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Mayfield JD, Ataya D, Abdalah M, Stringfield O, Bui MM, Raghunand N, Niell B, El Naqa I. Presurgical Upgrade Prediction of DCIS to Invasive Ductal Carcinoma Using Time-dependent Deep Learning Models with DCE MRI. Radiol Artif Intell 2024; 6:e230348. [PMID: 38900042 PMCID: PMC11427917 DOI: 10.1148/ryai.230348] [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] [Indexed: 06/21/2024]
Abstract
Purpose To determine whether time-dependent deep learning models can outperform single time point models in predicting preoperative upgrade of ductal carcinoma in situ (DCIS) to invasive malignancy at dynamic contrast-enhanced (DCE) breast MRI without a lesion segmentation prerequisite. Materials and Methods In this exploratory study, 154 cases of biopsy-proven DCIS (25 upgraded at surgery and 129 not upgraded) were selected consecutively from a retrospective cohort of preoperative DCE MRI in women with a mean age of 59 years at time of diagnosis from 2012 to 2022. Binary classification was implemented with convolutional neural network (CNN)-long short-term memory (LSTM) architectures benchmarked against traditional CNNs without manual segmentation of the lesions. Combinatorial performance analysis of ResNet50 versus VGG16-based models was performed with each contrast phase. Binary classification area under the receiver operating characteristic curve (AUC) was reported. Results VGG16-based models consistently provided better holdout test AUCs than did ResNet50 in CNN and CNN-LSTM studies (multiphase test AUC, 0.67 vs 0.59, respectively, for CNN models [P = .04] and 0.73 vs 0.62 for CNN-LSTM models [P = .008]). The time-dependent model (CNN-LSTM) provided a better multiphase test AUC over single time point (CNN) models (0.73 vs 0.67; P = .04). Conclusion Compared with single time point architectures, sequential deep learning algorithms using preoperative DCE MRI improved prediction of DCIS lesions upgraded to invasive malignancy without the need for lesion segmentation. Keywords: MRI, Dynamic Contrast-enhanced, Breast, Convolutional Neural Network (CNN) Supplemental material is available for this article. © RSNA, 2024.
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MESH Headings
- Humans
- Female
- Breast Neoplasms/diagnostic imaging
- Breast Neoplasms/pathology
- Breast Neoplasms/surgery
- Deep Learning
- Middle Aged
- Magnetic Resonance Imaging/methods
- Retrospective Studies
- Carcinoma, Intraductal, Noninfiltrating/diagnostic imaging
- Carcinoma, Intraductal, Noninfiltrating/pathology
- Carcinoma, Intraductal, Noninfiltrating/surgery
- Contrast Media
- Carcinoma, Ductal, Breast/diagnostic imaging
- Carcinoma, Ductal, Breast/pathology
- Carcinoma, Ductal, Breast/surgery
- Aged
- Adult
- Predictive Value of Tests
- Image Interpretation, Computer-Assisted/methods
- Breast/diagnostic imaging
- Breast/pathology
- Breast/surgery
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Affiliation(s)
- John D Mayfield
- From the Departments of Radiology (J.D.M.), Oncologic Sciences (D.A., M.M.B., N.R., B.N.), and Medical Engineering (J.D.M.), University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, Tampa, FL 33612; and Department of Diagnostic Imaging and Interventional Radiology (D.A., B.N.), Department of Pathology (M.M.B.), Department of Cancer Physiology (N.R.), Quantitative Imaging CORE (M.A., O.S., I.E.N.), and Department of Machine Learning (M.M.B., I.E.N.), H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla
| | - Dana Ataya
- From the Departments of Radiology (J.D.M.), Oncologic Sciences (D.A., M.M.B., N.R., B.N.), and Medical Engineering (J.D.M.), University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, Tampa, FL 33612; and Department of Diagnostic Imaging and Interventional Radiology (D.A., B.N.), Department of Pathology (M.M.B.), Department of Cancer Physiology (N.R.), Quantitative Imaging CORE (M.A., O.S., I.E.N.), and Department of Machine Learning (M.M.B., I.E.N.), H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla
| | - Mahmoud Abdalah
- From the Departments of Radiology (J.D.M.), Oncologic Sciences (D.A., M.M.B., N.R., B.N.), and Medical Engineering (J.D.M.), University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, Tampa, FL 33612; and Department of Diagnostic Imaging and Interventional Radiology (D.A., B.N.), Department of Pathology (M.M.B.), Department of Cancer Physiology (N.R.), Quantitative Imaging CORE (M.A., O.S., I.E.N.), and Department of Machine Learning (M.M.B., I.E.N.), H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla
