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Abdulwahid Mohammad Noor K, Mohd Norsuddin N, Che Isa IN, Abdul Karim MK. Breast imaging in focus: A bibliometric overview of visual quality, modality innovations, and diagnostic performance. Radiography (Lond) 2024; 30:1041-1052. [PMID: 38723445 DOI: 10.1016/j.radi.2024.04.019] [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: 01/16/2024] [Revised: 04/05/2024] [Accepted: 04/21/2024] [Indexed: 07/03/2024]
Abstract
INTRODUCTION Breast imaging plays a crucial role in the early detection and management of breast cancer, with visual quality, modality innovation and diagnostic performance being key factors in achieving accurate diagnoses and optimal patient outcomes. This paper presents a comprehensive bibliometric analysis of the literature on the three above elements focusing on breast imaging, aiming to uncover publication trends, identify influential works and authors, and highlight future research directions. METHODS We employed a methodical bibliometric approach, making use of Scopus and Web of Science (WoS) databases for gathering literatures. We planned our search strategy, concentrating on terms linked to "breast imaging," "image quality," and "diagnostic accuracy" to ensure a systematic examination of the subject. The enhanced search functions in these databases enabled us to narrow down and improve our findings, choosing only the articles, conference papers, and book sections that are most relevant. After conducting a thorough screening process to remove duplicates and evaluate significance, we utilized ScientoPy and VOSviewer software for an in-depth bibliometric analysis. This helped to explore trends in publications, patterns of citations, and thematic groups, giving us a better understanding of how the field has changed and where it currently stands. Our approach prioritized assessing methodological quality and bias in the studies we included, guaranteeing the reliability of our findings. RESULTS We reviewed 2984 relevant publications, revealing a consistent annual growth rate of 2.8% in breast imaging research, with the United States and Europe leading in contributions. The study found that advancements in radiological technologies and international collaboration are driving forces behind the field's expansion. Key subject areas such as 'Radiology, Nuclear Medicine, and Medical Imaging' dominated, underscoring their impact on diagnostic quality. Notable authors and institutions have been identified for their influential research, characterized by high citation metrics and significant scholarly impact. CONCLUSION The study shows a continuous increase in research on breast imaging, considered by new technologies and teamwork defining the present time. The assessment highlights a key move towards utilizing digital imaging methods and computational analysis, affecting the improvement of future diagnostic procedures and patients' results. The study highlights the importance of continued international collaborations to tackle the new barriers in breast imaging and make the most of technological progress. IMPLICATIONS FOR PRACTICE This study shows a focus on using interdisciplinary methods and cutting-edge technology in breast imaging to help healthcare professionals improve their performance and accuracy in diagnosis. Recognizing vital research and emerging trends should guide clinical guidelines, radiology training, and patient care plans to encourage the use of effective techniques and stimulate innovation in diagnostic approaches.
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Affiliation(s)
- K Abdulwahid Mohammad Noor
- Dubai Health Academic Corporation (DHAC), Rashid Hospital, Radiology Department, Dubai, United Arab Emirates; Center for Diagnostics, Therapeutics & Investigative (CODTIS), Faculty of Health Sciences, The National University of Malaysia (UKM), Kuala Lumpur, Malaysia
| | - N Mohd Norsuddin
- Center for Diagnostics, Therapeutics & Investigative (CODTIS), Faculty of Health Sciences, The National University of Malaysia (UKM), Kuala Lumpur, Malaysia.
| | - I N Che Isa
- Center for Diagnostics, Therapeutics & Investigative (CODTIS), Faculty of Health Sciences, The National University of Malaysia (UKM), Kuala Lumpur, Malaysia
| | - M K Abdul Karim
- Department of Physics, Faculty of Science, University Putra Malaysia (UPM), Malaysia
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Wang X, Jing L, Yan L, Wang P, Zhao C, Xu H, Xia H. A conditional inference tree model for predicting cancer risk of non-mass lesions detected on breast ultrasound. Eur Radiol 2024; 34:4776-4788. [PMID: 38133675 DOI: 10.1007/s00330-023-10504-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 10/12/2023] [Accepted: 11/01/2023] [Indexed: 12/23/2023]
Abstract
OBJECTIVES To generate and validate a prediction model based on imaging features for cancer risk of non-mass lesions (NMLs) detected on breast ultrasound (US). METHODS In this single-center study, consecutive women with 503 NMLs detected on breast US between 2012 and 2019 were retrospectively identified. The lesions were randomly assigned to the training or testing dataset with a 70/30 split. Age, symptoms, lesion size, and US features were collected. Multivariate analyses were employed to identify risk factors associated with malignancy. The predictive model was developed by using conditional inference trees (CTREE). RESULTS There were 498 patients (50.9 ± 13.29 years; range, 22-88 years) with 503 NMLs with histopathologic results or > 2-year follow-up, including 224 (44.5%) benign and 279 (55.5%) malignant lesions. At multivariate analysis, age (odds ratio (OR) = 1.08, 95% confidence interval (CI), 1.06-1.11, p < 0.001), NMLs with focal mass effect (OR = 3.03, 95% CI, 1.59-5.81, p = 0.001), indistinct glandular-fat interface (GFI) (OR = 4.23, 95% CI, 2.31-7.73, p < 0.001), geographic (OR = 3.47, 95% CI, 1.20-10.8, p = 0.022) and mottled (OR = 3.67, 95% CI, 1.32-10.21, p = 0.013) patterns, and calcifications (OR = 2.15, 95% CI, 1.16-4.01, p = 0.016) were associated with malignancy. The GFI status, architectural patterns, general morphology, and calcifications were consistently identified as the strongest US predictors of malignancy using CTREE analysis. Based on these factors, individuals were stratified into six risk groups. The predictive model showed an area under the curve of 0.797 in the testing dataset. CONCLUSION The CTREE model efficiently aids in interpreting and managing ultrasound-detected breast NMLs, overcoming BI-RADS limitations by refining cancer risk stratification. CLINICAL RELEVANCE STATEMENT The CTREE model allows for the reclassification of BI-RADS categories into subgroups with varying malignancy probabilities, thus providing a valuable enhancement to the BI-RADS assessment for the diagnosis of ultrasound-detected NMLs, with the potential to minimize unnecessary biopsies. KEY POINTS • The indistinct glandular-fat interface (GFI) status, NML with focal mass effect, geographic or mottled patterns, and calcifications are the strongest imaging predictors of malignant non-mass lesions (NMLs) detected on breast US. • A practical system has been created to categorize NMLs found in breast US; each classification is associated with a degree of diagnostic certainty. • The model may contribute to patient stratification by determining the relative likelihood of malignancy and thus support clinical decision-making and evidence-based management.
