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Bellini C, Pugliese F, Bicchierai G, Amato F, De Benedetto D, Di Naro F, Boeri C, Vanzi E, Migliaro G, Incardona L, Tommasi C, Orzalesi L, Miele V, Nori J. Contrast-enhanced mammography in the management of breast architectural distortions and avoidance of unnecessary biopsies. Breast Cancer 2024; 31:851-857. [PMID: 38811515 DOI: 10.1007/s12282-024-01599-x] [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: 03/10/2024] [Accepted: 05/25/2024] [Indexed: 05/31/2024]
Abstract
BACKGROUND To assess contrast-enhanced mammography (CEM) in the management of BI-RADS3 breast architectural distortions (AD) in digital breast tomosynthesis (DBT). METHODS We retrospectively reviewed 328 women with 332 ADs detected on DBT between 2017 and 2021 and selected those classified as BI-RADS3 receiving CEM as problem-solving. In CEM recombined images, we evaluated AD's contrast enhancement (CE) according to its presence/absence, type, and size. AD with enhancement underwent imaging-guided biopsy while AD without enhancement follow-up or biopsy if detected in high/intermediate-risk women. RESULTS AD with enhancement were 174 (52.4%): 72 (41.4%) were malignant lesions, 102 (59.6%) false positive results: 28 (16%) B3 lesions, and 74 (42.5%) benign lesions. AD without enhancement were 158 (47.6%): 26 (16.5%) were subjected to biopsy (1 malignant and 25 benign) while the other 132 cases were sent to imaging follow-up, still negative after two years. CEM's sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and accuracy were 98.63%, 60.62%, 41.38%, 99.37%, and 68.98%. The AUC determined by ROC was 0.796 (95% CI, 0.749-0.844). CONCLUSION CEM has high sensitivity and NPV in evaluating BI-RADS3 AD and can be a complementary tool in assessing AD, avoiding unnecessary biopsies without compromising cancer detection.
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Affiliation(s)
- Chiara Bellini
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.
| | - Francesca Pugliese
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Giulia Bicchierai
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Francesco Amato
- Department of Radiology, Breast Imaging Unit, "Ospedale San Giovanni di Dio", Agrigento, Italy
| | - Diego De Benedetto
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Federica Di Naro
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Cecilia Boeri
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Ermanno Vanzi
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Giuliano Migliaro
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Ludovica Incardona
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Cinzia Tommasi
- Breast Surgery Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Lorenzo Orzalesi
- Breast Surgery Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Vittorio Miele
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Jacopo Nori
- Department of Radiology, Breast Imaging Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
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Alcantara R, Azcona J, Pitarch M, Arenas N, Castells X, Milioni P, Iotti V, Besutti G. Breast radiation dose with contrast-enhanced mammography-guided biopsy: a retrospective comparison with stereotactic and tomosynthesis guidance. Eur Radiol 2024:10.1007/s00330-024-10920-3. [PMID: 39143245 DOI: 10.1007/s00330-024-10920-3] [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: 02/18/2024] [Revised: 04/21/2024] [Accepted: 05/25/2024] [Indexed: 08/16/2024]
Abstract
OBJECTIVES This retrospective study aimed to compare the average glandular dose (AGD) per acquisition in breast biopsies guided by contrast-enhanced mammography (CEM), conventional stereotactic breast biopsy (SBB), and digital breast tomosynthesis (DBT). The study also investigated the influence of compressed breast thickness (CBT) and density on AGD. Furthermore, the study aimed to estimate the AGD per procedure for each guidance modality. METHODS The study included 163 female patients (mean age 57 ± 10 years) who underwent mammography-guided biopsies using SBB (9%), DBT (65%), or CEM (26%) guidance. AGD and CBT data were extracted from DICOM headers, and breast density was visually assessed. Statistical analyses included two-sample t-tests and descriptive statistics. RESULTS Mean AGD per acquisition varied slightly among CEM (1.48 ± 0.22 mGy), SBB (1.49 ± 0.40 mGy), and DBT (1.55 ± 0.47 mGy), with CEM presenting higher AGD at lower CBTs and less dose escalation at higher CBTs. For CBT > 55 mm, CEM showed reduced AGD compared to SBB and DBT (p < 0.001). Breast density had minimal impact on AGD, except for category A. The estimated AGD per procedure was approximately 11.84 mGy for CEM, 11.92 mGy for SBB, and 6.2 mGy for DBT. CONCLUSION The study found mean AGD per acquisition to be similar for CEM and SBB, with DBT slightly higher. CEM demonstrated higher AGD at lower CBT but lower AGD at higher CBT, indicating reduced dose escalation with increasing thickness. While breast density had minimal overall impact, variations were noted in category A. DBT was more dose-efficient per procedure due to fewer acquisitions required. CLINICAL RELEVANCE STATEMENT CEM guidance provides effective lesion visualization within safe radiation limits, improving the precision of percutaneous image-guided breast interventions and supporting its potential consideration in a wider range of breast diagnostic procedures. KEY POINTS Limited data exist on the AGD using CEM guidance for breast biopsies. CEM and SBB exhibit similar AGD per acquisition; DBT demonstrated the lowest AGD per procedure. Radiation from CEM guidance fits within safe limits for percutaneous image-guided breast interventions.
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Affiliation(s)
- Rodrigo Alcantara
- Department of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain.
- Radiology and Nuclear Medicine Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain.
| | - Javier Azcona
- Radiology and Nuclear Medicine Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
| | - Mireia Pitarch
- Radiology and Nuclear Medicine Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
| | - Natalia Arenas
- Radiology and Nuclear Medicine Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
| | - Xavier Castells
- Department of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Epidemiology and Evaluation Department, Hospital del Mar Research Institute (IMIM), Barcelona, Spain
- Health Services Research on Chronic Patients Network (REDISSEC), Institute of Health Carlos III, Madrid, Spain
| | | | - Valentina Iotti
- Radiology Unit, Department of Diagnostic Imaging and Laboratory Medicine, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Giulia Besutti
- Radiology Unit, Department of Diagnostic Imaging and Laboratory Medicine, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
- Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, Modena, Italy
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Cheng BWT, Ko TY, Lai YTA. Radiologic-Pathologic Correlation: Is There an Association Between Contrast-Enhanced Mammography Imaging Features and Molecular Subtypes of Breast Cancer? Cureus 2024; 16:e64791. [PMID: 39156463 PMCID: PMC11329886 DOI: 10.7759/cureus.64791] [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] [Accepted: 07/18/2024] [Indexed: 08/20/2024] Open
Abstract
OBJECTIVE This study aims to assess the correlation between imaging features of contrast-enhanced mammography (CEM) and molecular subtypes of breast cancer. METHODS This is a retrospective single-institution study of patients who underwent CEM from December 2019 to August 2023. Each patient had at least one histologically proven invasive breast cancer with a core biopsy performed. Patients with a history of breast cancer treatment and lesions not entirely included in the CEM images were excluded. The images were interpreted using the American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) lexicon for CEM, published in 2022. Different imaging features, including the presence of calcifications, architectural distortion, non-mass enhancement, mass morphology, internal enhancement pattern, the extent of enhancement, and lesion conspicuity, were analyzed. The molecular subtypes were studied as dichotomous variables, including luminal A, luminal B, HER2, and basal-like. The association between the imaging features and molecular subtypes was analyzed with a Fisher's exact test. Statistical significance was assumed when the p-value was <0.05. RESULTS A total of 31 patients with 36 malignant lesions were included in this study. Sixteen lesions (44.4%) were luminal A, four lesions (11.1%) were luminal B, 10 lesions (27.8%) were HER2, and six (16.7%) were basal-like subtypes. The presence of calcifications was associated with the HER2 subtype (p=0.024). Rim-enhancement on recombined images was associated with a basal-like subtype (p=0.001). Heterogeneous enhancement on recombined images was associated with non-basal-like breast cancer (p=0.027). No statistically significant correlation was found between other analyzed CEM imaging features and molecular subtypes. CONCLUSION CEM imaging features, including the presence of calcifications and certain internal enhancement patterns, were correlated with distinguishing breast cancer molecular subtypes and thus may further expand the role of CEM.
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Affiliation(s)
| | - Tsz Yan Ko
- Department of Radiology, Pamela Youde Nethersole Eastern Hospital, Hong Kong, HKG
| | - Yee Tak Alta Lai
- Department of Radiology, Pamela Youde Nethersole Eastern Hospital, Hong Kong, HKG
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Wang L, Wang P, Shao H, Li J, Yang Q. Role of contrast-enhanced mammography in the preoperative detection of ductal carcinoma in situ of the breasts: a comparison with low-energy image and magnetic resonance imaging. Eur Radiol 2024; 34:3342-3351. [PMID: 37853174 DOI: 10.1007/s00330-023-10312-z] [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: 09/08/2022] [Revised: 08/13/2023] [Accepted: 08/20/2023] [Indexed: 10/20/2023]
Abstract
OBJECTIVES To compare contrast-enhanced mammography (CEM) with low-energy image (LEI) alone and with magnetic resonance imaging (MRI) in the preoperative diagnosis of ductal carcinoma in situ (DCIS). METHODS In this single-center retrospective study, we reviewed 98 pure DCIS lesions in 96 patients who underwent CEM and MRI within 2 weeks preoperatively. The diagnostic performances of each imaging modality, lesion morphology, and extent were evaluated. RESULTS The sensitivity of CEM to DCIS was similar to that of MRI (92.9% vs. 93.9%, p = 0.77) and was significantly higher than that of LEI alone (76.5%, p = 0.002). The sensitivity of CEM to calcified DCIS (92.4%) was not significantly different from LEI alone (92.4%) and from MRI (93.9%, p = 1.00). However, CEM contributed to the simultaneous comparison of calcifications with enhancements. CEM had considerably higher sensitivity compared with LEI alone (93.8% vs. 43.8%, p < 0.001) and performed similarly to MRI (93.8%, p = 1.00) for noncalcified DCIS. All DCIS lesions were enhanced in MRI, whereas 94.9% (93/98) were enhanced in CEM. Non-mass enhancement was the most common presentation (CEM 63.4% and MRI 66.3%). The difference between the lesion size on each imaging modality and the histopathological size was smallest in MRI, followed by CEM, and largest in LEI. CONCLUSION CEM was more sensitive than LEI alone and comparable to MRI in DCIS diagnosis. The enhanced morphology of DCIS in CEM was consistent with that in MRI. CEM was superior to LEI alone in size measurement of DCIS. CLINICAL RELEVANCE STATEMENT This study investigated the value of CEM in the diagnosis and evaluation of DCIS, aiming to offer a reference for the selection of examination methods for DCIS and contribute to the early diagnosis and precise treatment of DCIS. KEY POINTS • DCIS is an important indication for breast surgery. Early and accurate diagnosis is crucial for DCIS treatment and prognosis. • CEM overcomes the deficiency of mammography in noncalcified DCIS diagnosis, exhibiting similar sensitivity to MRI; and CEM contributes to the comparison of calcification and enhancement of calcified DCIS, thereby outperforming MRI. • CEM is superior to LEI alone and slightly inferior to MRI in the size evaluation of DCIS.
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Affiliation(s)
- Liping Wang
- Department of Radiology, Yantai Yuhuangding Hospital, The Affiliated Hospital of Qingdao University, No. 20 Yuhuangdingdong Road, Yantai, 264000, Shandong, People's Republic of China
| | - Ping Wang
- Department of Radiology, Yantai Yuhuangding Hospital, The Affiliated Hospital of Qingdao University, No. 20 Yuhuangdingdong Road, Yantai, 264000, Shandong, People's Republic of China
| | - Huafei Shao
- Department of Radiology, Yantai Yuhuangding Hospital, The Affiliated Hospital of Qingdao University, No. 20 Yuhuangdingdong Road, Yantai, 264000, Shandong, People's Republic of China
| | - Jun Li
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai, 264100, Shandong, People's Republic of China
| | - Qinglin Yang
- Department of Radiology, Yantai Yuhuangding Hospital, The Affiliated Hospital of Qingdao University, No. 20 Yuhuangdingdong Road, Yantai, 264000, Shandong, People's Republic of China.
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Xing D, Lv Y, Sun B, Chu T, Bao Q, Zhang H. Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer. Acad Radiol 2024:S1076-6332(24)00200-9. [PMID: 38641451 DOI: 10.1016/j.acra.2024.03.035] [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: 01/18/2024] [Revised: 03/23/2024] [Accepted: 03/26/2024] [Indexed: 04/21/2024]
Abstract
RATIONALE AND OBJECTIVES To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer. MATERIALS AND METHODS In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio. Deep learning models, based on the pre-trained ResNet34 model and initially fine-tuned for identifying breast cancer, were trained using low-energy and subtracted CESM images. The predicted results served as deep learning features for the deep learning-based model. Clinical-pathological features, including age, progesterone receptor (PR) status, estrogen receptor (ER) status, Ki67 expression levels, and neutrophil-to-lymphocyte ratio, were used for the clinical model. All these features contributed to the nomogram. Feature selection was performed through univariate analysis. Logistic regression models were developed and chosen using a stepwise selection method. The deep learning-based and clinical models, along with the nomogram, were evaluated using precision-recall curves, receiver operating characteristic (ROC) curves, specificity, recall, accuracy, negative predictive value, positive predictive value (PPV), balanced accuracy, F1-score, and decision curve analysis (DCA). RESULTS The nomogram demonstrated considerable predictive ability, with higher area under the ROC curve (0.95, P < 0.05), accuracy (0.94), specificity (0.98), PPV (0.89), and precision (0.89) compared to the deep learning-based and clinical models. In DCA, the nomogram showed substantial clinical value in assisting breast cancer treatment decisions, exhibiting a higher net benefit than the other models. CONCLUSION The nomogram, integrating CESM deep learning with clinical-pathological features, proved valuable for predicting NAC response in patients with ER-positive/HER2-negative breast cancer. Nomogram outperformed deep learning-based and clinical models.
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Affiliation(s)
- Dong Xing
- Department of Radiology,Yantai Yuhuangding Hospital, Yantai, Shandong 264000 China
| | - Yongbin Lv
- Department of Radiology,Yantai Yuhuangding Hospital, Yantai, Shandong 264000 China
| | - Bolin Sun
- Department of Interventional Therapy, Yantai Yuhuangding Hospital, Yantai, Shandong 264000, China
| | - Tongpeng Chu
- Department of Radiology,Yantai Yuhuangding Hospital, Yantai, Shandong 264000 China; Big Data and Artificial Intelligence Lab, Yantai Yuhuangding Hospital, Yantai, Shandong 264000, China
| | - Qianhao Bao
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250300, China
| | - Han Zhang
- Department of Radiology,Yantai Yuhuangding Hospital, Yantai, Shandong 264000 China.
