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Noorily AR, Heller SL, Regen-Tuero HC, Li X, Goldberg JD, Gao Y. Novel Wash-In Characteristics of Background Parenchymal Enhancement on Ultrafast Dynamic Contrast-Enhanced Breast MRI. AJR Am J Roentgenol 2025. [PMID: 40266709 DOI: 10.2214/ajr.24.32624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2025]
Abstract
Background - Ultrafast MRI (UFMRI) can minimize background parenchymal enhancement (BPE), improve cancer visualization, and inform characterization of malignancy. Although BPE is a biomarker for breast cancer risk, washin characteristics of BPE are unknown. Objective - The purpose of this study was to delineate wash-in behavior of normal BPE in healthy women on UFMRI and determine association with patient characteristics. Methods - This retrospective study evaluated consecutive normal screening breast MRI examinations (BI-RADS category 1) (January 2020 to May 2022) with 1 year of negative follow-up MRI. Characteristics including age, menopausal status, and cancer risk factors were recorded. Fibroglandular tissue and BPE on conventional postcontrast sequences were documented. UFMR images were analyzed for level, time to enhancement (TTE), and maximum slope (MS) of BPE as indicators of wash-in characteristics. Ordinal logistic regressions were conducted using a significance level of .05 (two-sided). Results - The final sample included 222 women (median age, 50 years; range, 25-81 years): 110 (49.5%) premenopausal and 112 (50.5%) postmenopausal. BPE was lower on UFMRI than on conventional MRI in 98.5% of examinations with moderate or marked BPE and 85.4% of examinations with mild to marked BPE on conventional postcontrast images (p < .001). BPE on UFMRI was marked in 0% and moderate in 4.1% of examinations. BPE was significantly associated with menopausal status, inversely related to age, and significantly associated with TTE. The odds of high BPE on UFMRI were 7.815 times greater in premenopausal women (95% CI, 4.461-13.689) (p < .001), 1.067 times less per 1-year increase in age (95% CI, 1.046-10.890) (p < .001), and 1.113 times greater per 1-second decrease in TTE (95% CI, 1.589-6.383) (p = .01). MS was higher in premenopausal women but was not statistically significant. BPE was not associated with cancer risk factors. Conclusion - UFMRI mitigates BPE, essentially eliminating marked and moderate BPE. TTE varies by age and menopausal status, suggesting hormonal underpinning. Clinical impact - Minimizing BPE on UFMRI could improve diagnostic accuracy. Wash-in kinetic parameters of BPE have potential to serve as biomarkers in breast cancer risk prediction.
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Affiliation(s)
- Ariella R Noorily
- NYU Langone Health, Department of Radiology, 660 First Avenue, New York, NY 10016
| | - Samantha L Heller
- NYU Langone Health, Department of Radiology, 660 First Avenue, New York, NY 10016
| | | | - Xiaochun Li
- NYU Grossman School of Medicine, Division of Biostatistics, Department of Population Health, 180 Madison Avenue, New York, New York 10016
| | - Judith D Goldberg
- NYU Grossman School of Medicine, Division of Biostatistics, Department of Population Health, 180 Madison Avenue, New York, New York 10016
| | - Yiming Gao
- NYU Langone Health, Department of Radiology, 660 First Avenue, New York, NY 10016
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Ma D, Wang C, Li J, Hao X, Zhu Y, Gao Z, Liu C, Luo C, Huang Y. Analysis of the diagnostic efficacy of ultrasound, MRI, and combined examination in benign and malignant breast tumors. Front Oncol 2025; 15:1494862. [PMID: 39949747 PMCID: PMC11821579 DOI: 10.3389/fonc.2025.1494862] [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: 09/11/2024] [Accepted: 01/13/2025] [Indexed: 02/16/2025] Open
Abstract
Background To compare the diagnostic effectiveness of ultrasound (US), magnetic resonance imaging (MRI), and their combined application in distinguishing between benign and malignant breast tumors, with particular emphasis on evaluating diagnostic performance in different breast densities-fatty breast tissue, where fat predominates, and dense breast tissue, which contains a significant amount of fibroglandular tissue. Materials and methods A retrospective analysis was conducted on 185 patients with breast tumors, including 90 malignant and 95 benign cases. All patients underwent both US and MRI examinations within one week prior to surgery. The diagnostic accuracy of US, MRI, and their combined use in differentiating benign and malignant tumors was evaluated. Results The combined examination demonstrated the highest area under the curve (AUC), sensitivity, and negative predictive value (NPV) (0.904, 90%, 90.4%), outperforming US (0.830, 73.3%, 78.6%) and MRI (0.897, 89.7%, 88.8%). DeLong test results revealed statistically significant differences in AUC between US and MRI, as well as between US and the combined examination (P < 0.05). However, the difference in AUC between MRI and the combined examination was not significant (P = 0.939). In patients with fatty breast tissue, no significant differences were found between MRI and US, or between MRI and the combined examination (P = 0.708 and P = 0.317, respectively). However, the diagnostic performance between US and the combined examination was statistically significant (P < 0.05). For patients with dense breast tissue, the differences in diagnostic performance between US and MRI, and between US and the combined examination, were significant (P < 0.05), while the difference between MRI and the combined examination was not significant (P = 0.317). Conclusion MRI and combined examination methods significantly enhance the ability to differentiate benign and malignant breast tumors and provide important clinical value for early breast cancer detection.