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Affiliation(s)
- Xi Wang
- Department of Ultrasound, Zhongshan Hospital Fudan University, 180 Feng-Lin Road, Shanghai, 200032, People's Republic of China
| | - Luxia Jing
- Department of Ultrasound, Zhongshan Hospital Fudan University, 180 Feng-Lin Road, Shanghai, 200032, People's Republic of China
| | - Lixia Yan
- Department of Ultrasound, Zhongshan Hospital Fudan University, 180 Feng-Lin Road, Shanghai, 200032, People's Republic of China
| | - Peilei Wang
- Department of Ultrasound, Zhongshan Hospital Fudan University, 180 Feng-Lin Road, Shanghai, 200032, People's Republic of China
| | - Chongke Zhao
- Department of Ultrasound, Zhongshan Hospital Fudan University, 180 Feng-Lin Road, Shanghai, 200032, People's Republic of China
| | - Huixiong Xu
- Department of Ultrasound, Zhongshan Hospital Fudan University, 180 Feng-Lin Road, Shanghai, 200032, People's Republic of China
| | - Hansheng Xia
- Department of Ultrasound, Zhongshan Hospital Fudan University, 180 Feng-Lin Road, Shanghai, 200032, People's Republic of China.
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Yu LF, Dai CC, Zhu LX, Xu XJ, Yan HJ, Jiang CX, Bao LY. Detection and diagnosis of automated breast ultrasound in patients with BI-RADS category 4 microcalcifications: a retrospective study. BMC Med Imaging 2024; 24:126. [PMID: 38807064 PMCID: PMC11134699 DOI: 10.1186/s12880-024-01287-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 04/30/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Automated Breast Ultrasound (AB US) has shown good application value and prospects in breast disease screening and diagnosis. The aim of the study was to explore the ability of AB US to detect and diagnose mammographically Breast Imaging Reporting and Data System (BI-RADS) category 4 microcalcifications. METHODS 575 pathologically confirmed mammographically BI-RADS category 4 microcalcifications from January 2017 to June 2021 were included. All patients also completed AB US examinations. Based on the final pathological results, analyzed and summarized the AB US image features, and compared the evaluation results with mammography, to explore the detection and diagnostic ability of AB US for these suspicious microcalcifications. RESULTS 250 were finally confirmed as malignant and 325 were benign. Mammographic findings including microcalcifications morphology (61/80 with amorphous, coarse heterogeneous and fine pleomorphic, 13/14 with fine-linear or branching), calcification distribution (189/346 with grouped, 40/67 with linear and segmental), associated features (70/96 with asymmetric shadow), higher BI-RADS category with 4B (88/120) and 4 C (73/38) showed higher incidence in malignant lesions, and were the independent factors associated with malignant microcalcifications. 477 (477/575, 83.0%) microcalcifications were detected by AB US, including 223 malignant and 254 benign, with a significantly higher detection rate for malignant lesions (x2 = 12.20, P < 0.001). Logistic regression analysis showed microcalcifications with architectural distortion (odds ratio [OR] = 0.30, P = 0.014), with amorphous, coarse heterogeneous and fine pleomorphic morphology (OR = 3.15, P = 0.037), grouped (OR = 1.90, P = 0.017), liner and segmental distribution (OR = 8.93, P = 0.004) were the independent factors which could affect the detectability of AB US for microcalcifications. In AB US, malignant calcification was more frequent in a mass (104/154) or intraductal (20/32), and with ductal changes (30/41) or architectural distortion (58/68), especially with the both (12/12). BI-RADS category results also showed that AB US had higher sensitivity to malignant calcification than mammography (64.8% vs. 46.8%). CONCLUSIONS AB US has good detectability for mammographically BI-RADS category 4 microcalcifications, especially for malignant lesions. Malignant calcification is more common in a mass and intraductal in AB US, and tend to associated with architectural distortion or duct changes. Also, AB US has higher sensitivity than mammography to malignant microcalcification, which is expected to become an effective supplementary examination method for breast microcalcifications, especially in dense breasts.
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Affiliation(s)
- Li-Fang Yu
- Department of Ultrasound, Hangzhou First People's Hospital, No.261 Huansha Road, Hangzhou, 310006, Zhejiang Province, China
| | - Chao-Chao Dai
- Department of Ultrasound, Hangzhou First People's Hospital, No.261 Huansha Road, Hangzhou, 310006, Zhejiang Province, China
| | - Luo-Xi Zhu
- Department of Ultrasound, Hangzhou First People's Hospital, No.261 Huansha Road, Hangzhou, 310006, Zhejiang Province, China
| | - Xiao-Jing Xu
- Department of Ultrasound, Hangzhou First People's Hospital, No.261 Huansha Road, Hangzhou, 310006, Zhejiang Province, China
| | - Hong-Ju Yan
- Department of Ultrasound, Hangzhou First People's Hospital, No.261 Huansha Road, Hangzhou, 310006, Zhejiang Province, China
| | - Chen-Xiang Jiang
- Department of Ultrasound, Hangzhou First People's Hospital, No.261 Huansha Road, Hangzhou, 310006, Zhejiang Province, China
| | - Ling-Yun Bao
- Department of Ultrasound, Hangzhou First People's Hospital, No.261 Huansha Road, Hangzhou, 310006, Zhejiang Province, China.
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Kwon MR, Youn I, Ko ES, Choi SH. Correlation of shear-wave elastography stiffness and apparent diffusion coefficient values with tumor characteristics in breast cancer. Sci Rep 2024; 14:7180. [PMID: 38531932 DOI: 10.1038/s41598-024-57832-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 03/22/2024] [Indexed: 03/28/2024] Open
Abstract
We aimed to investigate the correlation between shear-wave elastography (SWE) and apparent diffusion coefficient (ADC) values in breast cancer and to identify the associated characteristics. We included 91 breast cancer patients who underwent SWE and breast MRI prior to surgery between January 2016 and November 2017. We measured the lesion's mean (Emean) and maximum (Emax) elasticities of SWE and ADC values. We evaluated the correlation between SWE, ADC values and tumor size. The mean SWE and ADC values were compared for categorical variable of the pathological/imaging characteristics. ADC values showed negative correlation with Emean (r = - 0.315, p = 0.002) and Emax (r = - 0.326, p = 0.002). SWE was positively correlated with tumor size (r = 0.343-0.366, p < 0.001). A higher SWE value indicated a tendency towards a higher T stage (p < 0.001). Triple-negative breast cancer showed the highest SWE values (p = 0.02). SWE were significantly higher in breast cancers with posterior enhancement, vascularity, and washout kinetics (p < 0.02). SWE stiffness and ADC values were negatively correlated in breast cancer. SWE values correlated significantly with tumor size, and were higher in triple-negative subtype and aggressive imaging characteristics.
