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Demirci BÖ, Buğdaycı O, Ertaş G, Şanlı DET, Kaya H, Arıbal E. Linear Regression Modeling Based Scoring System to Reduce Benign Breast Biopsies Using Multi-parametric US with Color Doppler and SWE. Acad Radiol 2023; 30 Suppl 2:S143-S153. [PMID: 36804295 DOI: 10.1016/j.acra.2023.01.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/15/2023] [Accepted: 01/17/2023] [Indexed: 02/18/2023]
Abstract
RATIONALE AND OBJECTIVES To develop a simple ultrasound (US) based scoring system to reduce benign breast biopsies. MATERIALS AND METHODS Women with BI-RADS 4 or 5 breast lesions underwent shear-wave elastography (SWE) imaging before biopsy. Standard US and color Doppler US (CDUS) parameters were recorded, and the size ratio (SzR=longest/shortest diameter) was calculated. Measured/calculated SWE parameters were minimum (SWVMin) and maximum (SWVMax) shear velocity, velocity heterogeneity (SWVH=SWVMax-SWVMin), velocity ratio (SWVR=SWVMin/SWVMax), and normalized SWVR (SWVRn=(SWVMax-SWVMin)/SWVMin). Linear regression analysis was performed by converting continuous parameters into categorical corresponding equivalents using decision tree analyses. Linear regression models were fitted using stepwise regression analysis and optimal coefficients for the predictors in the models were determined. A scoring model was devised from the results and validated using a different data set from another center consisting of 187 cases with BI-RADS 3, 4, and 5 lesions. RESULTS A total of 418 lesions (238 benign, 180 malignant) were analyzed. US and CDUS parameters exhibited poor (AUC=0.592-0.696), SWE parameters exhibited poor-good (AUC=0.607-0.816) diagnostic performance in benign/malignant discrimination. Linear regression models of US+CDUS and US+SWE parameters revealed an AUC of 0.819 and 0.882, respectively. The developed scoring system could have avoided biopsy in 37.8% of benign lesions while missing 1.1% of malignant lesions. The scoring system was validated with a 100% NPV rate with a specificity of 74.6%. CONCLUSION The linear regression model using US+SWE parameters performed better than any single parameter alone. The developed scoring method could lead to a significant decrease in benign biopsies.
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Affiliation(s)
| | - Onur Buğdaycı
- Department of Radiology, Marmara University, Istanbul, Türkiye.
| | - Gökhan Ertaş
- Department of Biomedical Engineering, Yeditepe University, Istanbul, Türkiye
| | - Deniz E T Şanlı
- Department of Radiology, Acibadem Kozyatagi Hospital, Istanbul, Türkiye; Department of Radiology, Gaziantep University, Gaziantep, Türkiye
| | - Handan Kaya
- Department of Pathology, Marmara University, Istanbul, Türkiye
| | - Erkin Arıbal
- Department of Radiology, Marmara University, Istanbul, Türkiye; Department of Radiology, Acıbadem University Medical School, Istanbul, Türkiye
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Wang Y, Tang L, Chen P, Chen M. The Role of a Deep Learning-Based Computer-Aided Diagnosis System and Elastography in Reducing Unnecessary Breast Lesion Biopsies. Clin Breast Cancer 2023; 23:e112-e121. [PMID: 36653206 DOI: 10.1016/j.clbc.2022.12.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 11/27/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVES Ultrasound examination has inter-observer and intra-observer variability and a high false-positive rate. The aim of this study was to evaluate the value of the combined use of a deep learning-based computer-aided diagnosis (CAD) system and ultrasound elastography with conventional ultrasound (US) in increasing specificity and reducing unnecessary breast lesions biopsies. MATERIALS AND METHODS Conventional US, CAD system, and strain elastography (SE) were retrospectively performed on 216 breast lesions before biopsy or surgery. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and biopsy rate were compared between conventional US and the combination of conventional US, SE, and CAD system. RESULTS Of 216 lesions, 54 were malignant and 162 were benign. The addition of CAD system and SE to conventional US increased the AUC from 0.716 to 0.910 and specificity from 46.9% to 85.8% without a loss in sensitivity while 89.2% (66 of 74) of benign lesions in Breast Imaging Reporting and Data System (BI-RADS) category 4A lesions would avoid unnecessary biopsies. CONCLUSION The addition of CAD system and SE to conventional US improved specificity and AUC without loss of sensitivity, and reduced unnecessary biopsies.