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Affiliation(s)
- Dianpei Ma
- School of Medical Imaging, Bengbu Medical University, Bengbu, China
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China
| | - Changliang Wang
- College of Information Science and Technology, University of Science and Technology of China, Hefei, China
| | - Jie Li
- School of Medical Imaging, Bengbu Medical University, Bengbu, China
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China
| | - Xiaohan Hao
- the Research and Development Management Center of Anhui Fuqing Medical Equipment Co., Ltd., Hefei, China
| | - Yun Zhu
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China
| | - Zhizhen Gao
- School of Medical Imaging, Bengbu Medical University, Bengbu, China
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China
| | - Chun Liu
- the Research and Development Management Center of Anhui Fuqing Medical Equipment Co., Ltd., Hefei, China
| | - Changfan Luo
- Medical Imaging Center, Department of Electronic Science, University of Science and Technology of China, Hefei, China
| | - Yu Huang
- School of Medical Imaging, Bengbu Medical University, Bengbu, China
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Amitai Y, Freitas VAR, Golan O, Kessner R, Shalmon T, Neeman R, Mauda-Havakuk M, Mercer D, Sklair-Levy M, Menes TS. The diagnostic performance of ultrafast MRI to differentiate benign from malignant breast lesions: a systematic review and meta-analysis. Eur Radiol 2024; 34:6285-6295. [PMID: 38512492 PMCID: PMC11399157 DOI: 10.1007/s00330-024-10690-y] [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: 11/27/2023] [Revised: 02/11/2024] [Accepted: 02/15/2024] [Indexed: 03/23/2024]
Abstract
OBJECTIVES To assess the diagnostic performance of ultrafast magnetic resonance imaging (UF-DCE MRI) in differentiating benign from malignant breast lesions. MATERIALS AND METHODS A comprehensive search was conducted until September 1, 2023, in Medline, Embase, and Cochrane databases. Clinical studies evaluating the diagnostic performance of UF-DCE MRI in breast lesion stratification were screened and included in the meta-analysis. Pooled summary estimates for sensitivity, specificity, diagnostic odds ratio (DOR), and hierarchic summary operating characteristics (SROC) curves were pooled under the random-effects model. Publication bias and heterogeneity between studies were calculated. RESULTS A final set of 16 studies analyzing 2090 lesions met the inclusion criteria and were incorporated into the meta-analysis. Using UF-DCE MRI kinetic parameters, the pooled sensitivity, specificity, DOR, and area under the curve (AUC) for differentiating benign from malignant breast lesions were 83% (95% CI 79-88%), 77% (95% CI 72-83%), 18.9 (95% CI 13.7-26.2), and 0.876 (95% CI 0.83-0.887), respectively. We found no significant difference in diagnostic accuracy between the two main UF-DCE MRI kinetic parameters, maximum slope (MS) and time to enhancement (TTE). DOR and SROC exhibited low heterogeneity across the included studies. No evidence of publication bias was identified (p = 0.585). CONCLUSIONS UF-DCE MRI as a stand-alone technique has high accuracy in discriminating benign from malignant breast lesions. CLINICAL RELEVANCE STATEMENT UF-DCE MRI has the potential to obtain kinetic information and stratify breast lesions accurately while decreasing scan times, which may offer significant benefit to patients. KEY POINTS • Ultrafast breast MRI is a novel technique which captures kinetic information with very high temporal resolution. • The kinetic parameters of ultrafast breast MRI demonstrate a high level of accuracy in distinguishing between benign and malignant breast lesions. • There is no significant difference in accuracy between maximum slope and time to enhancement kinetic parameters.