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Affiliation(s)
- Mi-Ri Kwon
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Inyoung Youn
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Eun Sook Ko
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, South Korea.
| | - Seon-Hyeong Choi
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Queen's U Clinic, Seoul, South Korea
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Nguyen DL, Greenwood HI, Rahbar H, Grimm LJ. Evolving Treatment Paradigms for Low-Risk Ductal Carcinoma In Situ: Imaging Needs. AJR Am J Roentgenol 2024; 222:e2330503. [PMID: 38090808 DOI: 10.2214/ajr.23.30503] [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] [Indexed: 01/05/2024]
Abstract
Ductal carcinoma in situ (DCIS) is a nonobligate precursor to invasive cancer that classically presents as asymptomatic calcifications on screening mammography. The increase in DCIS diagnoses with organized screening programs has raised concerns about overdiagnosis, while a patientcentric push for more personalized care has increased awareness about DCIS overtreatment. The standard of care for most new DCIS diagnoses is surgical excision, but nonsurgical management via active monitoring is gaining attention, and multiple clinical trials are ongoing. Imaging, along with demographic and pathologic information, is a critical component of active monitoring efforts. Commonly used imaging modalities including mammography, ultrasound, and MRI, as well as newer modalities such as contrast-enhanced mammography and dedicated breast PET, can provide prognostic information to risk stratify patients for DCIS active monitoring eligibility. Furthermore, radiologists will be responsible for closely surveilling patients on active monitoring and identifying if invasive progression occurs. Active monitoring is a paradigm shift for DCIS care, but the success or failure will rely heavily on the interpretations and guidance of radiologists.
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Affiliation(s)
- Derek L Nguyen
- Department of Diagnostic Radiology, Duke University School of Medicine, Box 3808, Durham, NC 27710
| | - Heather I Greenwood
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Habib Rahbar
- Department of Radiology, University of Washington, Seattle, WA
- Fred Hutchinson Cancer Center, Seattle, WA
| | - Lars J Grimm
- Department of Diagnostic Radiology, Duke University School of Medicine, Box 3808, Durham, NC 27710
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Kwon MR, Youn I, Lee MY, Lee HA. Diagnostic Performance of Artificial Intelligence-Based Computer-Aided Detection Software for Automated Breast Ultrasound. Acad Radiol 2024; 31:480-491. [PMID: 37813703 DOI: 10.1016/j.acra.2023.09.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/25/2023] [Accepted: 09/12/2023] [Indexed: 10/11/2023]
Abstract
RATIONALE AND OBJECTIVES This study aimed to evaluate the diagnostic performance of radiologists following the utilization of artificial intelligence (AI)-based computer-aided detection software (CAD) in detecting suspicious lesions in automated breast ultrasounds (ABUS). MATERIALS AND METHODS ABUS-detected 262 breast lesions (histopathological verification; January 2020 to December 2022) were included. Two radiologists reviewed the images and assigned a Breast Imaging Reporting and Data System (BI-RADS) category. ABUS images were classified as positive or negative using AI-CAD. The BI-RADS category was readjusted in four ways: the radiologists modified the BI-RADS category using the AI results (AI-aided 1), upgraded or downgraded based on AI results (AI-aided 2), only upgraded for positive results (AI-aided 3), or only downgraded for negative results (AI-aided 4). The AI-aided diagnostic performances were compared to radiologists. The AI-CAD-positive and AI-CAD-negative cancer characteristics were compared. RESULTS For 262 lesions (145 malignant and 117 benign) in 231 women (mean age, 52.2 years), the area under the receiver operator characteristic curve (AUC) of radiologists was 0.870 (95% confidence interval [CI], 0.832-0.908). The AUC significantly improved to 0.919 (95% CI, 0.890-0.947; P = 0.001) using AI-aided 1, whereas it improved without significance to 0.884 (95% CI, 0.844-0.923), 0.890 (95% CI, 0.852-0.929), and 0.890 (95% CI, 0.853-0.928) using AI-aided 2, 3, and 4, respectively. AI-CAD-negative cancers were smaller, less frequently exhibited retraction phenomenon, and had lower BI-RADS category. Among nonmass lesions, AI-CAD-negative cancers showed no posterior shadowing. CONCLUSION AI-CAD implementation significantly improved the radiologists' diagnostic performance and may serve as a valuable diagnostic tool.
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Affiliation(s)
- Mi-Ri Kwon
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul, 03181, Republic of Korea (M.K., I.Y., H.-A.L.)
| | - Inyoung Youn
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul, 03181, Republic of Korea (M.K., I.Y., H.-A.L.).
| | - Mi Yeon Lee
- Division of Biostatistics, Department of R&D Management, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea (M.Y.L.)
| | - Hyun-Ah Lee
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul, 03181, Republic of Korea (M.K., I.Y., H.-A.L.)
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Tsunoda H, Moon WK. Beyond BI-RADS: Nonmass Abnormalities on Breast Ultrasound. Korean J Radiol 2024; 25:134-145. [PMID: 38238012 PMCID: PMC10831301 DOI: 10.3348/kjr.2023.0769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 11/11/2023] [Accepted: 11/14/2023] [Indexed: 01/31/2024] Open
Abstract
Abnormalities on breast ultrasound (US) images which do not meet the criteria for masses are referred to as nonmass lesions. These features and outcomes have been investigated in several studies conducted by Asian researchers. However, the term "nonmass" is not included in the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) 5th edition for US. According to the Japan Association of Breast and Thyroid Sonology guidelines, breast lesions are divided into mass and nonmass. US findings of nonmass abnormalities are classified into five subtypes: abnormalities of the ducts, hypoechoic areas in the mammary glands, architectural distortion, multiple small cysts, and echogenic foci without a hypoechoic area. These findings can be benign or malignant; however, focal or segmental distributions and presence of calcifications suggest malignancy. Intraductal, invasive ductal, and lobular carcinomas can present as nonmass abnormalities. For the nonmass concept to be included in the next BI-RADS and be widely accepted in clinical practice, standardized terminologies, an interpretation algorithm, and outcome-based evidence are required for both screening and diagnostic US.