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Affiliation(s)
- Yuqun Wang
- Department of Ultrasound Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai China
| | - Lei Tang
- Department of Ultrasound Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai China
| | - Pingping Chen
- Department of Ultrasound Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai China
| | - Man Chen
- Department of Ultrasound Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai China.
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Catalano O, Fusco R, De Muzio F, Simonetti I, Palumbo P, Bruno F, Borgheresi A, Agostini A, Gabelloni M, Varelli C, Barile A, Giovagnoni A, Gandolfo N, Miele V, Granata V. Recent Advances in Ultrasound Breast Imaging: From Industry to Clinical Practice. Diagnostics (Basel) 2023; 13:diagnostics13050980. [PMID: 36900124 PMCID: PMC10000574 DOI: 10.3390/diagnostics13050980] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
Breast ultrasound (US) has undergone dramatic technological improvement through recent decades, moving from a low spatial resolution, grayscale-limited technique to a highly performing, multiparametric modality. In this review, we first focus on the spectrum of technical tools that have become commercially available, including new microvasculature imaging modalities, high-frequency transducers, extended field-of-view scanning, elastography, contrast-enhanced US, MicroPure, 3D US, automated US, S-Detect, nomograms, images fusion, and virtual navigation. In the subsequent section, we discuss the broadened current application of US in breast clinical scenarios, distinguishing among primary US, complementary US, and second-look US. Finally, we mention the still ongoing limitations and the challenging aspects of breast US.
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Affiliation(s)
- Orlando Catalano
- Department of Radiology, Istituto Diagnostico Varelli, 80126 Naples, Italy
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
- Correspondence:
| | - Federica De Muzio
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, 86100 Campobasso, Italy
| | - Igino Simonetti
- Division of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli”, 80131 Naples, Italy
| | - Pierpaolo Palumbo
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, 67100 L’Aquila, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Federico Bruno
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, 67100 L’Aquila, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Alessandra Borgheresi
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, 60126 Ancona, Italy
| | - Andrea Agostini
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, 60126 Ancona, Italy
| | - Michela Gabelloni
- Department of Translational Research, Diagnostic and Interventional Radiology, University of Pisa, 56126 Pisa, Italy
| | - Carlo Varelli
- Department of Radiology, Istituto Diagnostico Varelli, 80126 Naples, Italy
| | - Antonio Barile
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, 67100 L’Aquila, Italy
| | - Andrea Giovagnoni
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, 60126 Ancona, Italy
| | - Nicoletta Gandolfo
- Diagnostic Imaging Department, Villa Scassi Hospital-ASL 3, Corso Scassi 1, 16149 Genoa, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Emergency Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Vincenza Granata
- Division of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli”, 80131 Naples, Italy
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Liu X, Xie L, Ye X, Cui Y, He N, Hu L. Evaluation of Ultrasound Elastography Combined With Chi-Square Automatic Interactive Detector in Reducing Unnecessary Fine-Needle Aspiration on TIRADS 4 Thyroid Nodules. Front Oncol 2022; 12:823411. [PMID: 35251988 PMCID: PMC8889496 DOI: 10.3389/fonc.2022.823411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Accepted: 01/26/2022] [Indexed: 12/09/2022] Open
Abstract
Background Conventional ultrasound diagnosis of thyroid nodules (TNs) had a high false-positive rate, resulting in many unnecessary fine-needle aspirations (FNAs). Objective This study aimed to establish a simple algorithm to reduce unnecessary FNA on TIRADS 4 TNs using different quantitative parameters of ultrasonic elasticity and chi-square automatic interactive detector (CHAID) method. Methods From January 2020 to May 2021, 432 TNs were included in the study, which were confirmed by FNA or surgical pathology. Each TN was examined using conventional ultrasound, sound touch elastography, and Shell measurement function. The quantitative parameters E and Eshell were recorded, and the Eshell/E values were calculated for each TN. The diagnostic performance of the quantitative parameters was evaluated using the receiver operating characteristic curves. The CHAID was used to classify and analyze the quantitative parameters, and the prediction model was established. Results A total of 226 TNs were malignant and 206 were benign. Eshell and Eshell/E ratio were included in the classification algorithm, which showed a depth of two ramifications (Eshell/E ≤ 0.988 or 0.988–1.043 or >1.043; if Eshell/E ≤ 0.988, then Eshell ≤ 64.0 or 64.0–74.0 or >74.0; if Eshell/E = 0.988–1.043, then Eshell ≤ 66.0 or > 66.0; if Eshell/E >1.043, then Eshell ≤ 69.0 or >69.0). The unnecessary FNAs could have been avoided in 57.3% of the cases using this algorithm. Conclusion The prediction model using quantitative parameters had high diagnostic performance; it could quickly distinguish benign lesions and avoid subjective influence to some extent.
