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Magni V, Cozzi A, Muscogiuri G, Benedek A, Rossini G, Fanizza M, Di Giulio G, Sardanelli F. Background parenchymal enhancement on contrast-enhanced mammography: associations with breast density and patient's characteristics. LA RADIOLOGIA MEDICA 2024; 129:1303-1312. [PMID: 39060886 DOI: 10.1007/s11547-024-01860-5] [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: 03/16/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024]
Abstract
PURPOSE To evaluate if background parenchymal enhancement (BPE) on contrast-enhanced mammography (CEM), graded according to the 2022 CEM-dedicated Breast Imaging Reporting and Data System (BI-RADS) lexicon, is associated with breast density, menopausal status, and age. METHODS This bicentric retrospective analysis included CEM examinations performed for the work-up of suspicious mammographic findings. Three readers independently and blindly evaluated BPE on recombined CEM images and breast density on low-energy CEM images. Inter-reader reliability was estimated using Fleiss κ. Multivariable binary logistic regression was performed, dichotomising breast density and BPE as low (a/b BI-RADS categories, minimal/mild BPE) and high (c/d BI-RADS categories, moderate/marked BPE). RESULTS A total of 200 women (median age 56.8 years, interquartile range 50.5-65.6, 140/200 in menopause) were included. Breast density was classified as a in 27/200 patients (13.5%), as b in 110/200 (55.0%), as c in 52/200 (26.0%), and as d in 11/200 (5.5%), with moderate inter-reader reliability (κ = 0.536; 95% confidence interval [CI] 0.482-0.590). BPE was minimal in 95/200 patients (47.5%), mild in 64/200 (32.0%), moderate in 25/200 (12.5%), marked in 16/200 (8.0%), with substantial inter-reader reliability (κ = 0.634; 95% CI 0.581-0.686). At multivariable logistic regression, premenopausal status and breast density were significant positive predictors of high BPE, with adjusted odds ratios of 6.120 (95% CI 1.847-20.281, p = 0.003) and 2.416 (95% CI 1.095-5.332, p = 0.029) respectively. CONCLUSION BPE on CEM is associated with well-established breast cancer risk factors, being higher in women with higher breast density and premenopausal status.
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Affiliation(s)
- Veronica Magni
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133, Milan, Italy.
- Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy.
| | - Andrea Cozzi
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097, San Donato Milanese, Italy
- Imaging Institute of Southern Switzerland (IIMSI), Ente Ospedaliero Cantonale, Via Tesserete 46, 6900, Lugano, Switzerland
| | - Giulia Muscogiuri
- Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy
| | - Adrienn Benedek
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097, San Donato Milanese, Italy
| | - Gabriele Rossini
- Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy
| | - Marianna Fanizza
- Department of Breast Radiology, Fondazione IRCCS Policlinico San Matteo, Viale Camillo Golgi 19, 27100, Pavia, Italy
| | - Giuseppe Di Giulio
- Department of Breast Radiology, Fondazione IRCCS Policlinico San Matteo, Viale Camillo Golgi 19, 27100, Pavia, Italy
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133, Milan, Italy
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097, San Donato Milanese, Italy
- Lega Italiana per la Lotta contro i Tumori (LILT) Milano Monza Brianza, Piazzale Paolo Gorini 22, 20133, Milan, Italy
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Mann RM, Longo V. Contrast-enhanced Mammography versus MR Imaging of the Breast. Radiol Clin North Am 2024; 62:643-659. [PMID: 38777540 DOI: 10.1016/j.rcl.2024.02.003] [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: 05/25/2024]
Abstract
Breast MR imaging and contrast-enhanced mammography (CEM) are both techniques that employ intravenously injected contrast agent to assess breast lesions. This approach is associated with a very high sensitivity for malignant lesions that typically exhibit rapid enhancement due to the leakiness of neovasculature. CEM may be readily available at the breast imaging department and can be performed on the spot. Breast MR imaging provides stronger enhancement than the x-ray-based techniques and offers higher sensitivity. From a patient perspective, both modalities have their benefits and downsides; thus, patient preference could also play a role in the selection of the imaging technique.
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Affiliation(s)
- Ritse M Mann
- Department of Imaging, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Valentina Longo
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiodiagnostica Presidio Columbus, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, Rome 00168, Italy
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Ripaud E, Jailin C, Quintana GI, Milioni de Carvalho P, Sanchez de la Rosa R, Vancamberg L. Deep-learning model for background parenchymal enhancement classification in contrast-enhanced mammography. Phys Med Biol 2024; 69:115013. [PMID: 38657641 DOI: 10.1088/1361-6560/ad42ff] [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: 01/12/2024] [Accepted: 04/24/2024] [Indexed: 04/26/2024]
Abstract
Background.Breast background parenchymal enhancement (BPE) is correlated with the risk of breast cancer. BPE level is currently assessed by radiologists in contrast-enhanced mammography (CEM) using 4 classes: minimal, mild, moderate and marked, as described inbreast imaging reporting and data system(BI-RADS). However, BPE classification remains subject to intra- and inter-reader variability. Fully automated methods to assess BPE level have already been developed in breast contrast-enhanced MRI (CE-MRI) and have been shown to provide accurate and repeatable BPE level classification. However, to our knowledge, no BPE level classification tool is available in the literature for CEM.Materials and methods.A BPE level classification tool based on deep learning has been trained and optimized on 7012 CEM image pairs (low-energy and recombined images) and evaluated on a dataset of 1013 image pairs. The impact of image resolution, backbone architecture and loss function were analyzed, as well as the influence of lesion presence and type on BPE assessment. The evaluation of the model performance was conducted using different metrics including 4-class balanced accuracy and mean absolute error. The results of the optimized model for a binary classification: minimal/mild versus moderate/marked, were also investigated.Results.The optimized model achieved a 4-class balanced accuracy of 71.5% (95% CI: 71.2-71.9) with 98.8% of classification errors between adjacent classes. For binary classification, the accuracy reached 93.0%. A slight decrease in model accuracy is observed in the presence of lesions, but it is not statistically significant, suggesting that our model is robust to the presence of lesions in the image for a classification task. Visual assessment also confirms that the model is more affected by non-mass enhancements than by mass-like enhancements.Conclusion.The proposed BPE classification tool for CEM achieves similar results than what is published in the literature for CE-MRI.
