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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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Zuiani C, Mansutti I, Caronia G, Linda A, Londero V, Girometti R. Added value of the EUSOBI diffusion levels in breast MRI. Eur Radiol 2024; 34:3352-3363. [PMID: 37932389 PMCID: PMC11126436 DOI: 10.1007/s00330-023-10418-4] [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: 07/28/2023] [Revised: 09/04/2023] [Accepted: 09/21/2023] [Indexed: 11/08/2023]
Abstract
OBJECTIVES To investigate whether using the diffusion levels (DLs) proposed by the European Society of Breast Imaging (EUSOBI) improves the diagnostic accuracy of breast MRI. MATERIALS AND METHODS This retrospective study included 145 women who, between September 2019 and June 2020, underwent breast 1.5-T MRI with DWI. Reader 1 and reader 2 (R1-R2) independently assessed breast lesions using the BI-RADS on dynamic contrast-enhanced imaging and T2-weighted imaging. DWI was subsequently disclosed, allowing readers able to measure lesions ADC and subjectively express the overall risk of malignancy on a 1-5 Likert scale. ADCs were interpreted as a range of values corresponding to the EUSOBI DLs. The analysis evaluated the inter-reader agreement in measuring ADC and DLs, the per-DL malignancy rate, and accuracy for malignancy using ROC analysis against histological examination or a 3-year follow-up. RESULTS Lesions were malignant and showed non-mass enhancement in 67.7% and 76.1% of cases, respectively. ADC was measurable in 63.2%/66.7% of lesions (R1/R2), with a minimal discrepancy on Bland-Altman analysis and 0.948 (95%CI 0.925-0.965)/0.989 (95%CI 0.988-0.991) intraclass correlation coefficient in measuring ADC/DLs. The malignancy rate (R1/R2) increased from 0.5/0.5% ("very high" DL) to 96.0/96.8% ("very low" DL), as expected. Likert categorization showed larger areas under the curve than the BI-RADS for both R1 (0.91 versus 0.87; p = 0.0208) and R2 (0.91 versus 0.89; p = 0.1171), with improved specificity (81.5% versus 78.5% for R1 and 84.4% versus 81.2% for R2). CONCLUSION Though ADC was not measurable in about one-third of lesions, DLs were categorized with excellent inter-reader agreement, improving the specificity for malignancy. CLINICAL RELEVANCE STATEMENT DLs proposed by the EUSOBI are a reproducible tool to interpret the ADC of breast lesions and, in turn, to improve the specificity of breast MRI and reduce unnecessary breast biopsies. KEY POINTS • The European Society of Breast Imaging proposed diffusion levels for the interpretation of the apparent diffusion coefficient in diffusion-weighted imaging of the breast. • Adding diffusion levels to the interpretation of magnetic resonance imaging improved the diagnostic accuracy for breast cancer, especially in terms of specificity. • Diffusion levels can favor a more widespread and standardized use of diffusion-weighted imaging of the breast.
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Affiliation(s)
- Chiara Zuiani
- Institute of Radiology, Department of Medicine, University of Udine, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy
| | - Iris Mansutti
- Institute of Radiology, Department of Medicine, University of Udine, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy
| | - Guido Caronia
- Institute of Radiology, Department of Medicine, University of Udine, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy
| | - Anna Linda
- Institute of Radiology, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy
| | - Viviana Londero
- Institute of Radiology, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy
| | - Rossano Girometti
- Institute of Radiology, Department of Medicine, University of Udine, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy.
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3
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Wu H, Jiang Y, Tian H, Ye X, Cui C, Shi S, Chen M, Ding Z, Li S, Huang Z, Luo Y, Peng Q, Xu J, Dong F. Sonography-based multimodal information platform for identifying the surgical pathology of ductal carcinoma in situ. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 245:108039. [PMID: 38266556 DOI: 10.1016/j.cmpb.2024.108039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 01/11/2024] [Accepted: 01/17/2024] [Indexed: 01/26/2024]
Abstract
BACKGROUND The risk of ductal carcinoma in situ (DCIS) identified by biopsy often increases during surgery. Therefore, confirming the DCIS grade preoperatively is necessary for clinical decision-making. PURPOSE To train a three-classification deep learning (DL) model based on ultrasound (US), combining clinical data, mammography (MG), US, and core needle biopsy (CNB) pathology to predict low-grade DCIS, intermediate-to-high-grade DCIS, and upstaged DCIS. MATERIALS AND METHODS Data of 733 patients with 754 DCIS cases confirmed by biopsy were retrospectively collected from May 2013 to June 2022 (N1), and other data (N2) were confirmed by biopsy as low-grade DCIS. The lesions were randomly divided into training (n=471), validation (n=142), and test (n = 141) sets to establish the DCIS-Net. Information on the DCIS-Net, clinical (age and sign), US (size, calcifications, type, breast imaging reporting and data system [BI-RADS]), MG (microcalcifications, BI-RADS), and CNB pathology (nuclear grade, architectural features, and immunohistochemistry) were collected. Logistic regression and random forest analyses were conducted to develop Multimodal DCIS-Net to calculate the specificity, sensitivity, accuracy, receiver operating characteristic curve, and area under the curve (AUC). RESULTS In the test set of N1, the accuracy and AUC of the multimodal DCIS-Net were 0.752-0.766 and 0.859-0.907 in the three-classification task, respectively. The accuracy and AUC for discriminating DCIS from upstaged DCIS were 0.751-0.780 and 0.829-0.861, respectively. In the test set of N2, the accuracy and AUC of discriminating low-grade DCIS from upstaged low-grade DCIS were 0.769-0.987 and 0.818-0.939, respectively. DL was ranked from one to five in the importance of features in the multimodal-DCIS-Net. CONCLUSION By developing the DCIS-Net and integrating it with multimodal information, diagnosing low-grade DCIS, intermediate-to high-grade DCIS, and upstaged DCIS is possible. It can also be used to distinguish DCIS from upstaged DCIS and low-grade DCIS from upstaged low-grade DCIS, which could pave the way for the DCIS clinical workflow.
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Affiliation(s)
- Huaiyu Wu
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China
| | - Yitao Jiang
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China; Research and Development Department, Microport Prophecy, Shanghai 201203, China
| | - Hongtian Tian
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China
| | - Xiuqin Ye
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China
| | - Chen Cui
- Research and Development Department, Illuminate, LLC, Shenzhen, Guangdong 518000, China
| | - Siyuan Shi
- Research and Development Department, Illuminate, LLC, Shenzhen, Guangdong 518000, China
| | - Ming Chen
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China
| | - Zhimin Ding
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China
| | - Shiyu Li
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China
| | - Zhibin Huang
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China
| | - Yuwei Luo
- Department of Breast Surgery, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China; Department of General Surgery, Shenzhen People's Hospital, Shenzhen 518020, Guangdong, China
| | - Quanzhou Peng
- Department of Pathology, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China
| | - Jinfeng Xu
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China
| | - Fajin Dong
- Department of Ultrasound, The Second Clinical Medical College, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Jinan University, Shenzhen 518020, Guangdong, China.