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Affiliation(s)
- Hiroko Tsunoda
- Department of Radiology, St. Luke's International Hospital, Tokyo, Japan
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
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Choi JS, Tsunoda H, Moon WK. Nonmass Lesions on Breast US: An International Perspective on Clinical Use and Outcomes. JOURNAL OF BREAST IMAGING 2024; 6:86-98. [PMID: 38243857 DOI: 10.1093/jbi/wbad077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Indexed: 01/22/2024]
Abstract
Nonmass lesions (NMLs) on breast US are defined as discrete areas of altered echotexture compared to surrounding breast tissue and lack the 3-dimensionality of a mass. They are not a component of American College of Radiology BI-RADS, but they are a finding type included in the Japan Association of Breast and Thyroid Sonology lexicon. Use of the NML finding is routine in many Asian practices, including the Samsung Medical Center and Seoul National University Hospital, and their features and outcomes have been investigated in multiple studies. Nonmass lesions are most often observed when US is used to evaluate mammographic asymmetries, suspicious calcifications, and nonmass enhancement on MRI and contrast-enhanced mammography. Nonmass lesions can be described by their echogenicity, distribution, presence or absence of associated calcifications, abnormal duct changes, architectural distortion, posterior shadowing, small cysts, and hypervascularity. Malignant lesions, especially ductal carcinoma in situ, can manifest as NMLs on US. There is considerable overlap between the US features of benign and malignant NMLs, and they also must be distinguished from normal variants. The literature indicates that NMLs with linear or segmental distribution, associated calcifications, abnormal duct changes, posterior shadowing, and hypervascularity are suggestive of malignancy, whereas NMLs with only interspersed small cysts are usually benign fibrocystic changes. In this article, we introduce the concepts of NMLs, illustrate US features suggestive of benign and malignant etiologies, and discuss our institutional approach for evaluating NMLs and an algorithm that we use to guide interpretation in clinical practice.
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Affiliation(s)
- Ji Soo Choi
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Hiroko Tsunoda
- Department of Radiology, St. Luke's International Hospital, Tokyo, Japan
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea
- Department of Radiology, Seoul National University Hospital, Seoul, South Korea
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Leung JWT. Nonmass Descriptor at Breast US to Expand Clinical Utility. JOURNAL OF BREAST IMAGING 2024; 6:99-101. [PMID: 38150381 DOI: 10.1093/jbi/wbad095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Indexed: 12/29/2023]
Affiliation(s)
- Jessica W T Leung
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Niu RL, Li JK, Wang B, Jiang Y, Li SY, Fu NQ, Liu G, Wang ZL. Combination of Breast Ultrasound With Magnetic Resonance Imaging in the Diagnosis of Non-mass-like Breast Lesions Detected on Ultrasound: A New Integrated Strategy to Improve Diagnostic Performance. ULTRASOUND IN MEDICINE & BIOLOGY 2024; 50:105-111. [PMID: 37833192 DOI: 10.1016/j.ultrasmedbio.2023.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 09/08/2023] [Accepted: 09/12/2023] [Indexed: 10/15/2023]
Abstract
OBJECTIVE The aim of the work described here was to evaluate the diagnostic performance of a new integrated strategy using breast ultrasound (US) combined with magnetic resonance imaging (MRI) to differentiate benign and malignant breast non-mass-like lesions (NMLs) detected on US. METHODS From October 2017 to January 2021, 183 NMLs detected on US that had undergone MRI examinations were included in this respective study. Pathological results were used as the reference standard. The integrated diagnostic strategy of breast US combined with MRI based on a combination of MRI Breast Imaging Reporting and Data System (BI-RADS) with discriminant sonographic indicators highly associated with malignancy was established and validated in a cohort of 61 women. The diagnostic performances of US, MRI and the combined method were calculated and compared. RESULTS In the training set, the area under the receiver operating characteristic curve (AUC), sensitivity and specificity of US, MRI and the integrated diagnostic strategy using US combined with MRI for NMLs were 0.730, 93.7% and 52.3%; 0.849, 94.7% and 75.0%; and 0.901, 92.6% and 87.5%, respectively. Compared with US or MRI alone, the integrated diagnostic strategy significantly increased the AUC (p < 0.001, p = 0.007) and specificity (p < 0.001, p = 0.034) while maintaining high sensitivity (p = 0.774, p = 0.551). In the validation set, the integrated strategy of US combined with MRI (AUC = 0.899) also had good performance compared with US (AUC = 0.728) or MRI (AUC = 0.838). CONCLUSION The integrated diagnostic strategy of US combined with MRI exhibited good performance for breast NMLs compared with either modality used alone, which can improve the diagnostic specificity while maintaining high sensitivity.
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Affiliation(s)
- Rui-Lan Niu
- Department of Ultrasound, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jun-Kang Li
- Department of Ultrasound, Chinese People's Liberation Army 63820 Hospital, Mianyang, Sichuan, China
| | - Bo Wang
- Department of Ultrasound, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Ying Jiang
- Department of Ultrasound, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Shi-Yu Li
- Department of Ultrasound, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Nai-Qin Fu
- Department of Ultrasound, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Gang Liu
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Zhi-Li Wang
- Department of Ultrasound, First Medical Center, Chinese PLA General Hospital, Beijing, China.
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Brown AL, Vijapura C, Patel M, De La Cruz A, Wahab R. Breast Cancer in Dense Breasts: Detection Challenges and Supplemental Screening Opportunities. Radiographics 2023; 43:e230024. [PMID: 37792590 DOI: 10.1148/rg.230024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
Dense breast tissue at mammography is associated with higher breast cancer incidence and mortality rates, which have prompted new considerations for breast cancer screening in women with dense breasts. The authors review the definition and classification of breast density, density assessment methods, breast cancer risk, current legislation, and future efforts and summarize trials and key studies that have affected the existing guidelines for supplemental screening. Cases of breast cancer in dense breasts are presented, highlighting a variety of modalities and specific imaging findings that can aid in cancer detection and staging. Understanding the current state of breast cancer screening in patients with dense breasts and its challenges is important to shape future considerations for care. Shifting the paradigm of breast cancer detection toward early diagnosis for women with dense breasts may be the answer to reducing the number of deaths from this common disease. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center. See the invited commentary by Yeh in this issue.
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Affiliation(s)
- Ann L Brown
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
| | - Charmi Vijapura
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
| | - Mitva Patel
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
| | - Alexis De La Cruz
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
| | - Rifat Wahab
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
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Li G, Tian H, Wu H, Huang Z, Yang K, Li J, Luo Y, Shi S, Cui C, Xu J, Dong F. Artificial intelligence for non-mass breast lesions detection and classification on ultrasound images: a comparative study. BMC Med Inform Decis Mak 2023; 23:174. [PMID: 37667320 PMCID: PMC10476370 DOI: 10.1186/s12911-023-02277-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 08/28/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND This retrospective study aims to validate the effectiveness of artificial intelligence (AI) to detect and classify non-mass breast lesions (NMLs) on ultrasound (US) images. METHODS A total of 228 patients with NMLs and 596 volunteers without breast lesions on US images were enrolled in the study from January 2020 to December 2022. The pathological results served as the gold standard for NMLs. Two AI models were developed to accurately detect and classify NMLs on US images, including DenseNet121_448 and MobileNet_448. To evaluate and compare the diagnostic performance of AI models, the area under the curve (AUC), accuracy, specificity and sensitivity was employed. RESULTS A total of 228 NMLs patients confirmed by postoperative pathology with 870 US images and 596 volunteers with 1003 US images were enrolled. In the detection experiment, the MobileNet_448 achieved the good performance in the testing set, with the AUC, accuracy, sensitivity, and specificity were 0.999 (95%CI: 0.997-1.000),96.5%,96.9% and 96.1%, respectively. It was no statistically significant compared to DenseNet121_448. In the classification experiment, the MobileNet_448 model achieved the highest diagnostic performance in the testing set, with the AUC, accuracy, sensitivity, and specificity were 0.837 (95%CI: 0.990-1.000), 70.5%, 80.3% and 74.6%, respectively. CONCLUSIONS This study suggests that the AI models, particularly MobileNet_448, can effectively detect and classify NMLs in US images. This technique has the potential to improve early diagnostic accuracy for NMLs.