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Grażyńska A, Niewiadomska A, Owczarek AJ, Winder M, Hołda J, Zwolińska O, Barczyk-Gutkowska A, Modlińska S, Lorek A, Kuźbińska A, Steinhof-Radwańska K. Comparison of the effectiveness of contrast-enhanced mammography in detecting malignant lesions in patients with extremely dense breasts compared to the all-densities population. Pol J Radiol 2024; 89:e240-e248. [PMID: 38938658 PMCID: PMC11210381 DOI: 10.5114/pjr/186180] [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: 12/28/2023] [Accepted: 03/17/2024] [Indexed: 06/29/2024] Open
Abstract
Purpose To assess the effectiveness of contrast-enhanced mammography (CEM) recombinant images in detecting malignant lesions in patients with extremely dense breasts compared to the all-densities population. Material and methods 792 patients with 808 breast lesions, in whom the final decision on core-needle biopsy was made based on CEM, and who received the result of histopathological examination, were qualified for a single-centre, retrospective study. Patient electronic records and imaging examinations were reviewed to establish demographics, clinical and imaging findings, and histopathology results. The CEM images were reassessed and assigned to the appropriate American College of Radiology (ACR) density categories. Results Extremely dense breasts were present in 86 (10.9%) patients. Histopathological examination confirmed the presence of malignant lesions in 52.6% of cases in the entire group of patients and 43% in the group of extremely dense breasts. CEM incorrectly classified the lesion as false negative in 16/425 (3.8%) cases for the whole group, and in 1/37 (2.7%) cases for extremely dense breasts. The sensitivity of CEM for the group of all patients was 96.2%, specificity - 60%, positive predictive values (PPV) - 72.8%, and negative predictive values (NPV) - 93.5%. In the group of patients with extremely dense breasts, the sensitivity of the method was 97.3%, specificity - 59.2%, PPV - 64.3%, and NPV - 96.7%. Conclusions CEM is characterised by high sensitivity and NPV in detecting malignant lesions regardless of the type of breast density. In patients with extremely dense breasts, CEM could serve as a complementary or additional examination in the absence or low availability of MRI.
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Affiliation(s)
- Anna Grażyńska
- Department of Radiology and Nuclear Medicine, Medical University of Silesia, Katowice, Poland
| | - Agnieszka Niewiadomska
- Department of Radiology and Nuclear Medicine, Medical University of Silesia, Katowice, Poland
| | - Aleksander J. Owczarek
- Health Promotion and Obesity Management Unit, Department of Pathophysiology, Medical University of Silesia, Katowice, Poland
| | - Mateusz Winder
- Department of Radiology and Nuclear Medicine, Medical University of Silesia, Katowice, Poland
| | - Jakub Hołda
- Department of Radiology and Nuclear Medicine, Medical University of Silesia, Katowice, Poland
- Department of Anatomy, Jagiellonian University Medical College, Cracow, Poland
| | - Olga Zwolińska
- Department of Radiology and Nuclear Medicine, Medical University of Silesia, Katowice, Poland
| | - Anna Barczyk-Gutkowska
- Department of Radiology and Nuclear Medicine, Medical University of Silesia, Katowice, Poland
| | - Sandra Modlińska
- Department of Radiology and Nuclear Medicine, Medical University of Silesia, Katowice, Poland
| | - Andrzej Lorek
- Department of Oncological Surgery, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Katowice, Poland
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Goh Y, Quek ST, Pillay P, Chou CP. Evaluation of architectural distortion with contrast-enhanced mammography. Clin Radiol 2024; 79:163-169. [PMID: 38114374 DOI: 10.1016/j.crad.2023.11.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 11/20/2023] [Accepted: 11/21/2023] [Indexed: 12/21/2023]
Abstract
Architectural distortion (AD) is the third most common abnormality detected on mammograms. In the absence of an accurate non-invasive tool to evaluate ADs, clinical management often requires surgical excision for histological diagnosis. This problem is expected to worsen with the growing use of digital breast tomosynthesis (DBT) and the resultant increasing detection of ADs. There is therefore a great clinical need for a diagnostic imaging tool to complement non-enhanced mammography for the evaluation of AD. Contrast-enhanced mammography (CEM) is an emerging breast imaging method that uses contrast media and the principle of dual-energy subtraction to evaluate vascularity of suspicious breast lesions. CEM, a cost-effective alternative to breast magnetic resonance imaging (MRI), can be used to evaluate AD by juxtaposing CEM images with non-enhanced mammograms for comparison. In this review, the authors aim to provide readers with an overview of the interpretation of AD on CEM using imaging examples. Relevant imaging features of CEM and their respective significance will be matched with information from a literature review. Finally, the authors would like to highlight the added value of CEM in relevant clinical applications in the assessment of AD.
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Affiliation(s)
- Y Goh
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd 119074, Singapore
| | - S T Quek
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd 119074, Singapore
| | - P Pillay
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd 119074, Singapore
| | - C-P Chou
- Kaohsiung Veterans General Hospital, Radiology Department, No. 386, Dazhong 1st Rd, Zuoying Dist., Kaohsiung City 81362, Taiwan, ROC.
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Lorente-Ramos RM, Azpeitia-Armán J, Oliva-Fonte C, Pérez-Bartolomé A, Azpeitia Hernández J. Contrast-enhanced Mammography Artifacts and Pitfalls: Tips and Tricks to Avoid Misinterpretation. Radiographics 2023; 43:e230021. [PMID: 37792595 DOI: 10.1148/rg.230021] [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
Contrast-enhanced mammography (CEM) involves addition of intravenous iodinated contrast material at digital mammography, thus increasing the ability to detect breast cancer owing to tumor contrast enhancement. After image acquisition, interpretation includes careful assessment of the technique, artifacts, and pitfalls and reporting with a standard lexicon category and appropriate follow-up recommendations. Artifacts and pitfalls that may cause image misinterpretation should be detected and distinguished from pathologic conditions. Different artifacts apparent on CEM images are usually caused during image acquisition and include CEM-specific and contrast agent-related artifacts, apart from the typical digital mammography artifacts. The pitfalls are related to technical and diagnostic difficulties. One disadvantage of CEM that MRI does not have is a technical factor related to a mammography technique that consists of blind spots that may not be included in the imaging field of mammography views, including the axilla, medial region of the breast, or areas close to the breast wall. Normal breast tissue enhancement called background parenchymal enhancement is also present at CEM and may affect interpretation performance. Diagnostic pitfalls are caused by minimally enhancing lesions, such as invasive lobular carcinomas and mucinous carcinomas, which are difficult to detect with CEM, resulting in false-negative findings. Benign lesions can show enhancement at CEM and represent false-positive lesions that should also be recognized. The authors discuss image interpretation of CEM studies and focus on the artifacts and pitfalls that may be encountered. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Rosa M Lorente-Ramos
- From the Department of Radiology, Unidad Central de Radiodiagnóstico de la CAM, Hospital Universitario Infanta Leonor, Av Gran Vía del Este 80, Madrid 28031, Spain (R.M.L.R., J.A.A., C.O.F., A.P.B.); Department of Radiology, Universidad Complutense de Madrid-Facultad de Medicina, Madrid, Spain (J.A.A.); and Department of Radiology, Hospital Central de la Defensa Gómez Ulla, Madrid, Spain (J.A.H.)
