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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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Goh Y, Quek ST, Pillay P, Chou CP. Evaluation of architectural distortion with contrast-enhanced mammography. Clin Radiol 2024; 79:163-169. [PMID: 38114374 DOI: 10.1016/j.crad.2023.11.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 11/20/2023] [Accepted: 11/21/2023] [Indexed: 12/21/2023]
Abstract
Architectural distortion (AD) is the third most common abnormality detected on mammograms. In the absence of an accurate non-invasive tool to evaluate ADs, clinical management often requires surgical excision for histological diagnosis. This problem is expected to worsen with the growing use of digital breast tomosynthesis (DBT) and the resultant increasing detection of ADs. There is therefore a great clinical need for a diagnostic imaging tool to complement non-enhanced mammography for the evaluation of AD. Contrast-enhanced mammography (CEM) is an emerging breast imaging method that uses contrast media and the principle of dual-energy subtraction to evaluate vascularity of suspicious breast lesions. CEM, a cost-effective alternative to breast magnetic resonance imaging (MRI), can be used to evaluate AD by juxtaposing CEM images with non-enhanced mammograms for comparison. In this review, the authors aim to provide readers with an overview of the interpretation of AD on CEM using imaging examples. Relevant imaging features of CEM and their respective significance will be matched with information from a literature review. Finally, the authors would like to highlight the added value of CEM in relevant clinical applications in the assessment of AD.
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Affiliation(s)
- Y Goh
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd 119074, Singapore
| | - S T Quek
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd 119074, Singapore
| | - P Pillay
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd 119074, Singapore
| | - C-P Chou
- Kaohsiung Veterans General Hospital, Radiology Department, No. 386, Dazhong 1st Rd, Zuoying Dist., Kaohsiung City 81362, Taiwan, ROC.
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DiPrete O, Wei CJ, Phillips J, Fishman MDC, Slanetz PJ, Lotfi P, Brook A, Dialani V. Management of Mammographic Architectural Distortion Based on Contrast-enhanced MRI and US Correlation. JOURNAL OF BREAST IMAGING 2023; 5:425-435. [PMID: 38416901 DOI: 10.1093/jbi/wbad032] [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: 11/20/2022] [Indexed: 03/01/2024]
Abstract
OBJECTIVE The objective was to evaluate outcomes of mammographic architectural distortion (AD) with and without MRI and US correlates. METHODS A retrospective review of unexplained mammographic AD with subsequent MRI from January 1, 2007 to September 30, 2017 was performed using a reader-based study design. Mammographic, MRI, and US features and outcomes were documented. Truth was based on biopsy results or minimum two-year imaging follow-up. Measures of diagnostic accuracy were calculated. RESULTS Fifty-six cases of AD were included: 29 (51.8%) detected on 2D mammogram and 27 (48.2%) detected on digital breast tomosynthesis. Of 35.7% (20/56) with MRI correlate, 40.0% (8/20) were enhancing masses, 55.0% (11/20) were non-mass enhancement (NME), and 5.0% (1/20) were nonenhancing AD. Of eight enhancing masses, 75.0% (6/8) were invasive cancers, and 25.0% (2/8) were high-risk lesions. Of 11 NME, 18.2% (2/11) were ductal carcinoma in situ, 36.4% (4/11) were high-risk lesions, and 45.4% (5/11) were benign. Of 64.3% (36/56) without MRI correlate, 94.4% (34/36) were benign by pathology or follow-up, one (2.8%, 1/36) was a 4-mm focus of invasive cancer with US correlate, and one (1/36, 2.8%) was a high-risk lesion. Of cases without MRI and US correlates, one (3.0%, 1/33) was a high-risk lesion and 97.0% (32/33) were benign. The negative predictive value of mammographic AD without MRI correlate was 97.2% (35/36) and without both MRI and US correlates was 100.0% (33/33). CONCLUSION Mammographic AD without MRI or US correlate was not cancer in our small cohort and follow-up could be considered, reducing interventions.