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Affiliation(s)
- Guoqiu Li
- Jinan University, Guangzhou, Guangdong 510632 China
| | - Hongtian Tian
- Ultrasound Department, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University), Shenzhen, Guangdong 518020 China
| | - Huaiyu Wu
- Jinan University, Guangzhou, Guangdong 510632 China
- Ultrasound Department, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University), Shenzhen, Guangdong 518020 China
| | - Zhibin Huang
- Jinan University, Guangzhou, Guangdong 510632 China
| | - Keen Yang
- Jinan University, Guangzhou, Guangdong 510632 China
| | - Jian Li
- Ultrasound Department, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University), Shenzhen, Guangdong 518020 China
| | - Yuwei Luo
- Department of Thyroid and Breast Surgery, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University), Shenzhen, Guangdong 518020 China
| | - Siyuan Shi
- Research and development department, Illuminate, LLC, Shenzhen, Guangdong 518000 China
| | - Chen Cui
- Research and development department, Illuminate, LLC, Shenzhen, Guangdong 518000 China
| | - Jinfeng Xu
- Jinan University, Guangzhou, Guangdong 510632 China
- Ultrasound Department, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University), Shenzhen, Guangdong 518020 China
| | - Fajin Dong
- Jinan University, Guangzhou, Guangdong 510632 China
- Ultrasound Department, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University), Shenzhen, Guangdong 518020 China
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Hassan RM, Almalki YE, Basha MAA, Alduraibi SK, Aboualkheir M, Almushayti ZA, Aldhilan AS, Aly SA, Alshamy AA. The Impact of Adding Digital Breast Tomosynthesis to BI-RADS Categorization of Mammographically Equivocal Breast Lesions. Diagnostics (Basel) 2023; 13:diagnostics13081423. [PMID: 37189524 DOI: 10.3390/diagnostics13081423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 04/12/2023] [Accepted: 04/13/2023] [Indexed: 05/17/2023] Open
Abstract
Digital mammography (DM) is the cornerstone of breast cancer detection. Digital breast tomosynthesis (DBT) is an advanced imaging technique used for diagnosing and screening breast lesions, particularly in dense breasts. This study aimed to evaluate the impact of combining DBT with DM on the BI-RADS categorization of equivocal breast lesions. We prospectively evaluated 148 females with equivocal BI-RADS breast lesions (BI-RADS 0, 3, and 4) with DM. All patients underwent DBT. Two experienced radiologists analyzed the lesions. They then assigned a BI-RADS category for each lesion according to the BI-RADS 2013 lexicon, using DM, DBT, and integrated DM and DBT. We compared the results based on major radiological characteristics, BI-RADS classification, and diagnostic accuracy, using the histopathological examination of the lesions as a reference standard. The total number of lesions was 178 on DBT and 159 on DM. Nineteen lesions were discovered using DBT and were missed by DM. The final diagnoses of 178 lesions were malignant (41.6%) and benign (58.4%). Compared to DM, DBT produced 34.8% downgrading and 32% upgrading of breast lesions. Compared with DM, DBT decreased the number of BI-RADS 4 and 3. All the upgraded BI-RADS 4 lesions were confirmed to be malignant. The combination of DM and DBT improves the diagnostic accuracy of BI-RADS for evaluating and characterizing mammographic equivocal breast lesions and allows for proper BI-RADS categorization.
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Affiliation(s)
- Rania Mostafa Hassan
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt
| | - Yassir Edrees Almalki
- Division of Radiology, Department of Internal Medicine, Medical College, Najran University, Najran 61441, Saudi Arabia
| | | | | | - Mervat Aboualkheir
- Department of Radiology and Medical Imaging, College of Medicine, Taibah University, Madinah 42353, Saudi Arabia
| | - Ziyad A Almushayti
- Department of Radiology, College of Medicine, Qassim University, Buraidah 52571, Saudi Arabia
| | - Asim S Aldhilan
- Department of Radiology, College of Medicine, Qassim University, Buraidah 52571, Saudi Arabia
| | - Sameh Abdelaziz Aly
- Department of Diagnostic Radiology, Faculty of Human Medicine, Benha University, Benha 13511, Egypt
| | - Asmaa A Alshamy
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt
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Yoon GY, Choi WJ, Kim HH, Cha JH, Shin HJ, Chae EY. Outcomes and imaging features of microinvasive carcinoma and ductal carcinoma in situ: Matched cohort study. Clin Imaging 2023; 96:64-70. [PMID: 36827842 DOI: 10.1016/j.clinimag.2023.01.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 12/23/2022] [Accepted: 01/08/2023] [Indexed: 01/15/2023]
Abstract
INTRODUCTION The purpose of this study is to investigate the differences in clinical outcomes between microinvasive carcinoma (mIC) and ductal carcinoma in situ (DCIS) and compare the imaging features of both using mammography, US and MRI. MATERIALS AND METHODS This retrospective study was approved by our institutional review board. Between January 2011 and December 2013, 516 women with mIC or DCIS confirmed by surgery were included. Patients were matched with propensity score matching to compare recurrence-free survival (RFS). RFS was compared using a Cox proportional hazards model. Imaging features were also compared between the two groups. RESULTS Among 516 women, 219 mIC and 297 DCIS tumors were identified. After matching, 132 women were allocated to each group. The mean follow-up duration was 80.2 months. In the matched cohort, no statistically significant association was observed between the DCIS and mIC groups in terms of total recurrence (hazard ratio [HR]: 1.7; 95% confidence interval [CI]: 0.8-4.0; P = 0.19), local-regional recurrence (HR: 3.4; 95% CI: 0.9-12.3, P = 0.07), or contralateral recurrence (HR: 0.9; 95% CI: 0.3-2.8, P = 0.89). Non-mass lesions at US (P = 0.004), moderate or marked background parenchymal enhancement (P = 0.04), and higher peak enhancement (P = 0.02) at MRI were more commonly seen in the mIC group than in the DCIS group. CONCLUSION Microinvasive carcinomas are distinct from DCIS in terms of imaging features, but no statistically significant association in recurrence survival.