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Nguyen DL, Greenwood HI, Rahbar H, Grimm LJ. Evolving Treatment Paradigms for Low-Risk Ductal Carcinoma In Situ: Imaging Needs. AJR Am J Roentgenol 2024; 222:e2330503. [PMID: 38090808 DOI: 10.2214/ajr.23.30503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Ductal carcinoma in situ (DCIS) is a nonobligate precursor to invasive cancer that classically presents as asymptomatic calcifications on screening mammography. The increase in DCIS diagnoses with organized screening programs has raised concerns about overdiagnosis, while a patientcentric push for more personalized care has increased awareness about DCIS overtreatment. The standard of care for most new DCIS diagnoses is surgical excision, but nonsurgical management via active monitoring is gaining attention, and multiple clinical trials are ongoing. Imaging, along with demographic and pathologic information, is a critical component of active monitoring efforts. Commonly used imaging modalities including mammography, ultrasound, and MRI, as well as newer modalities such as contrast-enhanced mammography and dedicated breast PET, can provide prognostic information to risk stratify patients for DCIS active monitoring eligibility. Furthermore, radiologists will be responsible for closely surveilling patients on active monitoring and identifying if invasive progression occurs. Active monitoring is a paradigm shift for DCIS care, but the success or failure will rely heavily on the interpretations and guidance of radiologists.
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Affiliation(s)
- Derek L Nguyen
- Department of Diagnostic Radiology, Duke University School of Medicine, Box 3808, Durham, NC 27710
| | - Heather I Greenwood
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Habib Rahbar
- Department of Radiology, University of Washington, Seattle, WA
- Fred Hutchinson Cancer Center, Seattle, WA
| | - Lars J Grimm
- Department of Diagnostic Radiology, Duke University School of Medicine, Box 3808, Durham, NC 27710
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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: 0] [Impact Index Per Article: 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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Medved M, Vicari M, Karczmar GS. Characterization of Effects of Compressed Sensing on High Spectral and Spatial Resolution (HiSS) MRI with Comparison to SENSE. Tomography 2023; 9:693-705. [PMID: 36961014 PMCID: PMC10037569 DOI: 10.3390/tomography9020055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/15/2023] [Accepted: 03/15/2023] [Indexed: 03/25/2023] Open
Abstract
High Spectral and Spatial resolution (HiSS) MRI shows high diagnostic performance in the breast. Acceleration methods based on k-space undersampling could allow stronger T2*-based image contrast and/or higher spectral resolution, potentially increasing diagnostic performance. An agar/oil phantom was prepared with water-fat boundaries perpendicular to the readout and phase encoding directions in a breast coil. HiSS MRI was acquired at 3T, at sensitivity encoding (SENSE) acceleration factors R of up to 10, and the R = 1 dataset was used to simulate corresponding compressed sensing (CS) accelerations. Image quality was evaluated by quantifying noise and artifact levels. Effective spatial resolution was determined via modulation transfer function analysis. Dispersion vs. absorption (DISPA) analysis and full width at half maximum (FWHM) quantified spectral lineshape changes. Noise levels remained constant with R for CS but amplified with SENSE. SENSE preserved the spatial resolution of HiSS MRI, while CS reduced it in the phase encoding direction. SENSE showed no effect on FWHM or DISPA markers, while CS increased FWHM. Thus, CS might perform better in noise-limited or geometrically constrained applications, but in geometric configurations specific to breast MRI, spectral analysis might be compromised, decreasing the diagnostic performance of HiSS MRI.
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Affiliation(s)
- Milica Medved
- Department of Radiology, University of Chicago, Chicago, IL 60637, USA
| | - Marco Vicari
- Fraunhofer Institute for Digital Medicine MEVIS, 28359 Bremen, Germany
- Philips Research, 5656 AE Eindhoven, The Netherlands
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Evaluation of apparent diffusion coefficient of two-dimensional BLADE turbo gradient- and spin-echo diffusion-weighted imaging with a breast phantom. Radiol Phys Technol 2023; 16:118-126. [PMID: 36596917 DOI: 10.1007/s12194-022-00694-y] [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: 07/27/2022] [Revised: 12/20/2022] [Accepted: 12/21/2022] [Indexed: 01/05/2023]
Abstract
This study aimed to evaluate the reliability of apparent diffusion coefficient (ADC) values generated with two-dimensional turbo gradient- and spin-echo with BLADE trajectory diffusion-weighted imaging (TGSE-BLADE-DWI) sequence using a breast diffusion phantom. TGSE-BLADE-DWI and single-shot spin-echo echo-planar imaging (SS-EPI-DWI) were performed using a 3.0 T magnetic resonance imaging scanner. Concordance rates of ADC values and the signal-to-noise ratio (SNR) were compared between TGSE-BLADE-DWI and SS-EPI-DWI. TGSE-BLADE-DWI provided a higher concordance rate for ADC values than SS-EPI-DWI when b-values > 2000s/mm2 and a slice thickness of 1 mm were used. TGSE-BLADE-DWI showed less image distortion than SS-EPI-DWI. The SNR of TGSE-BLADE-DWI was higher than that of SS-EPI-DWI, except at a number of excitations of 7 and a slice thickness of 1 mm. In conclusion, TGSE-BLADE-DWI can offer a better SNR, less distortion, and more reliable ADC measurements than SS-EPI-DWI in a breast phantom.
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Cho P, Park CS, Park GE, Kim SH, Kim HS, Oh SJ. Diagnostic Usefulness of Diffusion-Weighted MRI for Axillary Lymph Node Evaluation in Patients with Breast Cancer. Diagnostics (Basel) 2023; 13:diagnostics13030513. [PMID: 36766617 PMCID: PMC9914452 DOI: 10.3390/diagnostics13030513] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 01/20/2023] [Accepted: 01/21/2023] [Indexed: 02/01/2023] Open
Abstract
This study aimed to determine whether apparent diffusion coefficient (ADC) and morphological features on diffusion-weighted MRI (DW-MRI) can discriminate metastatic axillary lymph nodes (ALNs) from benign in patients with breast cancer. Two radiologists measured ADC, long and short diameters, long-to-short diameter ratio, and cortical thickness and assessed eccentric cortical thickening, loss of fatty hilum, irregular margin, asymmetry in shape or number, and rim sign of ALNs on DW-MRI and categorized them into benign or suspicious ALNs. Pathologic reports were used as a reference standard. Statistical analysis was performed using the Mann-Whitney U test and chi-square test. Overall sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of DW-MRI were calculated. The ADC of metastatic ALNs was 0.905 × 10-3 mm2/s, and that of benign ALNs was 0.991 × 10-3 mm2/s (p = 0.243). All morphologic features showed significant difference between the two groups. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the final categorization on DW-MRI were 77.1%, 93.3%, 79.4%, 92.5%, and 86.2%, respectively. Our results suggest that morphologic evaluation of ALNs on DWI can discriminate metastatic ALNs from benign. The ADC value of metastatic ALNs was lower than that of benign nodes, but the difference was not statistically significant.