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Affiliation(s)
- Olivia DiPrete
- Beth Israel Deaconess Medical Center, Department of Radiology, Boston, MA, USA
| | - Catherine J Wei
- Mass General Brigham - Salem Hospital, Department of Radiology, Salem, MA, USA
| | | | | | | | - Parisa Lotfi
- Danbury Radiological Associates, Department of Radiology, Danbury, CT, 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
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Liu J, Xu M, Ren J, Li Z, Xi L, Chen B. Synthetic MRI, multiplexed sensitivity encoding, and BI-RADS for benign and malignant breast cancer discrimination. Front Oncol 2023; 12:1080580. [PMID: 36818669 PMCID: PMC9936239 DOI: 10.3389/fonc.2022.1080580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 12/14/2022] [Indexed: 02/05/2023] Open
Abstract
Objective To assess the diagnostic value of predictive models based on synthetic magnetic resonance imaging (syMRI), multiplexed sensitivity encoding (MUSE) sequences, and Breast Imaging Reporting and Data System (BI-RADS) in the differentiation of benign and malignant breast lesions. Methods Clinical and MRI data of 158 patients with breast lesions who underwent dynamic contrast-enhanced MRI (DCE-MRI), syMRI, and MUSE sequences between September 2019 and December 2020 were retrospectively collected. The apparent diffusion coefficient (ADC) values of MUSE and quantitative relaxation parameters (longitudinal and transverse relaxation times [T1, T2], and proton density [PD] values) of syMRI were measured, and the parameter variation values and change in their ratios were calculated. The patients were randomly divided into training (n = 111) and validation (n = 47) groups at a ratio of 7:3. A nomogram was built based on univariate and multivariate logistic regression analyses in the training group and was verified in the validation group. The discriminatory and predictive capacities of the nomogram were assessed by the receiver operating characteristic curve and area under the curve (AUC). The AUC was compared by DeLong test. Results In the training group, univariate analysis showed that age, lesion diameter, menopausal status, ADC, T2pre, PDpre, PDGd, T2Delta, and T2ratio were significantly different between benign and malignant breast lesions (P < 0.05). Multivariate logistic regression analysis showed that ADC and T2pre were significant variables (all P < 0.05) in breast cancer diagnosis. The quantitative model (model A: ADC, T2pre), BI-RADS model (model B), and multi-parameter model (model C: ADC, T2pre, BI-RADS) were established by combining the above independent variables, among which model C had the highest diagnostic performance, with AUC of 0.965 and 0.986 in the training and validation groups, respectively. Conclusions The prediction model established based on syMRI, MUSE sequence, and BI-RADS is helpful for clinical differentiation of breast tumors and provides more accurate information for individualized diagnosis.
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Affiliation(s)
- Jinrui Liu
- School of Clinical Medicine, Ningxia Medical University, Yinchuan, China
| | - Mengying Xu
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Jialiang Ren
- Department of Pharmaceuticals Diagnostics, GE Healthcare, Beijing, China
| | - Zhihao Li
- Department of Pharmaceuticals Diagnostics, GE Healthcare, Xi’an, China
| | - Lu Xi
- Sales Department, GE Healthcare, Yinchuan, China
| | - Bing Chen
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China,*Correspondence: Bing Chen,
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Abstract
BACKGROUND The implementation of digital breast tomosynthesis has increased the detection of architectural distortion (AD). Managing this finding may be experienced as a clinical dilemma in daily practice. Breast Contrast-Enhanced MRI (CE-BMR) is a known modality in case of problem-solving tool for mammographic abnormalities. However, the data about AR and CE-BMR are scant. OBJECTIVE The purpose was to estimate the benefit of CE-BMR in the setting of architectural distortion detected mammographically through a systematic review and meta-analysis of the literature. METHODS A search of MEDLINE and EMBASE databases were conducted in 2020. Based on the PRISMA guidelines, an analysis was performed using the chi-square test of independence to determine if there was a significant association between the result of the test (positive or negative) and the participant condition (malignant or non-malignant). RESULTS Four studies were available. The negative predictive value (NPV) was 98.3% to 100%. The result of the chi-square indicated that there was significant association between the participant test result and the participant condition for the included publications (X(1,175)2= 84.051, p = 0.0001). CONCLUSIONS The high NPV could allow for deferral of a biopsy in favor of a short-interval imaging follow-up in the setting of a negative CE-BMR.
