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Kim JY, Partridge SC. Non-contrast Breast MR Imaging. Radiol Clin North Am 2024; 62:661-678. [PMID: 38777541 PMCID: PMC11116814 DOI: 10.1016/j.rcl.2023.12.009] [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] [Indexed: 05/25/2024]
Abstract
Considering the high cost of dynamic contrast-enhanced MR imaging and various contraindications and health concerns related to administration of intravenous gadolinium-based contrast agents, there is emerging interest in non-contrast-enhanced breast MR imaging. Diffusion-weighted MR imaging (DWI) is a fast, unenhanced technique that has wide clinical applications in breast cancer detection, characterization, prognosis, and predicting treatment response. It also has the potential to serve as a non-contrast MR imaging screening method. Standardized protocols and interpretation strategies can help to enhance the clinical utility of breast DWI. A variety of other promising non-contrast MR imaging techniques are in development, but currently, DWI is closest to clinical integration, while others are still mostly used in the research setting.
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Affiliation(s)
- Jin You Kim
- Department of Radiology and Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Savannah C Partridge
- Department of Radiology, University of Washington, Seattle, WA, USA; Fred Hutchinson Cancer Center, Seattle, WA, USA.
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Wielema M, Sijens PE, Pijnappel RM, De Bock GH, Zorgdrager M, Kok MGJ, Rainer E, Varga R, Clauser P, Oudkerk M, Dorrius MD, Baltzer PAT. Image quality of DWI at breast MRI depends on the amount of fibroglandular tissue: implications for unenhanced screening. Eur Radiol 2024; 34:4730-4737. [PMID: 38008743 PMCID: PMC11213722 DOI: 10.1007/s00330-023-10321-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: 04/11/2023] [Revised: 06/29/2023] [Accepted: 07/05/2023] [Indexed: 11/28/2023]
Abstract
OBJECTIVES To compare image quality of diffusion-weighted imaging (DWI) and contrast-enhanced breast MRI (DCE-T1) stratified by the amount of fibroglandular tissue (FGT) as a measure of breast density. METHODS Retrospective, multi-reader, bicentric visual grading analysis study on breast density (A-D) and overall image and fat suppression quality of DWI and DCE-T1, scored on a standard 5-point Likert scale. Cross tabulations and visual grading characteristic (VGC) curves were calculated for fatty breasts (A/B) versus dense breasts (C/D). RESULTS Image quality of DWI was higher in the case of increased breast density, with good scores (score 3-5) in 85.9% (D) and 88.4% (C), compared to 61.6% (B) and 53.5% (A). Overall image quality of DWI was in favor of dense breasts (C/D), with an area under the VGC curve of 0.659 (p < 0.001). Quality of DWI and DCE-T1 fat suppression increased with higher breast density, with good scores (score 3-5) for 86.9% and 45.7% of density D, and 90.2% and 42.9% of density C cases, compared to 76.0% and 33.6% for density B and 54.7% and 29.6% for density A (DWI and DCE-T1 respectively). CONCLUSIONS Dense breasts show excellent fat suppression and substantially higher image quality in DWI images compared with non-dense breasts. These results support the setup of studies exploring DWI-based MR imaging without IV contrast for additional screening of women with dense breasts. CLINICAL RELEVANCE STATEMENT Our findings demonstrate that image quality of DWI is robust in women with an increased amount of fibroglandular tissue, technically supporting the feasibility of exploring applications such as screening of women with mammographically dense breasts. KEY POINTS • Image and fat suppression quality of diffusion-weighted imaging are dependent on the amount of fibroglandular tissue (FGT) which is closely connected to breast density. • Fat suppression quality in diffusion-weighted imaging of the breast is best in women with a high amount of fibroglandular tissue. • High image quality of diffusion-weighted imaging in women with a high amount of FGT in MRI supports that the technical feasibility of DWI can be explored in the additional screening of women with mammographically dense breasts.
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Affiliation(s)
- Mirjam Wielema
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Paul E Sijens
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Ruud M Pijnappel
- Department of Radiology, Utrecht University, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Geertruida H De Bock
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Marcel Zorgdrager
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Marius G J Kok
- Department of Radiology, Medisch Spectrum Twente, Enschede, the Netherlands
| | - Eva Rainer
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Raoul Varga
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Paola Clauser
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | | | - Monique D Dorrius
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Pascal A T Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
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Pötsch N, Sodano C, Baltzer PAT. Performance of Diffusion-weighted Imaging-based Noncontrast MRI Protocols for Diagnosis of Breast Cancer: A Systematic Review and Meta-Analysis. Radiology 2024; 311:e232508. [PMID: 38771179 DOI: 10.1148/radiol.232508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Background Diffusion-weighted imaging (DWI) is increasingly recognized as a powerful diagnostic tool and tested alternative to contrast-enhanced (CE) breast MRI. Purpose To perform a systematic review and meta-analysis that assesses the diagnostic performance of DWI-based noncontrast MRI protocols (ncDWI) for the diagnosis of breast cancer. Materials and Methods A systematic literature search in PubMed for articles published from January 1985 to September 2023 was performed. Studies were excluded if they investigated malignant lesions or selected patients and/or lesions only, used DWI as an adjunct technique to CE MRI, or were technical studies. Statistical analysis included pooling of diagnostic accuracy and investigating between-study heterogeneity. Additional subgroup comparisons of ncDWI to CE MRI and standard mammography were performed. Results A total of 28 studies were included, with 4406 lesions (1676 malignant, 2730 benign) in 3787 patients. The pooled sensitivity and specificity of ncDWI were 86.5% (95% CI: 81.4, 90.4) and 83.5% (95% CI: 76.9, 88.6), and both measures presented with high between-study heterogeneity (I 2 = 81.6% and 91.6%, respectively; P < .001). CE MRI (18 studies) had higher sensitivity than ncDWI (95.1% [95% CI: 92.9, 96.7] vs 88.9% [95% CI: 82.4, 93.1], P = .004) at similar specificity (82.2% [95% CI: 75.0, 87.7] vs 82.0% [95% CI: 74.8, 87.5], P = .97). Compared with ncDWI, mammography (five studies) showed no evidence of a statistical difference for sensitivity (80.3% [95% CI: 56.3, 93.3] vs 56.7%; [95% CI: 41.9, 70.4], respectively; P = .09) or specificity (89.9% [95% CI: 85.5, 93.1] vs 90% [95% CI: 61.3, 98.1], respectively; P = .62), but ncDWI had a higher area under the summary receiver operating characteristic curve (0.93 [95% CI: 0.91, 0.95] vs 0.78 [95% CI: 0.74, 0.81], P < .001). Conclusion A direct comparison with CE MRI showed a modestly lower sensitivity at similar specificity for ncDWI, and higher diagnostic performance indexes for ncDWI than standard mammography. Heterogeneity was high, thus these results must be interpreted with caution. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kataoka and Iima in this issue.
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Affiliation(s)
- Nina Pötsch
- From the Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Claudia Sodano
- From the Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Pascal A T Baltzer
- From the Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
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Gullo RL, Partridge SC, Shin HJ, Thakur SB, Pinker K. Update on DWI for Breast Cancer Diagnosis and Treatment Monitoring. AJR Am J Roentgenol 2024; 222:e2329933. [PMID: 37850579 PMCID: PMC11196747 DOI: 10.2214/ajr.23.29933] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2023]
Abstract
DWI is a noncontrast MRI technique that measures the diffusion of water molecules within biologic tissue. DWI is increasingly incorporated into routine breast MRI examinations. Currently, the main applications of DWI are breast cancer detection and characterization, prognostication, and prediction of treatment response to neoadjuvant chemotherapy. In addition, DWI is promising as a noncontrast MRI alternative for breast cancer screening. Problems with suboptimal resolution and image quality have restricted the mainstream use of DWI for breast imaging, but these shortcomings are being addressed through several technologic advancements. In this review, we present an up-to-date assessment of the use of DWI for breast cancer imaging, including a summary of the clinical literature and recommendations for future use.
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Affiliation(s)
- Roberto Lo Gullo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Savannah C Partridge
- Department of Radiology, University of Washington School of Medicine, University of Washington, Seattle, WA, USA 98109, USA
| | - Hee Jung Shin
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, South Korea
| | - Sunitha B Thakur
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Katja Pinker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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Kim YS, Lee SH, Kim SY, Kim ES, Park AR, Chang JM, Park VY, Yoon JH, Kang BJ, Yun BL, Kim TH, Ko ES, Chu AJ, Kim JY, Youn I, Chae EY, Choi WJ, Kim HJ, Kang SH, Ha SM, Moon WK. Unenhanced Breast MRI With Diffusion-Weighted Imaging for Breast Cancer Detection: Effects of Training on Performance and Agreement of Subspecialty Radiologists. Korean J Radiol 2024; 25:11-23. [PMID: 38184765 PMCID: PMC10788600 DOI: 10.3348/kjr.2023.0528] [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: 06/04/2023] [Revised: 10/26/2023] [Accepted: 10/30/2023] [Indexed: 01/08/2024] Open
Abstract
OBJECTIVE To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI). MATERIALS AND METHODS A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm² was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive. The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC). RESULTS Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4-79.9), 90.8% (95% CI: 85.6-94.2), and 83.5% (95% CI: 78.6-87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8-97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9-89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1-79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52-0.63) before training and 0.68 (95% CI: 0.62-0.74) after training, with a difference of 0.11 (95% CI: 0.02-0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69-0.74) before training and 0.79 (95% CI: 0.76-0.80) after training (P = 0.002). CONCLUSION Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.