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Affiliation(s)
- Pyeonghwa Cho
- Department of Radiology, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea
| | - Chang Suk Park
- Department of Radiology, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea
- Correspondence: ; Tel.: +82-32-280-7305; Fax: +82-32-280-5192
| | - Ga Eun Park
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 06591, Republic of Korea
| | - Sung Hun Kim
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 06591, Republic of Korea
| | - Hyeon Sook Kim
- Department of Radiology, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea
| | - Se-Jeong Oh
- Department of General Surgery, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea School of Medicine, Seoul 21431, Republic of Korea
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Micek M, Aebisher D, Surówka J, Bartusik-Aebisher D, Madera M. Applications of T 1 and T 2 relaxation time calculation in tissue differentiation and cancer diagnostics-a systematic literature review. Front Oncol 2022; 12:1010643. [PMID: 36531030 PMCID: PMC9749890 DOI: 10.3389/fonc.2022.1010643] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 10/31/2022] [Indexed: 01/07/2024] Open
Abstract
INTRODUCTION The purpose of this review was to summarize current applications of non-contrast-enhanced quantitative magnetic resonance imaging (qMRI) in tissue differentiation, considering healthy tissues as well as comparisons of malignant and benign samples. The analysis concentrates mainly on the epithelium and epithelial breast tissue, especially breast cancer. METHODS A systematic review has been performed based on current recommendations by publishers and foundations. An exhaustive overview of currently used techniques and their potential in medical sciences was obtained by creating a search strategy and explicit inclusion and exclusion criteria. RESULTS AND DISCUSSION PubMed and Elsevier (Scopus & Science Direct) search was narrowed down to studies reporting T1 or T2 values of human tissues, resulting in 404 initial candidates, out of which roughly 20% were found relevant and fitting the review criteria. The nervous system, especially the brain, and connective tissue such as cartilage were the most frequently analyzed, while the breast remained one of the most uncommon subjects of studies. There was little agreement between published T1 or T2 values, and methodologies and experimental setups differed strongly. Few contemporary (after 2000) resources have been identified that were dedicated to studying the relaxation times of tissues and their diagnostic applications. Most publications concentrate on recommended diagnostic standards, for example, breast acquisition of T1- or T2-weighted images using gadolinium-based contrast agents. Not enough data is available yet to decide how repeatable or reliable analysis of relaxation times is in diagnostics, so it remains mainly a research topic. So far, qMRI might be recommended as a diagnostic help providing general insight into the nature of lesions (benign vs. malignant). However, additional means are generally necessary to differentiate between specific lesion types.
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Affiliation(s)
| | - David Aebisher
- Department of Photomedicine and Physical Chemistry, Medical College of The University of Rzeszow, Rzeszow, Poland
| | | | - Dorota Bartusik-Aebisher
- Department of Biochemistry and General Chemistry, Medical College of The University of Rzeszow, Rzeszow, Poland
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Grimm LJ, Rahbar H, Abdelmalak M, Hall AH, Ryser MD. Ductal Carcinoma in Situ: State-of-the-Art Review. Radiology 2021; 302:246-255. [PMID: 34931856 PMCID: PMC8805655 DOI: 10.1148/radiol.211839] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Ductal carcinoma in situ (DCIS) is a nonobligate precursor of invasive cancer, and its detection, diagnosis, and management are controversial. DCIS incidence grew with the expansion of screening mammography programs in the 1980s and 1990s, and DCIS is viewed as a major driver of overdiagnosis and overtreatment. For pathologists, the diagnosis and classification of DCIS is challenging due to undersampling and interobserver variability. Understanding the progression from normal breast tissue to DCIS and, ultimately, to invasive cancer is limited by a paucity of natural history data with multiple proposed evolutionary models of DCIS initiation and progression. Although radiologists are familiar with the classic presentation of DCIS as asymptomatic calcifications at mammography, the expanded pool of modalities, advanced imaging techniques, and image analytics have identified multiple potential biomarkers of histopathologic characteristics and prognosis. Finally, there is growing interest in the nonsurgical management of DCIS, including active surveillance, to reduce overtreatment and provide patients with more personalized management options. However, current biomarkers are not adept at enabling identification of occult invasive disease at biopsy or accurately predicting the risk of progression to invasive disease. Several active surveillance trials are ongoing and are expected to better identify women with low-risk DCIS who may avoid surgery.
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Affiliation(s)
- Lars J. Grimm
- From the Departments of Radiology (L.J.G.), Pathology (M.A., A.H.H.), and Population Health Sciences (M.D.R.), Duke University, 2301 Erwin Rd, Box 3808, Durham, NC 27710; and Department of Radiology, University of Washington, Seattle, Wash (H.R.)
| | - Habib Rahbar
- From the Departments of Radiology (L.J.G.), Pathology (M.A., A.H.H.), and Population Health Sciences (M.D.R.), Duke University, 2301 Erwin Rd, Box 3808, Durham, NC 27710; and Department of Radiology, University of Washington, Seattle, Wash (H.R.)
| | - Monica Abdelmalak
- From the Departments of Radiology (L.J.G.), Pathology (M.A., A.H.H.), and Population Health Sciences (M.D.R.), Duke University, 2301 Erwin Rd, Box 3808, Durham, NC 27710; and Department of Radiology, University of Washington, Seattle, Wash (H.R.)
| | - Allison H. Hall
- From the Departments of Radiology (L.J.G.), Pathology (M.A., A.H.H.), and Population Health Sciences (M.D.R.), Duke University, 2301 Erwin Rd, Box 3808, Durham, NC 27710; and Department of Radiology, University of Washington, Seattle, Wash (H.R.)
| | - Marc D. Ryser
- From the Departments of Radiology (L.J.G.), Pathology (M.A., A.H.H.), and Population Health Sciences (M.D.R.), Duke University, 2301 Erwin Rd, Box 3808, Durham, NC 27710; and Department of Radiology, University of Washington, Seattle, Wash (H.R.)
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11
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Blood Oxygenation Level Dependent Magnetic Resonance Imaging (MRI), Dynamic Contrast Enhanced MRI, and Diffusion Weighted MRI for Benign and Malignant Breast Cancer Discrimination: A Preliminary Experience. Cancers (Basel) 2021; 13:cancers13102421. [PMID: 34067721 PMCID: PMC8155852 DOI: 10.3390/cancers13102421] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 04/24/2021] [Accepted: 05/13/2021] [Indexed: 11/22/2022] Open
Abstract
Simple Summary The aim of the study is to combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. The results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D. Abstract Purpose. To combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. Methods. Thirty-seven breast lesions (11 benign and 21 malignant lesions) pathologically proven were included in this retrospective preliminary study. Pharmaco-kinetic parameters including Ktrans, kep, ve, and vp were extracted by DCE-MRI; BOLD parameters were estimated by basal signal S0 and the relaxation rate R2*; and diffusion and perfusion parameters were derived by DW-MRI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp), and tissue diffusivity (Dt)). The correlation coefficient, Wilcoxon-Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were calculated and area under the ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis and decision tree) with balancing technique and leave one out cross validation approach were considered. Results. R2* and D had a significant negative correlation (−0.57). The mean value, standard deviation, Skewness and Kurtosis values of R2* did not show a statistical significance between benign and malignant lesions (p > 0.05) confirmed by the ‘poor’ diagnostic value of ROC analysis. For DW-MRI derived parameters, the univariate analysis, standard deviation of D, Skewness and Kurtosis values of D* had a significant result to discriminate benign and malignant lesions and the best result at the univariate analysis in the discrimination of benign and malignant lesions was obtained by the Skewness of D* with an AUC of 82.9% (p-value = 0.02). Significant results for the mean value of Ktrans, mean value, standard deviation value and Skewness of kep, mean value, Skewness and Kurtosis of ve were obtained and the best AUC among DCE-MRI extracted parameters was reached by the mean value of kep and was equal to 80.0%. The best diagnostic performance in the discrimination of benign and malignant lesions was obtained at the multivariate analysis considering the DCE-MRI parameters alone with an AUC = 0.91 when the balancing technique was considered. Conclusions. Our results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D.