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Affiliation(s)
| | - Cherie M Kuzmiak
- Department of Radiology, UNC School of Medicine, Chapel Hill, NC, USA
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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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Architectural distortion outcome: digital breast tomosynthesis-detected versus digital mammography-detected. Radiol Med 2021; 127:30-38. [PMID: 34665431 DOI: 10.1007/s11547-021-01419-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Accepted: 09/29/2021] [Indexed: 12/30/2022]
Abstract
OBJECTIVES To compare the outcome for DBT-detected and DM-detected suspicious AD, to evaluate the risk of malignancy and if is affected by the US or MRI imaging correlation. METHODS All cases with suspicious AD (ultimately assigned BI-RADS 4 or 5 categories) were retrospectively included. Two radiologists independently reviewed DM and DBT images in two sessions for detection (DM vs. DBT). US and MRI imaging correlation findings were recorded. Pathologic results were compared between DBT-detected and DM-detected AD. RESULTS Among 137 detected ADs, 103 (75.2%) were DM-detected, and 34 (24.8%) were only DBT-detected (p = 0.01). The malignancy rate was lower for DBT-detected than DM-detected AD (14.7% vs. 45.6%) (p = 0.01). Malignancy rate was higher with US-positive than US-negative correlation at DM-detected AD (49.4% vs. 27.8%) (p = 0.01). Malignancy rate was not different for DBT-detected AD with (16.7%) or without (12.5%) sonographic correlation. NPV based on radiologists' level of suspicion was high (86.2%-97.2%) but not sufficient enough to forgo biopsy. Of 34 sonographically occult ADs, a positive-MRI correlation was identified in 19 (55.9%) ADs (7 were malignant, 12 were benign). A negative-MRI correlation was identified in 15 (44.1%) ADs; all had a benign outcome (p = 0.01). CONCLUSIONS DBT-detected AD is less likely to represent malignancy than does DM-detected; however, the risk of malignancy is not low enough to forgo biopsy. MRI-negative correlation in sonographically occult AD was significantly associated with benign outcomes and can avoid unnecessary interventions.
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Zhu CR, Chen KY, Li P, Xia ZY, Wang B. Accuracy of multiparametric MRI in distinguishing the breast malignant lesions from benign lesions: a meta-analysis. Acta Radiol 2021; 62:1290-1297. [PMID: 33059458 DOI: 10.1177/0284185120963900] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND The sensitivity of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for detecting breast cancer was high and the specificity was relatively low. However, diffusion-weighted imaging (DWI) has a high specificity in the diagnosis of malignant lesions. PURPOSE To evaluate the accuracy of the multiparametric MRI (mp-MRI) in distinguishing the breast malignant lesions from the benign lesions. MATERIAL AND METHODS A comprehensive search of the PubMed, Embase, and Cochrane Library electronic databases was conducted up to March 2020. Data were analyzed for the following indexes: pooled sensitivity and specificity; positive likelihood ratio; negative likelihood ratio; diagnostic odds ratio; and the area under the curve. RESULTS A total of 2356 patients with 1604 malignant and 967 benign breast lesions were included from 22 studies. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the curve for mp-MRI were 0.93, 0.85, 6.3, 0.08, 81, and 0.96, respectively. The pooled sensitivity, specificity, and area under the curve for DCE-MRI alone were 0.95, 0.71, and 0.92, respectively. The pooled sensitivity, specificity, and area under the curve for DWI alone were 0.88, 0.84, and 0.93, respectively. CONCLUSION The mp-MRI did not improve the sensitivity but increased the specificity for the diagnosis of breast malignant lesions.