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Nicosia L, Battaglia O, Venturini M, Fontana F, Minenna M, Pesenti A, Budascu D, Pesapane F, Bozzini AC, Pizzamiglio M, Meneghetti L, Latronico A, Signorelli G, Mariano L, Cassano E. Contrast-enhanced mammography BI-RADS: a case-based approach to radiology reporting. Insights Imaging 2024; 15:37. [PMID: 38332410 PMCID: PMC10853105 DOI: 10.1186/s13244-024-01612-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 12/28/2023] [Indexed: 02/10/2024] Open
Abstract
Contrast-enhanced mammography (CEM) is a relatively recent diagnostic technique increasingly being utilized in clinical practice. Until recently, there was a lack of standardized reporting for CEM findings. However, this has changed with the publication of a supplement in the Breast Imaging Reporting and Data System (BI-RADS). A comprehensive understanding of CEM is essential for further enhancing its role in both screening and managing patients with breast malignancies. CEM can also be beneficial for problem-solving, improving the management of uncertain breast findings. Practitioners in this field should become more cognizant of how and when to employ this technique and interpret the various CEM findings. This paper aims to outline the key findings in the updated version of the BI-RADS specifically dedicated to CEM. Additionally, it will present some clinical cases commonly encountered in clinical practice.Critical relevance statement Standardized reporting and a thorough understanding of CEM findings are pivotal for advancing the role of CEM in screening and managing breast cancer patients. This standardization contributes significantly to integrating CEM as an essential component of daily clinical practice.Key points • A complete knowledge and understanding of the findings outlined in the new BI-RADS CEM are necessary for accurate reporting.• BI-RADS CEM supplement is intuitive and practical to use.• Standardization of the CEM findings enables more accurate patient management.
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Affiliation(s)
- Luca Nicosia
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy.
| | - Ottavia Battaglia
- Postgraduation School of Diagnostic and Interventional Radiology, University of Milan, Via Festa del Perdono 7, 20122, Milan, Italy
| | - Massimo Venturini
- Diagnostic and Interventional Radiology Department, Circolo Hospital, ASST Sette Laghi, 21100, Varese, Italy
- School of Medicine and Surgery, Insubria University, 21100, Varese, Italy
| | - Federico Fontana
- Diagnostic and Interventional Radiology Department, Circolo Hospital, ASST Sette Laghi, 21100, Varese, Italy
- School of Medicine and Surgery, Insubria University, 21100, Varese, Italy
| | - Manuela Minenna
- School of Medicine and Surgery, Insubria University, 21100, Varese, Italy
| | - Aurora Pesenti
- Department of Radiology, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy
| | - Diana Budascu
- Department of Radiology, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy
| | - Filippo Pesapane
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy
| | - Anna Carla Bozzini
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy
| | - Maria Pizzamiglio
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy
| | - Lorenza Meneghetti
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy
| | - Antuono Latronico
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy
| | - Giulia Signorelli
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy
| | - Luciano Mariano
- Radiology Department, Università degli Studi di Torino, 10129, Turin, Italy
| | - Enrico Cassano
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy
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van Nijnatten TJA, Morscheid S, Baltzer PAT, Clauser P, Alcantara R, Kuhl CK, Wildberger JE. Contrast-enhanced breast imaging: Current status and future challenges. Eur J Radiol 2024; 171:111312. [PMID: 38237520 DOI: 10.1016/j.ejrad.2024.111312] [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: 12/21/2023] [Revised: 01/04/2024] [Accepted: 01/09/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND Contrast-enhanced breast MRI and recently also contrast-enhanced mammography (CEM) are available for breast imaging. The aim of the current overview is to explore existing evidence and ongoing challenges of contrast-enhanced breast imaging. METHODS This narrative provides an introduction to the contrast-enhanced breast imaging modalities breast MRI and CEM. Underlying principle, techniques and BI-RADS reporting of both techniques are described and compared, and the following indications and ongoing challenges are discussed: problem-solving, high-risk screening, supplemental screening in women with extremely dense breast tissue, breast implants, neoadjuvant systemic therapy (NST) response monitoring, MRI-guided and CEM- guided biopsy. RESULTS Technique and reporting for breast MRI are standardised, for the newer CEM standardisation is in progress. Similarly, compared to other modalities, breast MRI is well established as superior for problem-solving, screening women at high risk, screening women with extremely dense breast tissue or with implants; and for monitoring response to NST. Furthermore, MRI-guided biopsy is a reliable technique with low long-term false negative rates. For CEM, data is as yet either absent or limited, but existing results in these settings are promising. CONCLUSION Contrast-enhanced breast imaging achieves highest diagnostic performance and should be considered essential. Of the two contrast-enhanced modalities, evidence of breast MRI superiority is ample, and preliminary results on CEM are promising, yet CEM warrants further study.
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Affiliation(s)
- T J A van Nijnatten
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands; GROW - School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, the Netherlands.
| | - S Morscheid
- Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany
| | - P A T Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Vienna, Austria
| | - P Clauser
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Vienna, Austria
| | - R Alcantara
- Radiology and Nuclear Medicine Department, Hospital del Mar, Barcelona, Spain
| | - C K Kuhl
- Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany
| | - J E Wildberger
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center+, Maastricht, the Netherlands
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8
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Kinkar KK, Fields BKK, Yamashita MW, Varghese BA. Empowering breast cancer diagnosis and radiology practice: advances in artificial intelligence for contrast-enhanced mammography. FRONTIERS IN RADIOLOGY 2024; 3:1326831. [PMID: 38249158 PMCID: PMC10796447 DOI: 10.3389/fradi.2023.1326831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 12/07/2023] [Indexed: 01/23/2024]
Abstract
Artificial intelligence (AI) applications in breast imaging span a wide range of tasks including decision support, risk assessment, patient management, quality assessment, treatment response assessment and image enhancement. However, their integration into the clinical workflow has been slow due to the lack of a consensus on data quality, benchmarked robust implementation, and consensus-based guidelines to ensure standardization and generalization. Contrast-enhanced mammography (CEM) has improved sensitivity and specificity compared to current standards of breast cancer diagnostic imaging i.e., mammography (MG) and/or conventional ultrasound (US), with comparable accuracy to MRI (current diagnostic imaging benchmark), but at a much lower cost and higher throughput. This makes CEM an excellent tool for widespread breast lesion characterization for all women, including underserved and minority women. Underlining the critical need for early detection and accurate diagnosis of breast cancer, this review examines the limitations of conventional approaches and reveals how AI can help overcome them. The Methodical approaches, such as image processing, feature extraction, quantitative analysis, lesion classification, lesion segmentation, integration with clinical data, early detection, and screening support have been carefully analysed in recent studies addressing breast cancer detection and diagnosis. Recent guidelines described by Checklist for Artificial Intelligence in Medical Imaging (CLAIM) to establish a robust framework for rigorous evaluation and surveying has inspired the current review criteria.
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Affiliation(s)
- Ketki K. Kinkar
- Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Brandon K. K. Fields
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Mary W. Yamashita
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Bino A. Varghese
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
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9
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Nabipoorashrafi SA, Gulhane A, Chung C, Chalian H. A Pictorial Review of CT Guidance for Transcatheter Aortic Valve Replacement. Semin Roentgenol 2024; 59:44-56. [PMID: 38388096 DOI: 10.1053/j.ro.2023.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 11/15/2023] [Accepted: 11/18/2023] [Indexed: 02/24/2024]
Affiliation(s)
| | - Avanti Gulhane
- Cardiothoracic Imaging Section, Department of Radiology, University of Washington, Seattle, WA
| | - Christine Chung
- Department of Cardiology, University of Washington, Seattle, WA
| | - Hamid Chalian
- Cardiothoracic Imaging Section, Department of Radiology, University of Washington, Seattle, WA.
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10
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Phillips J, Mehta TS, Portnow LH, Fishman MDC, Zhang Z, Pisano ED. Comparison of Contrast-enhanced Mammography with MRI Utilizing an Enriched Reader Study: A Breast Cancer Study (CONTRRAST Trial). Radiology 2023; 309:e230530. [PMID: 37962503 DOI: 10.1148/radiol.230530] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background Despite growing interest in using contrast-enhanced mammography (CEM) for breast cancer screening as an alternative to breast MRI, limited literature is available. Purpose To determine whether CEM is noninferior to breast MRI or abbreviated breast MRI (AB MRI) and superior to two-dimensional mammography in an asymptomatic population simulating those who would present for screening and then undergo diagnostic work-up. Materials and Methods This enriched reader study used CEM and MRI data prospectively collected from asymptomatic individuals at a single institution from December 2014 to March 2020. Case sets were obtained at screening, as part of work-up for a screening-detected finding, or before biopsy of a screening-detected abnormality. All images were anonymized and randomized, and all 12 radiologists interpreted them. For CEM interpretation, readers were first shown low-energy images as a surrogate for digital mammography and asked to give a forced Breast Imaging Reporting and Data System score for up to three abnormalities. The highest score was used as the case score. Readers then reviewed the full CEM examination and scored it similarly. After a minimum 1-month washout, the readers similarly interpreted AB MRI and full MRI examinations. Receiver operating characteristic analysis, powered to test CEM noninferiority to full MRI, was performed. Results The study included 132 case sets (14 negative, 74 benign, and 44 malignant; all female participants; mean age, 54 years ± 12 [SD]). The mean areas under the receiver operating characteristic curve (AUCs) for digital mammography, CEM, AB MRI, and full MRI were 0.79, 0.91, 0.89, and 0.91, respectively. CEM was superior to digital mammography (P < .001). No evidence of a difference in AUC was found between CEM and AB MRI and MRI. Conclusion In an asymptomatic study sample, CEM was noninferior to full MRI and AB MRI and was superior to digital mammography. Clinical trial registration no. NCT03482557 and NCT02275871 © RSNA, 2023 Supplemental material is available for this article.
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Affiliation(s)
- Jordana Phillips
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Tejas S Mehta
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Leah H Portnow
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Michael D C Fishman
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Zheng Zhang
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Etta D Pisano
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
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Cockmartin L, Bosmans H, Marshall NW. Investigation of test methods for QC in dual-energy based contrast-enhanced digital mammography systems: I. Iodine signal testing. Phys Med Biol 2023; 68:215017. [PMID: 37820689 DOI: 10.1088/1361-6560/ad027d] [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: 05/24/2023] [Accepted: 10/11/2023] [Indexed: 10/13/2023]
Abstract
The technique of dual-energy contrast enhanced mammography (CEM) visualizes iodine uptake in cancerous breast lesions following an intravenous injection of a contrast medium. The CEM image is generated by recombining two images acquired in rapid succession: a low energy image, with a mean energy below the iodine K-edge, and a higher energy image. The first part of this study examines the use of both commercially available and custom made phantoms to investigate iodine imaging under different imaging conditions, with the focus on quality control (QC) testing. Four CEM equipped systems were included in the study, with units from Fujifilm, GE Healthcare, Hologic and Siemens-Healthineers. The CEM parameters assessed in part I were: (1) image signal as a function of iodine concentration, measured in breast tissue simulating backgrounds of varying thickness and adipose/glandular compositions; (2) normal breast texture cancellation in homogeneous and structured backgrounds; (3) visibility of iodinated structures. For all four systems, a linear response to iodine concentration was found but the degree to which this was independent of background composition differed between the systems. Good cancellation of the glandular tissue inserts was found on all the units. Visibility scores of iodinated targets were similar between the four systems. Specialized phantoms are needed to fully evaluate important CEM performance markers, such as system response to iodine concentration and the ability of the system to cancel background texture. An extensive evaluation of the iodine signal imaging performance is recommended at the Commissioning stage for a new CEM device.
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Affiliation(s)
- L Cockmartin
- UZ Gasthuisberg, Department of Radiology, Herestraat 49, 3000 Leuven, Belgium
| | - H Bosmans
- UZ Gasthuisberg, Department of Radiology, Herestraat 49, 3000 Leuven, Belgium
- Medical Imaging Research Center, Medical Physics and Quality Assessment, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
| | - N W Marshall
- UZ Gasthuisberg, Department of Radiology, Herestraat 49, 3000 Leuven, Belgium
- Medical Imaging Research Center, Medical Physics and Quality Assessment, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
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12
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Marshall NW, Cockmartin L, Bosmans H. Investigation of test methods for QC in dual-energy based contrast-enhanced digital mammography systems: II. Artefacts/uniformity, exposure time and phantom-based dosimetry. Phys Med Biol 2023; 68:215016. [PMID: 37820686 DOI: 10.1088/1361-6560/ad027f] [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: 09/21/2023] [Accepted: 10/11/2023] [Indexed: 10/13/2023]
Abstract
Part II of this study describes constancy tests for artefacts and image uniformity, exposure time, and phantom-based dosimetry; these are applied to four mammography systems equipped with contrast enhanced mammography (CEM) capability. Artefacts were tested using a breast phantom that simulated breast shape and thickness change at the breast edge. Image uniformity was assessed using rectangular poly(methyl)methacrylate PMMA plates at phantom thicknesses of 20, 40 and 60 mm, for the low energy (LE), high energy (HE) images and the recombined CEM image. Uniformity of signal and of the signal to noise ratio was quantified. To estimate CEM exposure times, breast simulating blocks were imaged in automatic exposure mode. The resulting x-ray technique factors were then set manually and exposure time for LE and HE images and total CEM acquisition time was measured with a multimeter. Mean glandular dose (MGD) was assessed as a function of simulated breast thickness using three different phantom compositions: (i) glandular and adipose breast tissue simulating blocks combined to give glandularity values that were typical of those in a screening population, as thickness was changed (ii) PMMA sheets combined with polyethylene blocks (iii) PMMA sheets with spacers. Image uniformity was superior for LE compared to HE images. Two systems did not generate recombined images for the uniformity test when the detector was fully covered. Acquisition time for a CEM image pair for a 60 mm thick breast equivalent phantom ranged from 3.4 to 10.3 s. Phantom composition did not have a strong influence on MGD, with differences generally smaller than 10%. MGD for the HE images was lower than for the LE images, by a factor of between 1.3 and 4.0, depending on system and simulated breast thickness. When combined with the iodine signal assessment in part I, these tests provide a comprehensive assessment of CEM system imaging performance.
