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Kubota K, Fujioka T, Tateishi U, Mori M, Yashima Y, Yamaga E, Katsuta L, Yamaguchi K, Tozaki M, Sasaki M, Uematsu T, Monzawa S, Isomoto I, Suzuki M, Satake H, Nakahara H, Goto M, Kikuchi M. Investigation of imaging features in contrast-enhanced magnetic resonance imaging of benign and malignant breast lesions. Jpn J Radiol 2024; 42:720-730. [PMID: 38503998 PMCID: PMC11217097 DOI: 10.1007/s11604-024-01551-1] [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: 12/01/2023] [Accepted: 02/20/2024] [Indexed: 03/21/2024]
Abstract
PURPOSE This study aimed to enhance the diagnostic accuracy of contrast-enhanced breast magnetic resonance imaging (MRI) using gadobutrol for differentiating benign breast lesions from malignant ones. Moreover, this study sought to address the limitations of current imaging techniques and criteria based on the Breast Imaging Reporting and Data System (BI-RADS). MATERIALS AND METHODS In a multicenter retrospective study conducted in Japan, 200 women were included, comprising 100 with benign lesions and 100 with malignant lesions, all classified under BI-RADS categories 3 and 4. The MRI protocol included 3D fast gradient echo T1- weighted images with fat suppression, with gadobutrol as the contrast agent. The analysis involved evaluating patient and lesion characteristics, including age, size, location, fibroglandular tissue, background parenchymal enhancement (BPE), signal intensity, and the findings of mass and non-mass enhancement. In this study, univariate and multivariate logistic regression analyses were performed, along with decision tree analysis, to identify significant predictors for the classification of lesions. RESULTS Differences in lesion characteristics were identified, which may influence malignancy risk. The multivariate logistic regression model revealed age, lesion location, shape, and signal intensity as significant predictors of malignancy. Decision tree analysis identified additional diagnostic factors, including lesion margin and BPE level. The decision tree models demonstrated high diagnostic accuracy, with the logistic regression model showing an area under the curve of 0.925 for masses and 0.829 for non-mass enhancements. CONCLUSION This study underscores the importance of integrating patient age, lesion location, and BPE level into the BI-RADS criteria to improve the differentiation between benign and malignant breast lesions. This approach could minimize unnecessary biopsies and enhance clinical decision-making in breast cancer diagnostics, highlighting the effectiveness of gadobutrol in breast MRI evaluations.
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Affiliation(s)
- Kazunori Kubota
- Department of Radiology, Dokkyo Medical University Saitama Medical Center, 2-1-50 Minamiko-Shigaya, Koshigaya, Saitama, 343-8555, Japan
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8519, Japan
| | - Tomoyuki Fujioka
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8519, Japan.
| | - Ukihide Tateishi
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8519, Japan
| | - Mio Mori
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8519, Japan
| | - Yuka Yashima
- Department of Radiology, Dokkyo Medical University Saitama Medical Center, 2-1-50 Minamiko-Shigaya, Koshigaya, Saitama, 343-8555, Japan
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8519, Japan
| | - Emi Yamaga
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8519, Japan
| | - Leona Katsuta
- Department of Diagnostic Radiology, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8519, Japan
| | - Ken Yamaguchi
- Department of Radiology, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, Saga City, Saga, 849-8501, Japan
| | - Mitsuhiro Tozaki
- Department of Radiology, Sagara Hospital, 3-31 Matsubara-Cho, Kagoshima City, Kagoshima, 892-0833, Japan
| | - Michiro Sasaki
- Department of Radiology, Sagara Hospital, 3-31 Matsubara-Cho, Kagoshima City, Kagoshima, 892-0833, Japan
| | - Takayoshi Uematsu
- Division of Breast Imaging and Breast Interventional Radiology, Shizuoka Cancer Center Hospital, Nagaizumi, Shizuoka, 411-8777, Japan
| | - Shuichi Monzawa
- Department of Diagnostic Radiology, Shinko Hospital, 1-4-47, Wakinohama-Cho, Chuo-Ku, Kobe City, Hyogo, 651-0072, Japan
| | - Ichiro Isomoto
- Department of Radiology, St. Francis Hospital, 9-20, Kominemachi, Nagasaki City, Nagasaki, 852-8125, Japan
| | - Mizuka Suzuki
- Department of Diagnostic Radiology, Tokyo Metropolitan Cancer and Infectious Disease Center, Komagome Hospital, 3-18-22 Honkomagome, Bunkyo-Ku, Tokyo, 113-8677, Japan
| | - Hiroko Satake
- Department of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, Aichi, 466-8550, Japan
| | - Hiroshi Nakahara
- Department of Radiology, Sagara Hospital Miyazaki, 2-112-1 Maruyama, Miyazaki City, Miyazaki, 880-0052, Japan
| | - Mariko Goto
- Department of Radiology, Kyoto Prefectural University of Medicine, 465 Kajii-Cho, Kamigyo-Ku, Kyoto City, 602-8566, Japan
| | - Mari Kikuchi