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Affiliation(s)
- Chun-Rong Zhu
- North Sichuan Medical College, Nanchong, Sichuan, PR China
| | - Ke-Yu Chen
- North Sichuan Medical College, Nanchong, Sichuan, PR China
| | - Pan Li
- North Sichuan Medical College, Nanchong, Sichuan, PR China
| | - Zhi-Yang Xia
- North Sichuan Medical College, Nanchong, Sichuan, PR China
| | - Bin Wang
- Department of Breast and Thyroid Surgery, The Third People’s Hospital of Chengdu, Chengdu, Sichuan, PR China
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Zhang B, Song L, Yin J. Texture Analysis of DCE-MRI Intratumoral Subregions to Identify Benign and Malignant Breast Tumors. Front Oncol 2021; 11:688182. [PMID: 34307153 PMCID: PMC8299951 DOI: 10.3389/fonc.2021.688182] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/15/2021] [Indexed: 12/13/2022] Open
Abstract
Purpose To evaluate the potential of the texture features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) intratumoral subregions to distinguish benign from malignant breast tumors. Materials and Methods A total of 299 patients with pathologically verified breast tumors who underwent breast DCE-MRI examination were enrolled in this study, including 124 benign cases and 175 malignant cases. The whole tumor area was semi-automatically segmented on the basis of subtraction images of DCE-MRI in Matlab 2018b. According to the time to peak of the contrast agent, the whole tumor area was partitioned into three subregions: early, moderate, and late. A total of 467 texture features were extracted from the whole tumor area and the three subregions, respectively. Patients were divided into training (n = 209) and validation (n = 90) cohorts by different MRI scanners. The least absolute shrinkage and selection operator (LASSO) method was used to select the optimal feature subset in the training cohort. The Kolmogorov-Smirnov test was first performed on texture features selected by LASSO to test whether the samples followed a normal distribution. Two machine learning methods, decision tree (DT) and support vector machine (SVM), were used to establish classification models with a 10-fold cross-validation method. The performance of the classification models was evaluated with receiver operating characteristic (ROC) curves. Results In the training cohort, the areas under the ROC curve (AUCs) for the DT_Whole model and SVM_Whole model were 0.744 and 0.806, respectively. In contrast, the AUCs of the DT_Early model (P = 0.004), DT_Late model (P = 0.015), SVM_Early model (P = 0.002), and SVM_Late model (P = 0.002) were significantly higher: 0.863 (95% CI, 0.808-0.906), 0.860 (95% CI, 0.806-0.904), 0.934 (95% CI, 0.891-0.963), and 0.921 (95% CI, 0.876-0.954), respectively. The SVM_Early model and SVM_Late model achieved better performance than the DT_Early model and DT_Late model (P = 0.003, 0.034, 0.008, and 0.026, respectively). In the validation cohort, the AUCs for the DT_Whole model and SVM_Whole model were 0.670 and 0.708, respectively. In comparison, the AUCs of the DT_Early model (P = 0.006), DT_Late model (P = 0.043), SVM_Early model (P = 0.001), and SVM_Late model (P = 0.007) were significantly higher: 0.839 (95% CI, 0.747-0.908), 0.784 (95% CI, 0.601-0.798), 0.890 (95% CI, 0.806-0.946), and 0.865 (95% CI, 0.777-0.928), respectively. Conclusion The texture features from intratumoral subregions of breast DCE-MRI showed potential in identifying benign and malignant breast tumors.