| | - Olya Stringfield
- From the Departments of Radiology (J.D.M.), Oncologic Sciences (D.A., M.M.B., N.R., B.N.), and Medical Engineering (J.D.M.), University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, Tampa, FL 33612; and Department of Diagnostic Imaging and Interventional Radiology (D.A., B.N.), Department of Pathology (M.M.B.), Department of Cancer Physiology (N.R.), Quantitative Imaging CORE (M.A., O.S., I.E.N.), and Department of Machine Learning (M.M.B., I.E.N.), H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla
| | - Marilyn M Bui
- From the Departments of Radiology (J.D.M.), Oncologic Sciences (D.A., M.M.B., N.R., B.N.), and Medical Engineering (J.D.M.), University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, Tampa, FL 33612; and Department of Diagnostic Imaging and Interventional Radiology (D.A., B.N.), Department of Pathology (M.M.B.), Department of Cancer Physiology (N.R.), Quantitative Imaging CORE (M.A., O.S., I.E.N.), and Department of Machine Learning (M.M.B., I.E.N.), H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla
| | - Natarajan Raghunand
- From the Departments of Radiology (J.D.M.), Oncologic Sciences (D.A., M.M.B., N.R., B.N.), and Medical Engineering (J.D.M.), University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, Tampa, FL 33612; and Department of Diagnostic Imaging and Interventional Radiology (D.A., B.N.), Department of Pathology (M.M.B.), Department of Cancer Physiology (N.R.), Quantitative Imaging CORE (M.A., O.S., I.E.N.), and Department of Machine Learning (M.M.B., I.E.N.), H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla
| | - Bethany Niell
- From the Departments of Radiology (J.D.M.), Oncologic Sciences (D.A., M.M.B., N.R., B.N.), and Medical Engineering (J.D.M.), University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, Tampa, FL 33612; and Department of Diagnostic Imaging and Interventional Radiology (D.A., B.N.), Department of Pathology (M.M.B.), Department of Cancer Physiology (N.R.), Quantitative Imaging CORE (M.A., O.S., I.E.N.), and Department of Machine Learning (M.M.B., I.E.N.), H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla
| | - Issam El Naqa
- From the Departments of Radiology (J.D.M.), Oncologic Sciences (D.A., M.M.B., N.R., B.N.), and Medical Engineering (J.D.M.), University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, Tampa, FL 33612; and Department of Diagnostic Imaging and Interventional Radiology (D.A., B.N.), Department of Pathology (M.M.B.), Department of Cancer Physiology (N.R.), Quantitative Imaging CORE (M.A., O.S., I.E.N.), and Department of Machine Learning (M.M.B., I.E.N.), H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla
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Le J, O’Keefe TJ, Khan S, Grossi SM, Choi HY, Ojeda-Fournier H, Armani A, Wallace AM, Blair SL. Distance of Biopsy-Confirmed High-Risk Breast Lesion from Concurrently Identified Breast Malignancy Associated with Risk of Carcinoma at the High-Risk Lesion Site. Cancers (Basel) 2024; 16:2268. [PMID: 38927976 PMCID: PMC11201489 DOI: 10.3390/cancers16122268] [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: 05/20/2024] [Revised: 06/10/2024] [Accepted: 06/14/2024] [Indexed: 06/28/2024] Open
Abstract
High-risk breast lesions including incidental intraductal papilloma without atypia (IPA), lobular hyperplasia (LCIS or ALH), flat epithelial atypia (FEA) and complex sclerosing lesion (CSL) are not routinely excised due to low upgrade rates to carcinoma. We aim to identify features of these lesions predictive of upgrade when identified concurrently with invasive disease. Methods: A single-center retrospective cohort study was performed for patients who underwent multi-site lumpectomies with invasive disease at one site and a high-risk lesion at another site between 2006 and 2021. A multinomial logistic regression was performed. Results: Sixty-five patients met the inclusion criteria. Four patients (6.2%) had an upgrade to in situ disease (DCIS) and one (1.5%) to invasive carcinoma. Three upgraded high-risk lesions were ipsilateral to the concurrent carcinoma and two were contralateral. In the multivariate model, a high-risk lesion within 5 cm of an ipsilateral malignancy was associated with increased risk of upgrade. The 3.8% upgrade rate for high-risk lesions located greater than 5 cm from ipsilateral malignancy or in the contralateral breast suggests that omission of excisional biopsy may be considered. Excisional biopsy of lesions within 5 cm of ipsilateral malignancy is recommended given the 25% upgrade risk in our series.