| | - Javier Azpeitia-Armán
- From the Department of Radiology, Unidad Central de Radiodiagnóstico de la CAM, Hospital Universitario Infanta Leonor, Av Gran Vía del Este 80, Madrid 28031, Spain (R.M.L.R., J.A.A., C.O.F., A.P.B.); Department of Radiology, Universidad Complutense de Madrid-Facultad de Medicina, Madrid, Spain (J.A.A.); and Department of Radiology, Hospital Central de la Defensa Gómez Ulla, Madrid, Spain (J.A.H.)
| | - Carlos Oliva-Fonte
- From the Department of Radiology, Unidad Central de Radiodiagnóstico de la CAM, Hospital Universitario Infanta Leonor, Av Gran Vía del Este 80, Madrid 28031, Spain (R.M.L.R., J.A.A., C.O.F., A.P.B.); Department of Radiology, Universidad Complutense de Madrid-Facultad de Medicina, Madrid, Spain (J.A.A.); and Department of Radiology, Hospital Central de la Defensa Gómez Ulla, Madrid, Spain (J.A.H.)
| | - Ana Pérez-Bartolomé
- From the Department of Radiology, Unidad Central de Radiodiagnóstico de la CAM, Hospital Universitario Infanta Leonor, Av Gran Vía del Este 80, Madrid 28031, Spain (R.M.L.R., J.A.A., C.O.F., A.P.B.); Department of Radiology, Universidad Complutense de Madrid-Facultad de Medicina, Madrid, Spain (J.A.A.); and Department of Radiology, Hospital Central de la Defensa Gómez Ulla, Madrid, Spain (J.A.H.)
| | - Javier Azpeitia Hernández
- From the Department of Radiology, Unidad Central de Radiodiagnóstico de la CAM, Hospital Universitario Infanta Leonor, Av Gran Vía del Este 80, Madrid 28031, Spain (R.M.L.R., J.A.A., C.O.F., A.P.B.); Department of Radiology, Universidad Complutense de Madrid-Facultad de Medicina, Madrid, Spain (J.A.A.); and Department of Radiology, Hospital Central de la Defensa Gómez Ulla, Madrid, Spain (J.A.H.)
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Xu C, Jiang M, Lin F, Zhang K, Xie H, Lv W, Ji H, Mao N. Qualitative assessments of density and background parenchymal enhancement on contrast-enhanced spectral mammography associated with breast cancer risk in high-risk women. Br J Radiol 2023; 96:20220051. [PMID: 37227804 PMCID: PMC10392639 DOI: 10.1259/bjr.20220051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 04/26/2023] [Accepted: 05/04/2023] [Indexed: 05/27/2023] Open
Abstract
OBJECTIVE To investigate the correlation between the risk of breast cancer for high-risk females and the density and background parenchymal enhancement (BPE) on contrast-enhanced spectral mammography (CESM). METHODS Females at high-risk, without breast cancer history and received CESM from July 2016 to December 2017 were retrospectively enrolled. The longest follow-up time was 4.5 years, and patients who developed breast cancer with maximized follow-up time were classified as cancer cohort, while females who did not develop breast cancer were categorized as control cohort. These two cohorts were one-to-one matched in age, family and/or genetic history of breast cancer, menopausal status and BRCA status. The density and BPE at CESM imaging were assessed. Conditional logistic regression was applied to evaluate the relationship between imaging features and breast cancer risk. RESULTS During the follow-up interval, 90 women at high-risk without history of breast cancer were newly diagnosed. Compared with minimal BPE, increasing BPE levels were associated with the risk of breast cancer among high-risk females in a time interval of 4.5 years (mild: odds ratio [OR]=3.2, p = 0.001; moderate: OR = 4.0, p = 0.002; marked: OR = 11.2, p < 0.001). In addition, females with mild, moderate or marked BPE were four times more likely to be diagnosed with breast cancer than females with minimal BPE in a time interval of 4.5 years (OR = 4.0, p < 0.001). CONCLUSION Qualitative CESM BPE assessment may be useful in the prediction of breast cancer risk among high-risk females. ADVANCES IN KNOWLEDGE • Qualitative CESM BPE assessment may be useful in the prediction of breast cancer risk among high-risk women during the follow-up period of 4.5 years. • The significance of breast density as an independent risk factor is not fully established for high-risk women during the follow-up period of 4.5 years.
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Affiliation(s)
- Cong Xu
- Physical Examination Center, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Meiping Jiang
- Department of Ultrasound, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Fan Lin
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Kun Zhang
- Department of Breast Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Wei Lv
- Physical Examination Center, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Haixia Ji
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
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Wang S, Sun Y, You C, Jiang T, Yang M, Shen X, Qian M, Duan S, Lynn HS, Li R, Gu Y. Association of Clinical Factors and Degree of Early Background Parenchymal Enhancement on Contrast-Enhanced Mammography. AJR Am J Roentgenol 2023; 221:45-55. [PMID: 36695647 DOI: 10.2214/ajr.22.28769] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND. Background parenchymal enhancement (BPE) may impact contrast-enhanced mammography (CEM) interpretation, although factors influencing the degree of BPE on CEM are poorly understood. OBJECTIVE. The purpose of our study was to evaluate relationships between clinical factors and the degree of early BPE on CEM. METHODS. This retrospective study included 207 patients (median age, 46 years) who underwent CEM between April 2020 and September 2021. Two radiologists independently assessed the degree of BPE on CEM as minimal, mild, moderate, or marked on the basis of two criteria (criterion 1, using the first of four obtained views; criterion 2, using the first two of four obtained views). The radiologists reached consensus for breast density on CEM. The EMR was reviewed for clinical factors. Radiologists' agreement for degree of BPE was assessed using weighted kappa coefficients. Univariable and multivariable analyses were performed to assess relationships between clinical factors and degree of BPE, treating readers' independent assessments as repeated measurements. RESULTS. Interreader agreement for degree of BPE, expressed as kappa, was 0.80 for both criteria. For both criteria, univariable analyses found degree of BPE to be negatively associated with age (both OR = 0.94), personal history of breast cancer (OR = 0.22-0.30), history of chemotherapy (OR = 0.18-0.21), history of radiation therapy (OR = 0.20-0.21), perimenopausal status (OR = 0.22-0.34), and postmenopausal status (OR = 0.10-0.11) and to be positively associated with dense breasts (OR = 4.13-4.26) and premenopausal status with irregular menstrual cycles (OR = 7.94-14.02). Among premenopausal patients with regular menstrual cycles, degree of BPE was lowest (using postmenopausal patients as reference) for patients in menstrual cycle days 8-14 (OR = 2.56-3.30). In multivariable analysis for both criteria, the only independent predictors of degree of BPE related to menstrual status and time of menstrual cycle (e.g., using premenopausal patients in days 1-7 as reference: OR = 0.21 for both criteria for premenopausal patients in days 8-14 and OR = 0.03-0.04 for postmenopausal patients). CONCLUSION. Clinical factors, including history of breast cancer or breast cancer treatment, breast density, menstrual status, and time of menstrual cycle, are associated with degree of early BPE on CEM. In premenopausal patients, the degree of BPE is lowest on days 8-14 of the menstrual cycle. CLINICAL IMPACT. Given the potential impact of BPE on diagnostic performance, the findings have implications for CEM scheduling and interpretation.
