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Kataoka M, Iima M, Miyake KK, Honda M. Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment. Invest Radiol 2024; 59:26-37. [PMID: 37994113 DOI: 10.1097/rli.0000000000001044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
ABSTRACT A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters. The increased use of ultrafast DCE-MRI has facilitated the introduction of novel kinetic parameters. In addition to DCE-MRI, diffusion-weighted imaging provides information associated with tumor cell density, with advanced diffusion-weighted imaging techniques such as intravoxel incoherent motion, diffusion kurtosis imaging, and time-dependent diffusion MRI opening up new horizons in microscale tissue evaluation. Furthermore, T2-weighted imaging plays a key role in measuring the degree of tumor aggressiveness, which may be related to the tumor microenvironment. Magnetic resonance imaging is, however, not the only imaging modality providing semiquantitative and quantitative parameters from breast tumors. Breast positron emission tomography demonstrates superior spatial resolution to whole-body positron emission tomography and allows comparable delineation of breast cancer to MRI, as well as providing metabolic information, which often precedes vascular and morphological changes occurring in response to treatment. The integration of these imaging-derived factors is accomplished through multiparametric imaging. In this article, we explore the relationship among the key imaging parameters, breast cancer diagnosis, and histological characteristics, providing a technical and theoretical background for these parameters. Furthermore, we review the recent studies on the application of multiparametric imaging to breast cancer and the significance of the key imaging parameters.
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Affiliation(s)
- Masako Kataoka
- From the Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan (M.K., M.I., M.H.); Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan (M.I.); Department of Advanced Imaging in Medical Magnetic Resonance, Graduate School of Medicine Kyoto University, Kyoto, Japan (K.K.M); and Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Japan (M.H.)
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Dietzel M, Bernathova M, Clauser P, Kapetas P, Uder M, Baltzer PAT. Added value of clinical decision rules for the management of enhancing breast MRI lesions: A systematic comparison of the Kaiser score and the Göttingen score. Eur J Radiol 2023; 169:111185. [PMID: 37939606 DOI: 10.1016/j.ejrad.2023.111185] [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: 08/17/2023] [Revised: 10/16/2023] [Accepted: 11/02/2023] [Indexed: 11/10/2023]
Abstract
PURPOSE We investigated the added value of two internationally used clinical decision rules in the management of enhancing lesions on breast MRI. METHODS This retrospective, institutional review board approved study included consecutive patients from two different populations. Patients received breast MRI according to the recommendations of the European Society of Breast Imaging (EUSOBI). Initially, all examinations were assessed by expert readers without using clinical decision rules. All lesions rated as category 4 or 5 according to the Breast Imaging Reporting and Data System were histologically confirmed. These lesions were re-evaluated by an expert reader blinded to the histology. He assigned each lesion a Göttingen score (GS) and a Kaiser score (KS) on different occasions. To provide an estimate on inter-reader agreement, a second fellowship-trained reader assessed a subset of these lesions. Subgroup analyses based on lesion type (mass vs. non-mass), size (>1 cm vs. ≤ 1 cm), menopausal status, and significant background parenchymal enhancement were conducted. The areas under the ROC curves (AUCs) for the GS and KS were compared, and the potential to avoid unnecessary biopsies was determined according to previously established cutoffs (KS > 4, GS > 3) RESULTS: 527 lesions in 506 patients were included (mean age: 51.8 years, inter-quartile-range: 43.0-61.0 years). 131/527 lesions were malignant (24.9 %; 95 %-confidence-interval: 21.3-28.8). In all subgroups, the AUCs of the KS (median = 0.91) were higher than those of the GS (median = 0.83). Except for "premenopausal patients" (p = 0.057), these differences were statistically significant (p ≤ 0.01). Kappa agreement was higher for the KS (0.922) than for the GS (0.358). CONCLUSION Both the KS and the GS provided added value for the management of enhancing lesions on breast MRI. The KS was superior to the GS in terms of avoiding unnecessary biopsies and showed superior inter-reader agreement; therefore, it may be regarded as the clinical decision rule of choice.
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Affiliation(s)
- Matthias Dietzel
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
| | - Maria Bernathova
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, Vienna, Austria.
| | - Paola Clauser
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, Vienna, Austria.
| | - Panagiotis Kapetas
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, Vienna, Austria.
| | - Michael Uder
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
| | - Pascal A T Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, Vienna, Austria.