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Affiliation(s)
- Yeon Soo Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Soo-Yeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Eun Sil Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ah Reum Park
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jung Min Chang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Vivian Youngjean Park
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jung Hyun Yoon
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Bong Joo Kang
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Bo La Yun
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Radiology, Seoul National University Bundang Hospital, Seoul, Republic of Korea
| | - Tae Hee Kim
- Department of Radiology, Ajou University Medical Center, Suwon, Republic of Korea
| | - Eun Sook Ko
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Seoul, Republic of Korea
| | - A Jung Chu
- Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Republic of Korea
| | - Jin You Kim
- Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Inyoung Youn
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Eun Young Chae
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Woo Jung Choi
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Hee Jeong Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Soo Hee Kang
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Su Min Ha
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
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Ahn HS, Kim SH, Kim JY, Hong MJ, Lee HS. Accelerating acquisition of readout-segmented echo planar imaging (rs-EPI) with a simultaneous multislice (SMS) technique for diffusion-weighted (DW) breast MRI: Evaluation of image quality factors. Eur J Radiol 2024; 170:111251. [PMID: 38128255 DOI: 10.1016/j.ejrad.2023.111251] [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: 01/13/2023] [Revised: 04/25/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023]
Abstract
PURPOSE This study aims to compare the image quality, apparent diffusion coefficient (ADC), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) values, and scan time between readout-segmented echo planar imaging (rs-EPI) and simultaneous multislice (SMS) rs-EPI sequences. METHODS A total of 80 consecutive women who underwent breast diffusion-weighted imaging (DWI) were included, and two rs-EPI DWI sequences with and without SMS were acquired and compared. Qualitative analysis involved three radiologists independently scoring image quality and radiologist preference. For quantitative comparison, the radiologists independently measured the ADC values in patients, while SNR, CNR, and ADC values were measured on a phantom. RESULTS The acquisition time was 5:47 min for rs-EPI and 3:20 min for SMS rs-EPI. In terms of image quality, scores were similar between rs-EPI and SMS rs-EPI sequences in the pooled data set, with the exception of skin-line distinction (p = 0.001) and background noise (p < 0.001). All radiologists considered SMS rs-EPI as equal or superior to rs-EPI in more than 70 % of cases. SMS rs-EPI demonstrated significantly higher ADC values than rs-EPI by all radiologists (p ≤ 0.002). For the phantom measurement, ADC (SMS: 1.26 ± 0.68 and RS: 1.26 ± 0.68, p = 0.198), SNR (SMS: 540.6 ± 342.1 and RS: 558.8 ± 523.2, p = 0.927), and CNR (SMS: 235.5 ± 38.9 and RS: 252.8 ± 108.0, p = 0.784) values did not significantly differ between the two sequences. CONCLUSION SMS rs-EPI exhibited comparable image quality and similar ADC, SNR, and CNR values to rs-EPI while reducing the scan time by 42%.
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Affiliation(s)
- Hye Shin Ahn
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea
| | - Sung Hun Kim
- Department of Radiology, College of Medicine, Seoul St. Mary's Hospital, The Catholic University of Korea, Seoul, Republic of Korea.
| | - Ji Youn Kim
- Department of Radiology, College of Medicine, Yeouido St. Mary's Hospital, The Catholic University of Korea, Seoul, Republic of Korea
| | - Min Ji Hong
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea
| | - Hyun-Soo Lee
- Siemens Healthineers Ltd., Seoul, Republic of Korea
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Kazama T, Takahara T, Endo J, Yamamuro H, Sekiguchi T, Niwa T, Niikura N, Okamura T, Kumaki N, Hashimoto J. Computed diffusion-weighted imaging with a low-apparent diffusion coefficient-pixel cut-off technique for breast cancer detection. Br J Radiol 2023; 96:20220951. [PMID: 37393536 PMCID: PMC10607411 DOI: 10.1259/bjr.20220951] [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: 10/10/2022] [Revised: 06/15/2023] [Accepted: 06/24/2023] [Indexed: 07/03/2023] Open
Abstract
OBJECTIVE This study aimed to compare the image quality and diagnostic performance of computed diffusion-weighted imaging (DWI) with low-apparent diffusion coefficient (ADC)-pixel cut-off technique (cDWI cut-off) and actual measured DWI (mDWI). METHODS Eighty-seven consecutive patients with malignant breast lesions and 72 with negative breast lesions who underwent breast MRI were retrospectively evaluated. Computed DWI with high b-values of 800, 1200, and 1500 s/mm2 and ADC cut-off thresholds of none, 0, 0.3, and 0.6 (×10-3 mm2/s) were generated from DWI with two b-values (0 and 800 s/mm2). To identify the optimal conditions, two radiologists evaluated the fat suppression and lesion reduction failure using a cut-off technique. The contrast between breast cancer and glandular tissue was evaluated using region of interest analysis. Three other board-certified radiologists independently assessed the optimised cDWI cut-off and mDWI data sets. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. RESULTS When an ADC cut-off threshold of 0.3 or 0.6 (× 10-3 mm2/s) was applied, fat suppression improved significantly (p < .05). The contrast of the cDWI cut-off with a b-value of 1200 or 1500 s/mm2 was better than the mDWI (p < .01). The ROC area under the curve for breast cancer detection was 0.837 for the mDWI and 0.909 for the cDWI cut-off (p < .01). CONCLUSION The cDWI cut-off provided better diagnostic performance than mDWI for breast cancer detection. ADVANCES IN KNOWLEDGE Using the low-ADC-pixel cut-off technique, computed DWI can improve diagnostic performance by increasing contrast and eliminating un-suppressed fat signals.
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Affiliation(s)
- Toshiki Kazama
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan
| | - Taro Takahara
- Department of Biomedical Engineering, Tokai University School of Engineering, Hiratsuka, Japan
| | - Jun Endo
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan
| | - Hiroshi Yamamuro
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan
| | - Tatsuya Sekiguchi
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan
| | - Tetsu Niwa
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan
| | - Naoki Niikura
- Department of Breast Oncology, Tokai University School of Medicine, Isehara, Japan
| | - Takuho Okamura
- Department of Breast Oncology, Tokai University School of Medicine, Isehara, Japan
| | - Nobue Kumaki
- Department of Pathology, Tokai University School of Medicine, Isehara, Japan
| | - Jun Hashimoto
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan
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Tsarouchi MI, Hoxhaj A, Mann RM. New Approaches and Recommendations for Risk-Adapted Breast Cancer Screening. J Magn Reson Imaging 2023; 58:987-1010. [PMID: 37040474 DOI: 10.1002/jmri.28731] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/23/2023] [Accepted: 03/24/2023] [Indexed: 04/13/2023] Open
Abstract
Population-based breast cancer screening using mammography as the gold standard imaging modality has been in clinical practice for over 40 years. However, the limitations of mammography in terms of sensitivity and high false-positive rates, particularly in high-risk women, challenge the indiscriminate nature of population-based screening. Additionally, in light of expanding research on new breast cancer risk factors, there is a growing consensus that breast cancer screening should move toward a risk-adapted approach. Recent advancements in breast imaging technology, including contrast material-enhanced mammography (CEM), ultrasound (US) (automated-breast US, Doppler, elastography US), and especially magnetic resonance imaging (MRI) (abbreviated, ultrafast, and contrast-agent free), may provide new opportunities for risk-adapted personalized screening strategies. Moreover, the integration of artificial intelligence and radiomics techniques has the potential to enhance the performance of risk-adapted screening. This review article summarizes the current evidence and challenges in breast cancer screening and highlights potential future perspectives for various imaging techniques in a risk-adapted breast cancer screening approach. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 5.
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Affiliation(s)
- Marialena I Tsarouchi
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Alma Hoxhaj
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Ritse M Mann
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
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Lee K, Jeong YJ, Choo KS, Nam SB, Kim HY, Jung YJ, Lee SJ, Joo JH, Kim JY, Kim JJ, Kim JY, Yun MS, Nam KJ. Comparison of Fused Diffusion-Weighted Imaging Using Unenhanced MRI and Abbreviated Post-Contrast-Enhanced MRI in Patients with Breast Cancer. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1563. [PMID: 37763682 PMCID: PMC10534817 DOI: 10.3390/medicina59091563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/25/2023] [Accepted: 08/26/2023] [Indexed: 09/29/2023]
Abstract
Background and Objectives: To determine the percentage of breast cancers detectable by fused diffusion-weighted imaging (DWI) using unenhanced magnetic resonance imaging (MRI) and abbreviated post-contrast-enhanced MRI. Materials and Methods: Between October 2016 and October 2017, 194 consecutive women (mean age, 54.2 years; age range, 28-82 years) with newly diagnosed unilateral breast cancer, who underwent preoperative 3.0 T breast MRI with DWI, were evaluated. Both fused DWI and abbreviated MRI were independently reviewed by two radiologists for the detection of index cancer (which showed the most suspicious findings in both breasts), location, lesion conspicuity, lesion type, and lesion size. Moreover, the relationship between cancer detection and histopathological results of surgical specimens was evaluated. Results: Index cancer detection rates were comparable between fused DWI and abbreviated MRI (radiologist 1: 174/194 [89.7%] vs. 184/194 [94.8%], respectively, p = 0.057; radiologist 2: 174/194 [89.7%] vs. 183/194 [94.3%], respectively, p = 0.092). In both radiologists, abbreviated MRI showed a significantly higher lesion conspicuity than fused DWI (radiologist 1: 9.37 ± 2.24 vs. 8.78 ± 3.03, respectively, p < 0.001; radiologist 2: 9.16 ± 2.32 vs. 8.39 ± 2.93, respectively, p < 0.001). The κ value for the interobserver agreement of index cancer detection was 0.67 on fused DWI and 0.85 on abbreviated MRI. For lesion conspicuity, the intraclass correlation coefficients were 0.72 on fused DWI and 0.82 on abbreviated MRI. Among the histopathological factors, tumor invasiveness was associated with cancer detection on both fused DWI (p = 0.011) and abbreviated MRI (p = 0.004, radiologist 1), lymphovascular invasion on abbreviated MRI (p = 0.032, radiologist 1), and necrosis on fused DWI (p = 0.031, radiologist 2). Conclusions: Index cancer detection was comparable between fused DWI and abbreviated MRI, although abbreviated MRI showed a significantly better lesion conspicuity.
