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Essien M, Cooper ME, Gore A, Min TL, Risk BB, Sadigh G, Hu R, Hoch MJ, Weinberg BD. Interrater Agreement of BT-RADS for Evaluation of Follow-up MRI in Patients with Treated Primary Brain Tumor. AJNR Am J Neuroradiol 2024; 45:1308-1315. [PMID: 38684320 PMCID: PMC11392352 DOI: 10.3174/ajnr.a8322] [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: 03/05/2024] [Accepted: 04/19/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND AND PURPOSE The Brain Tumor Reporting and Data System (BT-RADS) is a structured radiology reporting algorithm that was introduced to provide uniformity in posttreatment primary brain tumor follow-up and reporting, but its interrater reliability (IRR) assessment has not been widely studied. Our goal is to evaluate the IRR among neuroradiologists and radiology residents in the use of BT-RADS. MATERIALS AND METHODS This retrospective study reviewed 103 consecutive MR studies in 98 adult patients previously diagnosed with and treated for primary brain tumor (January 2019 to February 2019). Six readers with varied experience (4 neuroradiologists and 2 radiology residents) independently evaluated each case and assigned a BT-RADS score. Readers were blinded to the original score reports and the reports from other readers. Cases in which at least 1 neuroradiologist scored differently were subjected to consensus scoring. After the study, a post hoc reference score was also assigned by 2 readers by using future imaging and clinical information previously unavailable to readers. The interrater reliabilities were assessed by using the Gwet AC2 index with ordinal weights and percent agreement. RESULTS Of the 98 patients evaluated (median age, 53 years; interquartile range, 41-66 years), 53% were men. The most common tumor type was astrocytoma (77%) of which 56% were grade 4 glioblastoma. Gwet index for interrater reliability among all 6 readers was 0.83 (95% CI: 0.78-0.87). The Gwet index for the neuroradiologists' group (0.84 [95% CI: 0.79-0.89]) was not statistically different from that for the residents' group (0.79 [95% CI: 0.72-0.86]) (χ2 = 0.85; P = .36). All 4 neuroradiologists agreed on the same BT-RADS score in 57 of the 103 studies, 3 neuroradiologists agreed in 21 of the 103 studies, and 2 neuroradiologists agreed in 21 of the 103 studies. Percent agreement between neuroradiologist blinded scores and post hoc reference scores ranged from 41%-52%. CONCLUSIONS A very good interrater agreement was found when tumor reports were interpreted by independent blinded readers by using BT-RADS criteria. Further study is needed to determine if this high overall agreement can translate into greater consistency in clinical care.
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Affiliation(s)
- Michael Essien
- From the Department of Radiology and Imaging Sciences (M.E., M.E.C., A.G., T.L.M., R.H., B.D.W.)
| | - Maxwell E Cooper
- From the Department of Radiology and Imaging Sciences (M.E., M.E.C., A.G., T.L.M., R.H., B.D.W.)
| | - Ashwani Gore
- From the Department of Radiology and Imaging Sciences (M.E., M.E.C., A.G., T.L.M., R.H., B.D.W.)
| | - Taejin L Min
- From the Department of Radiology and Imaging Sciences (M.E., M.E.C., A.G., T.L.M., R.H., B.D.W.)
| | - Benjamin B Risk
- Rollins School of Public Health (B.B.R.), Emory University, Atlanta, Georgia
| | - Gelareh Sadigh
- Rollins School of Public Health (B.B.R.), Emory University, Atlanta, Georgia
| | - Ranliang Hu
- From the Department of Radiology and Imaging Sciences (M.E., M.E.C., A.G., T.L.M., R.H., B.D.W.)
| | - Michael J Hoch
- Department of Radiological Sciences (G.S.), University of California Irvine, Orange, California
| | - Brent D Weinberg
- From the Department of Radiology and Imaging Sciences (M.E., M.E.C., A.G., T.L.M., R.H., B.D.W.),
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Chikarmane SA, Smith S. Background Parenchymal Enhancement: A Comprehensive Update. Radiol Clin North Am 2024; 62:607-617. [PMID: 38777537 DOI: 10.1016/j.rcl.2023.12.013] [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] [Indexed: 05/25/2024]
Abstract
Breast MR imaging is a complementary screening tool for patients at high risk for breast cancer and has been used in the diagnostic setting. Normal enhancement of breast tissue on MR imaging is called breast parenchymal enhancement (BPE), which occurs after administration of an intravenous contrast agent. BPE varies widely due to menopausal status, use of exogenous hormones, and breast cancer treatment. Degree of BPE has also been shown to influence breast cancer risk and may predict treatment outcomes. The authors provide a comprehensive update on BPE with review of the recent literature.