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Affiliation(s)
- Simin Wang
- Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong'an Rd, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yuqi Sun
- Department of Biostatistics, Key Laboratory on Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai, China
| | - Chao You
- Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong'an Rd, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tingting Jiang
- Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong'an Rd, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Meng Yang
- Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong'an Rd, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xigang Shen
- Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong'an Rd, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Min Qian
- Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong'an Rd, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | | | - Henry S Lynn
- Department of Biostatistics, Key Laboratory on Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai, China
| | - Ruimin Li
- Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong'an Rd, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong'an Rd, Shanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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Background enhancement in contrast-enhanced spectral mammography (CESM): are there qualitative and quantitative differences between imaging systems? Eur Radiol 2023; 33:2945-2953. [PMID: 36474057 PMCID: PMC10017655 DOI: 10.1007/s00330-022-09238-9] [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: 05/13/2022] [Revised: 08/15/2022] [Accepted: 10/13/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVE To evaluate the impact of the digital mammography imaging system on overall background enhancement on recombined contrast-enhanced spectral mammography (CESM) images, the overall background enhancement of two different mammography systems was compared. METHODS In a retrospective single-center study, CESM images of n = 129 female patients who underwent CESM between 2016 and 2019 were analyzed independently by two radiologists. Two mammography machines of different manufacturers were compared qualitatively using a Likert-scale from 1 (minimal) to 4 (marked overall background enhancement) and quantitatively by placing a region of interest and measuring the intensity enhancement. Lesion conspicuity was analyzed using a Likert-scale from 1 (lesion not reliably distinguishable) to 5 (excellent lesion conspicuity). A multivariate regression was performed to test for potential biases on the quantitative results. RESULTS Significant differences in qualitative background enhancement measurements between machines A and B were observed for both readers (p = 0.003 and p < 0.001). The quantitative evaluation showed significant differences in background enhancement with an average difference of 75.69 (99%-CI [74.37, 77.02]; p < 0.001). Lesion conspicuity was better for machine A for the first and second reader respectively (p = 0.009 and p < 0.001). The factor machine was the only influencing factor (p < 0.001). The factors contrast agent, breast density, age, and menstrual cycle could be excluded as potential biases. CONCLUSION Mammography machines seem to significantly influence overall background enhancement qualitatively and quantitatively; thus, an impact on diagnostic accuracy appears possible. KEY POINTS • Overall background enhancement on CESM differs between different vendors qualitatively and quantitatively. • Our retrospective single-center study showed consistent results of the qualitative and quantitative data analysis of overall background enhancement. • Lesion conspicuity is higher in cases of lower background enhancement on CESM.
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Migliaro G, Bicchierai G, Valente P, Di Naro F, De Benedetto D, Amato F, Boeri C, Vanzi E, Miele V, Nori J. Contrast Enhanced Mammography (CEM) Enhancing Asymmetry: Single-Center First Case Analysis. Diagnostics (Basel) 2023; 13:diagnostics13061011. [PMID: 36980319 PMCID: PMC10047777 DOI: 10.3390/diagnostics13061011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/02/2023] [Accepted: 03/04/2023] [Indexed: 03/09/2023] Open
Abstract
(1) Purpose: The latest Breast Imaging Reporting and Data System (BI-RADS) lexicon for CEM introduced a new descriptor, enhancing asymmetries (EAs). The purpose of this study was to determine which types of lesions were correlated with EAs. (2) Methods: A total of 3359 CEM exams, executed at AOUC Careggi in Florence, Italy between 2019 and 2021 were retrospectively assessed by two radiologists. For each of the EAs found, the size, the enhancing conspicuity (degree of enhancement relative to background described as low, moderate, or high), whether there was a corresponding finding in the traditional radiology images (US or mammography), the biopsy results when performed including any follow-up exams, and the presence of background parenchymal enhancement (BPE) of the normal breast tissue (minimal, mild, moderate, marked) were described. (3) Results: A total of 64 women were included, 36 of them underwent CEM for a preoperative staging assessment, and 28 for a problem-solving examination. Among the 64 EAs, 19/64 (29.69%) resulted in being category B5 (B5) lesions, 5/64 (7.81%) as category B3 (B3) lesions, and 40/64(62.50%) were negative or benign either after biopsy or second-look exams or follow-up. We assessed that EAs with higher enhancing conspicuity correlated significantly with a higher risk of B5 lesions (p: 0.0071), especially bigger ones (p: 0.0274). Conclusions: EAs can relate both with benign and tumoral lesions, and they need to be assessed as the other CEM descriptors, with re-evaluation of low-energy images and second-look exams, particularly larger EAs with higher enhancing conspicuity.
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Affiliation(s)
- Giuliano Migliaro
- Breast Imaging Diagnostic Unit, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Giulia Bicchierai
- Breast Imaging Diagnostic Unit, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
- Correspondence:
| | - Pietro Valente
- Breast Imaging Diagnostic Unit, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Federica Di Naro
- Breast Imaging Diagnostic Unit, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Diego De Benedetto
- Breast Imaging Diagnostic Unit, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Francesco Amato
- Breast Imaging Diagnostic Unit, Radiology Department, Ospedale San Giovanni di Dio, 92100 Agrigento, Italy
| | - Cecilia Boeri
- Breast Imaging Diagnostic Unit, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Ermanno Vanzi
- Breast Imaging Diagnostic Unit, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Vittorio Miele
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Jacopo Nori
- Breast Imaging Diagnostic Unit, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
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Acciavatti RJ, Lee SH, Reig B, Moy L, Conant EF, Kontos D, Moon WK. Beyond Breast Density: Risk Measures for Breast Cancer in Multiple Imaging Modalities. Radiology 2023; 306:e222575. [PMID: 36749212 PMCID: PMC9968778 DOI: 10.1148/radiol.222575] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/23/2022] [Accepted: 12/05/2022] [Indexed: 02/08/2023]
Abstract
Breast density is an independent risk factor for breast cancer. In digital mammography and digital breast tomosynthesis, breast density is assessed visually using the four-category scale developed by the American College of Radiology Breast Imaging Reporting and Data System (5th edition as of November 2022). Epidemiologically based risk models, such as the Tyrer-Cuzick model (version 8), demonstrate superior modeling performance when mammographic density is incorporated. Beyond just density, a separate mammographic measure of breast cancer risk is parenchymal textural complexity. With advancements in radiomics and deep learning, mammographic textural patterns can be assessed quantitatively and incorporated into risk models. Other supplemental screening modalities, such as breast US and MRI, offer independent risk measures complementary to those derived from mammography. Breast US allows the two components of fibroglandular tissue (stromal and glandular) to be visualized separately in a manner that is not possible with mammography. A higher glandular component at screening breast US is associated with higher risk. With MRI, a higher background parenchymal enhancement of the fibroglandular tissue has also emerged as an imaging marker for risk assessment. Imaging markers observed at mammography, US, and MRI are powerful tools in refining breast cancer risk prediction, beyond mammographic density alone.
