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Pöschke P, Wenkel E, Hack CC, Beckmann MW, Uder M, Ohlmeyer S. Low-Risk Women with Suspicious Microcalcifications in Mammography-Can an Additional Breast MRI Reduce the Biopsy Rate? Diagnostics (Basel) 2023; 13:diagnostics13061197. [PMID: 36980504 PMCID: PMC10047574 DOI: 10.3390/diagnostics13061197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 03/14/2023] [Accepted: 03/20/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND In the German Mammography Screening Program, 62% of ductal carcinoma in situ (DCIS) and 38% of invasive breast cancers are associated with microcalcifications (MCs). Vacuum-assisted stereotactic breast biopsies are necessary to distinguish precancerous lesions from benign calcifications because mammographic discrimination is not possible. The aim of this study was to investigate if breast magnetic resonance imaging (MRM) could assist the evaluation of MCs and thus help reduce biopsy rates. METHODS In this IRB-approved study, 58 women (mean age 58 +/- 24 years) with 59 suspicious MC clusters in the MG were eligible for this prospective single-center trial. Additional breast magnetic resonance imaging (MRI) was conducted before biopsy. RESULTS The breast MRI showed a sensitivity of 86%, a specificity of 84%, a positive predictive value (PPV) of 75% and a negative predictive value (NPV) of 91% for the differentiation between benign and malignant in these 59 MCs found with MG. Breast MRI in addition to MG could increase the PPV from 36% to 75% compared to MG alone. The MRI examination led to nine additional suspicious classified lesions in the study cohort. A total of 55% (5/9) of them turned out to be malignant. A total of 32 of 59 (54 %) women with suspicious MCs and benign histology were classified as non-suspicious by MRI. CONCLUSION An additionally performed breast MRI could have increased the diagnostic reliability in the assessment of MCs. Further, in our small cohort, a considerable number of malignant lesions without mammographically visible MCs were revealed.
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Affiliation(s)
- Patrik Pöschke
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Universitätsstraße 21-23, 91054 Erlangen, Germany
| | - Evelyn Wenkel
- Radiologie München, Burgstraße 7, 80331 München, Germany
- Medizinische Fakultät, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany
| | - Carolin C Hack
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Universitätsstraße 21-23, 91054 Erlangen, Germany
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Universitätsstraße 21-23, 91054 Erlangen, Germany
| | - Michael Uder
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany
| | - Sabine Ohlmeyer
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany
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Eskreis-Winkler S, Simon K, Reichman M, Spincemaille P, Nguyen TD, Christos PJ, Drotman M, Prince MR, Pinker K, Sutton EJ, Morris EA, Wang Y. Multispectral Imaging for Metallic Biopsy Marker Detection During MRI-Guided Breast Biopsy: A Feasibility Study for Clinical Translation. Front Oncol 2021; 11:605014. [PMID: 33828972 PMCID: PMC8020905 DOI: 10.3389/fonc.2021.605014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 02/04/2021] [Indexed: 11/18/2022] Open
Abstract
Purpose To assess the feasibility and diagnostic accuracy of multispectral MRI (MSI) in the detection and localization of biopsy markers during MRI-guided breast biopsy. Methods This prospective study included 20 patients undergoing MR-guided breast biopsy. In 10 patients (Group 1), MSI was acquired following tissue sampling and biopsy marker deployment. In the other 10 patients (Group 2), MSI was acquired following tissue sampling but before biopsy marker deployment (to simulate deployment failure). All patients received post-procedure mammograms. Group 1 and Group 2 designations, in combination with the post-procedure mammogram, served as the reference standard. The diagnostic performance of MSI for biopsy marker identification was independently evaluated by two readers using two-spectral-bin MR and one-spectral-bin MR. The κ statistic was used to assess inter-rater agreement for biopsy marker identification. Results The sensitivity, specificity, and accuracy of biopsy marker detection for readers 1 and 2 using 2-bin MSI were 90.0% (9/10) and 90.0% (9/10), 100.0% (10/10) and 100.0% (10/10), 95.0% (19/20) and 95.0% (19/20); and using 1-bin MSI were 70.0% (7/10) and 80.0% (8/10), 100.0% (8/8) and 100.0% (10/10), 85.0% (17/20) and 90.0% (18/20). Positive predictive value was 100% for both readers for all numbers of bins. Inter-rater agreement was excellent: κ was 1.0 for 2-bin MSI and 0.81 for 1-bin MSI. Conclusion MSI is a feasible, diagnostically accurate technique for identifying metallic biopsy markers during MRI-guided breast biopsy and may eliminate the need for a post-procedure mammogram.
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Affiliation(s)
- Sarah Eskreis-Winkler
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Katherine Simon
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Melissa Reichman
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Paul J Christos
- Division of Biostatistics and Epidemiology, Department of Healthcare Policy & Research, Weill Cornell Medicine, New York, NY, United States
| | - Michele Drotman
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Martin R Prince
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Katja Pinker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Elizabeth J Sutton
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Elizabeth A Morris
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
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Whisenant JG, Romanoff J, Rahbar H, Kitsch AE, Harvey SM, Moy L, DeMartini WB, Dogan BE, Yang WT, Wang LC, Joe BN, Wilmes LJ, Hylton NM, Oh KY, Tudorica LA, Neal CH, Malyarenko DI, McDonald ES, Comstock CE, Yankeelov TE, Chenevert TL, Partridge SC. Factors Affecting Image Quality and Lesion Evaluability in Breast Diffusion-weighted MRI: Observations from the ECOG-ACRIN Cancer Research Group Multisite Trial (A6702). J Breast Imaging 2021; 3:44-56. [PMID: 33543122 PMCID: PMC7835633 DOI: 10.1093/jbi/wbaa103] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Indexed: 12/27/2022]
Abstract
OBJECTIVE The A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance. METHODS The A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b-value, echo-planar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping. RESULTS Thirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability (P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p <0.03), though not significant after multiplicity correction. The AUC for differentiating benign and malignant lesions increased after excluding non-evaluable lesions, from 0.61 (95% CI: 0.50-0.71) to 0.75 (95% CI: 0.65-0.84). CONCLUSION Image quality remains a technical challenge in breast DWI, particularly for smaller lesions. Protocol optimization and advanced acquisition and post-processing techniques would help to improve clinical utility.