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Affiliation(s)
- Ga Young Yoon
- Department of Radiology, Gangneung Asan Hospital, University of Ulsan College of Medicine, 38 Bangdong-gil, Sacheon-myeon, Gangneung-si, Gangwon-do 25440, Republic of Korea
| | - Woo Jung Choi
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea.
| | - Hak Hee Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea
| | - Joo Hee Cha
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea
| | - Hee Jung Shin
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea
| | - Eun Young Chae
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea
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Linck PA, Boisserie-Lacroix M, Deleau F, Brocard C, Gaillard AL, Manse L, Raykova M, Depetiteville MP, Chamming's F. Images subtiles en mammographie et échographie (non-masses). IMAGERIE DE LA FEMME 2023. [DOI: 10.1016/j.femme.2023.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Hanafy MM, Ahmed AAH, Ali EA. Mammographically detected asymmetries in the era of artificial intelligence. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2023. [DOI: 10.1186/s43055-023-00979-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2023] Open
Abstract
Abstract
Background
Proper assessment of mammographically detected asymmetries is essential to avoid unnecessary biopsies and missed cancers as they may be of a benign or malignant cause. According to ACR BIRADS atlas 2013, mammographically detected asymmetries are classified into asymmetry, focal asymmetry, global asymmetry, and developing asymmetry. We aimed to assess the diagnostic performance of artificial intelligence in mammographically detected asymmetries compared to breast ultrasound as well as combined mammography and ultrasound.
Results
This study was a prospective study that comprised 51 women with breast asymmetry found on screening as well as diagnostic mammography. All participants conducted full-field digital mammography and ultrasound. Then the obtained mammographic images were processed by the artificial intelligence software system. Mammography had a sensitivity of 100%, specificity of 73%, a positive predictive value of 56.52%, a negative predictive value of 100%, and diagnostic accuracy of 80%. The results of Ultrasound revealed a sensitivity of 100.00%, a specificity of 89.47%, a positive predictive value of 76.47%, a negative predictive value of 100.00%, and an accuracy of 92.16%. Combined mammography and breast ultrasound showed a sensitivity of 100.00%, a specificity of 86.84%, a positive predictive value of 72.22%, a negative predictive value of 100.00%, and an accuracy of 90.20%. Artificial intelligence results demonstrated a sensitivity of 84.62%, a specificity of 94.74%, a positive predictive value of 48.26%, a negative predictive value of 94.47%, and an accuracy of 92.16%.
Conclusions
Adding breast ultrasound in the assessment of mammographically detected asymmetries led to better characterization, so it reduced the false-positive results and improved the specificity. Also, Artificial intelligence showed better specificity compared to mammography, breast ultrasound, and combined Mammography and ultrasound, so AI can be used to decrease unnecessary biopsies as it increases confidence in diagnosis, especially in cases with no definite ultrasound suspicious abnormality.
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Comparison of the clinical and pathological characteristics of ultrasound-guided biopsy for breast masses and non-mass lesions between 16-gauge spring-loaded core needle biopsy and 12-gauge spring-loaded vacuum-assisted biopsy. J Med Ultrason (2001) 2023; 50:205-212. [PMID: 36645627 DOI: 10.1007/s10396-022-01279-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 12/07/2022] [Indexed: 01/17/2023]
Abstract
PURPOSE To retrospectively compare the clinical and pathological characteristics of breast masses and non-mass lesions that underwent ultrasound (US)-guided 16-gauge spring-loaded core needle biopsy (CNB) or 12-gauge spring-loaded vacuum-assisted biopsy (VAB). METHODS We retrospectively compared the results from US-guided diagnostic breast biopsy performed with a 16-gauge CNB (Magnum™) or a 12-gauge VAB (Celero®). The patients' backgrounds and pathological features for each device were examined. RESULTS In 453 patients with 500 lesions, 373 lesions underwent CNB and 127 underwent VAB. The positive biopsy rate (positive predictive value 3) was significantly higher for VAB (92/127; 72.4%) than for CNB (231/373; 61.9%) (P = 0.032). Non-mass lesions were biopsied more frequently with VAB (57/127; 47.4%) than with CNB (27/378; 7.14%) (P = 0.000). The upgrade rate from high-risk to malignant lesions was significantly higher for CNB (5/19; 26.3%) than for VAB (1/8; 12.5%) (P = 0.043). There were five (1.34%) specimen failures with CNB and one (0.78%) with VAB, 18 (4.82%) re-biopsies with CNB and three (2.36%) with VAB, and 11/21 (52.4%) upgrades from ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) with CNB and 11/30 (36.7%) with VAB. Although these rates tended to be higher with CNB than with VAB, the difference was not significant. CONCLUSION Although VAB had a significantly higher rate of non-mass lesion biopsies, the upgrade rate from high-risk to malignant lesions was significantly lower for VAB than for CNB. US-guided 12-gauge spring-loaded VAB may be more appropriate for biopsy of non-mass lesions.
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Choi JS. [Breast Imaging Reporting and Data System (BI-RADS): Advantages and Limitations]. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2023; 84:3-14. [PMID: 36818717 PMCID: PMC9935970 DOI: 10.3348/jksr.2022.0142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 12/05/2022] [Accepted: 12/13/2022] [Indexed: 06/18/2023]
Abstract
Breast Imaging Reporting and Data System (BI-RADS) is a communication and data tracking system that standardizes and controls the quality of reporting by presenting lexicon descriptors, assessment categories, and recommendations for managing breast lesions. Using standardized terminology recommended by BI-RADS, radiologists can concisely and reproducibly communicate breast imaging results to clinicians. They can also provide the estimated malignant probability of the lesions found and guide management for them by determining the final assessment category. The limitations of BI-RADS 5th edition currently in use are that there are some areas for which standardized terminologies still need to be established, and that the diagnostic criteria of MRI assessment categories 3 and 4 are ambiguous compared to those for mammography or ultrasound. The next revision of BI-RADS is expected to include solutions for overcoming current limitations.
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Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value. PLoS One 2022; 17:e0278299. [PMID: 36449518 PMCID: PMC9710769 DOI: 10.1371/journal.pone.0278299] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 11/14/2022] [Indexed: 12/05/2022] Open
Abstract
PURPOSE To investigate the positive predictive value of ultrasound classification of non-mass breast lesions (NMLs) following breast imaging reporting and data system (BI-RADS), and enhance understanding of NMLs. MATERIALS AND METHODS Fifty-nine women with 59 ultrasound-detected breast NMLs were finally enrolled. The ultrasound (US) features of breast NMLs were analyzed; the incidence of malignant NMLs was calculated; the malignancy risk stratification of US for breast NMLs was established using BI-RADS. RESULTS The incidence of malignant NMLs was 4.59% of all breast carcinoma. Non-ductal hypoechoic area, microcalcifications and posterior shadowing are the main US features of malignant NMLs, and there were significant differences between malignant and benign NMLs for microcalcifications and posterior shadowing. Taking BI-RADS 4B as a cutoff value, the sensitivity, specificity, area under the receiver operating characteristic curve (AUC), positive and negative predictive values, and odds ratio of the BI-RADS category were 82.98%,41.67%,0.62,84.78%,38.46% and 3.48, respectively. CONCLUSIONS Stratifying the malignancy risk of breast NMLs using the BI-RADS the sensitivity and positive and predictive value are promising, but the likelihood of malignancy of malignant NMLs is underestimated, and that of benign NMLs is overestimated. The solution may be that to separate NMLs from breast masses and use different malignancy risk stratification protocols.
