank our directors, specially Romeu Domingues and Roberto Domingues, and our colleagues from DASA who provided the structure, insight, and expertise that greatly assisted the research.  ... 
doi:10.1055/s-0040-1722156 pmid:33860502 fatcat:tertz2qe3nh5hjoprxgiqiii7e

ECR 2014, Part D

2014 Insights into Imaging  
To learn about MR-Mammography, though feasible, is probably not ready for "screening" today. Simultaneous acquisition of breast imaging with PET/MRI a powerful tool to better classify lesions L.  ...  Beyond imaging in breast MR: innovation and workflow optimisation in clinical practice Moderator L. Moy; New York, NY/US MR vacuum assisted biopsies and contrast injection optimisation F.  ...  This highly increases the feasibility of breast MRI as a screening tool. What the radiologist need to know in order to have breast MR referrals N.N.  ... 
doi:10.1007/s13244-014-0319-3 pmid:24573561 pmcid:PMC3948180 fatcat:hkued6wv2zduxpkzzlslgjr3nq
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