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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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Fusco R, Granata V, Pariante P, Cerciello V, Siani C, Di Bonito M, Valentino M, Sansone M, Botti G, Petrillo A. Blood oxygenation level dependent magnetic resonance imaging and diffusion weighted MRI imaging for benign and malignant breast cancer discrimination. Magn Reson Imaging 2020; 75:51-59. [PMID: 33080334 DOI: 10.1016/j.mri.2020.10.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 10/14/2020] [Accepted: 10/15/2020] [Indexed: 12/19/2022]
Abstract
PURPOSE The purpose of this study is to assess Blood oxygenation level dependent Magnetic Resonance Imaging (BOLD-MRI) and Diffusion Weighted Magnetic Resonance Imaging (DW-MRI) in the differentiation of benign and malignant breast lesions. METHODS Fifty-nine breast lesions (26 benign and 33 malignant lesions) pathologically proven in 59 patients were included in this retrospective study. As BOLD parameters were estimated basal signal S0 and the relaxation rate R2*, diffusion and perfusion parameters were derived by DWI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp) and tissue diffusivity (Dt)). Wilcoxon-Mann-Whitney U test and Receiver operating characteristic (ROC) analyses were calculated and area under ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis (LDA), support vector machine, k-nearest neighbours, decision tree) with least absolute shrinkage and selection operator (LASSO) method and leave one out cross validation approach were considered. RESULTS A significant discrimination was obtained by the standard deviation value of S0, as BOLD parameter, that reached an AUC of 0.76 with a sensitivity of 65%, a specificity of 85% and an accuracy of 76%. No significant discrimination was obtained considering diffusion and perfusion parameters. Considering LASSO results, the features to use as predictors were all extracted parameters except that the mean value of R2* and the best result was obtained by a LDA that obtained an AUC = 0.83, with a sensitivity of 88%, a specificity of 77% and an accuracy of 83%. CONCLUSIONS Good performance to discriminate benign and malignant lesions could be obtained using BOLD and DWI derived parameters with a LDA classification approach. However, these findings should be proven on larger and several dataset with different MR scanners.
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Affiliation(s)
- Roberta Fusco
- Radiology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Vincenza Granata
- Radiology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy.
| | - Paolo Pariante
- Radiology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Vincenzo Cerciello
- Health Physics Unit, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Claudio Siani
- Senology Surgical Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Maurizio Di Bonito
- Pathology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Marika Valentino
- Department, Electrical Engineering and Information Technologies, UNIVERSITA' DEGLI STUDI DI NAPOLI FEDERICO II, Naples, Italy
| | - Mario Sansone
- Department, Electrical Engineering and Information Technologies, UNIVERSITA' DEGLI STUDI DI NAPOLI FEDERICO II, Naples, Italy
| | - Gerardo Botti
- Scientific Director, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
| | - Antonella Petrillo
- Radiology Division, ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Naples, Italy
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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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Rotili A, Trimboli RM, Penco S, Pesapane F, Tantrige P, Cassano E, Sardanelli F. Double reading of diffusion-weighted magnetic resonance imaging for breast cancer detection. Breast Cancer Res Treat 2020; 180:111-120. [PMID: 31938940 DOI: 10.1007/s10549-019-05519-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 12/31/2019] [Indexed: 12/29/2022]
Abstract
PURPOSE To estimate the performance of diffusion-weighted imaging (DWI) for breast cancer detection. METHODS Consecutive breast magnetic resonance imaging examinations performed from January to September 2016 were retrospectively evaluated. Examinations performed before/after neoadjuvant therapy, lacking DWI sequences or reference standard were excluded; breasts after mastectomy were also excluded. Two experienced breast radiologists (R1, R2) independently evaluated only DWI. Final pathology or > 1-year follow-up served as reference standard. Mc Nemar, χ2, and κ statistics were applied. RESULTS Of 1,131 examinations, 672 (59.4%) lacked DWI sequence, 41 (3.6%) had no reference standard, 30 (2.7%) were performed before/after neoadjuvant therapy, and 10 (0.9%) had undergone bilateral mastectomy. Thus, 378 women aged 49 ± 11 years (mean ± standard deviation) were included, 51 (13%) with unilateral mastectomy, totaling 705 breasts. Per-breast cancer prevalence was 96/705 (13.6%). Per-breast sensitivity was 83/96 (87%, 95% confidence interval 78-93%) for both R1 and R2, 89/96 (93%, 86-97%) for double reading (DR) (p = 0.031); per-lesion DR sensitivity for cancers ≤ 10 mm was 22/31 (71%, 52-86%). Per-breast specificity was 562/609 (93%, 90-94%) for R1, 538/609 (88%, 86-91%) for R2, and 526/609 (86%¸ 83-89%) for DR (p < 0.001). Inter-observer agreement was substantial (κ = 0.736). Acquisition time varied from 3:00 to 6:22 min:s. Per-patient median interpretation time was 46 s (R1) and 51 s (R2). CONCLUSIONS DR DWI showed a 93% sensitivity and 88% specificity, with 71% sensitivity for cancers ≤ 10 mm, pointing out a potential for DWI as stand-alone screening method.
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Affiliation(s)
- Anna Rotili
- IEO, European Institute of Oncology IRCCS, Milan, Via Giuseppe Ripamonti, 435, 20141, Milan, Italy.
| | - Rubina Manuela Trimboli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Morandi 30, 20097, San Donato Milanese, Milan, Italy
| | - Silvia Penco
- IEO, European Institute of Oncology IRCCS, Milan, Via Giuseppe Ripamonti, 435, 20141, Milan, Italy
| | - Filippo Pesapane
- IEO, European Institute of Oncology IRCCS, Milan, Via Giuseppe Ripamonti, 435, 20141, Milan, Italy.,Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy
| | - Priyan Tantrige
- Unit of Radiology, King's College Hospital, Denmark Hill, Brixton, London, SE5 9RS, UK
| | - Enrico Cassano
- IEO, European Institute of Oncology IRCCS, Milan, Via Giuseppe Ripamonti, 435, 20141, Milan, Italy
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Morandi 30, 20097, San Donato Milanese, Milan, Italy.,Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Milan, Italy
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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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Partovi S, Sin D, Lu Z, Sieck L, Marshall H, Pham R, Plecha D. Fast MRI breast cancer screening - Ready for prime time. Clin Imaging 2019; 60:160-168. [PMID: 31927171 DOI: 10.1016/j.clinimag.2019.10.013] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Revised: 10/14/2019] [Accepted: 10/29/2019] [Indexed: 12/18/2022]
Abstract
OBJECTIVE The manuscript discusses landmark studies using abbreviated MRI for breast cancer screening. This includes abbreviated dynamic contrast enhanced MRI and diffusion weighted imaging. Our institutional experience with abbreviated MR protocol for breast cancer screening is also described. CONCLUSION Abbreviated MRI protocols were found to demonstrate value for screening of breast cancer. It has been shown that abbreviated protocol MRI provides similar diagnostic sensitivities to full protocol MRI for breast cancer in women with increased lifetime risk. Our institutional abbreviated MRI protocol for breast cancer offers improved time and workflow efficiencies and has the potential to increase the number of breast cancers detected and the detection of pathologically relevant invasive breast cancer at earlier stages.