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Zhang J, Cai L, Pan X, Chen L, Chen M, Yan D, Liu J, Luo L. Comparison and risk factors analysis of multiple breast cancer screening methods in the evaluation of breast non-mass-like lesions. BMC Med Imaging 2022; 22:202. [PMID: 36404330 PMCID: PMC9677910 DOI: 10.1186/s12880-022-00921-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 10/26/2022] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVE To compare multiple breast cancer screening methods for evaluating breast non-mass-like lesions (NMLs), and investigate new best screening method for breast non-mass-like lesions and the value of the lexicon of ACR BI-RADS in NML evaluation. METHODS This retrospective study examined 253 patients aged 24-68 years who were diagnosed with breast NMLs and described the lexicon of ACR BI-RADS from April 2017 to December 2019. All lesions were evaluated by HHUS, MG, and ABUS to determine BI-RADS category, and underwent pathological examination within six months or at least 2 years of follow-up. The sensitivity, specificity, accuracy, positive predictive values (PPV), and negative predictive values (NPV) of MG, HHUS and ABUS in the prediction of malignancy were compared. Independent risk factors for malignancy were assessed using non-conditional logistic regression. RESULTS HHUS, MG and ABUS findings significantly differed between benign and malignant breast NML, including internal echo, hyperechoic spot, peripheral blood flow, internal blood flow, catheter change, peripheral change, coronal features of ABUS, and structural distortion, asymmetry, and calcification in MG. ABUS is superior to MG and HHUS in sensitivity, specificity, PPV, NPV, as well as in evaluating the necessity of biopsy and accuracy in identifying malignancy. MG was superior to HHUS in specificity, PPV, and accuracy in evaluating the need for biopsy. CONCLUSIONS ABUS was superior to HHUS and MG in evaluating the need for biopsy in breast NMLs. Compared to each other, HHUS and MG had their own relative advantages. Internal blood flow, calcification, and coronal plane feature was independent risk factors in NMLs Management, and different screening methods had their own advantages in NML management. The lexicon of ACR BI-RADS could be used not only in the evaluation of mass lesions, but also in the evaluation of NML.
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Affiliation(s)
- Jianxing Zhang
- grid.258164.c0000 0004 1790 3548Department of Medical Imaging Center, The First Affiliated Hospital, Jinan University, No. 613, Huangpu Road West, Tianhe District, Guangzhou, 510630 Guangdong Province China ,grid.411866.c0000 0000 8848 7685Department of Ultrasound, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, No. 111, Dade Road, Yuexiu District, Guangzhou, 510120 Guangdong Province China
| | - Lishan Cai
- grid.411866.c0000 0000 8848 7685Department of Ultrasound, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, No. 16, Jichang Road, Baiyun District, Guangzhou, 510403 Guangdong Province China
| | - Xiyang Pan
- grid.411866.c0000 0000 8848 7685Department of Ultrasound, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, No. 111, Dade Road, Yuexiu District, Guangzhou, 510120 Guangdong Province China
| | - Ling Chen
- grid.411866.c0000 0000 8848 7685Department of Ultrasound, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, No. 111, Dade Road, Yuexiu District, Guangzhou, 510120 Guangdong Province China
| | - Miao Chen
- grid.411866.c0000 0000 8848 7685Department of Ultrasound, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, No. 111, Dade Road, Yuexiu District, Guangzhou, 510120 Guangdong Province China
| | - Dan Yan
- grid.411866.c0000 0000 8848 7685Department of Ultrasound, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, No. 111, Dade Road, Yuexiu District, Guangzhou, 510120 Guangdong Province China
| | - Jia Liu
- grid.411866.c0000 0000 8848 7685Department of Ultrasound, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, No. 111, Dade Road, Yuexiu District, Guangzhou, 510120 Guangdong Province China
| | - Liangping Luo
- grid.258164.c0000 0004 1790 3548Department of Medical Imaging Center, The First Affiliated Hospital, Jinan University, No. 613, Huangpu Road West, Tianhe District, Guangzhou, 510630 Guangdong Province China
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Armani M, Lissavarid É, Dyien B, Manceau J, Bereby Kahane M, Malhaire C, Tardivon A. Lésions classées ACR3 en IRM mammaire. IMAGERIE DE LA FEMME 2022. [DOI: 10.1016/j.femme.2022.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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22
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Feliciano-Rivera YZ, Net J, Velamuri S, Pluguez-Turull C, Yepes MM. The Challenge of Digital Breast Tomosynthesis-Detected Architectural Distortion of the Breast: Inter-reader Variability and Imaging Characteristics That May Improve Positive Predictive Value. JOURNAL OF BREAST IMAGING 2022; 4:263-272. [PMID: 38416967 DOI: 10.1093/jbi/wbac002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Indexed: 03/01/2024]
Abstract
OBJECTIVE To compare readers' performances when detecting architectural distortion (AD) on digital breast tomosynthesis (DBT). To determine the risk of malignancy of DBT with synthetic mammogram (SM)-detected AD and evaluate imaging features that are associated with malignancy risk. METHODS This IRB-approved retrospective review included all cases of DBT-detected AD that were recommended for biopsy from October 2013 to July 2019. Cases were reviewed by three breast radiologists and the overall agreement between radiologists was calculated. Medical records were reviewed for pathological outcomes and imaging findings. Statistical analyses used were Cohen's kappa and its 95% confidence interval, and one-way analysis of variance. RESULTS A total of 172 lesions were included. The overall agreement for the presence of AD in our study was fair (0.253). The majority (20/36, 55.5%) of the malignant ADs were associated with asymmetries (13/36, 36.1%), calcifications (4/36, 11.1%), or both (3/36, 8.3%), compared to nonmalignant ADs (40/136, 31.0%; P = 0.038). The positive predictive value (PPV) of DBT with SM-detected AD for malignancy was 21.8% (36/165), 18.8% (18/96) for DBT-detected AD, and 26.0% (18/69) for SM-detected AD, although the difference was not statistically significant (P = 0.258). A breast MRI correlate was identified for all malignant AD lesions (17/17, 100.0%; P = 0.004). CONCLUSION The detection of AD remains a challenging task for radiologists, with moderate-to-fair interobserver agreement. With a PPV for malignancy of 21.8%, percutaneous biopsy and subsequent pathology-imaging correlation are necessary for AD to exclude the possibility of malignancy.