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Affiliation(s)
| | | | - Beatriu Reig
- From the Department of Radiology, University of Pennsylvania, 3400
Spruce St, Philadelphia, PA 19104 (R.J.A., E.F.C., D.K.); Department of
Radiology, Seoul National University Hospital, Seoul, South Korea (S.H.L.,
W.K.M.); and Department of Radiology, NYU Langone Health, New York, NY (B.R.,
L.M.)
| | - Linda Moy
- From the Department of Radiology, University of Pennsylvania, 3400
Spruce St, Philadelphia, PA 19104 (R.J.A., E.F.C., D.K.); Department of
Radiology, Seoul National University Hospital, Seoul, South Korea (S.H.L.,
W.K.M.); and Department of Radiology, NYU Langone Health, New York, NY (B.R.,
L.M.)
| | - Emily F. Conant
- From the Department of Radiology, University of Pennsylvania, 3400
Spruce St, Philadelphia, PA 19104 (R.J.A., E.F.C., D.K.); Department of
Radiology, Seoul National University Hospital, Seoul, South Korea (S.H.L.,
W.K.M.); and Department of Radiology, NYU Langone Health, New York, NY (B.R.,
L.M.)
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12
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Lin F, Li Q, Wang Z, Shi Y, Ma H, Zhang H, Zhang K, Yang P, Zhang R, Duan S, Gu Y, Mao N, Xie H. Intratumoral and peritumoral radiomics for preoperatively predicting the axillary non-sentinel lymph node metastasis in breast cancer on the basis of contrast-enhanced mammography: a multicenter study. Br J Radiol 2023; 96:20220068. [PMID: 36542866 PMCID: PMC9975381 DOI: 10.1259/bjr.20220068] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 11/07/2022] [Accepted: 11/20/2022] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE To develop and test a contrast-enhanced mammography (CEM)-based radiomics model using intratumoral and peritumoral regions to predict non-sentinel lymph node (NSLN) metastasis in breast cancer before surgery. METHODS This multicenter study included 365 breast cancer patients with sentinel lymph node metastasis. Intratumoral regions of interest (ROIs) were manually delineated, and peritumoral ROIs (5 and 10 mm) were automatically obtained. Five models, including intratumoral model, peritumoral (5 and 10 mm) models, and intratumoral+peritumoral (5 and 10 mm) models, were constructed by support vector machine classifier on the basis of optimal features selected by variance threshold, SelectKbest, and least absolute shrinkage and selection operator algorithms. The predictive performance of radiomics models was evaluated by receiver operating characteristic curves. An external testing set was used to test the model. The Memorial Sloan Kettering Cancer Center (MSKCC) model was used to compare the predictive performance with radiomics model. RESULTS The intratumoral ROI and intratumoral+peritumoral 10-mm ROI-based radiomics model achieved the best performance with an area under the curve (AUC) of 0.8000 (95% confidence interval [CI]: 0.6871-0.8266) in the internal testing set. In the external testing set, the AUC of radiomics model was 0.7567 (95% CI: 0.6717-0.8678), higher than that of MSKCC model (AUC = 0.6681, 95% CI: 0.5148-0.8213) (p = 0.361). CONCLUSIONS The intratumoral and peritumoral radiomics based on CEM had an acceptable predictive performance in predicting NSLN metastasis in breast cancer, which could be seen as a supplementary predicting tool to help clinicians make appropriate surgical plans. ADVANCES IN KNOWLEDGE The intratumoral and peritumoral CEM-based radiomics model could noninvasively predict NSLN metastasis in breast cancer patients before surgery.
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Affiliation(s)
- Fan Lin
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Qin Li
- Department of Radiology, WeiFang Traditional Chinese Hospital, Weifang, China
| | - Zhongyi Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Yinghong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Haicheng Zhang
- Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Kun Zhang
- Department of Breast Surgery, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Ping Yang
- Department of Pathology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Ran Zhang
- Huiying Medical Technology, Beijing, China
| | | | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | | | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
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13
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Anandarajah A, Chen Y, Colditz GA, Hardi A, Stoll C, Jiang S. Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature. Breast Cancer Res 2022; 24:101. [PMID: 36585732 PMCID: PMC9805242 DOI: 10.1186/s13058-022-01600-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 12/21/2022] [Indexed: 12/31/2022] Open
Abstract
This systematic review aimed to assess the methods used to classify mammographic breast parenchymal features in relation to the prediction of future breast cancer. The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021 to extract published articles in English describing the relationship of parenchymal texture features with the risk of breast cancer. Twenty-eight articles published since 2016 were included in the final review. The identification of parenchymal texture features varied from using a predefined list to machine-driven identification. A reduction in the number of features chosen for subsequent analysis in relation to cancer incidence then varied across statistical approaches and machine learning methods. The variation in approach and number of features identified for inclusion in analysis precluded generating a quantitative summary or meta-analysis of the value of these features to improve predicting risk of future breast cancers. This updated overview of the state of the art revealed research gaps; based on these, we provide recommendations for future studies using parenchymal features for mammogram images to make use of accumulating image data, and external validation of prediction models that extend to 5 and 10 years to guide clinical risk management. Following these recommendations could enhance the applicability of models, helping improve risk classification and risk prediction for women to tailor screening and prevention strategies to the level of risk.
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Affiliation(s)
- Akila Anandarajah
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA
| | - Yongzhen Chen
- Saint Louis University School of Medicine, Saint Louis, MO, USA
| | - Graham A Colditz
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA
| | - Angela Hardi
- Bernard Becker Medical Library, Washington University School of Medicine, MSC 8132-12-01, 660 S Euclid Ave, Saint Louis, MO, 63110, USA
| | - Carolyn Stoll
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA
| | - Shu Jiang
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA.