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Affiliation(s)
- Bin Zhang
- School of Medicine and Bioinformatics Engineering, Northeastern University, Shenyang, China
| | - Lirong Song
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Jiandong Yin
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
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Goh Y, Chan CW, Pillay P, Lee HS, Pan HB, Hung BH, Quek ST, Chou CP. Architecture distortion score (ADS) in malignancy risk stratification of architecture distortion on contrast-enhanced digital mammography. Eur Radiol 2020; 31:2657-2666. [PMID: 33125555 PMCID: PMC8043942 DOI: 10.1007/s00330-020-07395-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 08/15/2020] [Accepted: 10/08/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To develop a risk predictor model in evaluation of tomosynthesis-detected architectural distortion (AD) based on characteristics of contrast-enhanced digital mammography (CEDM). METHODS Ninety-four AD lesions on CEDM in combination with tomosynthesis were retrospectively reviewed from 92 consecutive women (mean age, 52.4 years ± 7.9) with abnormal diagnostic or screening mammography. CEDM results were correlated with histology of ADs using cross-tabulation for statistical analysis. Predictors for risk of malignancy from CEDM characteristics (background parenchyma enhancement, degree of AD enhancement, enhancing morphology, size of enhancement, and enhancing spiculations) and patient's age were evaluated using logistic regression. We propose a sum score, termed AD score (ADS), for risk stratification and corresponding suggested BI-RADS category. RESULTS Thirty-three of ninety-four (35.1%) of detected AD lesions were malignant. The sensitivity, specificity, PPV, and NPV of CEDM in evaluation of malignant AD are 100%, 42.6%, 48.5%, and 100%, respectively. Absence of AD enhancement on CEDM is highly indicative of no underlying malignancy. On multivariate analysis, the predictors on CEDM with statistical significance are (1) marked intensity of AD enhancement (OR, 22.6; 95%CI 3.1, 166.6; p = .002); and (2) presence of enhancing spiculations (OR, 9.1; 95%CI 2.2, 36.5; p = .002). A prediction model whose scores (ADS) given by ranking of OR of all predictors with AUC of 0.934 and Brier score of 0.0956 was developed. CONCLUSION ADS-based lesion characterization on CEDM enables risk assessment of tomosynthesis-detected AD lesions. KEY POINTS • Architecture distortions presenting with marked enhancement intensity and presence of enhancing spiculations are highly associated with risk of malignancy. • Absence of architecture distortion enhancement in minimal or mild background parenchyma enhancement on CEDM indicates low risk of breast malignancy (NPV = 100%).
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Affiliation(s)
- Yonggeng Goh
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.
| | - Ching Wan Chan
- Department of Breast Surgery, National University Hospital, Singapore, Singapore
| | - Premilla Pillay
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | - Herng-Sheng Lee
- Department of Pathology and Laboratory Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Huay-Ben Pan
- Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Bao-Hui Hung
- Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | - Chen-Pin Chou
- Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. .,Department of Medical Laboratory Sciences and Biotechnology, Fooyin University, Kaohsiung, Taiwan.
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Wielema M, Dorrius MD, Pijnappel RM, De Bock GH, Baltzer PAT, Oudkerk M, Sijens PE. Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis. PLoS One 2020; 15:e0232856. [PMID: 32374781 PMCID: PMC7202642 DOI: 10.1371/journal.pone.0232856] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 04/22/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from malignant breast lesions in DWI in terms of sensitivity, specificity and area under the curve (AUC). METHODS AND FINDINGS In this systematic review and meta-analysis, adhering to the PRISMA statement, 61 studies, with 65 study subsets, in females with benign or malignant primary breast lesions (6291 lesions) were assessed. Studies on DWI, quantified by ADC, scanned on 1.5 and 3.0 Tesla and using b-values 0/50 and ≥ 800 s/mm2 were included. PubMed and EMBASE were searched for studies up to 23-10-2019 (n = 2897). Data were pooled based on four BTTS methods (by definition of measured region of interest, ROI): BTTS1: whole breast tumor tissue selection, BTTS2: subtracted whole breast tumor tissue selection, BTTS3: circular breast tumor tissue selection and BTTS4: lowest diffusion breast tumor tissue selection. BTTS methods 2 and 3 excluded necrotic, cystic and hemorrhagic areas. Pooled sensitivity, specificity and AUC of the BTTS methods were calculated. Heterogeneity was explored using the inconsistency index (I2) and considering covariables: field strength, lowest b-value, image of BTTS selection, pre-or post-contrast DWI, slice thickness and ADC threshold. Pooled sensitivity, specificity and AUC were: 0.82 (0.72-0.89), 0.79 (0.65-0.89), 0.88 (0.85-0.90) for BTTS1; 0.91 (0.89-0.93), 0.84 (0.80-0.87), 0.94 (0.91-0.96) for BTTS2; 0.89 (0.86-0.92), 0.90 (0.85-0.93), 0.95 (0.93-0.96) for BTTS3 and 0.90 (0.86-0.93), 0.84 (0.81-0.87), 0.86 (0.82-0.88) for BTTS4, respectively. Significant heterogeneity was found between studies (I2 = 95). CONCLUSIONS None of the breast tissue selection (BTTS) methodologies outperformed in differentiating benign from malignant breast lesions. The high heterogeneity of ADC data acquisition demands further standardization, such as DWI acquisition parameters and tumor tissue selection to substantially increase the reliability of DWI of the breast.