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Affiliation(s)
- Julie Le
- Division of Breast Surgery, The Comprehensive Breast Health Center, University of California San Diego, 3855 Health Sciences Dr, La Jolla, CA 92093, USA
| | - Thomas J. O’Keefe
- Department of Surgery, Jennifer Moreno Department of Veterans Affairs Medical Center, La Jolla, CA 92161, USA
| | - Sohini Khan
- Department of Surgery, University of California San Diego, 3855 Health Sciences Dr, La Jolla, CA 92093, USA
| | - Sara M. Grossi
- Division of Breast Surgery, The Comprehensive Breast Health Center, University of California San Diego, 3855 Health Sciences Dr, La Jolla, CA 92093, USA
- Department of Surgery, Jennifer Moreno Department of Veterans Affairs Medical Center, La Jolla, CA 92161, USA
| | - Hye Young Choi
- Division of Breast Imaging, University of California San Diego, 3855 Health Sciences Dr, La Jolla, CA 92093, USA
- Department of Medicine, Gyeongsang National University College of Medicine, Jinju-si 52727, Republic of Korea
| | - Haydee Ojeda-Fournier
- Division of Breast Imaging, University of California San Diego, 3855 Health Sciences Dr, La Jolla, CA 92093, USA
| | - Ava Armani
- Division of Breast Surgery, The Comprehensive Breast Health Center, University of California San Diego, 3855 Health Sciences Dr, La Jolla, CA 92093, USA
| | - Anne M. Wallace
- Division of Breast Surgery, The Comprehensive Breast Health Center, University of California San Diego, 3855 Health Sciences Dr, La Jolla, CA 92093, USA
| | - Sarah L. Blair
- Division of Breast Surgery, The Comprehensive Breast Health Center, University of California San Diego, 3855 Health Sciences Dr, La Jolla, CA 92093, USA
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Harper LK, Carnahan MB, Bhatt AA, Simmons CL, Patel BK, Downs E, Pockaj BA, Yancey K, Eversman SE, Sharpe RE. Imaging Characteristics of and Multidisciplinary Management Considerations for Atypical Ductal Hyperplasia and Flat Epithelial Atypia: Review of Current Literature. Radiographics 2023; 43:e230016. [PMID: 37768862 DOI: 10.1148/rg.230016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/30/2023]
Abstract
High-risk lesions of the breast are frequently encountered in percutaneous biopsy specimens. While benign, these lesions have historically undergone surgical excision due to their potential to be upgraded to malignancy. However, there is emerging evidence that a tailored management approach should be considered to reduce overtreatment of these lesions. Flat epithelial atypia (FEA) and atypical ductal hyperplasia (ADH) are two of the most commonly encountered high-risk lesions. FEA has been shown to have a relatively low rate of progression to malignancy, and some guidelines are now recommending observation over routine excision in select cases. Selective observation may be reasonable in cases where the target lesion is small and completely removed at biopsy and when there are no underlying risk factors, such as a history of breast cancer or genetic mutation or concurrent ADH. ADH has the highest potential upgrade rate to malignancy of all the high-risk lesions. Most society guidelines continue to recommend surgical excision of this lesion. More recently, some literature suggests that ADH lesions that appear completely removed at biopsy, involve limited foci (less than two or three) with no necrosis or significant atypia, manifest as a small group of mammographic calcifications, or demonstrate no enhancement at MRI may be reasonable for observation. Ultimately, management of all high-risk lesions must be based on a multidisciplinary approach that considers all patient, radiologic, clinical, and histopathologic factors. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Laura K Harper
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
| | - Molly B Carnahan
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
| | - Asha A Bhatt
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
| | - Curtis L Simmons
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
| | - Bhavika K Patel
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
| | - Erinn Downs
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
| | - Barbara A Pockaj
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
| | - Kristina Yancey
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
| | - Sarah E Eversman
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
| | - Richard E Sharpe
- From the Departments of Radiology (L.K.H., M.B.C., B.K.P., K.Y., S.E.E., R.E.S.), Pathology (E.D.), and Surgery (B.A.P.), Mayo Clinic, 5777 E Mayo Blvd, Phoenix, AZ 85054; Department of Radiology, Mayo Clinic, Rochester, Minn (A.A.B.); and Department of Radiology, Phoenix Children's Hospital, Phoenix, Ariz (C.L.S.)