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Affiliation(s)
- Sona A Chikarmane
- Breast Imaging Division, Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA.
| | - Sharon Smith
- Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA
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Ma Y, Liu A, Zhang Y, Zhu Y, Wang Y, Zhao M, Liang Z, Qu Z, Yin L, Lu H, Ye Z. Comparison of background parenchymal enhancement (BPE) on contrast-enhanced cone-beam breast CT (CE-CBBCT) and breast MRI. Eur Radiol 2022; 32:5773-5782. [PMID: 35320411 DOI: 10.1007/s00330-022-08699-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 02/15/2022] [Accepted: 02/21/2022] [Indexed: 11/26/2022]
Abstract
OBJECTIVES To compare the background parenchymal enhancement (BPE) levels on contrast-enhanced cone-beam breast CT (CE-CBBCT) and MRI, evaluate inter-reader reliability, and analyze the relationship between clinical factors and BPE level on CE-CBBCT. METHODS In this retrospective study, patients who underwent both CE-CBBCT and MRI were analyzed. BPE levels on CE-CBBCT and MRI were assessed by five specialists independently in random fashion, with a wash-out period of 4 weeks. Weighted kappa was used to analyze the agreement between CE-CBBCT and MRI, and intraclass correlation coefficient (ICC) was used to evaluate the inter-reader reliability for each modality. The association between BPE level on CE-CBBCT and clinical factors was evaluated by univariate and multivariate logistic regression. RESULTS A total of 221 patients from January 2017 to April 2021 were enrolled. CE-CBBCT showed substantial agreement (weighted kappa = 0.690) with MRI for BPE evaluation, with good degree of inter-reader reliability on both CE-CBBCT (ICC = 0.712) and MRI (ICC = 0.757). Based on majority reports, BPE levels on CE-CBBCT were lower than MRI (p < 0.001). BPE level on CE-CBBCT was significantly associated with menstrual status (odds ratio, OR = 0.125), breast density (OR = 2.308), and previously treated breast cancer (OR = 0.052) (all p < 0.05). BPE level for premenopausal patients was associated with menstrual cycle, with lower BPE level for the 2nd week of menstrual cycle (OR = 0.246). CONCLUSIONS CE-CBBCT showed substantial agreement and comparable inter-reader reliability with MRI for BPE evaluation, indicating that the corresponding BI-RADS lexicons could be used to describe BPE level on CE-CBBCT. The 2nd week of menstrual cycle timing is suggested as the optimal examination period for CE-CBBCT. KEY POINTS • CE-CBBCT showed substantial agreement and comparable inter-reader reliability with MRI for BPE evaluation. • Menstrual status, breast density, and previously treated breast cancer were associated with the BPE level on CE-CBBCT images. • The 2ndweek of the menstrual cycle is suggested as the optimal examination period for CE-CBBCT.
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Affiliation(s)
- Yue Ma
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Aidi Liu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Yuwei Zhang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Yueqiang Zhu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Yafei Wang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Mengran Zhao
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Zhiran Liang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Zhiye Qu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Lu Yin
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Hong Lu
- Department of Breast Imaging, Tianjin Medical University Cancer Institute and Hospital; National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China.
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Chalfant JS, Mortazavi S, Lee-Felker SA. Background Parenchymal Enhancement on Breast MRI: Assessment and Clinical Implications. CURRENT RADIOLOGY REPORTS 2021. [DOI: 10.1007/s40134-021-00386-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Abstract
Purpose of Review
To present recent literature regarding the assessment and clinical implications of background parenchymal enhancement on breast MRI.