- Department of Imaging Center, Cancer Institute Hospital, Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-Ku, Tokyo, 135-8550, Japan
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Grimm LJ. BI-RADS 3 on MRI: Shifting From an Art to a Science. JOURNAL OF BREAST IMAGING 2023; 5:315-317. [PMID: 38416891 DOI: 10.1093/jbi/wbad020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Indexed: 03/01/2024]
Affiliation(s)
- Lars J Grimm
- Duke University Medical Center, Department of Radiology, Durham, NC, USA
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Myers KS, Shey E, Ambinder EB, Mullen LA, Panigrahi B, Di Carlo PA, Yenokyan G, Oluyemi ET. Circumscribed Masses on Breast MRI: Can MRI Features Guide Management? JOURNAL OF BREAST IMAGING 2023; 5:306-314. [PMID: 38416892 DOI: 10.1093/jbi/wbad016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Indexed: 03/01/2024]
Abstract
OBJECTIVE Management of circumscribed breast masses seen on MRI is largely extrapolated from mammography and US data with limited MRI-specific data available. This study aimed to assess clinical and MRI imaging features of malignant circumscribed breast masses. METHODS In this IRB-approved retrospective study, breast MRIs performed between April 1, 2008, and August 30, 2020, containing circumscribed masses, excluding multiple bilateral circumscribed masses, were reviewed. Clinical and imaging features of all eligible masses were recorded, and associations with malignant outcomes were assessed using Fisher's exact test and Wilcoxon rank sum test, with P < 0.05 considered significant. RESULTS For the 165 masses that met study criteria in 158 women, the mean age was 48 years (SD 12.0 years). Nine of 165 masses were malignant (5.5%). Round masses were significantly more likely to be malignant (7/37, 18.9%) compared to oval masses (2/128, 1.7%) (P < 0.001). Among masses with available dynamic contrast kinetics data, the malignancy rate was 0/84 (0%) for persistent kinetics, 2/23 (8.7%) for plateau kinetics, and 4/24 (16.7%) for washout kinetics (P = 0.002). The malignancy rate for oval masses without washout kinetics was 0% (0/92). T2 hyperintense masses had a malignancy rate of 7/104 (6.7%), and homogeneously enhancing masses had a malignancy rate of 5/91 (5.5%). CONCLUSION These data support the use of mass shape and dynamic contrast enhancement kinetics to guide management of circumscribed breast masses seen by MRI, with oval masses without washout kinetics and any circumscribed mass with persistent kinetics showing no malignancies in this study.
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Affiliation(s)
- Kelly S Myers
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Erica Shey
- Lahey Clinic, Department of Radiology, Burlington, MA, USA
| | - Emily B Ambinder
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Lisa A Mullen
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Babita Panigrahi
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Philip A Di Carlo
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
| | - Gayane Yenokyan
- Johns Hopkins University Bloomberg School of Public Health, Department of Biostatistics, Baltimore, MD, USA
| | - Eniola T Oluyemi
- Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD, USA
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Ota R, Kataoka M, Iima M, Honda M, Kishimoto AO, Miyake KK, Yamada Y, Takeuchi Y, Toi M, Nakamoto Y. Evaluation of breast lesions based on modified BI-RADS using high-resolution readout-segmented diffusion-weighted echo-planar imaging and T2/T1-weighted image. Magn Reson Imaging 2023; 98:132-139. [PMID: 36608911 DOI: 10.1016/j.mri.2022.12.024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 12/31/2022] [Indexed: 01/09/2023]
Abstract
PURPOSE To evaluate the diagnostic performance of a non-contrast magnetic resonance imaging (MRI) protocol combining high-resolution diffusion-weighted images (HR-DWI) using readout-segmented echo planar imaging, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI), using our modified Breast Imaging-Reporting and Data System (modified BI-RADS). METHODS Two experienced radiologists, blinded to the final pathological diagnosis, categorized a total of 108 breast lesions (61 malignant and 47 benign) acquired with the above protocol using the modified BI-RADS with a diagnostic decision tree. The decision tree included subcategories of category 4, as in mammography (categories 2, 3, 4A, 4B, 4C, and 5). These results were compared with the pathological diagnoses. RESULTS The area under the ROC curve (AUC) was 0.89 (95% confidence interval [CI]: 0.83-0.95) for reader 1, and 0.89 (95% CI: 0.82-0.96) for reader 2. When categories 4C and above were classified as malignant, the sensitivity, specificity, and accuracy were 73.8%, 93.6%, and 82.4%, for reader 1; and 82.0%, 89.4%, and 85.2% for reader 2, respectively. CONCLUSION Our results suggest that using HR-DWI, T1WI/T2WI analyzed with a modified BI-RADS and a decision tree showed promising diagnostic performance in breast lesions, and is worthy of further study.