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Affiliation(s)
- Sasan Partovi
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, United States of America.
| | - David Sin
- School of Medicine, Case Western Reserve University, Cleveland, OH, United States of America
| | - Ziang Lu
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, United States of America
| | - Leah Sieck
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, United States of America
| | - Holly Marshall
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, United States of America
| | - Ramya Pham
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, United States of America
| | - Donna Plecha
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, United States of America
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Baltzer P, Mann RM, Iima M, Sigmund EE, Clauser P, Gilbert FJ, Martincich L, Partridge SC, Patterson A, Pinker K, Thibault F, Camps-Herrero J, Le Bihan D. Diffusion-weighted imaging of the breast-a consensus and mission statement from the EUSOBI International Breast Diffusion-Weighted Imaging working group. Eur Radiol 2019; 30:1436-1450. [PMID: 31786616 PMCID: PMC7033067 DOI: 10.1007/s00330-019-06510-3] [Citation(s) in RCA: 229] [Impact Index Per Article: 45.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 09/03/2019] [Accepted: 10/10/2019] [Indexed: 01/03/2023]
Abstract
The European Society of Breast Radiology (EUSOBI) established an International Breast DWI working group. The working group consists of clinical breast MRI experts, MRI physicists, and representatives from large vendors of MRI equipment, invited based upon proven expertise in breast MRI and/or in particular breast DWI, representing 25 sites from 16 countries. The aims of the working group are (a) to promote the use of breast DWI into clinical practice by issuing consensus statements and initiate collaborative research where appropriate; (b) to define necessary standards and provide practical guidance for clinical application of breast DWI; (c) to develop a standardized and translatable multisite multivendor quality assurance protocol, especially for multisite research studies; (d) to find consensus on optimal methods for image processing/analysis, visualization, and interpretation; and (e) to work collaboratively with system vendors to improve breast DWI sequences. First consensus recommendations, presented in this paper, include acquisition parameters for standard breast DWI sequences including specifications of b values, fat saturation, spatial resolution, and repetition and echo times. To describe lesions in an objective way, levels of diffusion restriction/hindrance in the breast have been defined based on the published literature on breast DWI. The use of a small ROI placed on the darkest part of the lesion on the ADC map, avoiding necrotic, noisy or non-enhancing lesion voxels is currently recommended. The working group emphasizes the need for standardization and quality assurance before ADC thresholds are applied. The working group encourages further research in advanced diffusion techniques and tailored DWI strategies for specific indications. Key Points • The working group considers breast DWI an essential part of a multiparametric breast MRI protocol and encourages its use. • Basic requirements for routine clinical application of breast DWI are provided, including recommendations on b values, fat saturation, spatial resolution, and other sequence parameters. • Diffusion levels in breast lesions are defined based on meta-analysis data and methods to obtain a reliable ADC value are detailed.
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Affiliation(s)
- Pascal Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna/Vienna General Hospital, Wien, Austria
| | - Ritse M Mann
- Department of Radiology, Radboud University Medical Centre, Nijmegen, Netherlands. .,Department of Radiology, The Netherlands Cancer Institute, Amsterdam, Netherlands.
| | - Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Eric E Sigmund
- Department of Radiology, New York University School of Medicine, NYU Langone Health, Ney York, NY, 10016, USA
| | - Paola Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna/Vienna General Hospital, Wien, Austria
| | - Fiona J Gilbert
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | | | - Savannah C Partridge
- Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA
| | - Andrew Patterson
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Katja Pinker
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna/Vienna General Hospital, Wien, Austria.,MSKCC, New York, NY, 10065, USA
| | | | | | - Denis Le Bihan
- NeuroSpin, Frédéric Joliot Institute, Gif Sur Yvette, France
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Greenwood HI, Wilmes LJ, Kelil T, Joe BN. Role of Breast MRI in the Evaluation and Detection of DCIS: Opportunities and Challenges. J Magn Reson Imaging 2019; 52:697-709. [PMID: 31746088 DOI: 10.1002/jmri.26985] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Revised: 10/15/2019] [Accepted: 10/16/2019] [Indexed: 12/29/2022] Open
Abstract
Historically, breast magnetic resonance imaging (MRI) was not considered an effective modality in the evaluation of ductal carcinoma in situ (DCIS). Over the past decade this has changed, with studies demonstrating that MRI is the most sensitive imaging tool for detection of all grades of DCIS. It has been suggested that not only is breast MRI the most sensitive imaging tool for detection but it may also detect the most clinically relevant DCIS lesions. The role and outcomes of MRI in the preoperative setting for patients with DCIS remains controversial; however, several studies have shown benefit in the preoperative evaluation of extent of disease as well as predicting an underlying invasive component. The most common presentation of DCIS on MRI is nonmass enhancement (NME) in a linear or segmental distribution pattern. Maximizing breast MRI spatial resolution is therefore beneficial, given the frequent presentation of DCIS as NME on MRI. Emerging MRI techniques, such as diffusion-weighted imaging (DWI), have shown promising potential to discriminate DCIS from benign and invasive lesions. Future opportunities including advanced imaging visual techniques, radiomics/radiogenomics, and machine learning / artificial intelligence may also be applicable to the detection and treatment of DCIS. Level of Evidence: 3 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2020;52:697-709.
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Affiliation(s)
- Heather I Greenwood
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Lisa J Wilmes
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Tatiana Kelil
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, USA
| | - Bonnie N Joe
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, USA
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20
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Palm T, Wenkel E, Ohlmeyer S, Janka R, Uder M, Weiland E, Bickelhaupt S, Ladd ME, Zaitsev M, Hensel B, Laun FB. Diffusion kurtosis imaging does not improve differentiation performance of breast lesions in a short clinical protocol. Magn Reson Imaging 2019; 63:205-216. [DOI: 10.1016/j.mri.2019.08.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 07/26/2019] [Accepted: 08/15/2019] [Indexed: 01/08/2023]
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21
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Surov A, Meyer HJ, Wienke A. Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions. BMC Cancer 2019; 19:955. [PMID: 31615463 PMCID: PMC6794799 DOI: 10.1186/s12885-019-6201-4] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Accepted: 09/24/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND The purpose of the present meta-analysis was to provide evident data about use of Apparent Diffusion Coefficient (ADC) values for distinguishing malignant and benign breast lesions. METHODS MEDLINE library and SCOPUS database were screened for associations between ADC and malignancy/benignancy of breast lesions up to December 2018. Overall, 123 items were identified. The following data were extracted from the literature: authors, year of publication, study design, number of patients/lesions, lesion type, mean value and standard deviation of ADC, measure method, b values, and Tesla strength. The methodological quality of the 123 studies was checked according to the QUADAS-2 instrument. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance weights were used without any further correction to account for the heterogeneity between the studies. Mean ADC values including 95% confidence intervals were calculated separately for benign and malign lesions. RESULTS The acquired 123 studies comprised 13,847 breast lesions. Malignant lesions were diagnosed in 10,622 cases (76.7%) and benign lesions in 3225 cases (23.3%). The mean ADC value of the malignant lesions was 1.03 × 10- 3 mm2/s and the mean value of the benign lesions was 1.5 × 10- 3 mm2/s. The calculated ADC values of benign lesions were over the value of 1.00 × 10- 3 mm2/s. This result was independent on Tesla strength, choice of b values, and measure methods (whole lesion measure vs estimation of ADC in a single area). CONCLUSION An ADC threshold of 1.00 × 10- 3 mm2/s can be recommended for distinguishing breast cancers from benign lesions.