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Affiliation(s)
- Kyeyoung Lee
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan-si 50612, Republic of Korea; (K.L.); (K.S.C.)
| | - Yeo Jin Jeong
- Department of Health Promotion Center, Pusan National University Yangsan Hospital, Yangsan-si 50612, Republic of Korea;
| | - Ki Seok Choo
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan-si 50612, Republic of Korea; (K.L.); (K.S.C.)
| | - Su Bong Nam
- Department of Plastic and Reconstructive Surgery, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan-si 50612, Republic of Korea;
| | - Hyun Yul Kim
- Department of Surgery, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan-si 50612, Republic of Korea; (H.Y.K.); (Y.J.J.); (S.J.L.)
| | - Youn Joo Jung
- Department of Surgery, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan-si 50612, Republic of Korea; (H.Y.K.); (Y.J.J.); (S.J.L.)
| | - Seung Ju Lee
- Department of Surgery, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan-si 50612, Republic of Korea; (H.Y.K.); (Y.J.J.); (S.J.L.)
| | - Ji Hyeon Joo
- Department of Radiation Oncology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan-si 50612, Republic of Korea;
| | - Jin You Kim
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Hospital, Pusan National University School of Medicine, Busan 49241, Republic of Korea; (J.Y.K.); (J.J.K.)
| | - Jin Joo Kim
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Hospital, Pusan National University School of Medicine, Busan 49241, Republic of Korea; (J.Y.K.); (J.J.K.)
| | - Jee Yeon Kim
- Department of Pathology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan-si 50612, Republic of Korea;
| | - Mi Sook Yun
- Division of Biostatistics, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan-si 50612, Republic of Korea;
| | - Kyung Jin Nam
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan-si 50612, Republic of Korea; (K.L.); (K.S.C.)
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10
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Park GE, Kang BJ, Kim SH, Jung NY. The Role of Diffusion-Weighted Imaging Based on Maximum-Intensity Projection in Young Patients with Marked Background Parenchymal Enhancement on Contrast-Enhanced Breast MRI. Life (Basel) 2023; 13:1744. [PMID: 37629601 PMCID: PMC10455098 DOI: 10.3390/life13081744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/03/2023] [Accepted: 08/11/2023] [Indexed: 08/27/2023] Open
Abstract
Diffusion-weighted imaging (DWI) utilizing maximum-intensity projection (MIP) was suggested as a cost-effective alternative tool without the risk of gadolinium-based contrast agents. The purpose of this study was to investigate whether DWI MIPs played a supportive role in young (≤60) patients with marked background parenchymal enhancement (BPE) on contrast-enhanced MRI (CE-MRI). The research included 1303 patients with varying degrees of BPE, and correlations between BPE on CE-MRI, the background diffusion signal (BDS) on DWI, and clinical parameters were analyzed. Lesion detection scores were compared between CE-MRI and DWI, with DWI showing higher scores. Among the 186 lesions in 181 patients with marked BPE on CE-MRI, the main lesion on MIPs of CE-MRI was partially or completely seen in 88.7% of cases, while it was not seen in 11.3% of cases. On the other hand, the main lesion on MIPs of DWI was seen in 91.4% of cases, with only 8.6% of cases showing no visibility. DWI achieved higher scores for lesion detection compared to CE-MRI. The presence of a marked BDS was significantly associated with a lower likelihood of a higher DWI score (p < 0.001), and non-mass lesions were associated with a decreased likelihood of a higher DWI score compared with mass lesions (p = 0.196). In conclusion, the inclusion of MIPs of DWI in the preoperative evaluation of breast cancer patients, particularly young women with marked BPE, proved highly beneficial in improving the overall diagnostic process.
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Affiliation(s)
- Ga-Eun Park
- Department of Radiology, Seoul Saint Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (G.-E.P.); (B.-J.K.); (S.-h.K.)
| | - Bong-Joo Kang
- Department of Radiology, Seoul Saint Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (G.-E.P.); (B.-J.K.); (S.-h.K.)
| | - Sung-hun Kim
- Department of Radiology, Seoul Saint Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (G.-E.P.); (B.-J.K.); (S.-h.K.)
| | - Na-Young Jung
- Department of Radiology, Uijeongbu Eulji Medical Center, College of Medicine, Eulji University, Uijeongbu 11759, Republic of Korea
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11
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Kapsner LA, Balbach EL, Folle L, Laun FB, Nagel AM, Liebert A, Emons J, Ohlmeyer S, Uder M, Wenkel E, Bickelhaupt S. Image quality assessment using deep learning in high b-value diffusion-weighted breast MRI. Sci Rep 2023; 13:10549. [PMID: 37386021 PMCID: PMC10310703 DOI: 10.1038/s41598-023-37342-3] [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: 11/10/2022] [Accepted: 06/20/2023] [Indexed: 07/01/2023] Open
Abstract
The objective of this IRB approved retrospective study was to apply deep learning to identify magnetic resonance imaging (MRI) artifacts on maximum intensity projections (MIP) of the breast, which were derived from diffusion weighted imaging (DWI) protocols. The dataset consisted of 1309 clinically indicated breast MRI examinations of 1158 individuals (median age [IQR]: 50 years [16.75 years]) acquired between March 2017 and June 2020, in which a DWI sequence with a high b-value equal to 1500 s/mm2 was acquired. From these, 2D MIP images were computed and the left and right breast were cropped out as regions of interest (ROI). The presence of MRI image artifacts on the ROIs was rated by three independent observers. Artifact prevalence in the dataset was 37% (961 out of 2618 images). A DenseNet was trained with a fivefold cross-validation to identify artifacts on these images. In an independent holdout test dataset (n = 350 images) artifacts were detected by the neural network with an area under the precision-recall curve of 0.921 and a positive predictive value of 0.981. Our results show that a deep learning algorithm is capable to identify MRI artifacts in breast DWI-derived MIPs, which could help to improve quality assurance approaches for DWI sequences of breast examinations in the future.
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Affiliation(s)
- Lorenz A Kapsner
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany.
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Krankenhausstraße 12, 91054, Erlangen, Germany.
| | - Eva L Balbach
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Lukas Folle
- Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Martensstraße 3, 91058, Erlangen, Germany
| | - Frederik B Laun
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Armin M Nagel
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Andrzej Liebert
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Julius Emons
- Department of Obstetrics and Gynaecology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Universitätsstraße 21-23, 91054, Erlangen, Germany
| | - Sabine Ohlmeyer
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Michael Uder
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Evelyn Wenkel
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Sebastian Bickelhaupt
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
- German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
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12
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Chung M, Calabrese E, Mongan J, Ray KM, Hayward JH, Kelil T, Sieberg R, Hylton N, Joe BN, Lee AY. Deep Learning to Simulate Contrast-enhanced Breast MRI of Invasive Breast Cancer. Radiology 2023; 306:e213199. [PMID: 36378030 PMCID: PMC9974793 DOI: 10.1148/radiol.213199] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background There is increasing interest in noncontrast breast MRI alternatives for tumor visualization to increase the accessibility of breast MRI. Purpose To evaluate the feasibility and accuracy of generating simulated contrast-enhanced T1-weighted breast MRI scans from precontrast MRI sequences in biopsy-proven invasive breast cancer with use of deep learning. Materials and Methods Women with invasive breast cancer and a contrast-enhanced breast MRI examination that was performed for initial evaluation of the extent of disease between January 2015 and December 2019 at a single academic institution were retrospectively identified. A three-dimensional, fully convolutional deep neural network simulated contrast-enhanced T1-weighted breast MRI scans from five precontrast sequences (T1-weighted non-fat-suppressed [FS], T1-weighted FS, T2-weighted FS, apparent diffusion coefficient, and diffusion-weighted imaging). For qualitative assessment, four breast radiologists (with 3-15 years of experience) blinded to whether the method of contrast was real or simulated assessed image quality (excellent, acceptable, good, poor, or unacceptable), presence of tumor enhancement, and maximum index mass size by using 22 pairs of real and simulated contrast-enhanced MRI scans. Quantitative comparison was performed using whole-breast similarity and error metrics and Dice coefficient analysis of enhancing tumor overlap. Results Ninety-six MRI examinations in 96 women (mean age, 52 years ± 12 [SD]) were evaluated. The readers assessed all simulated MRI scans as having the appearance of a real MRI scan with tumor enhancement. Index mass sizes on real and simulated MRI scans demonstrated good to excellent agreement (intraclass correlation coefficient, 0.73-0.86; P < .001) without significant differences (mean differences, -0.8 to 0.8 mm; P = .36-.80). Almost all simulated MRI scans (84 of 88 [95%]) were considered of diagnostic quality (ratings of excellent, acceptable, or good). Quantitative analysis demonstrated strong similarity (structural similarity index, 0.88 ± 0.05), low voxel-wise error (symmetric mean absolute percent error, 3.26%), and Dice coefficient of enhancing tumor overlap of 0.75 ± 0.25. Conclusion It is feasible to generate simulated contrast-enhanced breast MRI scans with use of deep learning. Simulated and real contrast-enhanced MRI scans demonstrated comparable tumor sizes, areas of tumor enhancement, and image quality without significant qualitative or quantitative differences. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Slanetz in this issue. An earlier incorrect version appeared online. This article was corrected on January 17, 2023.