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Clauser P, Rasul S, Kapetas P, Fueger BJ, Milos RI, Balber T, Berroterán-Infante N, Hacker M, Helbich TH, Baltzer PAT. Prospective validation of 18F-Fluoroethylcholine as a tracer in PET/MRI for the evaluation of breast lesions and prediction of lymph node status. LA RADIOLOGIA MEDICA 2023:10.1007/s11547-023-01633-6. [PMID: 37221356 DOI: 10.1007/s11547-023-01633-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/19/2023] [Indexed: 05/25/2023]
Abstract
PURPOSE To assess 18F-Fluoroethylcholine (18F-FEC) as a PET/MRI tracer in the evaluation of breast lesions, breast cancer aggressiveness, and prediction of lymph node status. MATERIALS AND METHODS This prospective, monocentric study was approved by the ethics committee and patients gave written, informed consent. This clinical trial was registered in the EudraCT database (Number 2017-003089-29). Women who presented with suspicious breast lesions were included. Histopathology was used as reference standard. Simultaneous 18F-FEC PET/MRI of the breast was performed in a prone position with a dedicated breast coil. MRI was performed using a standard protocol before and after contrast agent administration. A simultaneous read by nuclear medicine physicians and radiologists collected the imaging data of MRI-detected lesions, including the maximum standardized 18F-FEC-uptake value of breast lesions (SUVmaxT) and axillary lymph nodes (SUVmaxLN). Differences in SUVmax were evaluated with the Mann-Whitney U test. To calculate diagnostic performance, the area under the receiver operating characteristics curve (ROC) was used. RESULTS There were 101 patients (mean age 52.3 years, standard deviation 12.0) with 117 breast lesions included (30 benign, 7 ductal carcinomas in situ, 80 invasive carcinomas). 18F-FEC was well tolerated by all patients. The ROC to distinguish benign from malignant breast lesions was 0.846. SUVmaxT was higher if lesions were malignant (p < 0.001), had a higher proliferation rate (p = 0.011), and were HER2-positive (p = 0.041). SUVmaxLN was higher in metastatic lymph nodes, with an ROC of 0.761 for SUVmaxT and of 0.793 for SUVmaxLN. CONCLUSION: Simultaneous 18F-FEC PET/MRI is safe and has the potential to be used for the evaluation of breast cancer aggressiveness, and prediction of lymph node status.
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Affiliation(s)
- Paola Clauser
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Sazan Rasul
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Panagiotis Kapetas
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Barbara J Fueger
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Ruxandra-Iulia Milos
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Theresa Balber
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Neydher Berroterán-Infante
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Marcus Hacker
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Thomas Hans Helbich
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Structural Preclinical Imaging, Medical University of Vienna, Vienna, Austria
| | - Pascal Andreas Thomas Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
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Zhang J, Zhang Z, Mao N, Zhang H, Gao J, Wang B, Ren J, Liu X, Zhang B, Dou T, Li W, Wang Y, Jia H. Radiomics nomogram for predicting axillary lymph node metastasis in breast cancer based on DCE-MRI: A multicenter study. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2023; 31:247-263. [PMID: 36744360 DOI: 10.3233/xst-221336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
OBJECTIVES This study aims to develop and validate a radiomics nomogram based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to noninvasively predict axillary lymph node (ALN) metastasis in breast cancer. METHODS This retrospective study included 263 patients with histologically proven invasive breast cancer and who underwent DCE-MRI examination before surgery in two hospitals. All patients had a defined ALN status based on pathological examination results. Regions of interest (ROIs) of the primary tumor and ipsilateral ALN were manually drawn. A total of 1,409 radiomics features were initially computed from each ROI. Next, the low variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) algorithms were used to extract the radiomics features. The selected radiomics features were used to establish the radiomics signature of the primary tumor and ALN. A radiomics nomogram model, including the radiomics signature and the independent clinical risk factors, was then constructed. The predictive performance was evaluated by the receiver operating characteristic (ROC) curves, calibration curve, and decision curve analysis (DCA) by using the training and testing sets. RESULTS ALNM rates of the training, internal testing, and external testing sets were 43.6%, 44.3% and 32.3%, respectively. The nomogram, including clinical risk factors (tumor diameter) and radiomics signature of the primary tumor and ALN, showed good calibration and discrimination with areas under the ROC curves of 0.884, 0.822, and 0.813 in the training, internal and external testing sets, respectively. DCA also showed that radiomics nomogram displayed better clinical predictive usefulness than the clinical or radiomics signature alone. CONCLUSIONS The radiomics nomogram combined with clinical risk factors and DCE-MRI-based radiomics signature may be used to predict ALN metastasis in a noninvasive manner.