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Affiliation(s)
- Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstr. 20, 04103, Leipzig, Germany. .,Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081, Ulm, Germany.
| | - Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstr. 20, 04103, Leipzig, Germany
| | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Magdeburger Str. 8, 06097, Halle, Germany
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Cavallo Marincola B, Telesca M, Zaccagna F, Riemer F, Anzidei M, Catalano C, Pediconi F. Can unenhanced MRI of the breast replace contrast-enhanced MRI in assessing response to neoadjuvant chemotherapy? Acta Radiol 2019; 60:35-44. [PMID: 29742918 DOI: 10.1177/0284185118773512] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The goals of neoadjuvant chemotherapy (NAC) are to reduce tumor volume and to offer a prognostic indicator in assessing treatment response. Contrast-enhanced magnetic resonance imaging (CE-MRI) is an established method for evaluating response to NAC in patients with breast cancer. PURPOSE To validate the role of unenhanced MRI (ue-MRI) compared to CE-MRI for assessing response to NAC in women with breast cancer. MATERIAL AND METHODS Seventy-one patients with ongoing NAC for breast cancer underwent MRI before, during, and at the end of NAC. Ue-MRI was performed with T2-weighted sequences with iterative decomposition of water and fat and diffusion-weighted sequences. CE-MRI was performed using three-dimensional T1-weighted sequences before and after administration of gadobenate dimeglumine. Two blinded observers rated ue-MRI and CE-MRI for the evaluation of tumor response. Statistical analysis was performed to compare lesion size and ADC values changes during therapy, as well as inter-observer agreement. RESULTS There were no statistically significant differences between ue-MRI and CE-MRI sequences for evaluation of lesion size at baseline and after every cycle of treatment ( P > 0.05). The mean tumor ADC values at baseline and across the cycles of NAC were significantly different for the responder group. CONCLUSION Ue-MRI can achieve similar results to CE-MRI for the assessment of tumor response to NAC. ADC values can differentiate responders from non-responders.
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Affiliation(s)
- Beatrice Cavallo Marincola
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Marianna Telesca
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Fulvio Zaccagna
- Department of Radiology, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Frank Riemer
- Department of Radiology, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Michele Anzidei
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Carlo Catalano
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Federica Pediconi
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
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Kim JY, Kim JJ, Lee JW, Lee NK, Lee G, Kang T, Park H, Son YH, Grimm R. Risk stratification of ductal carcinoma in situ using whole-lesion histogram analysis of the apparent diffusion coefficient. Eur Radiol 2018; 29:485-493. [PMID: 30073498 DOI: 10.1007/s00330-018-5666-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 07/01/2018] [Accepted: 07/13/2018] [Indexed: 01/01/2023]
Abstract
OBJECTIVES To investigate the value of the whole-lesion histogram apparent diffusion coefficient (ADC) metrics for differentiating low-risk from non-low-risk ductal carcinoma in situ (DCIS). METHODS The authors identified 93 women with pure DCIS who had undergone preoperative MR imaging and diffusion-weighted imaging from 2013 to 2016. Histogram analysis of pixel-based ADC data of the whole tumour volume was performed by two radiologists using a software tool. The results were compared between low-risk and non-low-risk DCIS. Associations between quantitative ADC metrics and low-risk DCIS were evaluated by receiver operating characteristics (ROC) curve and logistic regression analyses. RESULTS In whole-lesion histogram analysis, mean ADC and 5th, 50th and 95th percentiles of ADC were significantly different between low-risk and non-low-risk DCIS (1.522, 1.207, 1.536 and 1.854 × 10-3 mm2/s versus 1.270, 0.917, 1.261 and 1.657 × 10-3 mm2/s, respectively; p = .004, p = .003, p = .004 and p = .024, respectively). ROC curve analysis for differentiating low-risk DCIS revealed that 5th percentile ADC yielded the largest area under the curve (0.786) among the metrics of whole-lesion histogram, and the optimal cut-off point was 1.078 × 10-3 mm2/s (sensitivity 80%, specificity 75.9%, p = .001). Multivariate regression analysis revealed that a high 5th percentile of ADC (> 1.078× 10-3 mm2/s; odds ratio [OR] = 10.494, p = .016), small tumour size (≤ 2 cm; OR = 12.692, p = .008) and low Ki-67 status (< 14%; OR = 10.879, p = .046) were significantly associated with low-risk DCIS. CONCLUSIONS Assessment with whole-lesion histogram analysis of the ADC could be helpful for identifying patients with low-risk DCIS. KEY POINTS • Whole-lesion histogram ADC metrics could be helpful for differentiating low-risk from non-low-risk DCIS. • A high 5th percentile ADC was a significant factor associated with low-risk DCIS. • Risk stratification of DCIS is important for their management.
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Affiliation(s)
- Jin You Kim
- Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea. .,Medical Research Institute, Pusan National University School of Medicine, Busan, Republic of Korea.
| | - Jin Joo Kim
- Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea
| | - Ji Won Lee
- Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea
| | - Nam Kyung Lee
- Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea
| | - Geewon Lee
- Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea
| | - Taewoo Kang
- Busan Cancer Center, Pusan National University Hospital, Busan, Republic of Korea
| | - Heesung Park
- Busan Cancer Center, Pusan National University Hospital, Busan, Republic of Korea
| | | | - Robert Grimm
- Siemens Healthineers, MR Application Predevelopment, Erlangen, 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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25
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Greenwood HI, Dodelzon K, Katzen JT. Impact of Advancing Technology on Diagnosis and Treatment of Breast Cancer. Surg Clin North Am 2018; 98:703-724. [PMID: 30005769 DOI: 10.1016/j.suc.2018.03.006] [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] [Indexed: 11/28/2022]
Abstract
New emerging breast imaging techniques have shown great promise in breast cancer screening, evaluation of extent of disease, and response to neoadjuvant therapy. Tomosynthesis, allows 3-dimensional imaging of the breast, and increases breast cancer detection. Fast abbreviated MRI has reduced time and costs associated with traditional breast MRI while maintaining cancer detection. Diffusion-weighted imaging is a functional MRI technique that does not require contrast and has shown potential in screening, lesion characterization and also evaluation of treatment response. New image-guided preoperative localizations are available that have increased patient satisfaction and decreased operating room delays.