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Affiliation(s)
- Maggie Chung
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - Evan Calabrese
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - John Mongan
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - Kimberly M. Ray
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - Jessica H. Hayward
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - Tatiana Kelil
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - Ryan Sieberg
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - Nola Hylton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - Bonnie N. Joe
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - Amie Y. Lee
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
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13
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Iima M, Le Bihan D. The road to breast cancer screening with diffusion MRI. Front Oncol 2023; 13:993540. [PMID: 36895474 PMCID: PMC9989267 DOI: 10.3389/fonc.2023.993540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 01/10/2023] [Indexed: 02/23/2023] Open
Abstract
Breast cancer is the leading cause of cancer in women with a huge medical, social and economic impact. Mammography (MMG) has been the gold standard method until now because it is relatively inexpensive and widely available. However, MMG suffers from certain limitations, such as exposure to X-rays and difficulty of interpretation in dense breasts. Among other imaging methods, MRI has clearly the highest sensitivity and specificity, and breast MRI is the gold standard for the investigation and management of suspicious lesions revealed by MMG. Despite this performance, MRI, which does not rely on X-rays, is not used for screening except for a well-defined category of women at risk, because of its high cost and limited availability. In addition, the standard approach to breast MRI relies on Dynamic Contrast Enhanced (DCE) MRI with the injection of Gadolinium based contrast agents (GBCA), which have their own contraindications and can lead to deposit of gadolinium in tissues, including the brain, when examinations are repeated. On the other hand, diffusion MRI of breast, which provides information on tissue microstructure and tumor perfusion without the use of contrast agents, has been shown to offer higher specificity than DCE MRI with similar sensitivity, superior to MMG. Diffusion MRI thus appears to be a promising alternative approach to breast cancer screening, with the primary goal of eliminating with a very high probability the existence of a life-threatening lesion. To achieve this goal, it is first necessary to standardize the protocols for acquisition and analysis of diffusion MRI data, which have been found to vary largely in the literature. Second, the accessibility and cost-effectiveness of MRI examinations must be significantly improved, which may become possible with the development of dedicated low-field MRI units for breast cancer screening. In this article, we will first review the principles and current status of diffusion MRI, comparing its clinical performance with MMG and DCE MRI. We will then look at how breast diffusion MRI could be implemented and standardized to optimize accuracy of results. Finally, we will discuss how a dedicated, low-cost prototype of breast MRI system could be implemented and introduced to the healthcare market.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan
| | - Denis Le Bihan
- NeuroSpin, Joliot Institute, Department of Fundamental Research, Commissariat á l'Energie Atomique (CEA)-Saclay, Gif-sur-Yvette, France
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14
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Ji Lee E, Chang YW, Kon Sung J, Thomas B. Feasibility of deep learning k-space-to-image reconstruction for diffusion weighted imaging in patients with breast cancers: focus on image quality and reduced scan time. Eur J Radiol 2022; 157:110608. [DOI: 10.1016/j.ejrad.2022.110608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/29/2022] [Accepted: 11/08/2022] [Indexed: 11/14/2022]
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15
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Performance of abbreviated protocols versus unenhanced MRI in detecting occult breast lesions of mammography in patients with dense breasts. Sci Rep 2022; 12:13660. [PMID: 35953551 PMCID: PMC9372172 DOI: 10.1038/s41598-022-17945-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 08/03/2022] [Indexed: 12/04/2022] Open
Abstract
To assess the diagnostic ability of abbreviated protocols of MRI (AP-MRI) compared with unenhanced MRI (UE-MRI) in mammographically occult cancers in patients with dense breast tissue. The retrospective analysis consisted of 102 patients without positive findings on mammography who received preoperative MRI full diagnostic protocols (FDP) between January 2015 and December 2018. Two breast radiologists read the UE, AP, and FDP. The interpretation times were recorded. The comparisons of the sensitivity, specificity and area under the curve of each MRI protocol, and the sensitivity of these protocols in each subgroup of different size tumors used the Chi-square test. The paired sample t-test was used for evaluating the difference of reading time of the three protocols. Among 102 women, there were 68 cancers and two benign lesions in 64 patients and 38 patients had benign or negative findings. Both readers found the sensitivity and specificity of AP and UE-MRI were similar (p > 0.05), whereas compared with FDP, UE had lower sensitivity (Reader 1/Reader 2: p = 0.023, 0.004). For different lesion size groups, one of the readers found that AP and FDP had higher sensitivities than UE-MRI for detecting the lesions ≤ 10 mm in diameter (p = 0.041, p = 0.023). Compared with FDP, the average reading time of UE-MRI and AP was remarkably reduced (p < 0.001). AP-MRI had more advantages than UE-MRI to detect mammographically occult cancers, especially for breast tumors ≤ 10 mm in diameter.
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16
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Mendez AM, Fang LK, Meriwether CH, Batasin SJ, Loubrie S, Rodríguez-Soto AE, Rakow-Penner RA. Diffusion Breast MRI: Current Standard and Emerging Techniques. Front Oncol 2022; 12:844790. [PMID: 35880168 PMCID: PMC9307963 DOI: 10.3389/fonc.2022.844790] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics.
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Affiliation(s)
- Ashley M. Mendez
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Lauren K. Fang
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Claire H. Meriwether
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Summer J. Batasin
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Stéphane Loubrie
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Ana E. Rodríguez-Soto
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Rebecca A. Rakow-Penner
- Department of Radiology, University of California San Diego, La Jolla, CA, United States,Department of Bioengineering, University of California San Diego, La Jolla, CA, United States,*Correspondence: Rebecca A. Rakow-Penner,
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17
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Jeong S, Kim TH. Diffusion-weighted imaging of breast invasive lobular carcinoma: comparison with invasive carcinoma of no special type using a histogram analysis. Quant Imaging Med Surg 2022; 12:95-105. [PMID: 34993063 DOI: 10.21037/qims-21-355] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 06/03/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND To investigate the imaging findings and visibility of breast invasive lobular carcinoma (ILC) on diffusion-weighted imaging (DWI) and compare quantitative apparent diffusion coefficient (ADC) metrics of ILC and invasive carcinoma of no special type (NST) using a histogram analysis. METHODS We performed an observational retrospective study of 629 consecutive women with pathologically proven ILC and invasive ductal carcinoma of NST, who underwent 3-T MRI including DWI, between January 2017 and August 2020. RESULTS After propensity score matching, 71 women were allocated to each group. On DWI, 9 (12.7%) lesions of ILC and 4 (5.6%) invasive carcinomas of the NST were not visualized. For the tumor visibility on DWI, tumor size, tumor ADC value, and background diffusion grade were significantly associated with the visibility score in both groups (all P<0.05), whereas the mean background ADC value was not significant (P>0.05). The mean ADC (1.226×10-3 vs. 1.052×10-3 mm2/s, P<0.001), median ADC (1.222×10-3 vs. 1.051×10-3 mm2/s, P=0.002), maximum ADC (1.758×10-3 vs. 1.504×10-3 mm2/s, P<0.001), minimum ADC (0.717×10-3 vs. 0.649×10-3 mm2/s, P=0.003), 90th percentile ADC (1.506×10-3 vs. 1.292×10-3 mm2/s, P<0.001) and 10th percentile ADC (0.956×10-3 vs. 0.818×10-3 mm2/s, P=0.008) were higher in ILC than in invasive carcinoma of NST. Additionally, the ADC difference value of the ILC was higher than that of invasive carcinoma of NST (1.04×10-3 vs. 0.855×10-3 mm2/s, P=0.027). CONCLUSIONS On DWI, the visibility of ILC was lower compared to invasive carcinoma of NST. ILC showed higher quantitative ADC values and higher ADC difference values.
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Affiliation(s)
- Seongkyun Jeong
- Department of Human Intelligence Robot Engineering, Sangmyung University, Cheonan, Republic of Korea
| | - Tae Hee Kim
- Department of Radiology, Ajou University School of Medicine and Graduate School of Medicine, Suwon, Republic of Korea
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18
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Samreen N, Mercado C, Heacock L, Chacko C, Partridge SC, Chhor C. Screening Breast MRI Primer: Indications, Current Protocols, and Emerging Techniques. JOURNAL OF BREAST IMAGING 2021; 3:387-398. [PMID: 38424773 DOI: 10.1093/jbi/wbaa116] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Indexed: 03/02/2024]
Abstract
Breast dynamic contrast-enhanced MRI (DCE-MRI) is the most sensitive imaging modality for the detection of breast cancer. Screening MRI is currently performed predominantly in patients at high risk for breast cancer, but it could be of benefit in patients at intermediate risk for breast cancer and patients with dense breasts. Decreasing scan time and image interpretation time could increase cost-effectiveness, making screening MRI accessible to a larger group of patients. Abbreviated breast MRI (Ab-MRI) reduces scan time by decreasing the number of sequences obtained, but as multiple delayed contrast enhanced sequences are not obtained, no kinetic information is available. Ultrafast techniques rapidly acquire multiple sequences during the first minute of gadolinium contrast injection and provide information about both lesion morphology and vascular kinetics. Diffusion-weighted imaging is a noncontrast MRI technique with the potential to detect mammographically occult cancers. This review article aims to discuss the current indications of breast MRI as a screening tool, examine the standard breast DCE-MRI technique, and explore alternate screening MRI protocols, including Ab-MRI, ultrafast MRI, and noncontrast diffusion-weighted MRI, which can decrease scan time and interpretation time.