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Affiliation(s)
- Yoav Amitai
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel.
| | - Vivianne A R Freitas
- Joint Department of Medical Imaging - University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, 610 University Avenue - M5G 2M9, Toronto, Ontario, Canada
| | - Orit Golan
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Rivka Kessner
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Tamar Shalmon
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Rina Neeman
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Michal Mauda-Havakuk
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Diego Mercer
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Miri Sklair-Levy
- Department of Medical Imaging, Sackler School of Medicine, Chaim Sheba Medical Center, Tel Aviv University, Tel Hashomer, Derech Shiba 2, 52621, Ramat-Gan, Israel
| | - Tehillah S Menes
- Department of Surgery, Sackler School of Medicine, Chaim Sheba Medical Center, Tel Aviv University, Tel Hashomer, Derech Shiba 2, 52621, Ramat-Gan, Israel
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Song Q, Ma C, Tian S, Meng X, Chen L, Wang N, Song Q, Lu S, Liu D, Gui H, Chen H, Lin L, Xu X, Wang J, Liu A. Acceleration of uterine 3D T2-weighted imaging by compressed SENSE-a multicentre study. Br J Radiol 2024; 97:1545-1551. [PMID: 38885406 PMCID: PMC11332668 DOI: 10.1093/bjr/tqae113] [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: 05/14/2023] [Revised: 12/01/2023] [Accepted: 06/03/2024] [Indexed: 06/20/2024] Open
Abstract
OBJECTIVES To find the optimal acceleration factor (AF) of the compressed SENSE (CS) technique for uterine isotropic high-resolution 3D T2-weighted imaging (3D-ISO-T2WI). METHODS A total of 91 female volunteers from the First Affiliated Hospital of Dalian Medical University, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, and The Fourth Hospital of Harbin were recruited. A total of 44 volunteers received uterus sagittal 3D-ISO-T2WI scans on 3.0T MRI device with different CS AFs (including SENSE3, CS3, CS4, CS5, CS6, and CS7), 51 received 3D-ISO-T2WI scans with different degrees of fat suppression (none, light, moderate, and severe), while 4 volunteers received both series of scans. Image quality was subjectively evaluated with a 3-point scoring system. Junction zone signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and myometrial SNR were also calculated. Intraclass correlation coefficients were used to analyse the consistency of the measurement results by 2 observers. Analysis of variance test or Friedman rank sum test was used to compare the differences in subjective scores, SNR, and CNR under different AFs/different degrees of fat suppression. RESULTS Images by AFs of CS3, CS4, and CS5 had the highest SNR and CNR. Among them, CS5 had the shortest scan time. CS5 also had one of the highest subjective scores. There was no significant difference in SNR and CNR among images acquired with different degrees of fat suppression. Also, images with moderate fat suppression had the highest subjective scores. CONCLUSION The CS5 combined with moderate fat suppression is recommended for routine female pelvic 3D-ISO-T2WI scan. ADVANCES IN KNOWLEDGE The CS5 has the highest image quality and has the shortest scan time, which is the best AF. Moderate fat suppression has the highest subjective scores. The CS5 and moderate fat suppression are the best combination for a female pelvic 3D-ISO-T2WI scan.