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Affiliation(s)
- N W Marshall
- UZ Gasthuisberg, Department of Radiology, Herestraat 49, B-3000 Leuven, Belgium
- Medical Imaging Research Center, Medical Physics and Quality Assessment, Katholieke Universiteit Leuven, B-3000 Leuven, Belgium
| | - L Cockmartin
- UZ Gasthuisberg, Department of Radiology, Herestraat 49, B-3000 Leuven, Belgium
| | - H Bosmans
- UZ Gasthuisberg, Department of Radiology, Herestraat 49, B-3000 Leuven, Belgium
- Medical Imaging Research Center, Medical Physics and Quality Assessment, Katholieke Universiteit Leuven, B-3000 Leuven, Belgium
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13
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Tsarouchi MI, Hoxhaj A, Mann RM. New Approaches and Recommendations for Risk-Adapted Breast Cancer Screening. J Magn Reson Imaging 2023; 58:987-1010. [PMID: 37040474 DOI: 10.1002/jmri.28731] [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] [Received: 01/19/2023] [Revised: 03/23/2023] [Accepted: 03/24/2023] [Indexed: 04/13/2023] Open
Abstract
Population-based breast cancer screening using mammography as the gold standard imaging modality has been in clinical practice for over 40 years. However, the limitations of mammography in terms of sensitivity and high false-positive rates, particularly in high-risk women, challenge the indiscriminate nature of population-based screening. Additionally, in light of expanding research on new breast cancer risk factors, there is a growing consensus that breast cancer screening should move toward a risk-adapted approach. Recent advancements in breast imaging technology, including contrast material-enhanced mammography (CEM), ultrasound (US) (automated-breast US, Doppler, elastography US), and especially magnetic resonance imaging (MRI) (abbreviated, ultrafast, and contrast-agent free), may provide new opportunities for risk-adapted personalized screening strategies. Moreover, the integration of artificial intelligence and radiomics techniques has the potential to enhance the performance of risk-adapted screening. This review article summarizes the current evidence and challenges in breast cancer screening and highlights potential future perspectives for various imaging techniques in a risk-adapted breast cancer screening approach. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 5.
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Affiliation(s)
- Marialena I Tsarouchi
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Alma Hoxhaj
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Ritse M Mann
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
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Taylor DB, Hobbs MM, Ronald MM, Burrows S, Ives A, Parizel PM, Saunders CM. Interpreting contrast imaging to plan breast surgery. ANZ J Surg 2023; 93:2197-2202. [PMID: 37438677 DOI: 10.1111/ans.18583] [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: 01/18/2023] [Revised: 06/20/2023] [Accepted: 06/22/2023] [Indexed: 07/14/2023]
Abstract
BACKGROUND Contrast enhanced mammography (CEM) and magnetic resonance imaging (MRI) are more accurate than conventional imaging (CI) for breast cancer staging. How adding CEM and MRI to CI might change the surgical plan is understudied. METHODS Surgical plans (breast conserving surgery (BCS), wider BCS, BCS with diagnostic excision (>1BCS), mastectomy) were devised by mock-MDT (radiologist, surgeon and pathology reports) according to disease extent on CI, CI + CEM and CI + MRI. Differences in the mock-MDT's surgical plans following the addition of CEM or MRI were investigated. Using pre-defined criteria, the appropriateness of the modified plans was assessed by comparing estimated disease extent on imaging with final pathology. Surgery performed was recorded from patient records. RESULTS Contrast imaging modified mock-MDT plans for 20 of 61(32.8%) breasts. The addition of CEM changed the plan in 16/20 (80%) and MRI in 17/20 breasts (85%). Identical changes were proposed by both CEM and MRI in 13/20 (65%) breasts. The modified surgical plan based on CI + CEM was possibly appropriate for 6/16 (37.5%), and CI + MRI in 9/17, (52.9%) breasts. The surgery performed was concordant with the mock-MDT plan for all 10 patients where the plans could be compared (BCS 1, >1 BCS 2 and mastectomy 7). CONCLUSION Adding CEM or MRI to CI changed mock-MDT plans in up to one third of women, but not all were appropriate. Changing surgical plans following addition of contrast imaging to CI without biopsy confirmation could lead to over or under-treatment.
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Affiliation(s)
- Donna B Taylor
- Department of Diagnostic and Interventional Radiology, Royal Perth Hospital, Perth, Western Australia, Australia
- Medical School, University of Western Australia, Perth, Western Australia, Australia
- BreastScreen WA, Perth, Western Australia, Australia
| | - Max M Hobbs
- Department of Diagnostic and Interventional Radiology, Royal Perth Hospital, Perth, Western Australia, Australia
| | - Maxine Mariri Ronald
- Department of Surgery, Royal Perth Hospital, Perth, Western Australia, Australia
| | - Sally Burrows
- Medical School, University of Western Australia, Perth, Western Australia, Australia
- Royal Perth Hospital Research Foundation, Perth, Western Australia, Australia
| | - Angela Ives
- Medical School, University of Western Australia, Perth, Western Australia, Australia
| | - Paul M Parizel
- Department of Diagnostic and Interventional Radiology, Royal Perth Hospital, Perth, Western Australia, Australia
- Medical School, University of Western Australia, Perth, Western Australia, Australia
| | - Christobel M Saunders
- Medical School, University of Western Australia, Perth, Western Australia, Australia
- Department of Surgery, Royal Perth Hospital, Perth, Western Australia, Australia
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15
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Endrikat J, Khater H, Boreham ADP, Fritze S, Schwenke C, Bhatti A, Trnkova ZJ, Seidensticker P. Iopromide for Contrast-Enhanced Mammography: A Systemic Review and Meta-Analysis of Pertinent Literature. Breast Cancer (Auckl) 2023; 17:11782234231189467. [PMID: 37600467 PMCID: PMC10433886 DOI: 10.1177/11782234231189467] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 07/06/2023] [Indexed: 08/22/2023] Open
Abstract
Background Contrast-enhanced mammography (CEM) is an emerging breast imaging modality. Clinical data is scarce. Objectives To summarize clinical evidence on the use of iopromide in CEM for the detection or by systematically analyzing the available literature on efficacy and safety. Design Systematic review and meta-analysis. Data sources and methods Iopromide-specific publications reporting its use in CEM were identified by a systematic search within Bayer's Product Literature Information (PLI) database and by levering a recent review publication. The literature search in PLI was performed up to January 2023. The confirmatory-supporting review publication was based on a MEDLINE/EMBASE + full text search for publications issued between September 2003 and January 2019. Relevant literature was selected based on pre-defined criteria by 2 reviewers. The comparison of CEM vs traditional mammography (XRM) was performed on published results of sensitivity and specificity. Differences in diagnostic parameters were assessed within a meta-analysis. Results Literature search: A total of 31 studies were identified reporting data on 5194 patients. Thereof, 19 studies on efficacy and 3 studies on safety. Efficacy: in 11 studies comparing iopromide CEM vs XRM, sensitivity was up to 43% higher (range 1%-43%) for CEM. Differences in specificity were found to be in a range of -4% to 46% for CEM compared with XRM. The overall gain in sensitivity for CEM vs XRM was 7% (95% CI [4%, 11%]) with no statistically significant loss in specificity in any study assessed. In most studies, accuracy, positive predictive value, and negative predictive value were found to be in favor of CEM. In 2 studies comparing CEM with breast magnetic resonance imaging (bMRI), both imaging modalities performed either equally well or CEM tended to show better results with respect to sensitivity and specificity. Safety: eight cases of iopromide-related adverse drug reactions were reported in 1022 patients (0.8%). Conclusions Pertinent literature provides evidence for clinical utility of iopromide in CEM for the detection or confirmation of breast cancer. The overall gain in sensitivity for iopromide CEM vs XRM was 7% with no statistically significant loss in specificity.
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Affiliation(s)
- Jan Endrikat
- Radiology R&D, Bayer AG, Berlin, Germany
- Department of Gynecology, Obstetrics and Reproductive Medicine, University Medical School of Saarland, Homburg, Germany
| | | | | | - Sabine Fritze
- Medical Affairs & Pharmacovigilance, Pharmaceuticals, Product Information, Bayer AG, Berlin, Germany
| | | | - Aasia Bhatti
- Benefit Risk Management Pharmacovigilance, Bayer US LLC, Whippany, NJ, USA
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Zhang S, Shao H, Li W, Zhang H, Lin F, Zhang Q, Zhang H, Wang Z, Gao J, Zhang R, Gu Y, Wang Y, Mao N, Xie H. Intra- and peritumoral radiomics for predicting malignant BiRADS category 4 breast lesions on contrast-enhanced spectral mammography: a multicenter study. Eur Radiol 2023; 33:5411-5422. [PMID: 37014410 DOI: 10.1007/s00330-023-09513-3] [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: 08/13/2022] [Revised: 12/20/2022] [Accepted: 02/01/2023] [Indexed: 04/05/2023]
Abstract
OBJECTIVE To construct and test a nomogram based on intra- and peritumoral radiomics and clinical factors for predicting malignant BiRADS 4 lesions on contrast-enhanced spectral mammography. METHODS A total of 884 patients with BiRADS 4 lesions were enrolled from two centers. For each lesion, five ROIs were defined using the intratumoral region (ITR), peritumoral regions (PTRs) of 5 and 10 mm around the tumor, and ITR plus PTRs of 5 mm and 10 mm. Five radiomics signatures were established by LASSO after selecting features. A nomogram was built using selected signatures and clinical factors by multivariable logistic regression analysis. The performance of the nomogram was assessed with the AUC, decision curve analysis, and calibration curves, and also compared with the radiomics model, clinical model, and radiologists. RESULTS The nomogram built by three radiomics signatures (constructed from ITR, 5 mm PTR, and ITR + 10 mm PTR) and two clinical factors (age and BiRADS category) showed powerful predictive ability in internal and external test sets with AUCs of 0.907 and 0.904, respectively. The calibration curves, decision curve analysis, showed favorable predictive performance of the nomogram. In addition, radiologists improved the diagnostic performance with the help of nomogram. CONCLUSION The nomogram established via intratumoral and peritumoral radiomics features and clinical risk factors had the best performance in distinguishing benign and malignant BiRADS 4 lesions, which could help radiologists improve diagnostic capabilities. KEY POINTS • Radiomics features from peritumoral regions in contrast-enhanced spectral mammography images may provide valuable information for the diagnosis of benign and malignant breast imaging reporting and data system category 4 breast lesions. • The nomogram incorporated intra- and peritumoral radiomics features and clinical variables have good application prospects in assisting clinical decision-makers.
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Affiliation(s)
- Shijie Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000
| | - Huafei Shao
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000
| | - Wenjuan Li
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000
| | - Haicheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000
| | - Fan Lin
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000
| | - Qianqian Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000
| | - Han Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000
| | - Zhongyi Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000
| | - Jing Gao
- School of Medical Imaging, Binzhou Medical University, Yantai, Shandong, People's Republic of China, 2640003
| | - Ran Zhang
- Huiying Medical Technology Co, Ltd, Beijing, People's Republic of China, 100192
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, 200000, China
| | - Yunqiang Wang
- Department of Radiology, Yantai Hospital of Traditional Chinese Medicine, Yantai, Shandong, People's Republic of China, 264000.
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000.
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20 Yuhuangding East Street, Yantai, Shandong, People's Republic of China, 264000.
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Daniaux M, Gruber L, De Zordo T, Geiger-Gritsch S, Amort B, Santner W, Egle D, Baltzer PAT. Preoperative staging by multimodal imaging in newly diagnosed breast cancer: Diagnostic performance of contrast-enhanced spectral mammography compared to conventional mammography, ultrasound, and MRI. Eur J Radiol 2023; 163:110838. [PMID: 37080064 DOI: 10.1016/j.ejrad.2023.110838] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 04/04/2023] [Accepted: 04/11/2023] [Indexed: 04/22/2023]
Abstract
PURPOSE To compare contrast-enhanced spectral mammography (CESM) with mammography (Mx), ultrasound (US), and magnetic resonance imaging (MRI) regarding breast cancer detection rate and preoperative local staging. MATERIAL AND METHODS This prospective observational, single-centre study included 128 female patients (mean age 55.8 ± 11.5 years) with a newly diagnosed malignant breast tumour during routine US and Mx were prospectively enrolled. CESM and MRI examinations were performed within the study. Analysis included interreader agreement, tumour type and grade distribution, detection rates (DR), imaging morphology, contrast-enhancement and was performed by two independent readers blinded to patient history and histopathological diagnosis. Assessment of local disease extent was compared between modalities via Bland-Altman plots. RESULTS One-hundred-and-ten tumours were classified as NST (85.9%), 4 as ILC (3.1%) and 10 as DCIS (7.8%). DR was highest for MRI (128/128, 100.0%), followed by US (124/128, 96.9%) and CESM (123/128, 96.1%) and lowest for conventional Mx (106/128, 82.8%) (p = 0.0002). Higher breast density did not negatively affect DR of US, CESM or MRI. Local tumour extent measurements based on CESM (Bland-Altman bias 6.6, standard deviation 30.2) showed comparable estimation results to MRI, surpassing Mx (23.4/43.7) and US (35.4/40.5). Even though detection of multifocality and multicentricity was highest for CESM and MRI (p < 0.0001), second-look rates, i.e., targeted US examinations after MRI or CESM, were significantly lower for CESM (10.2% of cases) compared to MRI (16.2%) with a significantly higher true positive rate for CESM (72.0%) vs. MRI (42.5%). CONCLUSION CESM is a viable alternative to MRI for lesion detection and local staging in newly diagnosed malignant breast cancer and provides higher specificity in regard to second-look examinations.