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14
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Coffey K, Jochelson MS. Contrast-enhanced mammography in breast cancer screening. Eur J Radiol 2022; 156:110513. [PMID: 36108478 PMCID: PMC10680079 DOI: 10.1016/j.ejrad.2022.110513] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 08/25/2022] [Accepted: 09/03/2022] [Indexed: 01/28/2023]
Abstract
Contrast-enhanced mammography (CEM) is a promising vascular-based breast imaging technique with high diagnostic performance in detecting breast cancer. Dual-energy acquisition using low and high energy x-ray spectra following intravenous iodinated contrast injection provides both anatomic and functional information in the same examination. The low-energy images are equivalent to standard digital mammography and the post-processed recombined images depict enhancement analogous to contrast-enhanced breast magnetic resonance imaging (MRI). Thus, CEM has the potential to detect abnormal morphologic features as well as neovascularity associated with breast cancer. Since its emergence in 2011, CEM has consistently demonstrated superior performance compared with standard mammography and mammography plus ultrasound, particularly in women with dense breasts, with high sensitivity approaching that of MRI, supporting its use as a cost-effective diagnostic and screening tool. CEM has been primarily used in the diagnostic setting to evaluate patients with screening abnormalities or with symptomatic breasts, to perform preoperative staging of newly diagnosed breast cancer, and to evaluate response to neoadjuvant chemotherapy. More recently, CEM has been performed to screen women who have an intermediate to high lifetime risk of developing breast cancer. In addition to its high diagnostic performance, CEM is less expensive and more accessible than MRI and potentially better tolerated by patients. Minor drawbacks to CEM include a slightly increased radiation dose compared with standard mammography and a low risk for contrast allergy reaction. The aim of this study is to review the background, current literature, and future applications of CEM in breast cancer screening.
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Affiliation(s)
- Kristen Coffey
- Memorial Sloan Kettering Cancer Center, Evelyn H. Lauder Breast Center, 300 East 66th Street New York, NY 10065, United States.
| | - Maxine S Jochelson
- Memorial Sloan Kettering Cancer Center, Evelyn H. Lauder Breast Center, 300 East 66th Street New York, NY 10065, United States.
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15
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Vasselli F, Fabi A, Ferranti FR, Barba M, Botti C, Vidiri A, Tommasin S. How Dual-Energy Contrast-Enhanced Spectral Mammography Can Provide Useful Clinical Information About Prognostic Factors in Breast Cancer Patients: A Systematic Review of Literature. Front Oncol 2022; 12:859838. [PMID: 35941874 PMCID: PMC9355886 DOI: 10.3389/fonc.2022.859838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 05/27/2022] [Indexed: 12/24/2022] Open
Abstract
Introduction In the past decade, a new technique derived from full-field digital mammography has been developed, named contrast-enhanced spectral mammography (CESM). The aim of this study was to define the association between CESM findings and usual prognostic factors, such as estrogen receptors, progesterone receptors, HER2, and Ki67, in order to offer an updated overview of the state of the art for the early differential diagnosis of breast cancer and following personalized treatments. Materials and Methods According to the PRISMA guidelines, two electronic databases (PubMed and Scopus) were investigated, using the following keywords: breast cancer AND (CESM OR contrast enhanced spectral mammography OR contrast enhanced dual energy mammography) AND (receptors OR prognostic factors OR HER2 OR progesterone OR estrogen OR Ki67). The search was concluded in August 2021. No restriction was applied to publication dates. Results We obtained 28 articles from the research in PubMed and 114 articles from Scopus. After the removal of six replicas that were counted only once, out of 136 articles, 37 articles were reviews. Eight articles alone have tackled the relation between CESM imaging and ER, PR, HER2, and Ki67. When comparing radiological characterization of the lesions obtained by either CESM or contrast-enhanced MRI, they have a similar association with the proliferation of tumoral cells, as expressed by Ki-67. In CESM-enhanced lesions, the expression was found to be 100% for ER and 77.4% for PR, while moderate or high HER2 positivity was found in lesions with non-mass enhancement and with mass closely associated with a non-mass enhancement component. Conversely, the non-enhancing breast cancer lesions were not associated with any prognostic factor, such as ER, PR, HER2, and Ki67, which may be associated with the probability of showing enhancement. Radiomics on CESM images has the potential for non-invasive characterization of potentially heterogeneous tumors with different hormone receptor status. Conclusions CESM enhancement is associated with the proliferation of tumoral cells, as well as to the expression of estrogen and progesterone receptors. As CESM is a relatively young imaging technique, a few related works were found; this may be due to the “off-label” modality. In the next few years, the role of CESM in breast cancer diagnostics will be more thoroughly investigated.
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Affiliation(s)
- Federica Vasselli
- Radiology and Diagnostic Imaging, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Regina Elena National Cancer Institute, Rome, Italy
| | - Alessandra Fabi
- Precision Medicine in Breast Cancer Unit, Fondazione Policlinico Universitario A. Gemelli, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
| | - Francesca Romana Ferranti
- Radiology and Diagnostic Imaging, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Regina Elena National Cancer Institute, Rome, Italy
| | - Maddalena Barba
- Division of Medical Oncology 2, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Regina Elena National Cancer Institute, Rome, Italy
| | - Claudio Botti
- Division of Breast Surgery, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Regina Elena National Cancer Institute, Rome, Italy
| | - Antonello Vidiri
- Radiology and Diagnostic Imaging, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Regina Elena National Cancer Institute, Rome, Italy
- *Correspondence: Antonello Vidiri,
| | - Silvia Tommasin
- Human Neuroscience Department, Sapienza University of Rome, Rome, Italy
- Neuroimmunology Unit, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Fondazione Santa Lucia, Rome, Italy
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16
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Green VL. Breast Cancer Risk Assessment and Management of the High-Risk Patient. Obstet Gynecol Clin North Am 2022; 49:87-116. [DOI: 10.1016/j.ogc.2021.11.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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17
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Bauer E, Levy MS, Domachevsky L, Anaby D, Nissan N. Background parenchymal enhancement and uptake as breast cancer imaging biomarkers: A state-of-the-art review. Clin Imaging 2021; 83:41-50. [PMID: 34953310 DOI: 10.1016/j.clinimag.2021.11.021] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 10/29/2021] [Accepted: 11/15/2021] [Indexed: 12/20/2022]
Abstract
Within the past decade, background parenchymal enhancement (BPE) and background parenchymal uptake (BPU) have emerged as novel imaging-derived biomarkers in the diagnosis and treatment monitoring of breast cancer. Growing evidence supports the role of breast parenchyma vascularity and metabolic activity as probable risk factors for breast cancer development. Furthermore, in the presence of a newly-diagnosed breast cancer, added clinically-relevant data was surprisingly found in the respective imaging properties of the non-affected contralateral breast. Evaluation of the contralateral BPE and BPU have been found to be especially instrumental in predicting the prognosis of a patient with breast cancer and even anticipating their response to neoadjuvant chemotherapy. Simultaneously, further research has found a link between these two biomarkers, even though they represent different physical properties. The aim of this review is to provide an up to date summary of the current clinical applications of BPE and BPU as breast cancer imaging biomarkers with the hope that it propels their further usage in clinical practice.