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Affiliation(s)
- Rie Ota
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University graduate school of medicine, Kyoto, Japan; Department of Radiology, Tenri Hospital, Nara, Japan
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University graduate school of medicine, Kyoto, Japan.
| | - Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University graduate school of medicine, Kyoto, Japan; Institute for Advancement of Clinical and Translational Science (iACT), Kyoto University Hospital, Kyoto, Japan
| | - Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University graduate school of medicine, Kyoto, Japan; Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Japan
| | - Ayami Ohno Kishimoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University graduate school of medicine, Kyoto, Japan; Department of Radiology, Rakuwakai Otowa Hospital, Kyoto, Japan
| | - Kanae Kawai Miyake
- Department of Advanced Medical Imaging and Research, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yosuke Yamada
- Department of Diagnostic Pathology, Kyoto University Hospital, Kyoto, Japan
| | - Yasuhide Takeuchi
- Department of Diagnostic Pathology, Kyoto University Hospital, Kyoto, Japan
| | - Masakazu Toi
- Department of Breast Surgery, Kyoto University Hospital, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University graduate school of medicine, Kyoto, Japan
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Jones LI, Klimczak K, Geach R. Breast MRI: an illustration of benign findings. Br J Radiol 2023; 96:20220280. [PMID: 36488196 PMCID: PMC9975519 DOI: 10.1259/bjr.20220280] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 08/24/2022] [Accepted: 09/29/2022] [Indexed: 12/13/2022] Open
Abstract
Despite its unparalleled sensitivity for aggressive breast cancer, breast MRI continually excites criticism for a specificity that lags behind that of modern mammographic techniques. Radiologists reporting breast MRI need to recognise the range of benign appearances on breast MRI to avoid unnecessary biopsy. This review summarises the reported diagnostic accuracy of breast MRI with particular attention to the technique's specificity, provides a referenced reporting strategy and discusses factors that compromise diagnostic confidence. We then present a pictorial review of benign findings on breast MRI. Enhancing radiological skills to discriminate malignant from benign findings will minimise false positive biopsies, enabling optimal use of multiparametric breast MRI for the benefit of screening clients and breast cancer patients.
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Affiliation(s)
- Lyn Isobel Jones
- Bristol Breast Care Centre, North Bristol NHS Trust, Bristol, United Kingdom
| | - Katherine Klimczak
- Bristol Breast Care Centre, North Bristol NHS Trust, Bristol, United Kingdom
| | - Rebecca Geach
- Bristol Breast Care Centre, North Bristol NHS Trust, Bristol, United Kingdom
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Automated Breast Volume Scanner (ABVS)-Based Radiomic Nomogram: A Potential Tool for Reducing Unnecessary Biopsies of BI-RADS 4 Lesions. Diagnostics (Basel) 2022; 12:diagnostics12010172. [PMID: 35054339 PMCID: PMC8774686 DOI: 10.3390/diagnostics12010172] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 01/07/2022] [Accepted: 01/10/2022] [Indexed: 01/22/2023] Open
Abstract
Improving the assessment of breast imaging reporting and data system (BI-RADS) 4 lesions and reducing unnecessary biopsies are urgent clinical issues. In this prospective study, a radiomic nomogram based on the automated breast volume scanner (ABVS) was constructed to identify benign and malignant BI-RADS 4 lesions and evaluate its value in reducing unnecessary biopsies. A total of 223 histologically confirmed BI-RADS 4 lesions were enrolled and assigned to the training and validation cohorts. A radiomic score was generated from the axial, sagittal, and coronal ABVS images. Combining the radiomic score and clinical-ultrasound factors, a radiomic nomogram was developed by multivariate logistic regression analysis. The nomogram integrating the radiomic score, lesion size, and BI-RADS 4 subcategories showed good discrimination between malignant and benign BI-RADS 4 lesions in the training (AUC, 0.959) and validation (AUC, 0.925) cohorts. Moreover, 42.5% of unnecessary biopsies would be reduced by using the nomogram, but nine (4%) malignant BI-RADS 4 lesions were unfortunately missed, of which 4A (77.8%) and small-sized (<10 mm) lesions (66.7%) accounted for the majority. The ABVS radiomics nomogram may be a potential tool to reduce unnecessary biopsies of BI-RADS 4 lesions, but its ability to detect small BI-RADS 4A lesions needs to be improved.