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Affiliation(s)
- Naziya Samreen
- New York University, Department of Radiology, Garden City, NY, USA
| | - Cecilia Mercado
- NYU School of Medicine, Department of Radiology, New York, NY, USA
| | - Laura Heacock
- NYU School of Medicine, Department of Radiology, New York, NY, USA
| | - Celin Chacko
- New York University, Department of Radiology, Garden City, NY, USA
| | | | - Chloe Chhor
- NYU School of Medicine, Department of Radiology, New York, NY, USA
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19
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Suh J, Kim JH, Kim SY, Cho N, Kim DH, Kim R, Kim ES, Jang MJ, Ha SM, Lee SH, Chang JM, Moon WK. Noncontrast-Enhanced MR-Based Conductivity Imaging for Breast Cancer Detection and Lesion Differentiation. J Magn Reson Imaging 2021; 54:631-645. [PMID: 33894088 DOI: 10.1002/jmri.27655] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 04/01/2021] [Accepted: 04/01/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND There is increasing interest in noncontrast-enhanced MRI due to safety concerns for gadolinium contrast agents. PURPOSE To investigate the clinical feasibility of MR-based conductivity imaging for breast cancer detection and lesion differentiation. STUDY TYPE Prospective. SUBJECTS One hundred and ten women, with 112 known cancers and 17 benign lesions (biopsy-proven), scheduled for preoperative MRI. FIELD STRENGTH/SEQUENCE Non-fat-suppressed T2-weighted turbo spin-echo sequence (T2WI), dynamic contrast-enhanced MRI and diffusion-weighted imaging (DWI) at 3T. ASSESSMENT Cancer detectability on each imaging modality was qualitatively evaluated on a per-breast basis: the conductivity maps derived from T2WI were independently reviewed by three radiologists (R1-R3). T2WI, DWI, and pre-operative digital mammography were independently reviewed by three other radiologists (R4-R6). Conductivity and apparent diffusion coefficient (ADC) measurements (mean, minimum, and maximum) were performed for 112 cancers and 17 benign lesions independently by two radiologists (R1 and R2). Tumor size was measured from surgical specimens. STATISTICAL TESTS Cancer detection rates were compared using generalized estimating equations. Multivariable logistic regression analysis was performed to identify factors associated with cancer detectability. Discriminating ability of conductivity and ADC was evaluated by using the areas under the receiver operating characteristic curve (AUC). RESULTS Conductivity imaging showed lower cancer detection rates (20%-32%) compared to T2WI (62%-71%), DWI (85%-90%), and mammography (79%-88%) (all P < 0.05). Fatty breast on MRI (odds ratio = 11.8, P < 0.05) and invasive tumor size (odds ratio = 1.7, P < 0.05) were associated with cancer detectability of conductivity imaging. The maximum conductivity showed comparable ability to the mean ADC in discriminating between cancers and benign lesions (AUC = 0.67 [95% CI: 0.59, 0.75] vs. 0.84 [0.76, 0.90], P = 0.06 (R1); 0.65 [0.56, 0.73] vs. 0.82 [0.74, 0.88], P = 0.07 (R2)). DATA CONCLUSION Although conductivity imaging showed suboptimal performance in breast cancer detection, the quantitative measurement of conductivity showed the potential for lesion differentiation. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- June Suh
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jun-Hyeong Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Soo-Yeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Nariya Cho
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Rihyeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eun Sil Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Myoung-Jin Jang
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Su Min Ha
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jung Min Chang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
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Ha SM, Chang JM, Lee SH, Kim ES, Kim SY, Kim YS, Cho N, Moon WK. Detection of Contralateral Breast Cancer Using Diffusion-Weighted Magnetic Resonance Imaging in Women with Newly Diagnosed Breast Cancer: Comparison with Combined Mammography and Whole-Breast Ultrasound. Korean J Radiol 2021; 22:867-879. [PMID: 33856137 PMCID: PMC8154781 DOI: 10.3348/kjr.2020.1183] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 12/14/2020] [Accepted: 12/27/2020] [Indexed: 12/02/2022] Open
Abstract
Objective To compare the screening performance of diffusion-weighted (DW) MRI and combined mammography and ultrasound (US) in detecting clinically occult contralateral breast cancer in women with newly diagnosed breast cancer. Materials and Methods Between January 2017 and July 2018, 1148 women (mean age ± standard deviation, 53.2 ± 10.8 years) with unilateral breast cancer and no clinical abnormalities in the contralateral breast underwent 3T MRI, digital mammography, and radiologist-performed whole-breast US. In this retrospective study, three radiologists independently and blindly reviewed all DW MR images (b = 1000 s/mm2 and apparent diffusion coefficient map) of the contralateral breast and assigned a Breast Imaging Reporting and Data System category. For combined mammography and US evaluation, prospectively assessed results were used. Using histopathology or 1-year follow-up as the reference standard, cancer detection rate and the patient percentage with cancers detected among all women recommended for tissue diagnosis (positive predictive value; PPV2) were compared. Results Of the 30 cases of clinically occult contralateral cancers (13 invasive and 17 ductal carcinoma in situ [DCIS]), DW MRI detected 23 (76.7%) cases (11 invasive and 12 DCIS), whereas combined mammography and US detected 12 (40.0%, five invasive and seven DCIS) cases. All cancers detected by combined mammography and US, except two DCIS cases, were detected by DW MRI. The cancer detection rate of DW MRI (2.0%; 95% confidence interval [CI]: 1.3%, 3.0%) was higher than that of combined mammography and US (1.0%; 95% CI: 0.5%, 1.8%; p = 0.009). DW MRI showed higher PPV2 (42.1%; 95% CI: 26.3%, 59.2%) than combined mammography and US (18.5%; 95% CI: 9.9%, 30.0%; p = 0.001). Conclusion In women with newly diagnosed breast cancer, DW MRI detected significantly more contralateral breast cancers with fewer biopsy recommendations than combined mammography and US.
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Affiliation(s)
- Su Min Ha
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Jung Min Chang
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Su Hyun Lee
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Eun Sil Kim
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Soo Yeon Kim
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Yeon Soo Kim
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Nariya Cho
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea.
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21
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Ahn HS, Kim SH, Kim JY, Park CS, Grimm R, Son Y. Image quality and diagnostic value of diffusion-weighted breast magnetic resonance imaging: Comparison of acquired and computed images. PLoS One 2021; 16:e0247379. [PMID: 33617567 PMCID: PMC7899336 DOI: 10.1371/journal.pone.0247379] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 02/06/2021] [Indexed: 11/18/2022] Open
Abstract
PURPOSE To compare the image quality of acquired diffusion-weighted imaging (DWI) and computed DWI and evaluate the lesion detectability and likelihood of malignancy in these datasets. MATERIALS AND METHODS This prospective study was approved by our institutional review board. A total of 29 women (mean age, 43.5 years) underwent DWI between August 2018 and April 2019 for 32 breast cancers and 16 benign breast lesions. Three radiologists independently reviewed the acquired DWI with b-values of 1000 and 2000 s/mm2 (A-b1000 and A-b2000) and the computed DWI with a b-value of 2000 s/mm2 (C-b2000). Image quality was scored and compared between the three DWI datasets. Lesion detectability was recorded, and the lesion's likelihood for malignancy was scored using a five-point scale. RESULTS The A-b1000 images were superior to the A-b2000 and C-b2000 images in chest distinction, fat suppression, and overall image quality. The A-b2000 and C-b2000 images showed comparable scores for all image quality parameters. C-b2000 showed the highest values for lesion detection among all readers, although there was no statistical difference in sensitivity, specificity, positive predictive value, negative predictive value, and accuracy between the DWI datasets. The malignancy scores of the DWI images were not significantly different among the three readers. CONCLUSIONS A-b1000 DWI is suitable for breast lesion evaluations, considering its better image quality and comparable diagnostic values compared to that of A-b2000 and C-b2000 images. The additional use of computed high b-value DWI may have the potential to increase the detectability of breast masses.