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Affiliation(s)
- M. Wielema
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - M. D. Dorrius
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - R. M. Pijnappel
- Department of Radiology, Utrecht University, University Medical Center Utrecht, Utrecht, The Netherlands
| | - G. H. De Bock
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - P. A. T. Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - M. Oudkerk
- University of Groningen, Groningen, The Netherlands
- Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - P. E. Sijens
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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Amitai Y, Scaranelo A, Menes TS, Fleming R, Kulkarni S, Ghai S, Freitas V. Can breast MRI accurately exclude malignancy in mammographic architectural distortion? Eur Radiol 2020; 30:2751-2760. [PMID: 32002641 DOI: 10.1007/s00330-019-06586-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Revised: 10/18/2019] [Accepted: 11/11/2019] [Indexed: 11/28/2022]
Abstract
OBJECTIVES To investigate the diagnostic accuracy of problem-solving breast magnetic resonance imaging (MRI) in excluding malignancy in a cohort of patients diagnosed with mammographic architectural distortion (MAD). METHODS The Institutional Review Board approved the study. Imaging database with 40,245 breast MRIs done between January 2008 and September 2018 was retrospectively reviewed. The study included all exams considered problem-solving MRI for MAD. Two radiologists reviewed the imaging data. Outcome was determined by the pathology results of biopsy/surgical excision or at least 1 year of clinical and radiological follow-up. Predictors for malignancy were examined, and appropriate statistical tests were applied. RESULTS One hundred seventy-five patients (median age 53 years) fulfilled the inclusion criteria and formed the study cohort. No cancers were diagnosed in 106 patients with a negative MRI. Out of 69 women with positive MRI findings, 48 (70%) had benign outcome defined either by pathology result or by negative follow-up, and 21 (30%) yielded malignancy. Malignancy was significantly associated with positive MRI (p < 0.001) and older age (p = 0.014). Falsely positive MRIs were frequently found in women with radial scars. The sensitivity, specificity, negative predictive value, positive predictive value, and overall accuracy of breast MRI were 100% (95% CI 84 to 100%), 68% (CI 61 to 76%), 100% (CI 95 to 100%), 30% (CI 26 to 36%), and 73% (95% CI 66-79), respectively. CONCLUSION A negative breast MRI in patients with MAD was reliable in excluding malignancy in this cohort and may have a role as a precision medicine tool for avoiding unnecessary interventions. KEY POINTS • MRI shows a high negative predictive value in MAD cases. • MRI displays low accuracy in differentiating malignancy from RS. • MRI is a reliable non-invasive method to exclude malignancy in women with mammographic architectural distortion, potentially avoiding unnecessary biopsies and surgeries.
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Affiliation(s)
- Yoav Amitai
- Joint Department of Medical Imaging, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada
| | - Anabel Scaranelo
- Joint Department of Medical Imaging, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada
| | - Tehillah S Menes
- Department of Surgery, Tel Aviv Sourasky Medical Center, Sackler School of Medicine, Tel Aviv University, 6 Weizmann St., 64239, Tel Aviv, Israel
| | - Rachel Fleming
- Joint Department of Medical Imaging, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada
| | - Supriya Kulkarni
- Joint Department of Medical Imaging, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada
| | - Sandeep Ghai
- Joint Department of Medical Imaging, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada
| | - Vivianne Freitas
- Joint Department of Medical Imaging, University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada.