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Affiliation(s)
- Heather I Greenwood
- Department of Radiology, University of California San Francisco, UCSF Medical Center at Mount Zion, 1600 Divisadero Street Room C-250, San Francisco, CA 94115, USA.
| | - Katerina Dodelzon
- Department of Radiology, Weill Cornell Medical Center, New York-Presbyterian, 425 East 61st Street, 9th Floor, New York, NY 10065, USA
| | - Janine T Katzen
- Department of Radiology, Weill Cornell Medical Center, New York-Presbyterian, 425 East 61st Street, 9th Floor, New York, NY 10065, USA
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26
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Abstract
Breast magnetic resonance imaging (MRI) is the most sensitive of the available imaging modalities to characterize breast cancer. Breast MRI has gained clinical acceptance for screening high-risk patients, but its role in the preoperative imaging of breast cancer patients remains controversial. This review focuses on the current indications for staging breast MRI, the evidence for and against the role of breast MRI in the preoperative staging workup, and the evaluation of treatment response of breast cancer patients.
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27
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Park GE, Kim SH, Kim EJ, Kang BJ, Park MS. Histogram analysis of volume-based apparent diffusion coefficient in breast cancer. Acta Radiol 2017; 58:1294-1302. [PMID: 28273747 DOI: 10.1177/0284185117694507] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background Breast cancer is a heterogeneous disease. Recent studies showed that apparent diffusion coefficient (ADC) values have various association with tumor aggressiveness and prognosis. Purpose To evaluate the value of histogram analysis of ADC values obtained from the whole tumor volume in invasive ductal cancer (IDC) and ductal carcinoma in situ (DCIS). Material and Methods This retrospective study included 201 patients with confirmed DCIS (n = 37) and IDC (n = 164). The IDC group was divided into two groups based on the presence of a DCIS component: IDC-DCIS (n = 76) and pure IDC (n = 88). All patients underwent preoperative breast magnetic resonance imaging (MRI) with diffusion-weighted images at 3.0 T. Histogram parameters of cumulative ADC values, skewness, and kurtosis were calculated and statistically analyzed. Results The differences between DCIS, IDC-DCIS, and pure IDC were significant in all percentiles of ADC values, in descending order of DCIS, IDC-DCIS, and pure IDC. IDC showed significantly lower ADC values than DCIS, and ADC50 was the best indicator for discriminating IDC from DCIS, with a threshold of 1.185 × 10-3 mm2/s (sensitivity of 82.9%, specificity of 75.7%). However, multivariate analysis of obtained ADC values showed no significant differences between DCIS, IDC-DCIS, and pure IDC ( P > 0.05). Conclusion Volume-based ADC values showed association with heterogeneity of breast cancer. However, there was no additional diagnostic performance in histogram analysis for differentiating between DCIS, IDC-DCIS, and pure IDC.
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Affiliation(s)
- Ga Eun Park
- 1 Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sung Hun Kim
- 1 Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Eun Jeong Kim
- 1 Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Bong Joo Kang
- 1 Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Mi Sun Park
- 2 Department of Biostatistics, Clinical Research Coordinating Center, The Catholic University of Korea, Seoul, Republic of Korea
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Dietzel M, Kaiser CG, Wenkel E, Clauser P, Uder M, Schulz-Wendtland R, Baltzer PAT. Differentiation of ductal carcinoma in situ versus fibrocystic changes by magnetic resonance imaging: are there pathognomonic imaging features? Acta Radiol 2017; 58:1206-1214. [PMID: 28173727 DOI: 10.1177/0284185117690420] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background In breast magnetic resonance imaging (MRI), the diagnosis of ductal carcinoma in situ (DCIS) remains controversial; the most challenging cause of false-positive DCIS diagnosis is fibrocystic changes (FC). Purpose To search for typical and pathognomonic patterns of DCIS and FC using a standard clinical MRI protocol. Material and Methods Consecutive patients scheduled for breast MRI (standardized protocols @ 1.5T: dynamic-T1-GRE before/after Gd-DTPA [0.1 mmol/kg body weight (BW)]; T1-TSE), with subsequent pathological sampling, were investigated. Sixteen MRI descriptors were prospectively assessed by two experienced radiologists in consensus (blinded to pathology) and explored in patients with DCIS (n = 77) or FC (n = 219). Univariate and multivariate statistics were performed to identify the accuracy of descriptors (alone, combined). Furthermore, pathognomonic descriptor-combinations with an accuracy of 100% were explored (χ2 statistics; decision trees). Results Six breast MRI descriptors significantly differentiated DCIS from FC ( Pcorrected < 0.05; odds ratio < 7.9). Pathognomonic imaging features were present in 33.8% (n = 100) of all cases allowing the identification of 42.9% of FC (n = 94). Conclusion Pathognomonic patterns of DCIS and FC were frequently observed in a standard clinical MRI protocol. Such imaging patterns could decrease the false-positive rate of breast MRI and hence might help to decrease the number of unnecessary biopsies in this clinically challenging subgroup.
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Affiliation(s)
- Matthias Dietzel
- Department of Radiology, University Hospital Erlangen-Nürnberg, Erlangen, Germany
| | - Clemens G Kaiser
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Mannheim, Germany
| | - Evelyn Wenkel
- Department of Radiology, University Hospital Erlangen-Nürnberg, Erlangen, Germany
| | - Paola Clauser
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria
| | - Michael Uder
- Department of Radiology, University Hospital Erlangen-Nürnberg, Erlangen, Germany
| | | | - Pascal AT Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria
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Abstract
Diffusion-weighted imaging (DWI) holds promise to address some of the shortcomings of routine clinical breast magnetic resonance imaging (MRI) and to expand the capabilities of imaging in breast cancer management. DWI reflects tissue microstructure, and provides unique information to aid in characterization of breast lesions. Potential benefits under investigation include improving diagnostic accuracy and guiding treatment decisions. As a result, DWI is increasingly being incorporated into breast MRI protocols and multicenter trials are underway to validate single-institution findings and to establish clinical guidelines. Advancements in DWI acquisition and modeling approaches are helping to improve image quality and extract additional biologic information from breast DWI scans, which may extend diagnostic and prognostic value.
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Affiliation(s)
- Savannah C Partridge
- *Department of Radiology, Breast Imaging Section, Seattle Cancer Care Alliance, University of Washington, Seattle, WA †University of Massachusetts Memorial Medical Center, Worcester, MA
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Christou A, Ghiatas A, Priovolos D, Veliou K, Bougias H. Accuracy of diffusion kurtosis imaging in characterization of breast lesions. Br J Radiol 2017; 90:20160873. [PMID: 28383279 DOI: 10.1259/bjr.20160873] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE The aim of this study was to evaluate the accuracy of diffusion kurtosis in the characterization and differentiation of breast lesions. METHODS 49 females with 53 breast lesions underwent breast MRI. The MRI magnetic field is 1.5 T, and the protocol is standard MRI sequences, dynamic sequences pre- and post-contrast agent administration and diffusion images. Diffusion kurtosis imaging (DKI) was applied as part of our standard breast MRΙ protocol. Two experienced radiologists on breast MRI, blinded to the final diagnosis, reviewed the parametric maps and placed a volume of interest on all slices including each lesion. Kurtosis [K apparent (Kapp)] and corrected apparent diffusion coefficient [D apparent (Dapp)] median values were then calculated from the whole-lesion histogram analysis. Receiver-operating characteristic analysis was used to determine the most effective cut-off values for the differentiation between benign and malignant pathologies. Histological analysis of the breast lesions was performed, and further comparative analysis of the results was performed to investigate the accuracy of the method. RESULTS Benign (n = 19) and malignant lesions (n = 34) had mean diameters of 20.8 mm (10.1-31.5 mm) and 26.4 mm (10.5-42.3 mm), respectively. The lowest and the highest kurtosis values (Kapp) of malignant lesions were significantly higher than those of benign lesions. A cut-off of 0.71 provided specificity of 93.7% and sensitivity 97.1%, and the area under the curve (AUC) was 0.976 (p < 0.0001). The lowest and the highest Dapp values of malignant lesions were lower than those of benign lesions. A cut-off value of 1.57 × 10-3 mm2 s-1 provided specificity of 93.7% and sensitivity of 91.2% with AUC of 0.949 (p < 0.0001). CONCLUSION DKI is an accurate additional tool for the characterization and differentiation of breast lesions with high Kapp and Dapp sensitivity and specificity rates. Advances in knowledge: DKI is able to distinguish benign from malignant breast pathologies. DKI increases the specificity of breast MRI.