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Affiliation(s)
- Hye Shin Ahn
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea
| | - Sung Hun Kim
- Department of Radiology, College of Medicine, Seoul St. Mary’s Hospital, The Catholic University of Korea, Seoul, Republic of Korea
- * E-mail:
| | - Ji Youn Kim
- Department of Radiology, College of Medicine, Yeouido St. Mary’s Hospital, The Catholic University of Korea, Seoul, Republic of Korea
| | - Chang Suk Park
- Department of Radiology, College of Medicine, Incheon St. Mary’s Hospital, The Catholic University of Korea, Icheon, Republic of Korea
| | - Robert Grimm
- MR Applications Development, Siemens Healthcare, Erlangen, Germany
| | - Yohan Son
- Siemens Healthineers Ltd., Seoul, Republic of Korea
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Kim JJ, Kim JY. Fusion of high b-value diffusion-weighted and unenhanced T1-weighted images to diagnose invasive breast cancer: factors associated with false-negative results. Eur Radiol 2021; 31:4860-4871. [PMID: 33443601 DOI: 10.1007/s00330-020-07644-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 11/06/2020] [Accepted: 12/17/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVES We sought factors associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast breast magnetic resonance imaging (MRI) using fused high b-value diffusion-weighted imaging (DWI) and unenhanced T1-weighted images (T1WI). METHODS Between 2018 and 2019, 316 consecutive women (mean age, 54.6 years) with invasive breast cancer who underwent preoperative breast MRI, including fused high b-value DWI and unenhanced T1WI, were retrospectively evaluated. Malignancy confidence ratings of the most suspicious breast lesions evident on fused DWI were derived by two radiologists using a 6-point Likert-type scale. Both clinicopathological and imaging features were analyzed. Multivariate regression analysis was performed to identify factors associated with false-negative DWI results in the diagnosis of invasive breast cancer. RESULTS Of the 316 breast cancers, fused DWI yielded 289 (91.5%) true-positive and 27 (8.5%) false-negative results. Multivariate analysis showed that small tumor size (≤ 1 cm) (odds ratio [OR], 5.95; 95% confidence interval [CI], 2.11, 16.81; p = 0.001), presence of calcifications in the tumor (OR, 3.41; 95% CI, 1.27, 9.15; p = 0.015), and a moderate/marked background diffusion signal (ORs, 4.23 and 19.18; 95% CI, 1.31, 13.67 and 6.51, 56.46; p = 0.016 and p < 0.001, respectively) were significantly associated with false-negative results. In subgroup analysis of 141 screening-detected cancers, a marked background diffusion signal (OR, 7.94; 95% CI, 2.30, 27.35; p = 0.001) remained significantly associated with false-negative results in the multivariate analysis. CONCLUSIONS In addition to histopathological features, a higher background diffusion signal was associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast MRI using fused high b-value DWI and unenhanced T1WI. KEY POINTS • Subcentimeter tumors and presence of calcifications in the tumor are associated with false-negative diffusion-weighted imaging results in the diagnosis of invasive breast cancer. • A higher degree of background diffusion signal may lead to false-negative interpretation of diffusion-weighted imaging in patients with invasive breast cancer.
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Affiliation(s)
- Jin Joo Kim
- Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea
| | - Jin You Kim
- Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea.
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Shin HJ, Lee SH, Park VY, Yoon JH, Kang BJ, Yun BL, Kim TH, Ko ES, Han BK, Chu AJ, Park SY, Kim HH, Moon WK. Diffusion-Weighted Magnetic Resonance Imaging for Breast Cancer Screening in High-Risk Women: Design and Imaging Protocol of a Prospective Multicenter Study in Korea. J Breast Cancer 2021; 24:218-228. [PMID: 33913277 PMCID: PMC8090809 DOI: 10.4048/jbc.2021.24.e19] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 03/16/2021] [Accepted: 03/17/2021] [Indexed: 12/12/2022] Open
Abstract
Purpose Interest in unenhanced magnetic resonance imaging (MRI) screening for breast cancer is growing due to concerns about gadolinium deposition in the brain and the high cost of contrast-enhanced MRI. The purpose of this report is to describe the protocol of the Diffusion-Weighted Magnetic Resonance Imaging Screening Trial (DWIST), which is a prospective, multicenter, intraindividual comparative cohort study designed to compare the performance of mammography, ultrasonography, dynamic contrast-enhanced (DCE) MRI, and diffusion-weighted (DW) MRI screening in women at high risk of developing breast cancer. Methods A total of 890 women with BRCA mutation or family history of breast cancer and lifetime risk ≥ 20% are enrolled. The participants undergo 2 annual breast screenings with digital mammography, ultrasonography, DCE MRI, and DW MRI at 3.0 T. Images are independently interpreted by trained radiologists. The reference standard is a combination of pathology and 12-month follow-up. Each image modality and their combination will be compared in terms of sensitivity, specificity, accuracy, positive predictive value, rate of invasive cancer detection, abnormal interpretation rate, and characteristics of detected cancers. The first participant was enrolled in April 2019. At the time of manuscript submission, 5 academic medical centers in South Korea are actively enrolling eligible women and a total of 235 women have undergone the first round of screening. Completion of enrollment is expected in 2022 and the results of the study are expected to be published in 2026. Discussion DWIST is the first prospective multicenter study to compare the performance of DW MRI and conventional imaging modalities for breast cancer screening in high-risk women. DWIST is currently in the patient enrollment phase. Trial Registration ClinicalTrials.gov Identifier: NCT03835897
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Affiliation(s)
- Hee Jung Shin
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, Seoul, Korea
| | - Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Vivian Youngjean Park
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Seoul, Korea
| | - Jung Hyun Yoon
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Seoul, Korea
| | - Bong Joo Kang
- Department of Radiology, Seoul St. Mary's Hospital, Seoul, Korea
| | - Bo La Yun
- Department of Radiology, Seoul National University Bundang Hospital, Seoul, Korea
| | - Tae Hee Kim
- Department of Radiology, Ajou University Medical Center, Suwon, Korea
| | - Eun Sook Ko
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Seoul, Korea
| | - Boo Kyung Han
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Seoul, Korea
| | - A Jung Chu
- Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea
| | - Seo Young Park
- Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, Seoul, Korea
| | - Hak Hee Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, Seoul, Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.
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Shin HJ, Lee SH, Moon WK. Diffusion-Weighted Imaging as a Stand-Alone Breast Imaging Modality. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2021; 82:29-48. [PMID: 36237448 PMCID: PMC9432391 DOI: 10.3348/jksr.2020.0215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 01/11/2021] [Accepted: 01/11/2021] [Indexed: 12/03/2022]
Abstract
확산강조영상은 유방암의 진단과 스크리닝에 있어 독립적 검사 방법으로서의 기대되는 결과를 보여주는 빠른 비조영증강 검사 방법이다. 현재까지의 연구 결과 유방암 진단에 있어 독립적 검사 방법으로서 확산강조영상의 민감도는 역동적 조영증강 검사보다는 낮으나 유방촬영술보다는 높으며, 이로써 유방암 스크리닝에 대한 유용한 대안이 될 수 있을 것으로 보인다. 확산강조영상의 표준화된 영상 획득과 판독을 통해 영상 화질이 개선될 수 있고, 판독 결과의 다양성도 감소할 것으로 기대된다. 또한, 최신 기법과 후처리 기법을 사용한 고해상도 확산강조영상을 시행함으로써 1 cm 미만의 작은 암의 발견율을 증가시킬 수 있고, 가음성 및 가양성 결과를 감소시킬 것으로 보인다. 현재 한국에서 진행 중인 고위험군 여성에서의 확산강조영상 스크리닝에 대한 다기관 연구 결과가 나온다면 독립적 검사로서의 확산강조영상의 사용을 촉진시킬 수 있을 것으로 기대된다.
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Affiliation(s)
- Hee Jung Shin
- Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, Korea
| | - Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
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Hernández ML, Osorio S, Florez K, Ospino A, Díaz GM. Abbreviated magnetic resonance imaging in breast cancer: A systematic review of literature. Eur J Radiol Open 2020; 8:100307. [PMID: 33364260 PMCID: PMC7750142 DOI: 10.1016/j.ejro.2020.100307] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 12/02/2020] [Accepted: 12/03/2020] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND : magnetic resonance imaging (MRI) has been increasingly used to study breast cancer for screening high-risk cases, pre-operative staging, and problem-solving because of its high sensitivity. However, its cost-effectiveness is still debated. Thus, the concept of abbreviated MRI (ABB-MRI) protocols was proposed as a possible solution for reducing MRI costs. PURPOSE : to investigate the role of the abbreviated MRI protocols in detecting and staging breast cancer. METHODS : a systematic search of the literature was carried out in the bibliographic databases: Scopus, PubMed, Medline, and Science Direct. RESULTS : forty-one articles were included, which described results of the assessment of fifty-three abbreviated protocols for screening, staging, recurrence assessing, and problem-solving or clarification. CONCLUSIONS : the use of ABB-MRI protocols allows reducing the acquisition and reading times, maintaining a high concordance with the final interpretation, in comparison to a complete protocol. However, larger prospective and multicentre trials are necessary to validate the performance in specific clinical environments.