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Istomin A, Masarwah A, Vanninen R, Okuma H, Sudah M. Diagnostic performance of the Kaiser score for characterizing lesions on breast MRI with comparison to a multiparametric classification system. Eur J Radiol 2021; 138:109659. [PMID: 33752000 DOI: 10.1016/j.ejrad.2021.109659] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/05/2021] [Accepted: 03/15/2021] [Indexed: 12/20/2022]
Abstract
PURPOSE To determine the diagnostic performance of the Kaiser score and to compare it with the BI-RADS-based multiparametric classification system (MCS). METHOD Two breast radiologists, blinded to the clinical and pathological information, separately evaluated a database of 499 consecutive patients with structural 3.0 T breast MRI and 697 histopathologically verified lesions. The Kaiser scores and corresponding MCS categories were recorded. The sensitivity and specificity of the Kaiser score and the MCS categories to differentiate benign from malignant lesions were calculated. The interobserver reproducibility and receiver operating characteristic (ROC) parameters were analysed. RESULTS The sensitivity and specificity of the MCS were 100 % and 12 %, respectively, and those of the Kaiser score were 98.5 % and 34.8 % for reader 1 and 98.7 % and 47.5 % for reader 2. The area under the ROC-curve was 85.9 and 87.6 for readers 1 and 2. The interobserver intraclass correlation coefficient was excellent at 0.882. Reader 1 upgraded six lesions from BI-RADS 3 to a Kaiser score of >4, and reader 2 upgraded seven lesions. When applying the Kaiser score to 158 benign lesions readers 1 and 2 would have reduced the biopsy rate by 22.8 % and 35.4 %, respectively. CONCLUSIONS The Kaiser score showed high diagnostic accuracy with excellent interobserver reproducibility. The MCS had perfect sensitivity but low specificity. Although the Kaiser score had slightly lower sensitivity, its specificity was 3-4 times greater than that of the MCS. Thus, the Kaiser score has the potential to considerably reduce the biopsy rate for true negative lesions.
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Affiliation(s)
- Aleksandr Istomin
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland
| | - Amro Masarwah
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland
| | - Ritva Vanninen
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland; University of Eastern Finland, Cancer Center of Eastern Finland, Kuopio, Finland; University of Eastern Finland, Institute of Clinical Medicine, School of Medicine, Kuopio, Finland
| | - Hidemi Okuma
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland
| | - Mazen Sudah
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland; University of Eastern Finland, Cancer Center of Eastern Finland, Kuopio, Finland.
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Subclassification of BI-RADS 4 Magnetic Resonance Lesions: A Systematic Review and Meta-Analysis. J Comput Assist Tomogr 2020; 44:914-920. [PMID: 33196599 DOI: 10.1097/rct.0000000000001108] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
OBJECTIVE This research aims to investigate and evaluate the diagnostic efficacy of magnetic resonance imaging (MRI) in classifying Breast Imaging Reporting and Data System (BI-RADS) 4 lesions into subcategories: 4a, 4b, and 4c, so as to limit biopsies of suspected lesions in the breast. METHODS The PubMed, Web of Science, Embase, and Cochrane Library foreign language databases were searched for literature published between January 2000 and July 2018. After analyzing the selection, data extraction, and quality assessment, a meta-analysis was performed, including data pooling, heterogeneity testing, and meta-regression. RESULTS Fourteen articles, including 18 studies, met the inclusion criteria. The diagnostic efficacy of MRI for BI-RADS 4-weighted summary assay sensitivity and specificity were estimated at 0.95 [95% confidence interval (CI), 0.89-0.98] and 0.87 (95% CI, 0.81-0.91), respectively. The positive and negative likelihood ratios were 7.1 (95% CI, 4.7-10.7) and 0.06 (95% CI, 0.02-0.14), respectively. The diagnostic odds ratio was 126 (95% CI, 37-426), and the area under the receiver operating characteristic curve was 0.95 (95% CI, 0.93-0.97). The malignancy ratio of BI-RADS 4a, 4b, and 4c and malignancy range were 2.5% to 18.3%, 23.5% to 57.1%, and 58.0% to 95.2%, respectively. CONCLUSION Risk stratification of suspected lesions (BI-RADS categories 4a, 4b, and 4c) can be achieved by MRI. The MRI is an effective auxiliary tool to further subclassify BI-RADS 4 lesions and prevent unnecessary biopsy of BI-RADS 4a lesions.