Recent Findings
The qualitative assessment of BPE remains variable within the literature, as well as in clinical practice. Several different quantitative approaches have been investigated in recent years, most commonly region of interest-based and segmentation-based assessments. However, quantitative assessment has not become standard in clinical practice to date. Numerous studies have demonstrated a clear association between higher BPE and future breast cancer risk. While higher BPE does not appear to significantly impact cancer detection, it may result in a higher abnormal interpretation rate. BPE is also likely a marker of pathologic complete response after neoadjuvant chemotherapy, with decreases in BPE during and after neoadjuvant chemotherapy correlated with pCR. In contrast, pre-treatment BPE does not appear to be predictive of pCR. The association between BPE and prognosis is less clear, with heterogeneous results in the literature.
Summary
Assessment of BPE continues to evolve, with heterogeneity in approaches to both qualitative and quantitative assessment. The level of BPE has important clinical implications, with associations with future breast cancer risk and treatment response. BPE may also be an imaging marker of prognosis, but future research is needed on this topic.
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Wise JC, Wilkes EJA, Raidal SL, Xie G, Crosby DE, Hale JN, Hughes KJ. Interobserver and intraobserver reliability for 2 grading systems for gastric ulcer syndrome in horses. J Vet Intern Med 2020; 35:571-579. [PMID: 33284465 PMCID: PMC7848314 DOI: 10.1111/jvim.15987] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 11/12/2020] [Accepted: 11/20/2020] [Indexed: 11/29/2022] Open
Abstract
Background Grading of equine gastric ulcer syndrome (EGUS) is undertaken in clinical and research settings, but the reliability of EGUS grading systems is poorly understood. Hypothesis/Objectives Investigate interobserver and intraobserver reliability of an established ordinal grading system and a novel visual analog scale (VAS), and assess the influence of observer experience. Animals Sixty deidentified gastroscopy videos. Methods Six observers (3 specialists and 3 residents) graded videos using the EGUS Council (EGUC) system and VAS. Observers graded the videos three 3 for each system, using a cross‐over design with at least 1 week between each phase. The order of videos was randomized for each phase. Methods Interobserver and intraobserver reliability were estimated using Gwet's agreement coefficient with ordinal weights applied (AC2) for the EGUC system and the intraclass correlation coefficient (ICC) for the VAS. Results Using the EGUC system, interobserver reliability was substantial for squamous (AC2 = 0.69; 95% confidence interval [CI], 0.57‐0.80) and glandular mucosa (AC2 = 0.72; 95% CI, 0.70‐0.75), and intraobserver reliability was substantial for squamous (AC2 = 0.80; 95% CI, 0.71‐0.90) and glandular mucosa (AC2 = 0.80; 95% CI, 0.74‐0.86). Interobserver reliability using the VAS was moderate for squamous (ICC = 0.64; 95% CI, 0.31‐0.96) and poor for glandular mucosa (ICC = 0.35; 95% CI, 0.06‐0.64), and intraobserver reliability was moderate for squamous (ICC = 0.74; 95% CI, 0.62‐0.86) and glandular mucosa (ICC = 0.56; 95% CI, 0.39‐0.72). Conclusions and Clinical Importance The EGUC system had acceptable intraobserver and interobserver reliability and performed well regardless of observer experience. Familiarity and observer experience improved reliability of the VAS.