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13
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Ghaderi KF, Phillips J, Perry H, Lotfi P, Mehta TS. Contrast-enhanced Mammography: Current Applications and Future Directions. Radiographics 2019; 39:1907-1920. [DOI: 10.1148/rg.2019190079] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Kimeya F. Ghaderi
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215 (K.F.G., J.P., P.L., T.S.M.); and Department of Radiology, University of Vermont Medical Center, Burlington, Vt (H.P.)
| | - Jordana Phillips
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215 (K.F.G., J.P., P.L., T.S.M.); and Department of Radiology, University of Vermont Medical Center, Burlington, Vt (H.P.)
| | - Hannah Perry
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215 (K.F.G., J.P., P.L., T.S.M.); and Department of Radiology, University of Vermont Medical Center, Burlington, Vt (H.P.)
| | - Parisa Lotfi
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215 (K.F.G., J.P., P.L., T.S.M.); and Department of Radiology, University of Vermont Medical Center, Burlington, Vt (H.P.)
| | - Tejas S. Mehta
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215 (K.F.G., J.P., P.L., T.S.M.); and Department of Radiology, University of Vermont Medical Center, Burlington, Vt (H.P.)
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14
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The Outcome of Primary Architectural Distortion in Mammography: Which are the Important Factors? INTERNATIONAL JOURNAL OF CANCER MANAGEMENT 2019. [DOI: 10.5812/ijcm.91323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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15
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Baxter GC, Graves MJ, Gilbert FJ, Patterson AJ. A Meta-analysis of the Diagnostic Performance of Diffusion MRI for Breast Lesion Characterization. Radiology 2019; 291:632-641. [PMID: 31012817 DOI: 10.1148/radiol.2019182510] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Background Various techniques are available to assess diffusion properties of breast lesions as a marker of malignancy at MRI. The diagnostic performance of these diffusion markers has not been comprehensively assessed. Purpose To compare by meta-analysis the diagnostic performance of parameters from diffusion-weighted imaging (DWI), diffusion-tensor imaging (DTI), and intravoxel incoherent motion (IVIM) in the differential diagnosis of malignant and benign breast lesions. Materials and Methods PubMed and Embase databases were searched from January to March 2018 for studies in English that assessed the diagnostic performance of DWI, DTI, and IVIM in the breast. Studies were reviewed according to eligibility and exclusion criteria. Publication bias and heterogeneity between studies were assessed. Pooled summary estimates for sensitivity, specificity, and area under the curve were obtained for each parameter by using a bivariate model. A subanalysis investigated the effect of MRI parameters on diagnostic performance by using a Student t test or a one-way analysis of variance. Results From 73 eligible studies, 6791 lesions (3930 malignant and 2861 benign) were included. Publication bias was evident for studies that evaluated apparent diffusion coefficient (ADC). Significant heterogeneity (P < .05) was present for all parameters except the perfusion fraction (f). The pooled sensitivity, specificity, and area under the curve for ADC was 89%, 82%, and 0.92, respectively. The highest performing parameter for DTI was the prime diffusion coefficient (λ1), and pooled sensitivity, specificity, and area under the curve was 93%, 90%, and 0.94, respectively. The highest performing parameter for IVIM was tissue diffusivity (D), and the pooled sensitivity, specificity, and area under the curve was 88%, 79%, and 0.90. Choice of MRI parameters had no significant effect on diagnostic performance. Conclusion Diffusion-weighted imaging, diffusion-tensor imaging, and intravoxel incoherent motion have comparable diagnostic accuracy with high sensitivity and specificity. Intravoxel incoherent motion is comparable to apparent diffusion coefficient. Diffusion-tensor imaging is potentially promising but to date the number of studies is limited. © RSNA, 2019 Online supplemental material is available for this article.