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Istomin A, Masarwah A, Okuma H, Sutela A, Vanninen R, Sudah M. A multiparametric classification system for lesions detected by breast magnetic resonance imaging. Eur J Radiol 2020; 132:109322. [DOI: 10.1016/j.ejrad.2020.109322] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 09/19/2020] [Accepted: 09/24/2020] [Indexed: 12/18/2022]
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A multiparametric approach to diagnosing breast lesions using diffusion-weighted imaging and ultrafast dynamic contrast-enhanced MRI. Magn Reson Imaging 2020; 71:154-160. [DOI: 10.1016/j.mri.2020.04.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 02/06/2020] [Accepted: 04/12/2020] [Indexed: 12/30/2022]
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Rahbar H, Zhang Z, Chenevert TL, Romanoff J, Kitsch AE, Hanna LG, Harvey SM, Moy L, DeMartini WB, Dogan B, Yang WT, Wang LC, Joe BN, Oh KY, Neal CH, McDonald ES, Schnall MD, Lehman CD, Comstock CE, Partridge SC. Utility of Diffusion-weighted Imaging to Decrease Unnecessary Biopsies Prompted by Breast MRI: A Trial of the ECOG-ACRIN Cancer Research Group (A6702). Clin Cancer Res 2019; 25:1756-1765. [PMID: 30647080 DOI: 10.1158/1078-0432.ccr-18-2967] [Citation(s) in RCA: 86] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Revised: 11/05/2018] [Accepted: 11/30/2018] [Indexed: 12/20/2022]
Abstract
PURPOSE Conventional breast MRI is highly sensitive for cancer detection but prompts some false positives. We performed a prospective, multicenter study to determine whether apparent diffusion coefficients (ADCs) from diffusion-weighted imaging (DWI) can decrease MRI false positives.Experimental Design: A total of 107 women with MRI-detected BI-RADS 3, 4, or 5 lesions were enrolled from March 2014 to April 2015. ADCs were measured both centrally and at participating sites. ROC analysis was employed to assess diagnostic performance of centrally measured ADCs and identify optimal ADC thresholds to reduce unnecessary biopsies. Lesion reference standard was based on either definitive biopsy result or at least 337 days of follow-up after the initial MRI procedure. RESULTS Of 107 women enrolled, 67 patients (median age 49, range 24-75 years) with 81 lesions with confirmed reference standard (28 malignant, 53 benign) and evaluable DWI were analyzed. Sixty-seven of 81 lesions were BI-RADS 4 (n = 63) or 5 (n = 4) and recommended for biopsy. Malignancies exhibited lower mean in centrally measured ADCs (mm2/s) than benign lesions [1.21 × 10-3 vs.1.47 × 10-3; P < 0.0001; area under ROC curve = 0.75; 95% confidence interval (CI) 0.65-0.84]. In centralized analysis, application of an ADC threshold (1.53 × 10-3 mm2/s) lowered the biopsy rate by 20.9% (14/67; 95% CI, 11.2%-31.2%) without affecting sensitivity. Application of a more conservative threshold (1.68 × 10-3 mm2/s) to site-measured ADCs reduced the biopsy rate by 26.2% (16/61) but missed three cancers. CONCLUSIONS DWI can reclassify a substantial fraction of suspicious breast MRI findings as benign and thereby decrease unnecessary biopsies. ADC thresholds identified in this trial should be validated in future phase III studies.
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Affiliation(s)
- Habib Rahbar
- University of Washington School of Medicine, Seattle, Washington.
| | - Zheng Zhang
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | | | - Justin Romanoff
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Averi E Kitsch
- University of Washington School of Medicine, Seattle, Washington
| | - Lucy G Hanna
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Sara M Harvey
- Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Linda Moy
- New York University School of Medicine, New York, New York
| | - Wendy B DeMartini
- University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | | | - Wei T Yang
- MD Anderson Cancer Center, Houston, Texas
| | - Lilian C Wang
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Bonnie N Joe
- University of California, San Francisco School of Medicine, San Francisco, California
| | - Karen Y Oh
- Oregon Health Sciences University, Portland, Oregon
| | - Colleen H Neal
- University of Michigan Medical School, Ann Arbor, Michigan
| | - Elizabeth S McDonald
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Mitchell D Schnall
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Constance D Lehman
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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