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Affiliation(s)
- María Liliana Hernández
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia
| | - Santiago Osorio
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia
- Especialización en Radiología, Universidad CES, Medellín, Colombia
| | - Katherine Florez
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia
- Especialización en Radiología, Universidad CES, Medellín, Colombia
| | - Alejandra Ospino
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia
| | - Gloria M. Díaz
- MIRP Lab–Parque i, Instituto Tecnológico Metropolitano (ITM), Medellín, Colombia
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Song SE, Woo OH, Cho KR, Seo BK, Son YH, Grimm R, Liu W, Moon WK. Simultaneous Multislice Readout-Segmented Echo Planar Imaging for Diffusion-Weighted MRI in Patients With Invasive Breast Cancers. J Magn Reson Imaging 2020; 53:1108-1115. [PMID: 33170536 DOI: 10.1002/jmri.27433] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 10/23/2020] [Accepted: 10/23/2020] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND In diffusion-weighted imaging (DWI) of breast MRI, simultaneous multislice acceleration techniques can be used for readout-segmented echo planar imaging (rs-EPI) to shorten the scan time. PURPOSE To compare the image quality, apparent diffusion coefficient (ADC) value, and scan time of rs-EPI and simultaneous multislice rs-EPI (SMS rs-EPI) sequences. STUDY TYPE Retrospective. SUBJECTS In all, 134 consecutive women (mean age: 55.3 years) with invasive breast cancer who underwent preoperative MRI. FIELD STRENGTH/ SEQUENCES 3.0T; rs-EPI sequence, prototypic SMS rs-EPI sequence and dynamic contrast-enhanced MRI (DCE-MRI) sequence ASSESSMENT: For quantitative comparison, two radiologists independently measured the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), lesion contrast, and apparent diffusion coefficient (ADC). For qualitative comparison, image quality, lesion conspicuity, and reader preference were assessed with a reference of DCE-MRI. STATISTICAL TESTS Paired t-tests and Mann-Whitney tests were used. RESULTS For SNR and CNR, there were no differences between the sequences (P = 0.342 and 0.665 for reader 1; P = 0.606 and P = 0.116 for reader 2). Lesion contrast of SMS rs-EPI was higher than that of rs-EPI (P < 0.05 for both reader 1 and reader 2). Mean tumor ADC was similar in rs-EPI and SMS rs-EPI sequences (0.98 ± 0.22 vs. 1.00 ± 0.22; P = 0.291 for reader 1, 0.98 ± 0.21 vs. 1.00 ± 0.22; P = 0.418 for reader 2). Regarding qualitative comparison, image quality and lesion conspicuity were higher in SMS rs-EPI than in rs-EPI (both P < 0.05 for both readers). The two readers regarded SMS rs-EPI as superior or equal to rs-EPI in over 90% of cases. The acquisition time was 4:30 minutes for rs-EPI and 2:31 minutes for SMS rs-EPI. DATA CONCLUSION The SMS rs-EPI sequence resulted in a similar ADC value and better image quality than the rs-EPI sequence in a 44.1% reduced scan time. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY: 3.
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Affiliation(s)
- Sung Eun Song
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Ok Hee Woo
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea
| | - Kyu Ran Cho
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Bo Kyoung Seo
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | | | | | - Wei Liu
- Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea
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27
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Lee SH, Shin HJ, Moon WK. Diffusion-Weighted Magnetic Resonance Imaging of the Breast: Standardization of Image Acquisition and Interpretation. Korean J Radiol 2020; 22:9-22. [PMID: 32901461 PMCID: PMC7772373 DOI: 10.3348/kjr.2020.0093] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 05/06/2020] [Accepted: 05/09/2020] [Indexed: 12/12/2022] Open
Abstract
Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a rapid, unenhanced imaging technique that measures the motion of water molecules within tissues and provides information regarding the cell density and tissue microstructure. DW MRI has demonstrated the potential to improve the specificity of breast MRI, facilitate the evaluation of tumor response to neoadjuvant chemotherapy and can be employed in unenhanced MRI screening. However, standardization of the acquisition and interpretation of DW MRI is challenging. Recently, the European Society of Breast Radiology issued a consensus statement, which described the acquisition parameters and interpretation of DW MRI. The current article describes the basic principles, standardized acquisition protocols and interpretation guidelines, and the clinical applications of DW MRI in breast imaging.
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Affiliation(s)
- Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Hee Jung Shin
- Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.
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Clinical Feasibility of Reduced Field-of-View Diffusion-Weighted Magnetic Resonance Imaging with Computed Diffusion-Weighted Imaging Technique in Breast Cancer Patients. Diagnostics (Basel) 2020; 10:diagnostics10080538. [PMID: 32751723 PMCID: PMC7460410 DOI: 10.3390/diagnostics10080538] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 07/20/2020] [Accepted: 07/28/2020] [Indexed: 11/29/2022] Open
Abstract
Background: We evaluated the feasibility of the reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with computed DWI technique by comparison and analysis of the inter-method agreement among acquired rFOV DWI (rFOVA), rFOV DWI with computed DWI technique (rFOVS), and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in patients with breast cancer. Methods: A total of 130 patients with biopsy-proven breast cancers who underwent breast MRI from April 2017 to December 2017 were included in this study. The rFOVS were reformatted by calculation of the apparent diffusion coefficient curve obtained from rFOVA b = 0 s/mm2 and b = 500 s/mm2. Visual assessment of the image quality of rFOVA b = 1000 s/mm2, rFOVS, and DCE MRI was performed using a four-point grading system. Morphologic analyses of the index cancer was performed on rFOVA, rFOVS, and DCE MRI. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and contrast of tumor-to-parenchyma (TPC) were calculated. Results: Image quality scores with rFOVA, rFOVS, and DCE MRI were not significantly different (p = 0.357). Lesion analysis of shape, margin, and size of the index cancer also did not show significant differences among the three sequences (p = 0.858, p = 0.242, and p = 0.858, respectively). SNR, CNR, and TPC of DCE MRI were significantly higher than those of rFOVA and rFOVS (p < 0.001, p = 0.001, and p = 0.016, respectively). Significant differences were not found between the SNR, CNR, and TPC of rFOVA and those of rFOVS (p > 0.999, p > 0.999, and p > 0.999, respectively). Conclusion: The rFOVA and rFOVS showed nearly equivalent levels of image quality required for morphological analysis of the tumors and for lesion conspicuity compared with DCE MRI.
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Ha SM, Chang JM, Lee SH, Kim ES, Kim SY, Cho N, Moon WK. Diffusion-weighted MRI at 3.0 T for detection of occult disease in the contralateral breast in women with newly diagnosed breast cancer. Breast Cancer Res Treat 2020; 182:283-297. [PMID: 32447596 DOI: 10.1007/s10549-020-05697-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 05/18/2020] [Indexed: 12/15/2022]
Abstract
PURPOSE Diffusion-weighted magnetic resonance imaging (DW-MRI) offers unenhanced method to detect breast cancer without cost and safety concerns associated with dynamic contrast-enhanced (DCE) MRI. Our purpose was to evaluate the performance of DW-MRI at 3.0T in detection of clinically and mammographically occult contralateral breast cancer in patients with unilateral breast cancer. METHODS Between 2017 and 2018, 1130 patients (mean age 53.3 years; range 26-84 years) with newly diagnosed unilateral breast cancer who underwent breast MRI and had no abnormalities on clinical and mammographic examinations of contralateral breast were included. Three experienced radiologists independently reviewed DW-MRI (b = 0 and 1000 s/mm2) and DCE-MRI and assigned a BI-RADS category. Using histopathology or 1-year clinical follow-up, performance measures of DW-MRI were compared with DCE-MRI. RESULTS A total of 21 (1.9%, 21/1130) cancers were identified (12 ductal carcinoma in situ and 9 invasive ductal carcinoma; mean invasive tumor size, 8.0 mm) in the contralateral breast. Cancer detection rate of DW-MRI was 13-15 with mean of 14 per 1000 examinations (95% confidence interval [CI] 9-23 per 1000 examinations), which was lower than that of DCE-MRI (18-19 with mean of 18 per 1000 examinations, P = 0.01). A lower abnormal interpretation rate (14.0% versus 17.0%, respectively, P < 0.001) with higher specificity (87.3% versus 84.6%, respectively, P < 0.001) but lower sensitivity (77.8% versus 96.8%, respectively, P < 0.001) was noted for DW-MRI compared to DCE-MRI. CONCLUSIONS DW-MRI at 3.0T has the potential as a cost-effective tool for evaluation of contralateral breast in women with newly diagnosed breast cancer.
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Affiliation(s)
- Su Min Ha
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Jung Min Chang
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea.
| | - Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Eun Sil Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Soo-Yeon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Nariya Cho
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Republic of Korea
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30
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Jung Y, Jeong S, Kim JY, Kang DK, Kim TH. Correlations of female hormone levels with background parenchymal enhancement and apparent diffusion coefficient values in premenopausal breast cancer patients: Effects on cancer visibility. Eur J Radiol 2020; 124:108818. [PMID: 31935597 DOI: 10.1016/j.ejrad.2020.108818] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 12/31/2019] [Accepted: 01/02/2020] [Indexed: 10/25/2022]
Abstract
PURPOSE To evaluate the relationships between female hormone levels and background parenchymal enhancement (BPE) or apparent diffusion coefficient (ADC) values of breast parenchyma, as well as the effects of BPE and ADC values on cancer visibility. METHODS This prospective study was performed in 164 consecutive premenopausal patients who were diagnosed with invasive breast cancer from November 2016 to December 2018. Two radiologists analyzed the qualitative, quantitative BPE and ADC values of normal contralateral breast parenchyma. We also analyzed the cancer visibility using a three-point scale (0: no visibility, 1: slight visibility, 2: excellent visibility). RESULTS The progesterone level was significantly correlated with qualitative BPE grade and quantitative values of the BPE, as well as with the mean ADC. On contrast enhanced image (CEI), the visibility score was significantly associated with tumor size, qualitative and quantitative BPE. On diffusion weighted image (DWI), tumor size was significantly associated with the visibility score, whereas the ADC value was not. Of four lesions with a score of 0 on CEI, three had a score of 2 and one a score of 1 on DWI. Regarding the visibility score on DWI, tumor size and histologic type were significantly different among the three groups. CONCLUSIONS Qualitative or quantitative BPE of breast parenchyma was positively correlated with the progesterone level and the mean ADC was negatively correlated. The cancer visibility was affected by BPE on CEI, but not by ADC on DWI. Small-sized cancer and invasive lobular cancer could be the causes of false-negative diagnoses on DWI.