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Affiliation(s)
- Xiao Liu
- Department of Ultrasound, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Li Xie
- Department of Ultrasound, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Xianjun Ye
- Department of Ultrasound, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yayun Cui
- Department of Ultrasound, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Nianan He
- Department of Ultrasound, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Lei Hu
- Department of Ultrasound, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
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Tang Y, Liang M, Tao L, Deng M, Li T. Machine learning-based diagnostic evaluation of shear-wave elastography in BI-RADS category 4 breast cancer screening: a multicenter, retrospective study. Quant Imaging Med Surg 2022; 12:1223-1234. [PMID: 35111618 DOI: 10.21037/qims-21-341] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 09/09/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND Ultrasound is commonly used in breast cancer screening but lacks quantification ability and diagnostic power due to its low specificity, which can lead to overdiagnosis and unnecessary biopsies. This study evaluated the diagnostic efficacy and clinical utility of adding shear-wave elastography (SWE) to the screening of the Breast Imaging Reporting and Data System (BI-RADS) category 4 breast cancer. METHODS A machine learning-based diagnostic model was constructed using data retrospectively collected from 3 independent cohorts with features selected using lasso regression and support vector machine-recursive feature elimination algorithms. Propensity score matching (PSM) was used to preclude confounding baseline characteristics between malignant and benign lesions. A decision curve analysis (DCA) was used to evaluate the clinical benefit of the diagnostic model in identifying high-risk tumor patients for intervention while simultaneously avoiding overtreatment of low-risk patients with integrative evaluation using a net benefit value and treatment reduction rate. RESULTS In our training center, a total of 122 patients were enrolled, and 577 breast tumors were collected. The comparison between malignant and benign lesions revealed significant differences in patient age, tumor size, resistance index (RI), and elasticity values. The maximum elasticity value (Emax) was identified as an independent diagnostic feature and was included in the diagnostic model. The combination of Emax with BI-RADS category 4 demonstrated a significantly better diagnostic efficacy than the BI-RADS category alone [BI-RADS+Emax: AUC =0.908, 95% confidence interval (CI): 0.842-0.974; BI-RADS: AUC =0.862, 95% CI: 0.784-0.94; P=0.024] and significantly increased the clinical benefit for patients and policy makers by effectively reducing overdiagnosis and biopsy rates. In the BI-RADS category 4A subgroup, adding Emax to breast cancer screening benefited patients and showed a greater absolute benefit than did the BI-RADS category alone when used for patients with a higher probability of cancer (>0.403), demonstrating a 50% overtreatment reduction. CONCLUSIONS Adding Emax to BI-RADS category 4 breast cancer screening using SWE significantly reduced overdiagnosis and biopsy rates compared with the BI-RADS category alone, especially for BI-RADS 4A patients.