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Affiliation(s)
- Martin Daniaux
- Department of Radiology, Medical University Innsbruck, Anichstraße 35, Innsbruck, Austria
| | - Leonhard Gruber
- Department of Radiology, Medical University Innsbruck, Anichstraße 35, Innsbruck, Austria.
| | - Tobias De Zordo
- Department of Radiology, Brixsana Private Clinic, Julius-Durst-Straße 28, Brixen, Italy
| | - Sabine Geiger-Gritsch
- Medizinisches Projektmanagement, Tirol Kliniken GmbH, Anichstraße 35, Innsbruck, Austria
| | - Birgit Amort
- Department of Radiology, Medical University Innsbruck, Anichstraße 35, Innsbruck, Austria
| | - Wolfram Santner
- Department of Radiology, Privatklinik Hirslanden, Rigistrasse 1, Cham, Switzerland
| | - Daniel Egle
- Department of Gynaecology and Obstetrics, Medical University Innsbruck, Anichstraße 35, Innsbruck, Austria
| | - Pascal A T Baltzer
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Währingergürtel 18-20, Vienna, Austria
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Contrast-Enhanced Spectral Mammography in the Evaluation of Breast Microcalcifications: Controversies and Diagnostic Management. Healthcare (Basel) 2023; 11:healthcare11040511. [PMID: 36833045 PMCID: PMC9956946 DOI: 10.3390/healthcare11040511] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 02/03/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023] Open
Abstract
The aim of this study was to evaluate the diagnostic performance of contrast-enhanced spectral mammography (CESM) in predicting breast lesion malignancy due to microcalcifications compared to lesions that present with other radiological findings. Three hundred and twenty-one patients with 377 breast lesions that underwent CESM and histological assessment were included. All the lesions were scored using a 4-point qualitative scale according to the degree of contrast enhancement at the CESM examination. The histological results were considered the gold standard. In the first analysis, enhancement degree scores of 2 and 3 were considered predictive of malignity. The sensitivity (SE) and positive predictive value (PPV) were significative lower for patients with lesions with microcalcifications without other radiological findings (SE = 53.3% vs. 82.2%, p-value < 0.001 and PPV = 84.2% vs. 95.2%, p-value = 0.049, respectively). On the contrary, the specificity (SP) and negative predictive value (NPV) were significative higher among lesions with microcalcifications without other radiological findings (SP = 95.8% vs. 84.2%, p-value = 0.026 and NPV = 82.9% vs. 55.2%, p-value < 0.001, respectively). In a second analysis, degree scores of 1, 2, and 3 were considered predictive of malignity. The SE (80.0% vs. 96.8%, p-value < 0.001) and PPV (70.6% vs. 88.3%, p-value: 0.005) were significantly lower among lesions with microcalcifications without other radiological findings, while the SP (85.9% vs. 50.9%, p-value < 0.001) was higher. The enhancement of microcalcifications has low sensitivity in predicting malignancy. However, in certain controversial cases, the absence of CESM enhancement due to its high negative predictive value can help to reduce the number of biopsies for benign lesions.
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Emory T, Hoven N, Nelson M, Church AL, Rubin N, Kuehn-Hajder J. Diagnostic Contrast-Enhanced Mammography Performed Immediately Prior to Same-Day Biopsy: An Analysis of Index Lesion Enhancement Compared to Histopathology and Follow-up in Patients With Suspicious Ultrasound Findings. JOURNAL OF BREAST IMAGING 2023; 5:40-47. [PMID: 36778652 PMCID: PMC9901423 DOI: 10.1093/jbi/wbac081] [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: 07/13/2022] [Indexed: 01/03/2023]
Abstract
Objective To measure the diagnostic performance of contrast-enhanced mammography (CEM) for the index lesion when it is performed the same day prior to biopsy in patients with suspicious findings at US. Methods This IRB-approved retrospective study compared radiologist original reports of the presence or absence of index lesion enhancement on CEM to biopsy results and follow-up. The most suspicious lesion or the larger of equally suspicious lesions recommended for biopsy by US after a diagnostic workup including mammography was considered the index lesion. CEM exams were performed the same day, immediately prior to the scheduled biopsy, as requested by the radiologist recommending the biopsy. Numeric variables were summarized with means and standard deviations, or medians and the minimum and maximum, where appropriate. Results Biopsy demonstrated cancer in 64.7% (200/309) of index lesions. Of these, 197/200 demonstrated enhancement for a sensitivity of 98.5% (95% CI: 95.7%-99.7%) (197/200) and the negative predictive value of CEM for non-enhancing index lesions was 95.1% (58/61; 95% CI: 86.1%-98.4%). The three false negative exams were two grade 1 ER+ HER2- invasive ductal cancers that were 6 mm and 7 mm in size, and a 3-mm grade 2 ductal carcinoma in situ in a complex cystic and solid mass. False positive exams made up 20.6% (51/248) of the positive exams. Conclusion Diagnostic CEM showed high sensitivity and specificity for cancer in lesions with suspicious US findings. CEM may reduce the need for some biopsies, and negative CEM may support a true negative biopsy result.
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Affiliation(s)
- Tim Emory
- University of Minnesota, Department of Radiology, Minneapolis, MN, USA
| | - Noelle Hoven
- University of Minnesota, Department of Radiology, Minneapolis, MN, USA
| | - Michael Nelson
- University of Minnesota, Department of Radiology, Minneapolis, MN, USA
| | - An L Church
- University of Minnesota, Department of Radiology, Minneapolis, MN, USA
| | - Nathan Rubin
- University of Minnesota, Department of Radiology, Minneapolis, MN, USA
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Nicosia L, Bozzini AC, Palma S, Montesano M, Pesapane F, Ferrari F, Dominelli V, Rotili A, Meneghetti L, Frassoni S, Bagnardi V, Sangalli C, Cassano E. A Score to Predict the Malignancy of a Breast Lesion Based on Different Contrast Enhancement Patterns in Contrast-Enhanced Spectral Mammography. Cancers (Basel) 2022; 14:cancers14174337. [PMID: 36077871 PMCID: PMC9455061 DOI: 10.3390/cancers14174337] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 08/29/2022] [Accepted: 09/02/2022] [Indexed: 11/17/2022] Open
Abstract
Background: To create a predictive score of malignancy of a breast lesion based on the main contrast enhancement features ascertained by contrast-enhanced spectral mammography (CESM). Methods: In this single-centre prospective study, patients with suspicious breast lesions (BIRADS > 3) were enrolled between January 2013 and February 2022. All participants underwent CESM prior to breast biopsy, and eventually surgery. A radiologist with 20 years’ experience in breast imaging evaluated the presence or absence of enhancement and the following enhancement descriptors: intensity, pattern, margin, and ground glass. A score of 0 or 1 was given for each descriptor, depending on whether the enhancement characteristic was predictive of benignity or malignancy (both in situ and invasive). Then, an overall enhancement score ranging from 0 to 4 was obtained. The histological results were considered the gold standard in the evaluation of the relationship between enhancement patterns and malignancy. Results: A total of 321 women (median age: 51 years; range: 22−83) with 377 suspicious breast lesions were evaluated. Two hundred forty-nine lesions (66%) have malignant histological results (217 invasive and 32 in situ). Considering an overall enhancement score ≥ 2 as predictive of malignancy, we obtain an overall sensitivity of 92.4%; specificity of 89.8%; positive predictive value of 94.7%; and negative predictive value of 85.8%. Conclusions: Our proposed predictive score on the enhancement descriptors of CESM to predict the malignancy of a breast lesion shows excellent results and can help in early breast cancer diagnosis and in avoiding unnecessary biopsies.
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Affiliation(s)
- Luca Nicosia
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
- Correspondence:
| | - Anna Carla Bozzini
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Simone Palma
- University Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Largo Francesco Vito 1, 00168 Rome, Italy
| | - Marta Montesano
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Filippo Pesapane
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Federica Ferrari
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Valeria Dominelli
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Anna Rotili
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Lorenza Meneghetti
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Samuele Frassoni
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy
| | - Vincenzo Bagnardi
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy
| | - Claudia Sangalli
- Data Management, European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Enrico Cassano
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
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Niroshani S, Nakamura T, Michiru N, Negishi T. Evaluation of exposure factors of dual-energy contrast-enhanced mammography to optimize radiation dose with improved image quality. Acta Radiol Open 2022; 11:20584601221117251. [PMID: 35983293 PMCID: PMC9379970 DOI: 10.1177/20584601221117251] [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: 05/03/2022] [Accepted: 07/15/2022] [Indexed: 11/30/2022] Open
Abstract
Background Dual-energy contrast-enhanced mammography (DECEM) is an advanced breast
imaging technique of digital mammography. Purpose To assess the total radiation dose received from complete DECEM using
different combinations of exposure parameters for low- and high-energy
images. Materials and methods A dedicated phantom with three different concentrations of iodine inserts was
used. Each iodine insert was 10 mm in diameter and concentration of
1.0 mgI/cm3, 2.0 mgI/cm3, and
4.0 mgI/cm3. The phantom was exposed at varying kVp levels.
Mean glandular dose (MGD) was estimated. Contrast to noise ratio (CNR) and
figure of merit (FOM) of the iodine inserts were used to assess the image
quality. Results The optimum CNR of the recombined images was obtained by using 28 kVp +
49 kVp tube voltage combination for 50 mm thickness, 50% fibroglandular
phantom only with a 26% dose increase compared to the highest voltages
(32 kVp + 49 kVp) that can be used for low energy (LE) and high energy (HE)
imaging. The CNR value was increased with increasing iodine concentration
(R2 > 0.99). Conclusion The use of as low as possible tube voltage for the LE imaging of standard 50%
fibroglandular–50% adipose, 50 mm thickness breast while using the highest
tube voltage for HE imaging has reduced the MGD while keeping optimum image
quality.
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Affiliation(s)
- Sachila Niroshani
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- Department of Radiography and Radiotherapy, Faculty of Allied Health Sciences, General Sir John Kotelawala Defence University, Werahera, Sri Lanka
| | - Tokiko Nakamura
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- Department of Radiology, Juntendo University Shizuoka Hospital, Japan
| | - Nikaidou Michiru
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Toru Negishi
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
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Niroshani S, Nakamura T, Michiru N, Negishi T. An approach to dual-energy contrast-enhanced spectral mammography (DE-CESM) using a double layer filter: dosimetric and image quality assessment. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2022; 42:021534. [PMID: 35730431 DOI: 10.1088/1361-6498/ac7aed] [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: 04/07/2022] [Accepted: 06/21/2022] [Indexed: 06/15/2023]
Abstract
Dual-energy contrast-enhanced spectral mammography (DE-CESM) is a recently developed advanced technique in digital mammography that uses an iodinated intravenous contrast agent to assess tumor angiogenesis. The aim of this study was to investigate the diagnostic potential of DE-CESM recombined images in terms of radiation dose and image quality. A 50% fibroglandular-50% adipose, custom-made phantom with iodine inserts of 1.0 mgI cm-3, 2.0 mgI cm-3, 4.0 mgI cm-3was used for the estimation of mean glandular dose (MGD) and the image quality. Low-energy (LE) images were acquired with the W/Rh, W/Rh + 0.01 mm Cu and W/Rh + 0.5 mm Al while high energy images (HE) are acquired with the W/Rh, W/Rh + 0.06 mm Ba, W/Rh + 0.01 mm Cu, and W/Rh + 0.03 mm Ce anode filter combinations. The total MGD was reduced up to a maximum from 1.75 mGy to 1.45 mGy by using Rh + 0.01 mm Cu double-layer filter for both LE and HE imaging of 50 mm, standard 50% fibroglandular phantom compared to Rh single-layer filter with W target. The minimum total MGD reduction (1.69 mGy) was observed when Rh + 0.5 mm Al was used for LE and Rh + 0.06 mm Ba was used for HE exposure. The image quality was comparable with the single-layer filter. The use of W/Rh + 0.01 mm Cu or W/Rh + 0.5 mm Al as target/filter combination for LE exposure and W/Rh + 0.01 mm Cu for HE exposure can reduce the additional radiation dose delivered by DE-CESM without degrading the image quality.
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Affiliation(s)
- Sachila Niroshani
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- Department of Radiography and Radiotherapy, Faculty of Allied Health Sciences, General Sir John Kotelawala Defence University, Werahera, Sri Lanka
| | - Tokiko Nakamura
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- Department of Radiology, Juntendo University Shizuoka Hospital, Shizuoka, Japan
| | - Nikaidou Michiru
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Toru Negishi
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
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Bellini C, Bicchierai G, Amato F, Savi E, De Benedetto D, Di Naro F, Boeri C, Vanzi E, Miele V, Nori J. Comparison between second-look ultrasound and second-look digital breast tomosynthesis in the detection of additional lesions with presurgical CESM. Br J Radiol 2022; 95:20210927. [PMID: 35451312 PMCID: PMC10996408 DOI: 10.1259/bjr.20210927] [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: 08/10/2021] [Revised: 03/02/2022] [Accepted: 03/10/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVES To compare second-look ultrasound (SL-ultrasound) with second-look digital breast tomosynthesis (SL-DBT) in the detection of additional lesions (ALs) with presurgical contrast-enhanced spectral mammography (CESM). METHODS We retrospectively included 121 women with 128 ALs from patients who underwent CESM for presurgical staging at our centre from September 2016 to December 2018. These ALs underwent SL-ultrasound and a retrospective review of DBT (SL-DBT) performed 1-3 weeks prior to CESM to evaluate the performance of each technique individually and in combination. ALs in CESM images were evaluated according to enhancement type (focus, mass, or non-mass), size (<10 mm or >10 mm) and level of suspicion (BI-RADS 2, 3, 4 or 5). Our gold-standard was post-biopsy histology, post-surgical specimen or >24 month negative follow-up. McNemar's test was used for the statistical analysis. RESULTS Out of the 128 ALs, an imaging correlate was found for 71 (55.5 %) with ultrasound, 79 (61.7%) with DBT, 53 (41.4 %) with DBT and ultrasound, and 97 (75.8%) with ultrasound and/or DBT. SL-DBT demonstrated a higher detection rate vs SL-ultrasound in non-mass enhancement (NME) pattern (p: 0.0325) and ductal carcinoma in situ histological type (p: 0.0081). Adding SL-DBT improved the performance vs SL-ultrasound alone in the overall sample (p: <0.0001) and in every subcategory identified; adding SL-ultrasound to SL-DBT improved the detectability of ALs in the overall sample and in every category except for NME (p: 0.0833), foci (p: 0.0833) and B3 lesions (p: 0.3173). CONCLUSION Combined second-look imaging (SL-DBT+ SL-ultrasound) for CESM ALs is superior to SL-DBT alone and SL-ultrasound alone. In B3 lesions, NME, and foci, the analysis of a larger sample could determine whether adding SL-ultrasound to SL-DBT is necessary or not. ADVANCES IN KNOWLEDGE Thanks to its high sensitivity, CESM is a useful tool in presurgical staging to detect the extent of the disease burden and identify ALs not detected with conventional imaging. Since CESM-guided biopsy systems are still scarcely available in clinical practice, it is necessary to look for other approaches to histologically characterize ALs detected with CESM. In our study, combined second-look imaging (SL-DBT + SL-ultrasound) showed better performance in terms of detectability of ALs, than either SL-DBT or SL-ultrasound alone, and allowed us to identify 91.2% of ALs that turned out to be malignant at final histology; for the remaining 8.8% it was still necessary to perform MRI or MRI-guided biopsy. However, this issue could be solved once CESM-guided biopsies spread in clinical practice. SL-DBT demonstrated a higher detection rate than SL-ultrasound in NME and ductal carcinoma in situ histology.