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Affiliation(s)
- Qingling Song
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian 116011, P. R. China
- Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian 116011, P. R. China
| | - Changjun Ma
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian 116011, P. R. China
- Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian 116011, P. R. China
| | - Shifeng Tian
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian 116011, P. R. China
- Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian 116011, P. R. China
| | - Xing Meng
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian 116011, P. R. China
- Department of Radiology, Dalian Women and Children Medical Center, Dalian 116033, P. R. China
| | - Lihua Chen
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian 116011, P. R. China
- Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian 116011, P. R. China
| | - Nan Wang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian 116011, P. R. China
- Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian 116011, P. R. China
| | - Qingwei Song
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian 116011, P. R. China
- Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian 116011, P. R. China
| | - Shan Lu
- Radiology Department, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin 300134, P. R. China
| | - Dengping Liu
- Radiology Department, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin 300134, P. R. China
| | - Haiyan Gui
- Magnetic Resonance Department, The Fourth Hospital of Harbin, Harbin 150026, P. R. China
| | - Honghao Chen
- Magnetic Resonance Department, The Fourth Hospital of Harbin, Harbin 150026, P. R. China
| | - Liangjie Lin
- Clinical and Technical Support, Philips Healthcare, Beijing, 100036, P. R. China
| | - Xiaofang Xu
- Clinical and Technical Support, Philips Healthcare, Beijing, 100036, P. R. China
| | - Jiazheng Wang
- Clinical and Technical Support, Philips Healthcare, Beijing, 100036, P. R. China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian 116011, P. R. China
- Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian 116011, P. R. China
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Kataoka M, Honda M, Sagawa H, Ohashi A, Sakaguchi R, Hashimoto H, Iima M, Takada M, Nakamoto Y. Ultrafast Dynamic Contrast-Enhanced MRI of the Breast: From Theory to Practice. J Magn Reson Imaging 2024; 60:401-416. [PMID: 38085134 DOI: 10.1002/jmri.29082] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 07/13/2024] Open
Abstract
The development of ultrafast dynamic contrast-enhanced (UF-DCE) MRI has occurred in tandem with fast MRI scan techniques, particularly view-sharing and compressed sensing. Understanding the strengths of each technique and optimizing the relevant parameters are essential to their implementation. UF-DCE MRI has now shifted from research protocols to becoming a part of clinical scan protocols for breast cancer. UF-DCE MRI is expected to compensate for the low specificity of abbreviated MRI by adding kinetic information from the upslope of the time-intensity curve. Because kinetic information from UF-DCE MRI is obtained from the shape and timing of the initial upslope, various new kinetic parameters have been proposed. These parameters may be associated with receptor status or prognostic markers for breast cancer. In addition to the diagnosis of malignant lesions, more emphasis has been placed on predicting and evaluating treatment response because hyper-vascularity is linked to the aggressiveness of breast cancers. In clinical practice, it is important to note that breast lesion images obtained from UF-DCE MRI are slightly different from those obtained by conventional DCE MRI in terms of morphology. A major benefit of using UF-DCE MRI is avoidance of the marked or moderate background parenchymal enhancement (BPE) that can obscure the target enhancing lesions. BPE is less prominent in the earlier phases of UF-DCE MRI, which offers better lesion-to-noise contrast. The excellent contrast of early-enhancing vessels provides a key to understanding the detailed pathological structure of tumor-associated vessels. UF-DCE MRI is normally accompanied by a large volume of image data for which automated/artificial intelligence-based processing is expected to be useful. In this review, both the theoretical and practical aspects of UF-DCE MRI are summarized. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan
| | - Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan
- Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Japan
| | - Hajime Sagawa
- Division of Clinical Radiology Service, Kyoto University Hospital, Kyoto, Japan
| | - Akane Ohashi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan
- Department of Translational Medicine, Diagnostic Radiology, Lund University, Malmö, Sweden
- Department of Imaging and Functional Medicine, Skåne University Hospital, Malmö, Sweden
| | - Rena Sakaguchi
- Department of Diagnostic Radiology, Kobe City Medical Center General Hospital, Kobe, Japan
| | - Hina Hashimoto
- Department of Human Health Science, Graduate School of Medicine Kyoto University, Kyoto, Japan
| | - Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan
- Institute for Advancement of Clinical and Translational Science (iACT), Kyoto University Hospital, Kyoto, Japan
| | - Masahiro Takada
- Department of Breast Surgery, Graduate School of Medicine Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan
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