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Affiliation(s)
- Jiwen Zhang
- Department of First Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Zhongsheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Haicheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Jing Gao
- School of Medical Imaging, Binzhou Medical University, Yantai, China
| | - Bin Wang
- Department of Breast Surgery, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jianlin Ren
- Department of Breast Surgery, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xin Liu
- Department of Breast Surgery, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Binyue Zhang
- Department of First Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Tingyao Dou
- Department of First Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Wenjuan Li
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Yanhong Wang
- Department of Microbiology and immunology, Shanxi Medical University, Taiyuan, China
| | - Hongyan Jia
- Department of Breast Surgery, First Hospital of Shanxi Medical University, Taiyuan, China
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Prvulovic Bunovic N, Sveljo O, Kozic D, Boban J. Is Elevated Choline on Magnetic Resonance Spectroscopy a Reliable Marker of Breast Lesion Malignancy? Front Oncol 2021; 11:610354. [PMID: 34567998 PMCID: PMC8462297 DOI: 10.3389/fonc.2021.610354] [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: 09/25/2020] [Accepted: 08/20/2021] [Indexed: 12/15/2022] Open
Abstract
Background Contemporary magnetic resonance imaging (MRI) of the breast represents a powerful diagnostic modality for cancer detection, with excellent sensitivity and high specificity. Magnetic resonance spectroscopy (MRS) is being explored as an additional tool for improving specificity in breast cancer detection, using multiparametric MRI. The aim of this study was to examine the possibility of 1H-MRS to discriminate malignant from benign breast lesions, using elevated choline (Cho) peak as an imaging biomarker. Methods A total of 60 patients were included in this prospective study: 30 with malignant (average age, 55.2 years; average lesion size, 35 mm) and 30 with benign breast lesions (average age, 44.8 years; average lesion size, 20 mm), who underwent multiparametric MRI with multivoxel 3D 1H-MRS on a 1.5-T scanner in a 3-year period. Three patients with benign breast lesions were excluded from the study. All lesions were histologically verified. Peaks identified on 1H-MRS were lipid (0.9, 2.3, 2.8, and 5.2 ppm), choline (3.2 ppm), and water peaks (4.7 ppm). Sensitivity and specificity, as well as positive and negative predictive values, were defined using ROC curves. Cohen's Kappa test of inter-test reliability was performed [testing the agreement between 1H-MRS and histologic finding, and 1H-MRS and MR mammography (MRM)]. Results Choline peak was elevated in 24/30 malignant lesions and in 20/27 benign breast lesions. The sensitivity of 1H-MRS was 0.8, specificity was 0.741, positive predictive value was 0.774, and negative predictive value was 0.769. Area under ROC was 0.77 (CI 0.640-0.871). Inter-test reliability between 1H-MRS and histologic finding was 0.543 (moderate agreement) and that between 1H-MRS and MRM was 0.573 (moderate agreement). False-negative findings were most frequently observed in invasive lobular cancers, while false-positive findings were most frequently observed in adenoid fibroadenomas. Conclusion Although elevation of the choline peak has a good sensitivity and specificity in breast cancer detection, both are significantly lower than those of multiparametric MRM. Inclusion of spectra located on tumor margins as well as analysis of lipid peaks could aid both sensitivity and specificity. An important ratio of false-positive and false-negative findings in specific types of breast lesions (lobular cancer and adenoid fibroadenoma) suggests interpreting these lesions with a caveat.