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Affiliation(s)
- Chiara Bellini
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria
Careggi, Florence,
Italy
| | - Giulia Bicchierai
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria
Careggi, Florence,
Italy
| | - Francesco Amato
- Diagnostic Senology Unit – Radiology Dpt.,
“Ospedale San Giovanni di Dio”,
Agrigento, Italy
| | - Elena Savi
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria
Careggi, Florence,
Italy
| | - Diego De Benedetto
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria
Careggi, Florence,
Italy
| | - Federica Di Naro
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria
Careggi, Florence,
Italy
| | - Cecilia Boeri
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria
Careggi, Florence,
Italy
| | - Ermanno Vanzi
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria
Careggi, Florence,
Italy
| | - Vittorio Miele
- Department of Radiology, Azienda Ospedaliero-Universitaria
Careggi, Florence,
Italy
| | - Jacopo Nori
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria
Careggi, Florence,
Italy
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Sun Y, Wang S, Liu Z, You C, Li R, Mao N, Duan S, Lynn HS, Gu Y. Identifying factors that may influence the classification performance of radiomics models using contrast-enhanced mammography (CEM) images. Cancer Imaging 2022; 22:22. [PMID: 35550658 PMCID: PMC9101829 DOI: 10.1186/s40644-022-00460-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 04/26/2022] [Indexed: 11/10/2022] Open
Abstract
Background Radiomics plays an important role in the field of oncology. Few studies have focused on the identification of factors that may influence the classification performance of radiomics models. The goal of this study was to use contrast-enhanced mammography (CEM) images to identify factors that may potentially influence the performance of radiomics models in diagnosing breast lesions. Methods A total of 157 women with 161 breast lesions were included. Least absolute shrinkage and selection operator (LASSO) regression and the random forest (RF) algorithm were employed to construct radiomics models. The classification result for each lesion was obtained by using 100 rounds of five-fold cross-validation. The image features interpreted by the radiologists were used in the exploratory factor analyses. Univariate and multivariate analyses were performed to determine the association between the image features and misclassification. Additional exploratory analyses were performed to examine the findings. Results Among the lesions misclassified by both LASSO and RF ≥ 20% of the iterations in the cross-validation and those misclassified by both algorithms ≤5% of the iterations, univariate analysis showed that larger lesion size and the presence of rim artifacts and/or ripple artifacts were associated with more misclassifications among benign lesions, and smaller lesion size was associated with more misclassifications among malignant lesions (all p < 0.050). Multivariate analysis showed that smaller lesion size (odds ratio [OR] = 0.699, p = 0.002) and the presence of air trapping artifacts (OR = 35.568, p = 0.025) were factors that may lead to misclassification among malignant lesions. Additional exploratory analyses showed that benign lesions with rim artifacts and small malignant lesions (< 20 mm) with air trapping artifacts were misclassified by approximately 50% more in rate compared with benign and malignant lesions without these factors. Conclusions Lesion size and artifacts in CEM images may affect the diagnostic performance of radiomics models. The classification results for lesions presenting with certain factors may be less reliable. Supplementary Information The online version contains supplementary material available at 10.1186/s40644-022-00460-8.
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Affiliation(s)
- Yuqi Sun
- Department of Biostatistics, Key Laboratory on Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Simin Wang
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270 Dongan Road, Shanghai, 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, No. 270 Dongan Road, Shanghai, 200032, China
| | - Ziang Liu
- Department of Biostatistics, School of Public Health, Yale University, New Haven, CT, USA
| | - Chao You
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270 Dongan Road, Shanghai, 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, No. 270 Dongan Road, Shanghai, 200032, China
| | - Ruimin Li
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270 Dongan Road, Shanghai, 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, No. 270 Dongan Road, Shanghai, 200032, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Shandong, 264000, China
| | - Shaofeng Duan
- GE Healthcare China, No. 1 Huatuo Road, Shanghai, 210000, 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, 200032, China.
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270 Dongan Road, Shanghai, 200032, China. .,Department of Oncology, Shanghai Medical College, Fudan University, No. 270 Dongan Road, Shanghai, 200032, China.
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Gennaro G, Cozzi A, Schiaffino S, Sardanelli F, Caumo F. Radiation Dose of Contrast-Enhanced Mammography: A Two-Center Prospective Comparison. Cancers (Basel) 2022; 14:1774. [PMID: 35406546 PMCID: PMC8997084 DOI: 10.3390/cancers14071774] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 03/24/2022] [Accepted: 03/28/2022] [Indexed: 12/10/2022] Open
Abstract
The radiation dose associated with contrast-enhanced mammography (CEM) has been investigated only by single-center studies. In this retrospective study, we aimed to compare the radiation dose between two centers performing CEM within two prospective studies, using the same type of equipment. The CEM mean glandular dose (MGD) was computed for low energy (LE) and high energy (HE) images and their sum was calculated for each view. MGD and related parameters (entrance dose, breast thickness, compression, and density) were compared between the two centers using the Mann−Whitney test. Finally, per-patient MGD was calculated by pooling the two datasets and determining the contribution of LE and HE images. A total of 348 CEM examinations were analyzed (228 from Center 1 and 120 from Center 2). The median total MGD per view was 2.33 mGy (interquartile range 2.19−2.51 mGy) at Center 1 and 2.46 mGy (interquartile range 2.32−2.70 mGy) at Center 2, with a 0.15 mGy median difference (p < 0.001) equal to 6.2%. LE-images contributed between 64% and 77% to the total patient dose in CEM, with the remaining 23−36% being associated with HE images. The mean radiation dose for a two-view bilateral CEM exam was 4.90 mGy, about 30% higher than for digital mammography.
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Affiliation(s)
- Gisella Gennaro
- Unit of Breast Radiology, Veneto Institute of Oncology (IOV) IRCCS, Via Gattamelata 64, 35128 Padua, Italy;
| | - Andrea Cozzi
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy; (A.C.); (F.S.)
| | - Simone Schiaffino
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy;
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy; (A.C.); (F.S.)
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy;
| | - Francesca Caumo
- Unit of Breast Radiology, Veneto Institute of Oncology (IOV) IRCCS, Via Gattamelata 64, 35128 Padua, Italy;
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Khaled R, Helal M, Alfarghaly O, Mokhtar O, Elkorany A, El Kassas H, Fahmy A. Categorized contrast enhanced mammography dataset for diagnostic and artificial intelligence research. Sci Data 2022; 9:122. [PMID: 35354835 PMCID: PMC8967853 DOI: 10.1038/s41597-022-01238-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 02/22/2022] [Indexed: 12/30/2022] Open
Abstract
Contrast-enhanced spectral mammography (CESM) is a relatively recent imaging modality with increased diagnostic accuracy compared to digital mammography (DM). New deep learning (DL) models were developed that have accuracies equal to that of an average radiologist. However, most studies trained the DL models on DM images as no datasets exist for CESM images. We aim to resolve this limitation by releasing a Categorized Digital Database for Low energy and Subtracted Contrast Enhanced Spectral Mammography images (CDD-CESM) to evaluate decision support systems. The dataset includes 2006 images, with an average resolution of 2355 × 1315, consisting of 310 mass images, 48 architectural distortion images, 222 asymmetry images, 238 calcifications images, 334 mass enhancement images, 184 non-mass enhancement images, 159 postoperative images, 8 post neoadjuvant chemotherapy images, and 751 normal images, with 248 images having more than one finding. This is the first dataset to incorporate data selection, segmentation annotation, medical reports, and pathological diagnosis for all cases. Moreover, we propose and evaluate a DL-based technique to automatically segment abnormal findings in images. Measurement(s) | Dual-Energy Contrast-Enhanced Digital Spectral Mammography | Technology Type(s) | digital curation | Sample Characteristic - Organism | Homo sapiens • Breast | Sample Characteristic - Location | Egypt |
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Wang S, Wang Z, Li R, You C, Mao N, Jiang T, Wang Z, Xie H, Gu Y. Association between quantitative and qualitative image features of contrast-enhanced mammography and molecular subtypes of breast cancer. Quant Imaging Med Surg 2022; 12:1270-1280. [PMID: 35111622 DOI: 10.21037/qims-21-589] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 09/24/2021] [Indexed: 01/21/2023]
Abstract
Background The molecular subtype of breast cancer is one of the most important factors affecting patient prognosis. The study aimed to analyze the association between quantitative and qualitative features of contrast-enhanced mammography (CEM) images and breast cancer molecular subtypes. Methods This retrospective double-center study included women who underwent CEM between November 2017 and April 2020. Each patient had at least 1 malignant lesion confirmed by pathology. The CEM images were evaluated by 2 radiologists to obtain quantitative and qualitative image features. The molecular subtypes were studied as dichotomous outcomes, including luminal versus non-luminal, human epidermal growth factor receptor (HER2)-enriched versus non-HER2-enriched, and triple-negative breast cancer (TNBC) versus non-TNBC subtypes. The association between the image features and molecular subtypes was analyzed by multivariate logistic regression, with odds ratios (ORs) and 95% confidence intervals (CIs) provided. Results A total of 151 patients with 160 malignant lesions were included in the study. For quantitative features, a higher standard deviation of lesion density was associated with non-luminal (OR =0.88, 95% CI: 0.81 to 0.96, P=0.004) and HER2-enriched breast cancers (OR =1.16, 95% CI: 1.04 to 1.28, P=0.006). The relative degree of enhancement (RDE) and contrast-to-noise ratio (CNR) were not associated with molecular subtypes. However, a higher CNR/lesion size (OR =1.06, 95% CI: 1.01 to 1.12, P=0.012) was associated with luminal subtype cancers, and a higher RDE/lesion size (OR =0.94, 95% CI: 0.88 to 1.00, P=0.035) or a higher CNR/lesion size (OR =0.94, 95% CI: 0.88-1.00, P=0.038) was associated with non-TNBCs. For qualitative features, the presence of calcification was associated with HER2-enriched breast cancers (OR =2.91, 95% CI: 1.10 to 7.67, P=0.031). The presence of architectural distortion was associated with luminal cancer (OR =14.50, 95% CI: 1.91 to 110.14, P=0.010) and non-TNBC (OR =0.05, 95% CI: 0.00 to 0.43, P=0.022). Non-mass enhancement (OR =2.78, 95% CI: 1.08 to 7.14, P=0.033) was associated with HER2-enriched breast cancers. An association remained after adjustments for age, breast thickness, and breast density (all adjusted P<0.050). Conclusions The quantitative and qualitative imaging features of CEM could contribute to distinguishing breast cancer molecular subtypes.
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Affiliation(s)
- Simin Wang
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | | | - Ruimin Li
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chao You
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Qingdao, China
| | - Tingting Jiang
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhongyi Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Qingdao, China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Qingdao, China
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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Dominique C, Callonnec F, Berghian A, Defta D, Vera P, Modzelewski R, Decazes P. Deep learning analysis of contrast-enhanced spectral mammography to determine histoprognostic factors of malignant breast tumours. Eur Radiol 2022; 32:4834-4844. [PMID: 35094119 PMCID: PMC8800426 DOI: 10.1007/s00330-022-08538-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 11/06/2022]
Abstract
Objective To evaluate if a deep learning model can be used to characterise breast cancers on contrast-enhanced spectral mammography (CESM). Methods This retrospective mono-centric study included biopsy-proven invasive cancers with an enhancement on CESM. CESM images include low-energy images (LE) comparable to digital mammography and dual-energy subtracted images (DES) showing tumour angiogenesis. For each lesion, histologic type, tumour grade, estrogen receptor (ER) status, progesterone receptor (PR) status, HER-2 status, Ki-67 proliferation index, and the size of the invasive tumour were retrieved. The deep learning model used was a CheXNet-based model fine-tuned on CESM dataset. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated for the different models: images by images and then by majority voting combining all the incidences for one tumour. Results In total, 447 invasive breast cancers detected on CESM with pathological evidence, in 389 patients, which represented 2460 images analysed, were included. Concerning the ER, the deep learning model on the DES images had an AUC of 0.83 with the image-by-image analysis and of 0.85 for the majority voting. For the triple-negative analysis, a high AUC was observable for all models, in particularity for the model on LE images with an AUC of 0.90 for the image-by-image analysis and 0.91 for the majority voting. The AUC for the other histoprognostic factors was lower. Conclusion Deep learning analysis on CESM has the potential to determine histoprognostic tumours makers, notably estrogen receptor status, and triple-negative receptor status. Key Points • A deep learning model developed for chest radiography was adapted by fine-tuning to be used on contrast-enhanced spectral mammography. • The adapted models allowed to determine for invasive breast cancers the status of estrogen receptors and triple-negative receptors. • Such models applied to contrast-enhanced spectral mammography could provide rapid prognostic and predictive information. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-022-08538-4.