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Affiliation(s)
- Jennifer G Whisenant
- Vanderbilt University Medical Center, Department of Medicine, Nashville, TN
- Vanderbilt-Ingram Cancer Center, Nashville, TN
| | - Justin Romanoff
- Brown University, Center for Statistical Sciences, Providence, RI
| | - Habib Rahbar
- University of Washington, Department of Radiology, Seattle, WA
| | - Averi E Kitsch
- University of Washington, Department of Radiology, Seattle, WA
| | - Sara M Harvey
- Vanderbilt University Medical Center, Department of Radiology and Radiological Sciences, Nashville, TN
| | - Linda Moy
- New York University School of Medicine, Department of Radiology, New York, NY
| | - Wendy B DeMartini
- Stanford University School of Medicine, Department of Radiology, Stanford, CA
| | - Basak E Dogan
- University of Texas Southwestern Medical Center, Department of Diagnostic Radiology, Dallas, TX
| | - Wei T Yang
- MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX
| | - Lilian C Wang
- Northwestern University Feinberg School of Medicine, Department of Radiology, Chicago, IL
| | - Bonnie N Joe
- University of California San Francisco School of Medicine, Department of Radiology and Biomedical Engineering, San Francisco, CA
| | - Lisa J Wilmes
- University of California San Francisco School of Medicine, Department of Radiology and Biomedical Engineering, San Francisco, CA
| | - Nola M Hylton
- University of California San Francisco School of Medicine, Department of Radiology and Biomedical Engineering, San Francisco, CA
| | - Karen Y Oh
- Oregon Health and Science University, Department of Radiology, Portland, OR
| | | | - Colleen H Neal
- University of Michigan, Department of Radiology/MRI, Ann Arbor, MI
| | | | - Elizabeth S McDonald
- University of Pennsylvania Perelman School of Medicine, Department of Radiology, Philadelphia, PA
| | | | - Thomas E Yankeelov
- University of Texas Austin, Department of Biomedical Engineering, Austin, TX
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Sun H, Li H, Si S, Qi S, Zhang W, Ma H, Liu S, Yingxue L, Qian W. Performance evaluation of breast cancer diagnosis with mammography, ultrasonography and magnetic resonance imaging. J Xray Sci Technol 2018; 26:805-813. [PMID: 30103371 DOI: 10.3233/xst-18388] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
OBJECTIVE Various imaging modalities have been used to diagnose suspicious breast lesions. Purpose of this study is to compare the diagnostic accuracy for breast cancer using mammography, ultrasonography and magnetic resonance imaging (MRI). METHODS Total 107 patients aged from 19 to 62 years are included in this retrospective study. Mammography, ultrasonography and MRI scans were performed for each patient detected with suspected breast tumor within a month. In addition, the tumor diversity (10 types of benign and 5 types of malignant) was confirmed by pathological findings of tumor biopsy. To compare the diagnosis performance of the three imaging modalities, the overall fraction correct (accuracy), positive predict value (PPV), negative predict value (NPV), sensitivity and specificity were calculated. Meanwhile, the receiver operating characteristic (ROC) analysis was also performed. RESULTS The diagnostic accuracy ranged from 78.5% to 86.9% among three imaging modalities. All modalities yielded a PPV lower than 77.8% and a NPV higher than 90.0% in identifying the presence of malignant tumors. MRI presented a diagnostic accuracy of 86.9%, as well as a sensitivity of 95.5% and an area under curve (AUC) of 0.948, which are higher than mammography and ultrasonography. CONCLUSION By using a diverse dataset and comparing the diagnostic accuracy of three imaging modalities commonly used in breast cancer detection and diagnosis, this study also demonstrated that mammography, ultrasonography and MRI had different diagnostic performance in breast tumor identification. Among them, MRI yielded the highest performance even though the unexpected specificity may lead to over-diagnosis, and ultrosonography is slightly better than mammography.
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Affiliation(s)
- Hang Sun
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, Liaoning, China
| | - Hong Li
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, Liaoning, China
| | - Shuang Si
- Department of Radiology, Shengjing hospital of China Medical University, Shenyang, Liaoning, China
| | - Shouliang Qi
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, Liaoning, China
| | - Wei Zhang
- Department of Radiology, Shengjing hospital of China Medical University, Shenyang, Liaoning, China
| | - He Ma
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, Liaoning, China
| | - Siqi Liu
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, Liaoning, China
| | - Li Yingxue
- Department of Radiology, Shengjing hospital of China Medical University, Shenyang, Liaoning, China
| | - Wei Qian
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, Liaoning, China
- Department of Electrical and Computer Engineering, University of Texas, El Paso, TX, USA
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