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Affiliation(s)
- Gabrielle C Baxter
- From the Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, England (G.C.B., F.J.G.); and Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, England (M.J.G., A.J.P.)
| | - Martin J Graves
- From the Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, England (G.C.B., F.J.G.); and Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, England (M.J.G., A.J.P.)
| | - Fiona J Gilbert
- From the Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, England (G.C.B., F.J.G.); and Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, England (M.J.G., A.J.P.)
| | - Andrew J Patterson
- From the Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, England (G.C.B., F.J.G.); and Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, England (M.J.G., A.J.P.)
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Contrast-Enhanced Mammography: A Systematic Guide to Interpretation and Reporting. AJR Am J Roentgenol 2019; 212:222-231. [DOI: 10.2214/ajr.17.19265] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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17
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Cohen E, Leung JWT. Problem-Solving MR Imaging for Equivocal Imaging Findings and Indeterminate Clinical Symptoms of the Breast. Magn Reson Imaging Clin N Am 2018; 26:221-233. [PMID: 29622127 DOI: 10.1016/j.mric.2017.12.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Breast MR imaging is commonly used for high-risk screening and for assessing the extent of disease in patients with newly diagnosed breast cancer, but its utility for assessing suspicious symptoms and equivocal imaging findings is less widely accepted. The authors review current literature and guidelines regarding the use of breast MR imaging for these indications. Overall, problem-solving breast MR imaging is best reserved for pathologic nipple discharge and sonographically occult architectural distortion with limited biopsy options. Further study is necessary to define the role of problem-solving MR imaging for calcifications, mammographic asymmetries, and surgical scarring.
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Affiliation(s)
- Ethan Cohen
- Department of Diagnostic Radiology, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 1350, Houston, TX 77030-4009, USA.
| | - Jessica W T Leung
- Department of Diagnostic Radiology, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 1350, Houston, TX 77030-4009, USA
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Clinical utility of contrast-enhanced spectral mammography as an adjunct for tomosynthesis-detected architectural distortion. Clin Imaging 2017; 46:44-52. [DOI: 10.1016/j.clinimag.2017.07.003] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 06/13/2017] [Accepted: 07/07/2017] [Indexed: 11/20/2022]
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Diagnostic Performance of Breast Magnetic Resonance Imaging in Non-Calcified Equivocal Breast Findings: Results from a Systematic Review and Meta-Analysis. PLoS One 2016; 11:e0160346. [PMID: 27482715 PMCID: PMC4970763 DOI: 10.1371/journal.pone.0160346] [Citation(s) in RCA: 89] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2016] [Accepted: 07/18/2016] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES To evaluate the performance of MRI for diagnosis of breast cancer in non-calcified equivocal breast findings. MATERIALS AND METHODS We performed a systematic review and meta-analysis of peer-reviewed studies in PubMed from 01/01/1986 until 06/15/2015. Eligible were studies applying dynamic contrast-enhanced breast MRI as an adjunct to conventional imaging (mammography, ultrasound) to clarify equivocal findings without microcalcifications. Reference standard for MRI findings had to be established by histopathological sampling or imaging follow-up of at least 12 months. Number of true or false positives and negatives and other characteristics were extracted, and possible bias was determined using the QUADAS-2 applet. Statistical analyses included data pooling and heterogeneity testing. RESULTS Fourteen out of 514 studies comprising 2,316 lesions met our inclusion criteria. Pooled diagnostic parameters were: sensitivity (99%, 95%-CI: 93-100%), specificity (89%, 95%-CI: 85-92%), PPV (56%, 95%-CI: 42-70%) and NPV (100%, 95%-CI: 99-100%). These estimates displayed significant heterogeneity (P<0.001). CONCLUSIONS Breast MRI demonstrates an excellent diagnostic performance in case of non-calcified equivocal breast findings detected in conventional imaging. However, considering the substantial heterogeneity with regard to prevalence of malignancy, problem solving criteria need to be better defined.
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