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Harvey JA. So Many Ways to Screen. JOURNAL OF BREAST IMAGING 2022; 4:1-2. [PMID: 38422418 DOI: 10.1093/jbi/wbab093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Indexed: 03/02/2024]
Affiliation(s)
- Jennifer A Harvey
- University of Rochester Medical Center, Department of Imaging Sciences, Rochester, NY, USA
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Konstantopoulos C, Mehta TS, Brook A, Dialani V, Mehta R, Fein-Zachary V, Phillips J. Cancer Conspicuity on Low-energy Images of Contrast-enhanced Mammography Compared With 2D Mammography. JOURNAL OF BREAST IMAGING 2022; 4:31-38. [PMID: 38422415 DOI: 10.1093/jbi/wbab085] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Indexed: 03/02/2024]
Abstract
OBJECTIVE Low-energy (LE) images of contrast-enhanced mammography (CEM) have been shown to be noninferior to digital mammography. However, our experience is that LE images are superior to 2D mammography. Our purpose was to compare cancer appearance on LE to 2D images. METHODS In this IRB-approved retrospective study, seven breast radiologists evaluated 40 biopsy-proven cancer cases on craniocaudal (CC) and mediolateral oblique (MLO) LE images and recent 2D images for cancer visibility, confidence in margins, and conspicuity of findings using a Likert scale. Objective measurements were performed using contrast-to-noise ratio (CNR) estimated from regions of interest placed on tumor and background parenchyma. Reader agreement was evaluated using Fleiss kappa. Per-reader comparisons were performed using Wilcoxon test and overall comparisons used three-way analysis of variance. RESULTS Low-energy images showed improved performance for visibility (CC LE 4.0 vs 2D 3.5, P < 0.001 and MLO LE 3.7 vs 2D 3.5, P = 0.01), confidence in margins (CC LE 3.2 vs 2D 2.8, P < 0.001 and MLO LE 3.1 vs 2D 2.9, P < 0.008), and conspicuity compared to tissue density compared to 2D mammography (CC LE 3.6 vs 2D 3.2, P < 0.001 and MLO LE 3.5 vs 2D 3.2, P < 0.001). The average CNR was significantly higher for LE than for digital mammography (CC 2.1 vs 3.2, P < 0.001 and MLO 2.1 vs 3.4, P < 0.001). CONCLUSION Our results suggest that cancers may be better visualized on the LE CEM images compared with the 2D digital mammogram.
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Affiliation(s)
| | - Tejas S Mehta
- University of Massachusetts Worcester, Department of Radiology, Worcester, MA, USA
| | - Alexander Brook
- Beth Israel Deaconess Medical Center, Department of Radiology, Boston, MA, USA
| | - Vandana Dialani
- Beth Israel Deaconess Medical Center, Department of Radiology, Boston, MA, USA
| | - Rashmi Mehta
- Newton-Wellesley Hospital, Department of Radiology, Newton, MA, USA
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Bicchierai G, Busoni S, Tortoli P, Bettarini S, Naro FD, De Benedetto D, Savi E, Bellini C, Miele V, Nori J. Single Center Evaluation of Comparative Breast Radiation dose of Contrast Enhanced Digital Mammography (CEDM), Digital Mammography (DM) and Digital Breast Tomosynthesis (DBT). Acad Radiol 2022; 29:1342-1349. [PMID: 35065889 DOI: 10.1016/j.acra.2021.12.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 12/17/2021] [Accepted: 12/22/2021] [Indexed: 11/25/2022]
Abstract
RATIONALE AND OBJECTIVES The aim of this retrospective study is to compare the radiation dose received during CEDM, short and long protocol (CEDM SP and CEDM LP), with dose received during DM and DBT on patients with varying breast thickness, age and density. MATERIALS AND METHODS Between January 2019 and December 2019, patients having 6214 DM, 3662 DBT and 173 CEDM examinations in our department were analyzed. Protocol total single breast AGD has been evaluated for all clinical imaging protocols, extracting AGD values and exposure data from the dose DICOM Structured Report (SR) information stored in the hospital PACS system. Protocol AGD was calculated as the sum of single projection AGDs carried out in every exam for each clinical protocol. A total amount of 23,383 exams for each breast were analyzed. Protocol AGDs, stratified as a function of patient breast compression thickness, age, and breast density were assessed. RESULTS The total protocol AGD median values for each protocol are: 2.8 mGy for DM, 3.2 mGy for DBT, 6.0 mGy for DM+DBT, 4.5 mGy for CEDM SP, 7.4 mGy for CEDM SP_DBT (CEDM SP protocol with DBT), 8.4 mGy for CEDM LP and 11.6 mGy for CEDM LP_DBT (CEDM LP protocol with DBT). CEDM SP AGD median value is 59% higher than DM AGD median value and 40% lesser than DM+DBT AGD median; this last difference was statistically confirmed with a p-value <0.001. AGD value for each standard breast CEDM SP projection results to be below 3-mGy limit. AGD value for each standard breast CEDM SP projection results to be below 3 mGy, as required by international legislation. For dense breasts, the AGD median value is 4.2 mGy, with the first and third quartile of 3.3 mGy and 6.0 mGy respectively; for non-dense breasts, the AGD median value is 4.7 mGy, with first and third quartile of 3.5 mGy and 6.3 mGy respectively. The difference between the two groups was statistically tested and confirmed, with a p-value of 0.039. CONCLUSION CEDM SP results in higher radiation exposure compared with conventional DM and DBT but lower than the Combo mode. The dose administered during the CEDM SP is lower in patients with dense breasts regardless of their size. An interesting outcome, considering the ongoing studies on CEDM screening in patients with dense breasts.
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Cozzi A, Schiaffino S, Fanizza M, Magni V, Menicagli L, Monaco CG, Benedek A, Spinelli D, Di Leo G, Di Giulio G, Sardanelli F. Contrast-enhanced mammography for the assessment of screening recalls: a two-centre study. Eur Radiol 2022; 32:7388-7399. [PMID: 35648209 PMCID: PMC9668944 DOI: 10.1007/s00330-022-08868-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 04/19/2022] [Accepted: 05/08/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVES To evaluate the potential of contrast-enhanced mammography (CEM) for reducing the biopsy rate of screening recalls. METHODS Recalled women were prospectively enrolled to undergo CEM alongside standard assessment (SA) through additional views, tomosynthesis, and/or ultrasound. Exclusion criteria were symptoms, implants, allergy to contrast agents, renal failure, and pregnancy. SA and CEM were independently evaluated by one of six radiologists, who recommended biopsy or 2-year follow-up. Biopsy rates according to SA or recombined CEM (rCEM) were compared with the McNemar's test. Diagnostic performance was calculated considering lesions with available final histopathology. RESULTS Between January 2019 and July 2021, 220 women were enrolled, 207 of them (median age 56.6 years) with 225 suspicious findings analysed. Three of 207 patients (1.4%) developed mild self-limiting adverse reactions to iodinated contrast agent. Overall, 135/225 findings were referred for biopsy, 90/225 by both SA and rCEM, 41/225 by SA alone and 4/225 by rCEM alone (2/4 being one DCIS and one invasive carcinoma). The rCEM biopsy rate (94/225, 41.8%, 95% CI 35.5-48.3%) was 16.4% lower (p < 0.001) than the SA biopsy rate (131/225, 58.2%, 95% CI 51.7-64.5%). Considering the 124/135 biopsies with final histopathology (44 benign, 80 malignant), rCEM showed a 93.8% sensitivity (95% CI 86.2-97.3%) and a 65.9% specificity (95% CI 51.1-78.1%), all 5 false negatives being ductal carcinoma in situ detectable as suspicious calcifications on low-energy images. CONCLUSIONS Compared to SA, the rCEM-based work-up would have avoided biopsy for 37/225 (16.4%) suspicious findings. Including low-energy images in interpretation provided optimal overall CEM sensitivity. KEY POINTS • The work-up of suspicious findings detected at mammographic breast cancer screening still leads to a high rate of unnecessary biopsies, involving between 2 and 6% of screened women. • In 207 recalled women with 225 suspicious findings, recombined images of contrast-enhanced mammography (CEM) showed a 93.8% sensitivity and a 65.9% specificity, all 5 false negatives being ductal carcinoma in situ detectable on low-energy images as suspicious calcifications. • CEM could represent an easily available one-stop shop option for the morphofunctional assessment of screening recalls, potentially reducing the biopsy rate by 16.4%.
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Affiliation(s)
- Andrea Cozzi
- grid.4708.b0000 0004 1757 2822Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milano, Italy
| | - Simone Schiaffino
- grid.419557.b0000 0004 1766 7370Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy
| | - Marianna Fanizza
- grid.419425.f0000 0004 1760 3027Department of Breast Radiology, Fondazione IRCCS Policlinico San Matteo, Viale Camillo Golgi 19, 27100 Pavia, Italy
| | - Veronica Magni
- grid.4708.b0000 0004 1757 2822Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milano, Italy
| | - Laura Menicagli
- grid.419557.b0000 0004 1766 7370Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy
| | - Cristian Giuseppe Monaco
- grid.419557.b0000 0004 1766 7370Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy
| | - Adrienn Benedek
- grid.419557.b0000 0004 1766 7370Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy
| | - Diana Spinelli
- grid.419557.b0000 0004 1766 7370Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy
| | - Giovanni Di Leo
- grid.419557.b0000 0004 1766 7370Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy
| | - Giuseppe Di Giulio
- grid.419425.f0000 0004 1760 3027Department of Breast Radiology, Fondazione IRCCS Policlinico San Matteo, Viale Camillo Golgi 19, 27100 Pavia, Italy
| | - Francesco Sardanelli
- grid.4708.b0000 0004 1757 2822Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milano, Italy ,grid.419557.b0000 0004 1766 7370Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy
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Avramova-Cholakova S, Kulama E, Daskalov S, Loveland J. PERFORMANCE COMPARISON OF SYSTEMS WITH FULL-FIELD DIGITAL MAMMOGRAPHY, DIGITAL BREAST TOMOSYNTHESIS AND CONTRAST-ENHANCED SPECTRAL MAMMOGRAPHY. RADIATION PROTECTION DOSIMETRY 2021; 197:212-229. [PMID: 34977945 DOI: 10.1093/rpd/ncab172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/12/2021] [Accepted: 11/16/2021] [Indexed: 06/14/2023]
Abstract
The purpose is to compare full-field digital mammography (FFDM), digital breast tomosynthesis (DBT) and contrast-enhanced spectral mammography (CESM) technologies on three mammography systems in terms of image quality and patient dose. Two Senographe Essential with DBT and CESM (denoted S1 and S2) and one Selenia Dimensions (S3) with FFDM and DBT were considered. Dosimetry methods recommended in the European protocol were used. Image quality was tested with CDMAM in FFDM and DBT and with ideal observer method in FFDM. Mean values of mean glandular dose (MGD) from whole patient samples on S1, S2 and S3 were as follows: FFDM 1.65, 1.84 and 2.23 mGy; DBT 2.03, 1.96 and 2.87 mGy; CESM 2.65 and 3.16 mGy, respectively. S3 exhibited better low-contrast detectability for the smallest sized discs of CDMAM and ideal observer in FFDM, and for the largest sized discs in DBT, at similar dose levels.
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Woodard S, Murray A. Contrast-Enhanced Mammography: Reviewing the Past and Looking to the Future. Semin Roentgenol 2021; 57:126-133. [DOI: 10.1053/j.ro.2021.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 12/12/2021] [Accepted: 12/13/2021] [Indexed: 01/17/2023]
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Influence of double layer filter on mean glandular dose (MGD) and image quality in low energy image of contrast enhanced spectral mammography (LE-CESM). Radiography (Lond) 2021; 28:340-347. [PMID: 34838440 DOI: 10.1016/j.radi.2021.11.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 11/08/2021] [Accepted: 11/10/2021] [Indexed: 11/24/2022]
Abstract
INTRODUCTION The aim of this study was to evaluate mean glandular dose (MGD) and image quality in low energy imaging from contrast-enhanced spectral mammography (CESM) when using double-layer filtration. METHODOLOGY A dedicated phantom was used to quantitatively estimate the MGD and image quality. The target slab of the phantom consisted of three iodine coins having a concentration of 1.0 mgI/cm3, 2.0 mgI/cm3, 4.0 mgI/cm3, a 100% adipose equivalent coin and a 100% glandular equivalent coin. The phantom was exposed using a semiautomated function at 28 k, 30 kV and 32 kV. MGD. Contrast to noise ratio (CNR) and figure of merit (FOM) were estimated for Mo/Rh, Mo/Rh + Cu, Mo/Rh + Al and Mo/Rh + Cd combinations using three breast equivalent compositions. RESULTS MGD was reduced up to a maximum of 1.03 mGy from 1.17 mGy for 100% adipose tissue. 1.18 mGy from 1.34 mGy for 50% glandular tissue and 1.39 mGy from 1.72 mGy for the 100% glandular phantom when using double-layer filtration. All of the above-mentioned results were obtained for the 50 mm phantom using 32 kV. CNR and FOM values were not significantly reduced with a double-layer filter when compared to a single-layer filter. CONCLUSION The present study concluded that Mo/Rh + Cu is the best combination to reduce the MGD significantly when compared to Mo/Rh + Al or Mo/Rh + Cd. Mo/Rh + Cu also achieved optimal image quality when compared to the Mo/Rh single filter combination. IMPLICATIONS OF PRACTICE The use of a double-layer filter in low energy imaging of CESM results in a significant reduction in MGD without degrading the quality of the image.
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The diagnostic value of contrast-enhanced 2D mammography in everyday clinical use. Sci Rep 2021; 11:22224. [PMID: 34782698 PMCID: PMC8593172 DOI: 10.1038/s41598-021-01622-7] [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: 06/11/2021] [Accepted: 10/28/2021] [Indexed: 11/09/2022] Open
Abstract
Contrast-enhanced mammography (CEM) has shown to be superior to full-field digital mammography (FFDM), but current results are dominated by studies performed on systems by one vendor. Information on diagnostic accuracy of other CEM systems is limited. Therefore, we aimed to evaluate the diagnostic performance of CEM on an alternative vendor’s system. We included all patients who underwent CEM in one hospital in 2019, except those with missing data or in whom CEM was used as response monitoring tool. Three experienced breast radiologists scored the low-energy images using the BI-RADS classification. Next, the complete CEM exams were scored similarly. Histopathological results or a minimum of one year follow-up were used as reference standard. Diagnostic performance and AUC were calculated and compared between low-energy images and the complete CEM examination, for all readers independently as well as combined. Breast cancer was diagnosed in 23.0% of the patients (35/152). Compared to low-energy images, overall CEM sensitivity increased from 74.3 to 87.6% (p < 0.0001), specificity from 87.8 to 94.6% (p = 0.0146). AUC increased from 0.872 to 0.957 (p = 0.0001). Performing CEM on the system tested, showed that, similar to earlier studies mainly performed on another vendor’s systems, both sensitivity and specificity improved when compared to FFDM.
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Hannsun G, Saponaro S, Sylvan P, Elmi A. Contrast-Enhanced Mammography: Technique, Indications, and Review of Current Literature. CURRENT RADIOLOGY REPORTS 2021. [DOI: 10.1007/s40134-021-00387-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Abstract
Purpose of Review
To provide an update on contrast-enhanced mammography (CEM) regarding current technique and interpretation, the performance of this modality versus conventional breast imaging modalities (mammography, ultrasound, and MRI), existing clinical applications, potential challenges, and pitfalls.