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Affiliation(s)
- Natasa Prvulovic Bunovic
- Department of Radiology, Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia.,Center for Diagnostic Imaging, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia
| | - Olivera Sveljo
- Center for Diagnostic Imaging, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia.,Department for Telecommunications and Signal Processing, Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia
| | - Dusko Kozic
- Department of Radiology, Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia.,Center for Diagnostic Imaging, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia
| | - Jasmina Boban
- Department of Radiology, Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia.,Center for Diagnostic Imaging, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia
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Iorio E, Podo F, Leach MO, Koutcher J, Blankenberg FG, Norfray JF. A novel roadmap connecting the 1H-MRS total choline resonance to all hallmarks of cancer following targeted therapy. Eur Radiol Exp 2021; 5:5. [PMID: 33447887 PMCID: PMC7809082 DOI: 10.1186/s41747-020-00192-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 10/29/2020] [Indexed: 11/15/2022] Open
Abstract
This review describes a cellular adaptive stress signalling roadmap connecting the 1H magnetic resonance spectroscopy (MRS) total choline peak at 3.2 ppm (tCho) to cancer response after targeted therapy (TT). Recent research on cell signalling, tCho metabolism, and TT of cancer has been retrospectively re-examined. Signalling research describes how the unfolded protein response (UPR), a major stress signalling network, transduces, regulates, and rewires the total membrane turnover in different cancer hallmarks after a TT stress. In particular, the UPR signalling maintains or increases total membrane turnover in all pro-survival hallmarks, whilst dramatically decreases turnover during apoptosis, a pro-death hallmark. Recent research depicts the TT-induced stress as a crucial event responsible for interrupting UPR pro-survival pathways, leading to an UPR-mediated cell death. The 1H-MRS tCho resonance represents the total mobile precursors and products during the enzymatic modification of phosphatidylcholine membrane abundance. The tCho profile represents a biomarker that noninvasively monitors TT-induced enzymatic changes in total membrane turnover in a wide variety of existing and new anticancer treatments targeting specific layers of the UPR signalling network. Our overview strongly suggests further evaluating and validating the 1H-MRS tCho peak as a powerful noninvasive imaging biomarker of cancer response in TT clinical trials.
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Affiliation(s)
- Egidio Iorio
- High Resolution NMR Unit-Core Facilities, Istituto Superiore di Sanità, Viale Regina Elena, 299, 00161, Roma, Italy.
| | - Franca Podo
- High Resolution NMR Unit-Core Facilities, Istituto Superiore di Sanità, Viale Regina Elena, 299, 00161, Roma, Italy
| | - Martin O Leach
- MRI Unit, Royal Marsden Hospital, Downs Road, Sutton, Surrey, SM2 5PT, UK
| | - Jason Koutcher
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | | | - Joseph F Norfray
- Emeritus, Chicago Northside MRI Center, 2818 N. Sheridan Rd, Chicago, IL, 60657, USA
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Mao N, Dai Y, Lin F, Ma H, Duan S, Xie H, Zhao W, Hong N. Radiomics Nomogram of DCE-MRI for the Prediction of Axillary Lymph Node Metastasis in Breast Cancer. Front Oncol 2021; 10:541849. [PMID: 33381444 PMCID: PMC7769044 DOI: 10.3389/fonc.2020.541849] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 09/29/2020] [Indexed: 12/14/2022] Open
Abstract
Purpose This study aimed to establish and validate a radiomics nomogram based on dynamic contrast-enhanced (DCE)-MRI for predicting axillary lymph node (ALN) metastasis in breast cancer. Method This retrospective study included 296 patients with breast cancer who underwent DCE-MRI examinations between July 2017 and June 2018. A total of 396 radiomics features were extracted from primary tumor. In addition, the least absolute shrinkage and selection operator (LASSO) algorithm was used to select the features. Radiomics signature and independent risk factors were incorporated to build a radiomics nomogram model. Calibration and receiver operator characteristic (ROC) curves were used to confirm the performance of the nomogram in the training and validation sets. The clinical usefulness of the nomogram was evaluated by decision curve analysis (DCA). Results The radiomics signature consisted of three ALN-status-related features, and the nomogram model included the radiomics signature and the MR-reported lymph node (LN) status. The model showed good calibration and discrimination with areas under the ROC curve (AUC) of 0.92 [95% confidence interval (CI), 0.87-0.97] in the training set and 0.90 (95% CI, 0.85-0.95) in the validation set. In the MR-reported LN-negative (cN0) subgroup, the nomogram model also exhibited favorable discriminatory ability (AUC, 0.79; 95% CI, 0.70-0.87). DCA findings indicated that the nomogram model was clinically useful. Conclusions The MRI-based radiomics nomogram model could be used to preoperatively predict the ALN metastasis of breast cancer.
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Affiliation(s)
- Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
| | - Yi Dai
- Department of Radiology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Fan Lin
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
| | - Shaofeng Duan
- Precision Health Institution, GE Healthcare, China, Shanghai, China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
| | - Wenlei Zhao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
| | - Nan Hong
- Department of Radiology, Peking University People's Hospital, Beijing, China
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Radiomics nomogram of contrast-enhanced spectral mammography for prediction of axillary lymph node metastasis in breast cancer: a multicenter study. Eur Radiol 2020; 30:6732-6739. [DOI: 10.1007/s00330-020-07016-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Revised: 04/06/2020] [Accepted: 06/05/2020] [Indexed: 12/13/2022]
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