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Affiliation(s)
- Ethan Bauer
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Miri Sklair Levy
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Liran Domachevsky
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Debbie Anaby
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Noam Nissan
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel.
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18
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MRI of the Lactating Breast: Computer-Aided Diagnosis False Positive Rates and Background Parenchymal Enhancement Kinetic Features. Acad Radiol 2021; 29:1332-1341. [PMID: 34857455 DOI: 10.1016/j.acra.2021.11.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 11/01/2021] [Accepted: 11/01/2021] [Indexed: 12/28/2022]
Abstract
RATIONALE AND OBJECTIVES To investigate the application of computer-added diagnosis (CAD) in dynamic contrast-enhanced (DCE) MRI of the healthy lactating breast, focusing on false-positive rates and background parenchymal enhancement (BPE) coloring patterns in comparison with breast cancer features in non-lactating patients. MATERIALS AND METHODS The study population was composed of 58 healthy lactating patients and control groups of 113 healthy premenopausal non-lactating patients and 55 premenopausal non-lactating patients with newly-diagnosed breast cancer. Patients were scanned on 1.5-T MRI using conventional DCE protocol. A retrospective analysis of DCE-derived CAD properties was conducted using a commercial software that is regularly utilized in our routine radiological work-up. Qualitative morphological characterization and automatically-obtained quantitative parametric measurements of the BPE-induced CAD coloring were categorized and subgroups' trends and differences between the lactating and cancer cohorts were statistically assessed. RESULTS CAD false-positive coloring was found in the majority of lactating cases (87%). Lactation BPE coloring was characteristically non-mass enhancement (NME)-like shaped (87%), bilateral (79%) and symmetric (64%), whereas, unilateral coloring was associated with prior irradiation (p <0.0001). Inter-individual variability in CAD appearance of both scoring-grade and kinetic-curve dominance was found among the lactating cohort. When compared with healthy non-lactating controls, CAD false positive probability was significantly increased [Odds ratio 40.2, p <0001], while in comparison with the breast cancer cohort, CAD features were mostly inconclusive, even though increased size parameters were significantly associated with lactation-BPE (p <0.00001). CONCLUSION BPE was identified as a common source for false-positive CAD coloring on breast DCE-MRI among lactating population. Despite several typical characteristics, overlapping features with breast malignancy warrant a careful evaluation and clinical correlation in all cases with suspected lactation induced CAD coloring.
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19
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Neeter LM, Raat H(F, Alcantara R, Robbe Q, Smidt ML, Wildberger JE, Lobbes MB. Contrast-enhanced mammography: what the radiologist needs to know. BJR Open 2021; 3:20210034. [PMID: 34877457 PMCID: PMC8611680 DOI: 10.1259/bjro.20210034] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/29/2021] [Accepted: 07/30/2021] [Indexed: 12/12/2022] Open
Abstract
Contrast-enhanced mammography (CEM) is a combination of standard mammography and iodinated contrast material administration. During the last decade, CEM has found its place in breast imaging protocols: after i.v. administration of iodinated contrast material, low-energy and high-energy images are retrieved in one acquisition using a dual-energy technique, and a recombined image is constructed enabling visualisation of areas of contrast uptake. The increased incorporation of CEM into everyday clinical practice is reflected in the installation of dedicated equipment worldwide, the (commercial) availability of systems from different vendors, the number of CEM examinations performed, and the number of scientific articles published on the subject. It follows that ever more radiologists will be confronted with this technique, and thus be required to keep up to date with the latest developments in the field. Most importantly, radiologists must have sufficient knowledge on how to interpret CEM images and be acquainted with common artefacts and pitfalls. This comprehensive review provides a practical overview of CEM technique, including CEM-guided biopsy; reading, interpretation and structured reporting of CEM images, including the accompanying learning curve, CEM artefacts and interpretation pitfalls; indications for CEM; disadvantages of CEM; and future developments.
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Affiliation(s)
| | - H.P.J. (Frank) Raat
- Department of Medical Imaging, Laurentius Hospital, Roermond, the Netherlands
| | | | - Quirien Robbe
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | | | - Joachim E. Wildberger
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
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20
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Xu W, Zheng B, Chen W, Wen C, Zeng H, He Z, Qin G, Li Y. Can the delayed phase of quantitative contrast-enhanced mammography improve the diagnostic performance on breast masses? Quant Imaging Med Surg 2021; 11:3684-3697. [PMID: 34341742 DOI: 10.21037/qims-20-1092] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 04/09/2021] [Indexed: 11/06/2022]
Abstract
Background Contrast-enhanced mammography (CEM) is an imaging tool for breast cancer detection. Most quantitative analyses of CEM involve two phases, and it is unknown whether an added delayed phase can improve its diagnostic performance compared to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). This study aimed to evaluate whether the delayed phase improves the diagnostic performance of CEM in distinguishing malignant and benign masses. Methods This prospective study enrolled 111 women with 111 pathologically confirmed breast masses. CEM was performed after the injection of contrast agent between 2-3 minutes (T1, early phase), 4-5 minutes (T2, second phase), and 7-9 minutes (T3, delayed phase). The quantitative enhanced gray value of lesions (LGV) and the lesion to background grey value ratio (LBR) were measured within each phase's corresponding region of interest (ROI). Based on their changes, the kinetic enhancement pattern was assessed among the three phases, and the diagnostic performance was subsequently measured. Results The LGV and LBR of malignant masses were significantly greater than those of benign lesions. The diagnostic performance of LGV and LBR at the delayed phase was consistent with that of the second phase but poorer than that of the early phase. The sensitivity of LGVT1 + LGVT2 + LGVT3 was less than that of LGVT1 + LGVT2 (86.5% vs. 95.1%) with a similar area under the curve (AUC), specificity, positive-predictive value (PPV), negative-predictive value (NPV), and accuracy. The sensitivity of LBRT1 + LBRT2 + LBRT3 increased by 19.6%, and specificity decreased by 20.7% compared with LBRT1 + LBRT2. The LGVT1 + LGVT2 + LGVT3 + kinetic enhancement (T1-T3) had the lowest sensitivity (67.0%), but the highest specificity (75.8%), and the sensitivity of LBRT1 + LBRT2 + LBRT3 + kinetic enhancement (T1-T3) was higher than that of LBRT1 + LBRT2 + kinetic enhancement (T1-T2) (90.2% vs. 63.4%, respectively). Conclusions The addition of a delayed CEM phase for breast cancer diagnosis yielded limited performance improvement. The quantitative analysis combined with enhancement patterns between the two consecutive phases has great potential to distinguish between malignant and benign lesions.