Recent Findings
Multiple studies have shown that the low-energy, non-contrast-enhanced images obtained when performing CEM are non-inferior to full-field digital mammography with the added benefit of recombined post-contrast images, which have been shown to provide comparable information compared to MRI without sacrificing sensitivity and negative predictive values. While CEMs' usefulness for further diagnostic characterization of indeterminate breast findings is apparent, additional studies have provided strong evidence of potential roles in screening intermediate to high-risk populations, evaluation of disease extent, and monitoring response to therapy, particularly in patients in whom MRI is either unavailable or contraindicated. Others have shown that some patients prefer CEM over MRI given the ease of performance and patient comfort. Additionally, some health systems may find significantly reduced costs compared to MRI. Currently, CEM is hindered by the limited availability of CEM-guided tissue sampling and issues of intravenous contrast administration. However, commercially available CEM-guided biopsy systems are on the horizon, and small changes in practice workflow can be quickly adopted. As of now, MRI remains a mainstay of high-risk screening, evaluation of the extent of disease, and monitoring response to therapy, but smaller studies have suggested that CEM may be equivalent to MRI for these indications, and larger confirmatory studies are needed.
Summary
CEM is an emerging problem-solving breast imaging modality that provides complementary information to conventional imaging modalities and may potentially be used in place of MRI for specific indications and/or patient populations.
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Shin HJ, Choi WJ, Park SY, Ahn SH, Son BH, Chung IY, Lee JW, Ko BS, Kim JS, Chae EY, Cha JH, Kim HH. Prediction of Underestimation Using Contrast-Enhanced Spectral Mammography in Patients Diagnosed as Ductal Carcinoma In Situ on Preoperative Core Biopsy. Clin Breast Cancer 2021; 22:e374-e386. [PMID: 34776365 DOI: 10.1016/j.clbc.2021.10.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 10/01/2021] [Accepted: 10/04/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND To assess the performance of contrast-enhanced spectral mammography (CESM) for the prediction of DCIS underestimation in comparison with mammography, breast US, and breast MRI. PATIENTS AND METHODS We prospectively enrolled patients diagnosed with DCIS on preoperative core biopsy. Visibility, lesion type, and extent on each imaging modality, CESM gray values (CGV) were evaluated. Pathologic features of core biopsy and surgery were recorded. Chi-square or Fisher's exact test were used for univariate analysis. Multivariate logistic regression analysis was used to find independent predictors for DCIS underestimation and receiver operating characteristic (ROC) curve analysis was performed. RESULTS A total of 113 lesions in 108 patients were analyzed (50 pure DCIS; 63 underestimated DCIS). Visibility on mammography, breast US, CESM, and breast MRI were 44%, 76%, 58%, and 80% for pure DCIS, and 73%, 81%, 86%, and 92% for underestimated DCIS. Tumor extents on surgical pathology of pure and underestimated DCIS were 1.11 ± 1.35 cm and 2.61 ± 2.09 cm. On multivariate analysis, nuclear grade and suspected invasion on core biopsy, visibility on mammography, and extent on breast MRI were independent factors for the model 1, whereas nuclear grade on core biopsy, extent on CESM, and mean CGV on MLO-recombined image were independent factors for the model 2. Area under ROC curve (AUC) was 0.843 for model 1 including breast MRI, whereas AUC was 0.823 for model 2 including CESM, which didn't show a significant difference (P = .968). CONCLUSION For detecting underestimated DCIS, CESM was superior to mammography and breast US, and comparable to breast MRI.
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Affiliation(s)
- Hee Jung Shin
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea.
| | - Woo Jung Choi
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Seo Young Park
- Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Sei Hyun Ahn
- Department of Breast Surgery, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Byung Ho Son
- Department of Breast Surgery, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Il Yong Chung
- Department of Breast Surgery, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Jong Won Lee
- Department of Breast Surgery, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Beom Seok Ko
- Department of Breast Surgery, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Ji Sun Kim
- Department of Breast Surgery, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Eun Young Chae
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Joo Hee Cha
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
| | - Hak Hee Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea
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Wang S, Sun Y, Mao N, Duan S, Li Q, Li R, Jiang T, Wang Z, Xie H, Gu Y. Incorporating the clinical and radiomics features of contrast-enhanced mammography to classify breast lesions: a retrospective study. Quant Imaging Med Surg 2021; 11:4418-4430. [PMID: 34603996 DOI: 10.21037/qims-21-103] [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: 01/26/2021] [Accepted: 05/11/2021] [Indexed: 12/21/2022]
Abstract
Background Contrast-enhanced mammography (CEM) is a promising breast imaging technique. A limited number of studies have focused on the radiomics analysis of CEM. We intended to explore whether a model constructed with both clinical and radiomics features of CEM can better classify benign and malignant breast lesions. Methods This retrospective, double-center study included women who underwent CEM between August 2017 and February 2020. The data from Center 1 were used as training set and the data from Center 2 were used as external testing set (training: testing =2:1). Models were constructed with the clinical, radiomics, and clinical + radiomics features of CEM. The clinical features included patient age and clinical image features interpreted by the radiologists. The radiomics features were extracted from high-energy (HE), low-energy (LE), and dual-energy subtraction (DES) images of CEM. The Mann-Whitney U test, Pearson correlation and Boruta's approach were used to select the radiomics features. Random Forest (RF) and logistic regression were used to establish the models. For the testing set, the areas under the curve (AUCs) and 95% confidence intervals (CIs) were employed to evaluate the performance of the models. For the training set, the mean AUCs were obtained by performing internal validation for 100 iterations and then compared by the Kruskal-Wallis and Mann-Whitney U tests. Results A total of 226 women (mean age: 47.4±10.1 years) with 226 pathologically proven breast lesions (101 benign; 125 malignant) were included. For the external testing set, the AUCs were 0.964 (95% CI: 0.918-1.000) for the combined model, 0.947 (95% CI: 0.891-0.997) for the radiomics model, and 0.882 (95% CI: 0.803-0.962) for the clinical model. In the internal validation process, the combined model achieved a mean AUC of 0.934±0.030, which was significantly higher than those of the radiomics (mean AUC =0.921±0.031, adjusted P<0.050) and clinical models (mean AUC =0.907±0.036; adjusted P<0.050). Conclusions Incorporating both clinical and radiomics features of CEM may achieve better classification results for breast lesions.
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Affiliation(s)
- Simin Wang
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yuqi Sun
- Department of Biostatistics, School of Public Health, Fudan University, Shanghai, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Qingdao, China
| | | | - Qin Li
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ruimin Li
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tingting Jiang
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhongyi Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Qingdao, China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Qingdao, China
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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Gilbert FJ, Hickman SE, Baxter GC, Allajbeu I, James J, Caraco C, Vinnicombe S. Opportunities in cancer imaging: risk-adapted breast imaging in screening. Clin Radiol 2021; 76:763-773. [PMID: 33820637 DOI: 10.1016/j.crad.2021.02.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 02/19/2021] [Indexed: 12/17/2022]
Abstract
In the UK, women between 50-70 years are invited for 3-yearly mammography screening irrespective of their likelihood of developing breast cancer. The only risk adaption is for women with >30% lifetime risk who are offered annual magnetic resonance imaging (MRI) and mammography, and annual mammography for some moderate-risk women. Using questionnaires, breast density, and polygenic risk scores, it is possible to stratify the population into the lowest 20% risk, who will develop <4% of cancers and the top 4%, who will develop 18% of cancers. Mammography is a good screening test but has low sensitivity of 60% in the 9% of women with the highest category of breast density (BIRADS D) who have a 2.5- to fourfold breast cancer risk. There is evidence that adding ultrasound to the screening mammogram can increase the cancer detection rate and reduce advanced stage interval and next round cancers. Similarly, alternative tests such as contrast-enhanced mammography (CESM) or abbreviated MRI (ABB-MRI) are much more effective in detecting cancer in women with dense breasts. Scintimammography has been shown to be a viable alternative for dense breasts or for follow-up in those with a personal history of breast cancer and scarring as result of treatment. For supplemental screening to be worthwhile in these women, new technologies need to reduce the number of stage II cancers and be cost effective when tested in large scale trials. This article reviews the evidence for supplemental imaging and examines whether a risk-stratified approach is feasible.
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Affiliation(s)
- F J Gilbert
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK; Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
| | - S E Hickman
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - G C Baxter
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - I Allajbeu
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK; Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - J James
- Nottingham Breast Institute, City Hospital, Nottingham, UK
| | - C Caraco
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - S Vinnicombe
- Thirlestaine Breast Centre, Cheltenham, UK; Ninewells Hospital and Medical School, University of Dundee, UK
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Kornecki A. Current Status of Contrast Enhanced Mammography: A Comprehensive Review. Can Assoc Radiol J 2021; 73:141-156. [PMID: 34492211 DOI: 10.1177/08465371211029047] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVES The purpose of this article is to provide a detailed and updated review of the physics, techniques, indications, limitations, reporting, implementation and management of contrast enhanced mammography. BACKGROUND Contrast enhanced mammography (CEM), is an emerging iodine-based modified dual energy mammography technique. In addition to having the same advantages as standard full-field digital mammography (FFDM), CEM provides information regarding tumor enhancement, relying on tumor angiogenesis, similar to dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). This article reviews current literature on CEM and highlights considerations that are critical to the successful use of this modality. CONCLUSION Multiple studies point to the advantage of using CEM in the diagnostic setting of breast imaging, which approaches that of DCE-MRI.
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Affiliation(s)
- Anat Kornecki
- Department of Medical Imaging, Breast Division, Western University, St. Joseph Health Care, London, Ontario, Canada
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Steinhof-Radwańska K, Grażyńska A, Lorek A, Gisterek I, Barczyk-Gutowska A, Bobola A, Okas K, Lelek Z, Morawska I, Potoczny J, Niemiec P, Szyluk K. Contrast-Enhanced Spectral Mammography Assessment of Patients Treated with Neoadjuvant Chemotherapy for Breast Cancer. Curr Oncol 2021; 28:3448-3462. [PMID: 34590596 PMCID: PMC8482113 DOI: 10.3390/curroncol28050298] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 09/01/2021] [Accepted: 09/02/2021] [Indexed: 11/16/2022] Open
Abstract
Background: Evaluating the tumor response to neoadjuvant chemotherapy is key to planning further therapy of breast cancer. Our study aimed to evaluate the effectiveness of low-energy and subtraction contrast-enhanced spectral mammography (CESM) images in the detection of complete response (CR) for neoadjuvant chemotherapy (NAC) in breast cancer. Methods: A total of 63 female patients were qualified for our retrospective analysis. Low-energy and subtraction CESM images just before the beginning of NAC and as a follow-up examination 2 weeks before the end of chemotherapy were compared with one another and assessed for compliance with the postoperative histopathological examination (HP). The response to preoperative chemotherapy was evaluated based on the RECIST 1.1 criteria (Response Evaluation Criteria in Solid Tumors). Results: Low-energy images tend to overestimate residual lesions (6.28 mm) and subtraction images tend to underestimate them (2.75 mm). The sensitivity of low-energy images in forecasting CR amounted to 33.33%, while the specificity was 92.86%. In the case of subtraction CESM, the sensitivity amounted to 85.71% and the specificity to 71.42%. Conclusions: CESM is characterized by high sensitivity in the assessment of CR after NAC. The use of only morphological assessment is insufficient. CESM correlates well with the size of residual lesions on histopathological examination but tends to underestimate the dimensions.
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Affiliation(s)
- Katarzyna Steinhof-Radwańska
- Department of Radiology and Nuclear Medicine, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland;
- Correspondence: ; Tel.: +48-32-358-1350
| | - Anna Grażyńska
- Students’ Scientific Society, Department of Radiology and Nuclear Medicine, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland; (A.G.); (K.O.); (Z.L.); (I.M.); (J.P.)
| | - Andrzej Lorek
- Department of Oncological Surgery, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland;
| | - Iwona Gisterek
- Department of Oncology and Radiotherapy, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland; (I.G.); (A.B.)
| | - Anna Barczyk-Gutowska
- Department of Radiology and Nuclear Medicine, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland;
| | - Agnieszka Bobola
- Department of Oncology and Radiotherapy, Prof. Kornel Gibiński Independent Public Central Clinical Hospital, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland; (I.G.); (A.B.)
| | - Karolina Okas
- Students’ Scientific Society, Department of Radiology and Nuclear Medicine, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland; (A.G.); (K.O.); (Z.L.); (I.M.); (J.P.)
| | - Zuzanna Lelek
- Students’ Scientific Society, Department of Radiology and Nuclear Medicine, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland; (A.G.); (K.O.); (Z.L.); (I.M.); (J.P.)
| | - Irmina Morawska
- Students’ Scientific Society, Department of Radiology and Nuclear Medicine, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland; (A.G.); (K.O.); (Z.L.); (I.M.); (J.P.)
| | - Jakub Potoczny
- Students’ Scientific Society, Department of Radiology and Nuclear Medicine, Medical University of Silesia, Medyków 18, 40-514 Katowice, Poland; (A.G.); (K.O.); (Z.L.); (I.M.); (J.P.)
| | - Paweł Niemiec
- Department of Biochemistry and Medical Genetics, School of Health Sciences in Katowice, Medical University of Silesia, Medyków 18, 40-752 Katowice, Poland;
| | - Karol Szyluk
- 1st Department of Orthopaedic and Trauma Surgery, District Hospital of Orthopaedics and Trauma Surgery, Bytomska 62, 41-940 Piekary Śląskie, Poland;
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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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Quantitative Breast Density in Contrast-Enhanced Mammography. J Clin Med 2021; 10:jcm10153309. [PMID: 34362092 PMCID: PMC8348046 DOI: 10.3390/jcm10153309] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/20/2021] [Accepted: 07/22/2021] [Indexed: 11/16/2022] Open
Abstract
Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the paired datasets were compared by Wilcoxon tests. A multivariate regression model was applied to analyze the relationship between VBD differences and multiple independent variables certainly or potentially affecting VBD. Median VBD was comparable for LE-CEM and DM/DBT (12.73% vs. 12.39%), not evidencing any statistically significant difference (p = 0.5855). VBD differences between LE-CEM and DM were associated with significant differences of glandular volume, breast thickness, compression force and pressure, contact area, and nipple-to-posterior-edge distance, i.e., variables reflecting differences in breast positioning (coefficient of determination 0.6023; multiple correlation coefficient 0.7761). Volumetric breast density was obtained from low-energy contrast-enhanced spectral mammography and was not significantly different from volumetric breast density measured from standard mammograms.