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Affiliation(s)
| | - Jose Net
- University of Miami Miller School of Medicine, Department of Radiology, Miami, FL, USA
| | - Sriram Velamuri
- University of Miami Miller School of Medicine, Department of Radiology, Miami, FL, USA
| | - Cedric Pluguez-Turull
- University of Miami Miller School of Medicine, Department of Radiology, Miami, FL, USA
| | - Monica M Yepes
- University of Miami Miller School of Medicine, Department of Radiology, Miami, FL, USA
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Sefidbakht S, Haseli S, Khalili N, Bazojoo V, Keshavarz P, Zeinali-Rafsanjani B. Can shear wave elastography be utilized as an additional tool for the assessment of non-mass breast lesions? ULTRASOUND (LEEDS, ENGLAND) 2022; 30:44-51. [PMID: 35173778 PMCID: PMC8841944 DOI: 10.1177/1742271x21998721] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 02/06/2021] [Indexed: 02/03/2023]
Abstract
INTRODUCTION We aimed to describe shear wave elastography parameters of non-mass lesions of the breast and to assess the measures of diagnostic accuracy of shear wave elastography in the differentiation of non-mass lesions compared with conventional ultrasound, using histopathologic results as the reference standard. METHODS This retrospective study included breast ultrasound-detected non-mass lesions with a confirmed pathologic diagnosis during a two-year study period. B-mode ultrasound and shear wave elastography were performed for all lesions before biopsy. Ultrasound features, shear wave elastography parameters (mean elasticity and maximum stiffness color), as well as Breast Imaging-Reporting and Data System categories were recorded for each lesion. Measures of diagnostic accuracy of ultrasound and ultrasound + shear wave elastography were also assessed. RESULTS From a total of 567 breast lesions requiring core-needle biopsy, 49 (8.6%) were considered as non-mass lesions. Based on histopathologic reports, 32 patients (65.3%) had non-high-risk benign lesions, five (10.2%) had high-risk benign lesions, five (10.2%) had ductal carcinoma in situ, and seven (14.3%) had invasive carcinoma. There was no significant difference in patients' age and palpability between benign and malignant lesions (p = 0.16 and p = 0.12, respectively). Mean elasticity values and Breast Imaging-Reporting and Data System categories were significantly higher among malignant lesions compared with benign non-mass lesions (both p < 0.001). Furthermore, the addition of shear wave elastography to grayscale ultrasound increased the specificity, positive predictive value, and diagnostic accuracy. CONCLUSION The complementary use of shear wave elastography with conventional ultrasound might help in the differentiation of non-mass breast lesions and has the potential to decrease the frequency of unnecessary biopsies performed for benign non-mass lesions.
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Affiliation(s)
- Sepideh Sefidbakht
- Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Sara Haseli
- Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran,Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran,Sara Haseli, Shahid Beheshti University of Medical Sciences, Tehran 19839-6311, Iran.
| | - Neda Khalili
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Vahid Bazojoo
- Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Pedram Keshavarz
- Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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Goto M, Nakano S, Saito M, Banno H, Ito Y, Ido M, Ando T, Kousaka J, Fujii K, Suzuki K. Evaluation of an MRI/US fusion technique for the detection of non-mass enhancement of breast lesions detected by MRI yet occult on conventional B-mode second-look US. J Med Ultrason (2001) 2022; 49:269-278. [PMID: 35083535 DOI: 10.1007/s10396-021-01175-2] [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: 07/06/2021] [Accepted: 10/08/2021] [Indexed: 12/01/2022]
Abstract
PURPOSE The aim of this study was to verify the utility of second-look ultrasound (US) using real-time virtual sonography (RVS), a magnetic resonance imaging (MRI)/US fusion technique, in identifying MRI-detected breast lesions with non-mass enhancement (NME). METHODS Consecutive patients who had one or more NME lesions detected by MRI yet occult on the subsequent second-look US in conventional B (cB)-mode imaging were enrolled in the study between June 2015 and April 2020. Supine MRI of the lesions was performed and, using its data, second-look US using RVS was performed. RESULTS Twenty patients with 21 NME lesions were included. The overall median lesion size on prone MRI was 23 mm (range, 5-63 mm). Supine MRI identified all the 21 NME lesions, and second-look US using RVS successfully detected 18 (86%) of them. RVS-guided biopsy was performed for histopathological evaluation, showing that nine of the 18 lesions were benign and the other nine malignant. Of the nine malignant lesions, two (22%) were invasive cancer and seven (78%) were ductal carcinoma in situ. In four of five patients who underwent prone MRI for preoperative evaluation, the diagnosis was benign and surgery was conducted as originally planned. In the other patient, the diagnosis was malignant and contralateral breast-conserving surgery was added. Three (14%) of the 21 NME lesions had no RVS correlates and were judged to be benign after 24-month follow-up. CONCLUSION The results suggest that second-look US using RVS helps identify MRI-detected NME lesions that are occult on cB-mode second-look US.
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Affiliation(s)
- Manami Goto
- Division of Breast and Endocrine Surgery, Department of Surgery, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
| | - Shogo Nakano
- Division of Breast and Endocrine Surgery, Department of Surgery, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan.
| | - Masayuki Saito
- Division of Breast and Endocrine Surgery, Department of Surgery, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
| | - Hirona Banno
- Division of Breast and Endocrine Surgery, Department of Surgery, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
| | - Yukie Ito
- Division of Breast and Endocrine Surgery, Department of Surgery, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
| | - Mirai Ido
- Division of Breast and Endocrine Surgery, Department of Surgery, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
| | - Takahito Ando
- Division of Breast and Endocrine Surgery, Department of Surgery, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
| | - Junko Kousaka
- Division of Breast and Endocrine Surgery, Department of Surgery, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
| | - Kimihito Fujii
- Division of Breast and Endocrine Surgery, Department of Surgery, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
| | - Kojiro Suzuki
- Department of Radiology, Aichi Medical University, 1-1 Yazakokarimata, Nagakute City, Aichi, 480-1195, Japan
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Yoon GY, Cha JH, Kim HH, Bang MS, Lee HJ, Gong G. Comparison of the Imaging Features of Lobular Carcinoma In Situ and Invasive Lobular Carcinoma of the Breast. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2021; 82:1231-1245. [PMID: 36238391 PMCID: PMC9432355 DOI: 10.3348/jksr.2020.0148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 10/23/2020] [Accepted: 01/14/2021] [Indexed: 11/15/2022]
Affiliation(s)
- Ga Young Yoon
- Department of Radiology, Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Korea
| | - Joo Hee Cha
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Hak Hee Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Min Seo Bang
- Department of Radiology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea
| | - Hee Jin Lee
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Gyungyub Gong
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
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