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Affiliation(s)
- Yi Tang
- Department of Medical Technology, Guangdong Key Laboratory of Traditional Chinese Medicine Research and Development, Guangdong Second Hospital of Traditional Chinese Medicine, Guangzhou, China.,Medical Imaging Center, First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Minjie Liang
- Medical Imaging Center, First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Li Tao
- Department of Obstetrics and Gynecology, The First Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Minjun Deng
- Department of Medical Technology, Guangdong Key Laboratory of Traditional Chinese Medicine Research and Development, Guangdong Second Hospital of Traditional Chinese Medicine, Guangzhou, China
| | - Tianfu Li
- Breast Disease Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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Quang-Huy T, Doan PT, Yen NTH, Tran DT. Shear wave imaging and classification using extended Kalman filter and decision tree algorithm. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:7631-7647. [PMID: 34814267 DOI: 10.3934/mbe.2021378] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Shear wave ultrasound elastography is a quantitative imaging approach in soft tissues based on viscosity-elastic properties. Complex shear modulus (CSM) estimation is an effective solution to analyze tissues' physical properties for elasticity and viscosity based on the wavenumber and attenuation coefficient. CSM offers a way to detect and classify some types of soft tissues. However, CSM-based elastography inherits some obstacles, such as estimation precision and calculation complexity. This work proposes an approach for two-dimensional CSM estimation and soft tissue classification using the Extended Kalman Filter (EKF) and Decision Tree (DT) algorithm, named the EKF-DT approach. CSM estimation is obtained by applying EKF to exploit shear wave propagation at each spatial point. Afterward, the classification of tissues is done by a direct and efficient decision tree algorithm categorizing three types of normal, cirrhosis, and fibrosis liver tissues. Numerical simulation scenarios have been employed to illustrate the recovered quality and practicality of the proposed method's liver tissue classification. With the EKF, the estimated wave number and attenuation coefficient are close to the ideal values, especially the estimated wave number. The states of three liver tissue types were automatically classified by applying the DT coupled with two proposed thresholds of elasticity and viscosity: (2.310 kPa, 1.885 Pa.s) and (3.620 kPa 3.146 Pa.s), respectively. The proposed method shows the feasibility of CSM estimation based on the wavenumber and attenuation coefficient by applying the EKF. Moreover, the DT can automate the classification of liver tissue conditions by proposing two thresholds. The proposed EKF-DT method can be developed by 3D image reconstruction and empirical data before applying it in medical practice.
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Affiliation(s)
- Tran Quang-Huy
- Faculty of Physics, Hanoi Pedagogical University 2, Hanoi, Vietnam
| | - Phuc Thinh Doan
- NTT Hi-Tech Institute - Nguyen Tat Thanh University, HoChiMinh City, Vietnam
- Faculty of Mechanical, Electrical, Electronic and Automotive Engineering, Nguyen Tat Thanh University, Ho Chi Minh 700000, Vietnam
| | - Nguyen Thi Hoang Yen
- Faculty of Technology and education, Hanoi National University of Education, Hanoi, Vietnam
| | - Duc-Tan Tran
- Faculty of Electrical and Electronic Engineering, Phenikaa University, Hanoi 12116, Vietnam
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Histopathology and elastography discordance in evaluation of breast lesions with acoustic radiation force impulse elastography. Pol J Radiol 2019; 84:e224-e233. [PMID: 31481994 PMCID: PMC6717941 DOI: 10.5114/pjr.2019.86852] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 05/14/2019] [Indexed: 12/21/2022] Open
Abstract
Purpose It is known that, besides its benefits, ultrasound (US) elastography may show discordance findings, leading to biopsy, so this technique has some limitations. The purpose of the present study was to compare histopathological results and shear wave velocity (SWV) values in patients, to reveal discordance findings, and to investigate its statistical significance in making the decision for biopsy with SWV values. Material and methods A total of 190 patients presenting with breast lesions were included in the study. The mean age of the patients was 39.87 ± 13.56 years. All morphological features of lesions were evaluated by B-mode US. The mean SWV values were measured using the region of interest (ROI) through all lesions with ARFI elastography. An ultrasound-guided Tru-Cut needle biopsy was performed, and histopathologic data were obtained. Results The SWV values of false positive benign lesions, such as: granulomatous mastitis, sclerosing adenosis, chronic inflammation, fat necrosis, fibrotic breast tissue, and scar tissue, were as high as the SWV values of malignant lesions. Sensitivity was found as 91.6% and specificity as 40.9% for SWV values in ARFI US. Conclusions Our results showed that breast lesions showed false positivity (59.1%) and false negativity (8.3%) in ARFI US. Elastography is useful and sensitive in the evaluation of breast lesions, but some benign lesions may mimic malignant lesions; thus, this information should not be underestimated in biopsy decision-making for elastography users.
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