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Affiliation(s)
- Yongsik Jung
- Department of Surgery, Ajou University School of Medicine and Graduate School of Medicine, South Korea
| | - Seongkyun Jeong
- Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology, South Korea
| | - Ji Young Kim
- Department of Surgery, Ajou University School of Medicine and Graduate School of Medicine, South Korea
| | - Doo Kyoung Kang
- Department of Radiology, Ajou University School of Medicine and Graduate School of Medicine, South Korea
| | - Tae Hee Kim
- Department of Radiology, Ajou University School of Medicine and Graduate School of Medicine, South Korea.
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31
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Amornsiripanitch N, Bickelhaupt S, Shin HJ, Dang M, Rahbar H, Pinker K, Partridge SC. Diffusion-weighted MRI for Unenhanced Breast Cancer Screening. Radiology 2019; 293:504-520. [PMID: 31592734 PMCID: PMC6884069 DOI: 10.1148/radiol.2019182789] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 06/18/2019] [Accepted: 07/10/2019] [Indexed: 01/12/2023]
Abstract
Diffusion-weighted (DW) MRI is a rapid technique that measures the mobility of water molecules within tissue, reflecting the cellular microenvironment. At DW MRI, breast cancers typically exhibit reduced diffusivity and appear hyperintense to surrounding tissues. On the basis of this characteristic, DW MRI may offer an unenhanced method to detect breast cancer without the costs and safety concerns associated with dynamic contrast material-enhanced MRI, the current reference standard in the setting of high-risk screening. This application of DW MRI has not been widely explored but is particularly timely given the growing health concerns related to the long-term use of gadolinium-based contrast material. Moreover, increasing breast density notification legislation across the United States is raising awareness of the limitations of mammography in women with dense breasts, emphasizing the need for additional cost-effective supplemental screening examinations. Preliminary studies suggest unenhanced MRI with DW MRI may provide higher sensitivity than screening mammography for the detection of breast malignancies. Larger prospective multicenter trials are needed to validate single-center findings and assess the performance of DW MRI for generalized breast cancer screening. Standardization of DW MRI acquisition and interpretation is essential to ensure reliable sensitivity and specificity, and an optimal approach for screening using readily available techniques is proposed here.
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Affiliation(s)
- Nita Amornsiripanitch
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Sebastian Bickelhaupt
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Hee Jung Shin
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Madeline Dang
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Habib Rahbar
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Katja Pinker
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
| | - Savannah C. Partridge
- From the Department of Breast Imaging, University of Massachusetts Memorial Medical Center, Worcester, Mass (N.A.); Medical Imaging and Radiology–Cancer Prevention, German Cancer Research Center, Heidelberg, Germany (S.B.); Department of Radiology, Asan Medical Center, University of Ulsan, Seoul, South Korea (H.J.S.); Department of Radiology, University of Washington, 825 Eastlake Ave E, G2-600, Seattle, WA 98109 (M.D., H.R., S.C.P.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (K.P.)
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32
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Iima M, Honda M, Sigmund EE, Ohno Kishimoto A, Kataoka M, Togashi K. Diffusion MRI of the breast: Current status and future directions. J Magn Reson Imaging 2019; 52:70-90. [PMID: 31520518 DOI: 10.1002/jmri.26908] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 08/12/2019] [Indexed: 12/30/2022] Open
Abstract
Diffusion-weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non-Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characterization of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:70-90.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan
| | - Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Eric E Sigmund
- Department of Radiology, NYU Langone Health, New York, New York, USA.,Center for Advanced Imaging and Innovation (CAI2R), New York, New York, USA
| | - Ayami Ohno Kishimoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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Deike-Hofmann K, Koenig F, Paech D, Dreher C, Delorme S, Schlemmer HP, Bickelhaupt S. Abbreviated MRI Protocols in Breast Cancer Diagnostics. J Magn Reson Imaging 2018; 49:647-658. [PMID: 30328180 DOI: 10.1002/jmri.26525] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 09/11/2018] [Accepted: 09/12/2018] [Indexed: 12/12/2022] Open
Abstract
Oncologic imaging focused on the detection of breast cancer is of increasing importance, with over 1.7 million new cases detected each year worldwide. MRI of the breast has been described to be one of the most sensitive imaging modalities in breast cancer detection; however, clinical use is limited due to high costs. In the past, the objective and clinical routine of oncologic imaging was to provide one extended imaging protocol covering all potential needs and clinical implications regardless of the specific clinical indication or question. Future protocols might be more focused according to a "keep it short and simple" approach, with a reduction of patient magnet time and a limited number of images to review. Rather than replacing conventional full-diagnostic breast MRI protocols, these approaches aim at introducing a new thinking in oncologic imaging using a diversification of available imaging approaches targeted to the dedicated clinical needs of the individual patient. Here we review current approaches on using abbreviated protocols that aim to increase the clinical availability and use of breast MRI for improved early detection of breast cancer. Level of Evidence: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:647-658.
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Affiliation(s)
| | - Franziska Koenig
- German Cancer Research Center (dkfz), Department of Radiology, Heidelberg, Germany
| | - Daniel Paech
- German Cancer Research Center (dkfz), Department of Radiology, Heidelberg, Germany
| | - Constantin Dreher
- German Cancer Research Center (dkfz), Department of Radiology, Heidelberg, Germany
| | - Stefan Delorme
- German Cancer Research Center (dkfz), Department of Radiology, Heidelberg, Germany
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Abstract
Magnetic resonance imaging (MRI) of the breast represents one of the most sensitive imaging modalities in breast cancer detection. Diffusion-weighted imaging (DWI) is a sequence variation introduced as a complementary MRI technique that relies on mapping the diffusion process of water molecules thereby providing additional information about the underlying tissue. Since water diffusion is more restricted in most malignant tumors than in benign ones owing to the higher cellularity of the rapidly proliferating neoplasia, DWI has the potential to contribute to the identification and characterization of suspicious breast lesions. Thus, DWI might increase the diagnostic accuracy of breast MRI and its clinical value. Future applications including optimized DWI sequences, technical developments in MR devices, and the application of radiomics/artificial intelligence algorithms may expand the potential of DWI in breast imaging beyond its current supplementary role.
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35
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Kul S, Metin Y, Kul M, Metin N, Eyuboglu I, Ozdemir O. Assessment of breast mass morphology with diffusion-weighted MRI: Beyond apparent diffusion coefficient. J Magn Reson Imaging 2018; 48:1668-1677. [PMID: 29734493 DOI: 10.1002/jmri.26175] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Accepted: 04/12/2018] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Diffusion-weighted imaging (DWI) is a noncontrast-enhanced MRI technique. There are new promising studies on the use of DWI as a part of the enhanced or unenhanced abbreviated breast MRI protocols. PURPOSE To evaluate the ability of breast DWI in the assessment of mass morphology and determine the contribution of this morphologic evaluation in their characterization. STUDY TYPE Retrospective. POPULATION In all, 213 consecutive women were breast MR imaged and had a later confirmed diagnosis. FIELD STRENGTH/SEQUENCE Breast dynamic contrast-enhanced-MRI (DCE-MRI) and DWI at 1.5T. ASSESSMENT After Institutional Review Board approval, two radiologists first independently, and later in consensus, evaluated the visibility and morphology of the 143 malignant, 70 benign masses on DWI and DCE-MRI in separate sessions, blindly. Shape, margin, and internal pattern of the masses were evaluated according to BI-RADS lexicon. Apparent diffusion coefficient (ADC) and tumor size were measured by one radiologist. STATISTICAL TESTS Consistency between imaging methods and readers was evaluated with Cohen's kappa statistics. Multivariate analysis was applied to find the best predictors of malignancy. RESULTS Tumor visibility on DWI was high to moderate in at least 88% of cases. Consistency between DWI and DCE-MRI was substantial (kappa ≥0.757) for shape and margin and moderate (kappa = 0.505) for internal pattern. Interobserver agreement was substantial to moderate for all morphologic parameters (kappa ≥0.596). Morphology evaluated on DWI provided 83-84% accuracy in discriminating malignant from benign masses. ADC alone provided 90-91% accuracy. Both morphologic parameters and ADC were significantly associated with malignancy on multivariate analysis and provided 91-93% accuracy. DATA CONCLUSION DWI might be used not only for ADC evaluation but also for the morphological evaluation of breast masses to characterize them. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1668-1677.
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Affiliation(s)
- Sibel Kul
- Karadeniz Technical University, School of Medicine, Department of Radiology, Trabzon, Turkey
| | - Yavuz Metin
- Recep Tayyib Erdoğan University, Faculty of Medicine, Department of Radiology, Rize, Turkey
| | - Musa Kul
- Trabzon Kanuni Training and Research Hospital, Department of Radiology, Trabzon, Turkey
| | - Nurgul Metin
- Recep Tayyib Erdoğan University, Faculty of Medicine, Department of Radiology, Rize, Turkey
| | - Ilker Eyuboglu
- Karadeniz Technical University, School of Medicine, Department of Radiology, Trabzon, Turkey
| | - Oguzhan Ozdemir
- Recep Tayyib Erdoğan University, Faculty of Medicine, Department of Radiology, Rize, Turkey
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