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Affiliation(s)
- Jessica C Wise
- School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia
| | - Edwina J A Wilkes
- School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia
| | - Sharanne L Raidal
- School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia
| | - Gang Xie
- Quantitative Consultant Unit, Charles Sturt University, Wagga Wagga, New South Wales, Australia
| | - Danielle E Crosby
- School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia
| | - Josephine N Hale
- School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia
| | - Kristopher J Hughes
- School of Animal and Veterinary Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia
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Watt GP, Sung J, Morris EA, Buys SS, Bradbury AR, Brooks JD, Conant EF, Weinstein SP, Kontos D, Woods M, Colonna SV, Liang X, Stein MA, Pike MC, Bernstein JL. Association of breast cancer with MRI background parenchymal enhancement: the IMAGINE case-control study. Breast Cancer Res 2020; 22:138. [PMID: 33287857 PMCID: PMC7722419 DOI: 10.1186/s13058-020-01375-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 11/25/2020] [Indexed: 01/09/2023] Open
Abstract
Background Background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) may be associated with breast cancer risk, but previous studies of the association are equivocal and limited by incomplete blinding of BPE assessment. In this study, we evaluated the association between BPE and breast cancer based on fully blinded assessments of BPE in the unaffected breast. Methods The Imaging and Epidemiology (IMAGINE) study is a multicenter breast cancer case-control study of women receiving diagnostic, screening, or follow-up breast MRI, recruited from three comprehensive cancer centers in the USA. Cases had a first diagnosis of unilateral breast cancer and controls had no history of or current breast cancer. A single board-certified breast radiologist with 12 years’ experience, blinded to case-control status and clinical information, assessed the unaffected breast for BPE without view of the affected breast of cases (or the corresponding breast laterality of controls). The association between BPE and breast cancer was estimated by multivariable logistic regression separately for premenopausal and postmenopausal women. Results The analytic dataset included 835 cases and 963 controls. Adjusting for fibroglandular tissue (breast density), age, race/ethnicity, BMI, parity, family history of breast cancer, BRCA1/BRCA2 mutations, and other confounders, moderate/marked BPE (vs minimal/mild BPE) was associated with breast cancer among premenopausal women [odds ratio (OR) 1.49, 95% CI 1.05–2.11; p = 0.02]. Among postmenopausal women, mild/moderate/marked vs minimal BPE had a similar, but statistically non-significant, association with breast cancer (OR 1.45, 95% CI 0.92–2.27; p = 0.1). Conclusions BPE is associated with breast cancer in premenopausal women, and possibly postmenopausal women, after adjustment for breast density and confounders. Our results suggest that BPE should be evaluated alongside breast density for inclusion in models predicting breast cancer risk.
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Affiliation(s)
- Gordon P Watt
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 485 Lexington Ave., Second Floor, New York, NY, 10017, USA.
| | - Janice Sung
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Elizabeth A Morris
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Saundra S Buys
- Huntsman Cancer Institute, University of Utah, Salt Lake City, USA
| | - Angela R Bradbury
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Jennifer D Brooks
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Emily F Conant
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Susan P Weinstein
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Despina Kontos
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Meghan Woods
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 485 Lexington Ave., Second Floor, New York, NY, 10017, USA
| | - Sarah V Colonna
- Huntsman Cancer Institute, University of Utah, Salt Lake City, USA
| | - Xiaolin Liang
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 485 Lexington Ave., Second Floor, New York, NY, 10017, USA
| | - Matthew A Stein
- Huntsman Cancer Institute, University of Utah, Salt Lake City, USA
| | - Malcolm C Pike
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 485 Lexington Ave., Second Floor, New York, NY, 10017, USA
| | - Jonine L Bernstein
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 485 Lexington Ave., Second Floor, New York, NY, 10017, USA
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Reig B, Heacock L, Geras KJ, Moy L. Machine learning in breast MRI. J Magn Reson Imaging 2019; 52:998-1018. [PMID: 31276247 DOI: 10.1002/jmri.26852] [Citation(s) in RCA: 93] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 06/18/2019] [Accepted: 06/19/2019] [Indexed: 12/13/2022] Open
Abstract
Machine-learning techniques have led to remarkable advances in data extraction and analysis of medical imaging. Applications of machine learning to breast MRI continue to expand rapidly as increasingly accurate 3D breast and lesion segmentation allows the combination of radiologist-level interpretation (eg, BI-RADS lexicon), data from advanced multiparametric imaging techniques, and patient-level data such as genetic risk markers. Advances in breast MRI feature extraction have led to rapid dataset analysis, which offers promise in large pooled multiinstitutional data analysis. The object of this review is to provide an overview of machine-learning and deep-learning techniques for breast MRI, including supervised and unsupervised methods, anatomic breast segmentation, and lesion segmentation. Finally, it explores the role of machine learning, current limitations, and future applications to texture analysis, radiomics, and radiogenomics. Level of Evidence: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2020;52:998-1018.
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Affiliation(s)
- Beatriu Reig
- The Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Laura Heacock
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Krzysztof J Geras
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Linda Moy
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.,Center for Advanced Imaging Innovation and Research (CAI2 R), New York University School of Medicine, New York, New York, USA
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