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Hong M, Fan S, Yu Z, Gao C, Fang Z, Du L, Wang S, Chen X, Xu M, Zhou C. Evaluating Upstaging in Ductal Carcinoma In Situ Using Preoperative
MRI‐Based
Radiomics. J Magn Reson Imaging 2022. [DOI: 10.1002/jmri.28539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 11/12/2022] [Accepted: 11/14/2022] [Indexed: 11/29/2022] Open
Affiliation(s)
- Minping Hong
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
- Department of Radiology Jiaxin TCM Hospital Affiliated to Zhejiang Chinese Medical University Zhejiang China
- Department of Radiology The First Affiliated Hospital of Zhejiang Chinese Medical University Zhejiang China
| | - Sijia Fan
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
- Department of Radiology The First Affiliated Hospital of Zhejiang Chinese Medical University Zhejiang China
- Department of Radiology, Affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine Zhejiang China
| | - Zhexuan Yu
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
| | - Chen Gao
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
- Department of Radiology The First Affiliated Hospital of Zhejiang Chinese Medical University Zhejiang China
| | - Zhen Fang
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
- Department of Radiology The First Affiliated Hospital of Zhejiang Chinese Medical University Zhejiang China
| | - Liang Du
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
- Department of Radiology The First Affiliated Hospital of Zhejiang Chinese Medical University Zhejiang China
- Department of Radiology Hangzhou TCM Hospital of Zhejiang Chinese Medical University Zhejiang China
| | - Shiwei Wang
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
- Department of Radiology The First Affiliated Hospital of Zhejiang Chinese Medical University Zhejiang China
| | - Xiaobo Chen
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
- Department of Radiology The First Affiliated Hospital of Zhejiang Chinese Medical University Zhejiang China
| | - Maosheng Xu
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
- Department of Radiology The First Affiliated Hospital of Zhejiang Chinese Medical University Zhejiang China
| | - Changyu Zhou
- School of First Clinical Medicine Zhejiang Chinese Medical University Hangzhou China
- Department of Radiology The First Affiliated Hospital of Zhejiang Chinese Medical University Zhejiang China
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Hussein SA, EL-Dhurani S, Abdelnaby Y, Fahim M, Abdelazeem H, Moustafa AF. High-risk breast lesions: role of multi-parametric DCE-MRI in detection and histopathological upgrade prediction. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [DOI: 10.1186/s43055-022-00898-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
High-risk breast lesions represent 3–21% of all breast lesions and are non-obligate precursors of malignancy. Various studies have evaluated the value of DCE-MRI including DWI and ADC mapping in the detection of high-risk breast lesions, differentiating them from malignant lesions and predicting upgrade risk after surgical excision reducing misdiagnosis and overtreatment. This study is a retrospective review of all image-guided breast biopsy procedures performed in 2021 at our institution, identified 68 patients with histopathologically proven high-risk breast and available MRI examinations with no concurrent ipsilateral malignancy. Image analysis of MRI examinations included morphological criteria, enhancement pattern, dynamic curves, DWI and ADC mapping assessment. Since our knowledge of high-risk breast lesions is still growing, this study is important to evaluate the merits of DCE-MRI in the assessment of high-risk breast lesions, to allow optimization of treatment, better limit it to those women at risk, and avoid overtreatment in women at low risk.
Results
The mean ADC value of high-risk breast lesions was not significantly different from that of malignant breast lesions (p value = 0.015). Non-mass enhancement and type III enhancing curve proved to be significant indicators of high-risk breast lesions upgrade in surgical pathology. Cut-off average ADC value for differentiating upgraded high-risk lesions from non-upgraded high-risk lesions proved 1.24 mm2/sec with sensitivity and specificity of 94 & 100%, respectively.