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Affiliation(s)
- Weimin Xu
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Bowen Zheng
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Weiguo Chen
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Chanjuan Wen
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Hui Zeng
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Zilong He
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Genggeng Qin
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yingjia Li
- Department of Ultrasonic Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China
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21
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Improving the Diagnostic Accuracy of Breast BI-RADS 4 Microcalcification-Only Lesions Using Contrast-Enhanced Mammography. Clin Breast Cancer 2020; 21:256-262.e2. [PMID: 33243676 DOI: 10.1016/j.clbc.2020.10.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 10/25/2020] [Accepted: 10/27/2020] [Indexed: 12/31/2022]
Abstract
BACKGROUND Contrast-enhanced mammography (CEM) is a novel breast imaging technique that can provide additional information of breast tissue blood supply. This study aimed to test the possibility of CEM in improving the diagnostic accuracy of Breast Imaging Reporting and Data System (BI-RADS) 4 calcification-only lesions with consideration of morphology and distribution. PATIENTS AND METHODS Data of patients with suspicious malignant calcification-only lesions (BI-RADS 4) on low-energy CEM and proved pathologic diagnoses were retrospectively collected. Two junior radiologists independently reviewed the two sets of CEM images, low-energy images (LE) to describe the calcifications by morphology and distribution type, and recombined images (CE) to record the presence of enhancement. Low-risk and high-risk groups were divided by calcification morphology, distribution, and both, respectively. Positive predictive values and misdiagnosis rates (MDR) were compared between LE-only reading and CE reading. Diagnostic performance was also tested using machine learning method. RESULTS The study included 74 lesions (26 malignant and 48 benign). Positive predictive values were significantly higher and MDRs were significantly lower using CE images than using LE alone for both the low-risk morphology type and low-risk distribution type (P < .05). MDRs were significantly lower when using CE images (18.18%-24.00%) than using LE images alone in low-risk group (76.36%-80.00%) (P < .05). Using a machine learning method, significant improvements in the area under the receiver operating characteristic curve were observed in both low-risk and high-risk groups. CONCLUSION CEM has the potential to aid in the diagnosis of BI-RADS 4 calcification-only lesions; in particular, those presented as low risk in morphology and/or distribution may benefit more.
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22
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Lin F, Wang Z, Zhang K, Yang P, Ma H, Shi Y, Liu M, Wang Q, Cui J, Mao N, Xie H. Contrast-Enhanced Spectral Mammography-Based Radiomics Nomogram for Identifying Benign and Malignant Breast Lesions of Sub-1 cm. Front Oncol 2020; 10:573630. [PMID: 33194677 PMCID: PMC7662120 DOI: 10.3389/fonc.2020.573630] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 10/12/2020] [Indexed: 12/16/2022] Open
Abstract
Objectives To develop a radiomics nomogram that incorporates contrast-enhanced spectral mammography (CESM)-based radiomics features and clinico-radiological variables for identifying benign and malignant breast lesions of sub-1 cm. Methods This retrospective study included 139 patients with the diameter of sub-1 cm on cranial caudal (CC) position of recombined images. Radiomics features were extracted from low-energy and recombined images on CC position. The variance threshold, analysis of variance (ANOVA) and least absolute shrinkage and selection operator (LASSO) algorithms were used to select optimal predictive features. Radiomics signature (Rad-score) was calculated by a linear combination of selected features. The independent predictive factors were identified by ANOVA and multivariate logistic regression. A radiomics nomogram was developed to predict the malignant probability of lesions. The performance and clinical utility of the nomogram was evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results Nineteen radiomics features were selected to calculate Rad-score. Breast imaging reporting and data system (BI-RADS) category and age were identified as predictive factors. The radiomics nomogram combined with Rad-score, BI-RADS category, and age showed better performance (area under curves [AUC]: 0.940, 95% confidence interval [CI]: 0.804-0.992) than Rad-score (AUC: 0.868, 95% CI: 0.711-0.958) and clinico-radiological model (AUC: 0.864, 95% CI: 0.706-0.956) in the validation cohort. The calibration curve and DCA showed that the radiomics nomogram had good consistency and clinical utility. Conclusions The radiomics nomogram incorporated with CESM-based radiomics features, BI-RADS category and age could identify benign and malignant breast lesions of sub-1 cm.
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Affiliation(s)
- Fan Lin
- School of Medical Imaging, Binzhou Medical University, Yantai, China.,Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Zhongyi Wang
- School of Medical Imaging, Binzhou Medical University, Yantai, China.,Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Kun Zhang
- Department of Breast Surgery, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Ping Yang
- Department of Pathology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Yinghong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Meijie Liu
- School of Medical Imaging, Binzhou Medical University, Yantai, China.,Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Qinglin Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Jingjing Cui
- Collaboration Department, Huiying Medical Technology, Beijing, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
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Factors Associated With Background Parenchymal Enhancement on Contrast-Enhanced Mammography. AJR Am J Roentgenol 2020; 216:340-348. [PMID: 32755162 DOI: 10.2214/ajr.19.22353] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE. The purpose of this study was to determine the relationship between background parenchymal enhancement (BPE) on contrast-enhanced mammography (CEM) and breast tissue density, menstrual status, endocrine therapy, and risk factors for breast cancer and also to evaluate interreader agreement on classification of BPE on CEM. MATERIALS AND METHODS. Five subspecialty-trained breast radiologists independently and blindly graded tissue density (with fatty tissue and scattered fibroglandular tissue classified as nondense tissue and with heterogeneously dense and extremely dense classified as dense tissue) and BPE (with minimal or mild BPE categorized as low BPE and moderate or marked BPE categorized as high BPE) on CEM examinations performed from 2014 to 2018. Electronic medical charts were reviewed for information on menstrual status, endocrine therapy, history of breast surgery, and other risk factors for breast cancer. Comparisons were performed using the Kruskal-Wallis test, Mann-Whitney test, and Spearman rank correlation. Interreader agreement was estimated using the Fleiss kappa test. RESULTS. A total of 202 patients (mean [± SD] age, 54 ± 10 years; range, 25-84 years) underwent CEM. Tissue density was categorized as fatty in two patients (1%), scattered fibroglandular in 67 patients (33%), heterogeneously dense in 117 patients (58%), and extremely dense in 16 patients (8%). Among the 202 patients, BPE was minimal in 77 (38%), mild in 80 (40%), moderate in 31 (15%), and marked in 14 (7%). Dense breasts, younger age, premenopausal status, no history of endocrine therapy, and no history of breast cancer were significantly associated with high BPE. Among premenopausal patients, no association was found between BPE and time from last menstrual period to CEM. Overall interreader agreement on BPE was moderate (κ = 0.41; 95% CI, 0.40-0.42). Interreader agreement on tissue density was substantial (κ = 0.67; 95% CI, 0.66-0.69). CONCLUSION. Women with dense breasts, premenopausal status, and younger age are more likely to have greater BPE. Targeting CEM to the last menstrual period is not indicated.
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