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Wang S, Mao N, Duan S, Li Q, Li R, Jiang T, Wang Z, Xie H, Gu Y. Radiomic Analysis of Contrast-Enhanced Mammography With Different Image Types: Classification of Breast Lesions. Front Oncol 2021; 11:600546. [PMID: 34123776 PMCID: PMC8195270 DOI: 10.3389/fonc.2021.600546] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 02/15/2021] [Indexed: 12/09/2022] Open
Abstract
Objective: A limited number of studies have focused on the radiomic analysis of contrast-enhanced mammography (CEM). We aimed to construct several radiomics-based models of CEM for classifying benign and malignant breast lesions. Materials and Methods: The retrospective, double-center study included women who underwent CEM between November 2013 and February 2020. Radiomic analysis was performed using high-energy (HE), low-energy (LE), and dual-energy subtraction (DES) images from CEM. Datasets were randomly divided into the training and testing sets at a ratio of 7:3. The maximum relevance minimum redundancy (mRMR) method and least absolute shrinkage and selection operator (LASSO) logistic regression were used to select the radiomic features and construct the best classification models. The performances of the models were assessed by the area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI). Leave-group-out cross-validation (LGOCV) for 100 rounds was performed to obtain the mean AUCs, which were compared by the Wilcoxon rank-sum test and the Kruskal–Wallis rank-sum test. Results: A total of 192 women with 226 breast lesions (101 benign; 125 malignant) were enrolled. The median age was 48 years (range, 22–70 years). For the classification of breast lesions, the AUCs of the best models were 0.931 (95% CI: 0.873–0.989) for HE, 0.897 (95% CI: 0.807–0.981) for LE, 0.882 (95% CI: 0.825–0.987) for DES images and 0.960 (95% CI: 0.910–0.998) for all of the CEM images in the testing set. According to LGOCV, the models constructed with the HE images and all of the CEM images showed the highest mean AUCs for the training (0.931 and 0.938, respectively; P < 0.05 for both) and testing sets (0.892 and 0.889, respectively; P = 0.55 for both), which were significantly higher than those of the two models constructed with the LE and DES images in the training (0.912 and 0.899, respectively; all P < 0.05) and testing sets (0.866 and 0.862, respectively; all P < 0.05). Conclusions: Radiomic analysis of CEM images was valuable for classifying benign and malignant breast lesions. The use of HE images or all three types of CEM images can achieve the best performance.
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Affiliation(s)
- Simin Wang
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, China
| | | | - Qin Li
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ruimin Li
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tingting Jiang
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhongyi Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, China
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification. Diagnostics (Basel) 2021; 11:diagnostics11050815. [PMID: 33946333 PMCID: PMC8146084 DOI: 10.3390/diagnostics11050815] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 12/29/2022] Open
Abstract
The aim of the study was to estimate the diagnostic accuracy of textural features extracted by dual-energy contrast-enhanced mammography (CEM) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. In total, 80 patients with known breast lesion were enrolled in this prospective study according to regulations issued by the local Institutional Review Board. All patients underwent dual-energy CEM examination in both craniocaudally (CC) and double acquisition of mediolateral oblique (MLO) projections (early and late). The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy, and vacuum assisted breast biopsy for benign lesions. In total, 104 samples of 80 patients were analyzed. Furthermore, 48 textural parameters were extracted by manually segmenting regions of interest. Univariate and multivariate approaches were performed: non-parametric Wilcoxon–Mann–Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), artificial neural network (NNET), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance considering the CC view (accuracy (ACC) = 0.75; AUC = 0.82) was reached with a DT trained with leave-one-out cross-variation (LOOCV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of three robust textural features (MAD, VARIANCE, and LRLGE). The best performance (ACC = 0.77; AUC = 0.83) considering the early-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of ten robust features (MEAN, MAD, RANGE, IQR, VARIANCE, CORRELATION, RLV, COARSNESS, BUSYNESS, and STRENGTH). The best performance (ACC = 0.73; AUC = 0.82) considering the late-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of eleven robust features (MODE, MEDIAN, RANGE, RLN, LRLGE, RLV, LZLGE, GLV_GLSZM, ZSV, COARSNESS, and BUSYNESS). Multivariate analyses using pattern recognition approaches, considering 144 textural features extracted from all three mammographic projections (CC, early MLO, and late MLO), optimized by adaptive synthetic sampling and feature selection operations obtained the best results (ACC = 0.87; AUC = 0.90) and showed the best performance in the discrimination of benign and malignant lesions.
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Massafra R, Bove S, Lorusso V, Biafora A, Comes MC, Didonna V, Diotaiuti S, Fanizzi A, Nardone A, Nolasco A, Ressa CM, Tamborra P, Terenzio A, La Forgia D. Radiomic Feature Reduction Approach to Predict Breast Cancer by Contrast-Enhanced Spectral Mammography Images. Diagnostics (Basel) 2021; 11:diagnostics11040684. [PMID: 33920221 PMCID: PMC8070152 DOI: 10.3390/diagnostics11040684] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 04/07/2021] [Accepted: 04/08/2021] [Indexed: 02/06/2023] Open
Abstract
Contrast-enhanced spectral mammography (CESM) is an advanced instrument for breast care that is still operator dependent. The aim of this paper is the proposal of an automated system able to discriminate benign and malignant breast lesions based on radiomic analysis. We selected a set of 58 regions of interest (ROIs) extracted from 53 patients referred to Istituto Tumori "Giovanni Paolo II" of Bari (Italy) for the breast cancer screening phase between March 2017 and June 2018. We extracted 464 features of different kinds, such as points and corners of interest, textural and statistical features from both the original ROIs and the ones obtained by a Haar decomposition and a gradient image implementation. The features data had a large dimension that can affect the process and accuracy of cancer classification. Therefore, a classification scheme for dimension reduction was needed. Specifically, a principal component analysis (PCA) dimension reduction technique that includes the calculation of variance proportion for eigenvector selection was used. For the classification method, we trained three different classifiers, that is a random forest, a naïve Bayes and a logistic regression, on each sub-set of principal components (PC) selected by a sequential forward algorithm. Moreover, we focused on the starting features that contributed most to the calculation of the related PCs, which returned the best classification models. The method obtained with the aid of the random forest classifier resulted in the best prediction of benign/malignant ROIs with median values for sensitivity and specificity of 88.37% and 100%, respectively, by using only three PCs. The features that had shown the greatest contribution to the definition of the same were almost all extracted from the LE images. Our system could represent a valid support tool for radiologists for interpreting CESM images.
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Affiliation(s)
- Raffaella Massafra
- Struttura Semplice Dipartimentale di Fisica Sanitaria, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy; (R.M.); (M.C.C.); (V.D.); (P.T.)
| | - Samantha Bove
- Dipartimento di Matematica, Università degli Studi di Bari, 70121 Bari, Italy;
| | - Vito Lorusso
- Unità Operativa Complessa di Oncologia Medica, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy; (V.L.); (A.N.)
| | - Albino Biafora
- Dipartimento di Economia e Finanza, Università degli Studi di Bari, 70124 Bari, Italy;
| | - Maria Colomba Comes
- Struttura Semplice Dipartimentale di Fisica Sanitaria, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy; (R.M.); (M.C.C.); (V.D.); (P.T.)
| | - Vittorio Didonna
- Struttura Semplice Dipartimentale di Fisica Sanitaria, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy; (R.M.); (M.C.C.); (V.D.); (P.T.)
| | - Sergio Diotaiuti
- Struttura Semplice Dipartimentale di Chirurgia, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy;
| | - Annarita Fanizzi
- Struttura Semplice Dipartimentale di Fisica Sanitaria, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy; (R.M.); (M.C.C.); (V.D.); (P.T.)
- Correspondence: ; Tel.: +39-080-555-5111
| | - Annalisa Nardone
- Unita Opertiva Complessa di Radioterapia, IRCCS Istituto Tumori ”Giovanni Paolo II”, 70124 Bari, Italy;
| | - Angelo Nolasco
- Unità Operativa Complessa di Oncologia Medica, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy; (V.L.); (A.N.)
| | - Cosmo Maurizio Ressa
- Unità Operativa Complessa di Chirurgica Plastica e Ricostruttiva, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy;
| | - Pasquale Tamborra
- Struttura Semplice Dipartimentale di Fisica Sanitaria, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy; (R.M.); (M.C.C.); (V.D.); (P.T.)
| | - Antonella Terenzio
- Unità di Oncologia Medica, Università Campus Bio-Medico, 00128 Roma, Italy;
| | - Daniele La Forgia
- Struttura Semplice Dipartimentale di Radiologia Senologica, I.R.C.C.S. Istituto Tumori “Giovanni Paolo II”, Viale Orazio Flacco 65, 70124 Bari, Italy;
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Sensakovic WF, Carnahan MB, Czaplicki CD, Fahrenholtz S, Panda A, Zhou Y, Pavlicek W, Patel B. Contrast-enhanced Mammography: How Does It Work? Radiographics 2021; 41:829-839. [PMID: 33835871 DOI: 10.1148/rg.2021200167] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Contrast-enhanced mammography (CEM) is an imaging technique that uses iodinated contrast medium to improve visualization of breast lesions and assessment of tumor neovascularity. Through modifications in x-ray energy, high- and low-energy images of the breast are combined to highlight areas of contrast medium pooling. The use of contrast material introduces different workflows, artifacts, and risks related to the contrast medium dose. In addition, the need to acquire multiple images in each view introduces different workflows, artifacts, and risks associated with the radiation dose. Although CEM and conventional mammography share many underlying principles, it is important to understand how these two mammographic examinations differ and the mechanisms that facilitate image contrast at CEM. ©RSNA, 2021.
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Affiliation(s)
- William F Sensakovic
- From the Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ 85259
| | - Molly B Carnahan
- From the Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ 85259
| | | | - Samuel Fahrenholtz
- From the Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ 85259
| | - Anshuman Panda
- From the Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ 85259
| | - Yuxiang Zhou
- From the Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ 85259
| | - William Pavlicek
- From the Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ 85259
| | - Bhavika Patel
- From the Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ 85259
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Jochelson MS, Lobbes MBI. Contrast-enhanced Mammography: State of the Art. Radiology 2021; 299:36-48. [PMID: 33650905 PMCID: PMC7997616 DOI: 10.1148/radiol.2021201948] [Citation(s) in RCA: 132] [Impact Index Per Article: 44.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 10/09/2020] [Accepted: 10/13/2020] [Indexed: 12/19/2022]
Abstract
Contrast-enhanced mammography (CEM) has emerged as a viable alternative to contrast-enhanced breast MRI, and it may increase access to vascular imaging while reducing examination cost. Intravenous iodinated contrast materials are used in CEM to enhance the visualization of tumor neovascularity. After injection, imaging is performed with dual-energy digital mammography, which helps provide a low-energy image and a recombined or iodine image that depict enhancing lesions in the breast. CEM has been demonstrated to help improve accuracy compared with digital mammography and US in women with abnormal screening mammographic findings or symptoms of breast cancer. It has also been demonstrated to approach the accuracy of breast MRI in preoperative staging of patients with breast cancer and in monitoring response after neoadjuvant chemotherapy. There are early encouraging results from trials evaluating CEM in the screening of women who are at an increased risk of breast cancer. Although CEM is a promising tool, it slightly increases radiation dose and carries a small risk of adverse reactions to contrast materials. This review details the CEM technique, diagnostic and screening uses, and future applications, including artificial intelligence and radiomics.
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Affiliation(s)
- Maxine S. Jochelson
- From the Department of Radiology, Breast Imaging Service, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065 (M.S.J.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); and GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (M.B.I.L.)
| | - Marc B. I. Lobbes
- From the Department of Radiology, Breast Imaging Service, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065 (M.S.J.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); and GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (M.B.I.L.)
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Berg WA, Bandos AI, Zuley ML, Waheed UX. Training Radiologists to Interpret Contrast-enhanced Mammography: Toward a Standardized Lexicon. JOURNAL OF BREAST IMAGING 2021; 3:176-189. [PMID: 38424825 DOI: 10.1093/jbi/wbaa115] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 12/05/2020] [Indexed: 03/02/2024]
Abstract
OBJECTIVE Using terms adapted from the BI-RADS Mammography and MRI lexicons, we trained radiologists to interpret contrast-enhanced mammography (CEM) and assessed reliability of their description and assessment. METHODS A 60-minute presentation on CEM and terminology was reviewed independently by 21 breast imaging radiologist observers. For 21 CEM exams with 31 marked findings, observers recorded background parenchymal enhancement (BPE) (minimal, mild, moderate, marked), lesion type (oval/round or irregular mass, or non-mass enhancement), intensity of enhancement (none, weak, medium, strong), enhancement quality (none, homogeneous, heterogeneous, rim), and BI-RADS assessment category (2, 3, 4A, 4B, 4C, 5). "Expert" consensus of 3 other radiologists experienced in CEM was developed. Kappa statistic was used to assess agreement between radiologists and expert consensus, and between radiologists themselves, on imaging feature categories and final assessments. Reproducibility of specific feature descriptors was assessed as fraction of consensus-concordant responses. RESULTS Radiologists demonstrated moderate agreement for BPE, (mean kappa, 0.43; range, 0.05-0.69), and lowest reproducibility for "minimal." Agreement was substantial for lesion type (mean kappa, 0.70; range, 0.47-0.93), moderate for intensity of enhancement (mean kappa, 0.57; range, 0.44-0.76), and moderate for enhancement quality (mean kappa, 0.59; range, 0.20-0.78). Agreement on final assessment was fair (mean kappa, 0.26; range, 0.09-0.44), with BI-RADS category 3 the least reproducible. Decision to biopsy (BI-RADS 2-3 vs 4-5) showed moderate agreement with consensus (mean kappa, 0.54; range, -0.06-0.87). CONCLUSION With minimal training, agreement for description of CEM findings by breast imaging radiologists was comparable to other BI-RADS lexicons.
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Affiliation(s)
- Wendie A Berg
- University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Department of Radiology, Pittsburgh, PA
| | - Andriy I Bandos
- University of Pittsburgh Graduate School of Public Health, Department of Biostatistics, Pittsburgh, PA
| | - Margarita L Zuley
- University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Department of Radiology, Pittsburgh, PA
| | - Uzma X Waheed
- University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Department of Radiology, Pittsburgh, PA
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