Discussion
Management of high-risk breast lesions is important in the screening setting, as they are non-obligate precursors of malignancy, and also function as risk indicators. Frequency and upgrade rates of high-risk lesions detected by MRI provide a reference for clinical management. DCE-MRI has a high negative predictive value in predicting the upgrade risk of high-risk lesions. In this study, non-mass enhancement and type III curve were proven to be indicators of high-risk lesion upgrade. Limitations of the study included small number of patients and limited follow-up period.
Conclusions
The use of multi-parametric DCE-MRI including DWI and ADC mapping provides complementary information to detect high-risk breast lesions and predict their upgrade rate.
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Li X, Zhu H, Sun K, Chai W, Fu C, Yan F. Is simultaneous multi-slice readout-segmented echo-planar imaging valuable for predicting molecular subtypes of breast cancer? Eur J Radiol 2022; 150:110232. [DOI: 10.1016/j.ejrad.2022.110232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 02/15/2022] [Accepted: 02/25/2022] [Indexed: 11/03/2022]
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Kayadibi Y, Bulut IN, Aladag Kurt S, Erginöz E, Ozturk T, Velidedeoglu M, Taskin F, Esen Icten G. The Role of Superb Microvascular Imaging and Shearwave Elastography in the Evaluation of Intraductal Papilloma-Like Lesions. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2022; 41:995-1008. [PMID: 34862641 DOI: 10.1002/jum.15907] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 11/12/2021] [Accepted: 11/20/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVES The aim of this study was to investigate the role of quantitative values obtained by superb microvascular imaging (SMI) and shearwave elastography (SWE) in the prediction of malignancy in intraductal papilloma-like lesions (IDPL). METHODS In the study, 61 patients between the ages of 14 to 73 years (mean age 44) diagnosed with IDPL on ultrasound (US) examination between the years 2020 and 2021 were included. The B-Mode US findings (shape, margins, size, echo pattern, and accompanying ductal dilatation), SMI vascular index (SMIvi), E-mean, and SWE-ratio values were recorded. RESULTS There was a statistically significant difference between malignant (n = 14) and benign (n = 47) groups in terms of symptoms (P = .005), size (P = .042), shape (P = .002), margins (P = .001), echogenicity (P = .023), microcalcifications (P = .009), SMIvi (P = .031), E-mean (P < .005), and SWE-ratio (P = .007). According to receiver operating characteristic (ROC) curve analysis, sensitivity, specificity, accuracy, area under the curve (AUC), positive predictive values (PPV), and negative predictive values (NPV) were 57.1%, 87.2%, 80%, 0.722, 57.1%, 87.2% for US; 71.4%, 49%, 55.7%, 0.692, 30.3%, 85.7% for SMIvi; 85.7%, 71%, 74%, 0.864, 46%, 94.3% for E-mean, and 50%, 75.4%, 83%, 0.707, 91.5%, and 50% for SWE-ratio, respectively. Best results were obtained when SMI and SWE values were used together, achieving a sensitivity, specificity, accuracy, AUC, PPD, NPD of 78.6%, 93.6%, 93.4%, 0.872, 91.7%, and 93.9%, respectively. CONCLUSIONS The SMI and SWE examinations are successful in the differentiation of benign and malignant intraductal lesions. They complement each other and contribute to B-mode US in managing IDPLs especially when used together. Our study is the first to compare the quantitative data of SWE and SMI in the differentiation of IDPLs.
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Affiliation(s)
- Yasemin Kayadibi
- Department of Radiology, Istanbul University-Cerrahpasa, Cerrahpasa Medical Faculty, Istanbul, Turkey
| | - Iclal Nur Bulut
- Department of Radiology, Istanbul University-Cerrahpasa, Cerrahpasa Medical Faculty, Istanbul, Turkey
| | - Seda Aladag Kurt
- Department of Radiology, Istanbul University-Cerrahpasa, Cerrahpasa Medical Faculty, Istanbul, Turkey
| | - Ergin Erginöz
- Department of General Surgery, Istanbul University-Cerrahpasa, Cerrahpasa Medical Faculty, Istanbul, Turkey
| | - Tulin Ozturk
- Department of Pathology, Istanbul University-Cerrahpasa, Cerrahpasa Medical Faculty, Istanbul, Turkey
| | - Mehmet Velidedeoglu
- Department of General Surgery, Istanbul University-Cerrahpasa, Cerrahpasa Medical Faculty, Istanbul, Turkey
| | - Fusun Taskin
- Senology Research Institute, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Gul Esen Icten
- Senology Research Institute, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
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