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Affiliation(s)
- Alexandra Christou
- 1 Department of Medical Imaging, Doncaster and Bassetlaw Hospitals NHS Foundation Trust, Doncaster, UK
| | - Abraham Ghiatas
- 2 Department of Medical Imaging, Director and owner of Global Teleradiology Services, Athens, Greece
| | | | - Konstantia Veliou
- 4 Department of Medical Imaging, at Chatzikosta General Hospital of Ioannina, Ioannina, Greece
| | - Haralambos Bougias
- 5 Department of Medical Imaging, University Hospital of Ioannina, Ioannina, Greece
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Rinaldi P, Buccheri C, Giuliani M, Bufi E, Romani M, Patrolecco F, Belli P, Bonomo L. Sensitivity of breast MRI for ductal carcinoma in situ appearing as microcalcifications only on mammography. Clin Imaging 2016; 40:1207-1212. [DOI: 10.1016/j.clinimag.2016.08.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2016] [Revised: 06/21/2016] [Accepted: 08/02/2016] [Indexed: 11/17/2022]
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33
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Bougias H, Ghiatas A, Priovolos D, Veliou K, Christou A. Whole-lesion apparent diffusion coefficient (ADC) metrics as a marker of breast tumour characterization-comparison between ADC value and ADC entropy. Br J Radiol 2016; 89:20160304. [PMID: 27718592 DOI: 10.1259/bjr.20160304] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To prospectively assess the role of whole-lesion apparent diffusion coefficient (ADC) metrics in the characterization of breast tumours by comparing ADC value with ADC entropy. METHODS 49 patients with 53 breast lesions underwent phased-array breast coil 1.5-T MRI. Two radiologists experienced in breast MRI, blinded to the final diagnosis, reviewed the ADC maps and placed a volume of interest on all slices including each lesion on the ADC map to obtain whole-lesion mean ADC value and ADC entropy. The mean ADC value and ADC entropy in benign and malignant lesions were compared by the Mann-Whitney U-test. Receiver-operating characteristic analysis was performed to assess the sensitivity and specificity of the two variables in the characterization of the breast lesions. RESULTS The benign (n = 19) and malignant lesions (n = 34) had mean diameters of 20.8 mm (10.1-31.5 mm) and 26.4 mm (10.5-42.3 mm), respectively. The mean ADC value of the malignant lesions was significantly lower than that of the benign ones (0.87 × 10-3 vs 1.49 × 10-3 mm2 s-1; p < 0.0001). Malignant ADC entropy was higher than benign entropy, without reaching levels of statistical significance (5.4 vs 5.0; p = 0.064). At a mean ADC cut-off value of 1.16 × 10-3 mm2 s-1, the sensitivity and specificity for diagnosing malignancy became optimal (97.1% and 93.7, respectively) with an area under the curve (AUC) of 0.975. With regard to ADC entropy, the sensitivity and specificity at a cut-off of 5.18 were 67.6 and 68.7%, respectively, with an AUC of 0.664. CONCLUSION Whole-lesion mean ADC could be a helpful index in the characterization of suspicious breast lesions, with higher sensitivity and specificity than ADC entropy. Advances in knowledge: Two separate parameters of the whole-lesion histogram were compared for their diagnostic accuracy in characterizing breast lesions. Mean ADC was found to be able to characterize breast lesions, whereas entropy proved to be unable to differentiate benign from malignant breast lesions. It is, however, likely that entropy may distinguish these two groups if a larger cohort were used, or the fact that this may be influenced by the molecular subtypes of breast cancers included.
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Affiliation(s)
- Haralambos Bougias
- 1 Department of Medical Imaging University Hospital of loannina, loannina, Greece
| | - Abraham Ghiatas
- 2 Department of Medical Imaging IASO Maternity Hospital, Athens, Greece
| | | | - Konstantia Veliou
- 3 Department of Medical Imaging Chatzikosta General Hospital of loannina, loannina, Greece
| | - Alexandra Christou
- 4 Department of Medical Imaging, Doncaster and Bassetlaw Hospitals NHS Foundation Trust, Doncaster, UK
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34
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Partridge SC, Nissan N, Rahbar H, Kitsch AE, Sigmund EE. Diffusion-weighted breast MRI: Clinical applications and emerging techniques. J Magn Reson Imaging 2016; 45:337-355. [PMID: 27690173 DOI: 10.1002/jmri.25479] [Citation(s) in RCA: 215] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Accepted: 08/29/2016] [Indexed: 12/28/2022] Open
Abstract
Diffusion-weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and noncontrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion-weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools. LEVEL OF EVIDENCE 5 J. Magn. Reson. Imaging 2016 J. Magn. Reson. Imaging 2017;45:337-355.
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Affiliation(s)
- Savannah C Partridge
- Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA.,Breast Imaging, Seattle Cancer Care Alliance, Seattle, Washington, USA
| | - Noam Nissan
- Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel
| | - Habib Rahbar
- Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA.,Breast Imaging, Seattle Cancer Care Alliance, Seattle, Washington, USA
| | - Averi E Kitsch
- Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA.,Breast Imaging, Seattle Cancer Care Alliance, Seattle, Washington, USA
| | - Eric E Sigmund
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
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Rahbar H, Kurland BF, Olson ML, Kitsch AE, Scheel JR, Chai X, Usoro J, Lehman CD, Partridge SC. Diffusion-Weighted Breast Magnetic Resonance Imaging: A Semiautomated Voxel Selection Technique Improves Interreader Reproducibility of Apparent Diffusion Coefficient Measurements. J Comput Assist Tomogr 2016; 40:428-35. [PMID: 27192501 PMCID: PMC4874523 DOI: 10.1097/rct.0000000000000372] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To determine whether a semiautomated voxel selection technique improves interreader reproducibility for breast apparent diffusion coefficient (ADC) measurements. METHODS Three readers retrospectively performed ADC measurements of 31 breast lesions (16 malignant, 15 benign) and contralateral normal tissue in 26 women both unassisted (manual method) and assisted by a semiautomated software tool that excludes voxels below a dynamically specified signal intensity threshold. Reproducibility between readers for each technique was assessed by Bland-Altman analysis and concordance correlation coefficients (CCCs). RESULTS Differences between readers' measured ADCs of lesions were smaller with the semiautomated tool vs the manual method. Concordance correlation coefficients for each reader pair were greater with the semiautomated tool for lesions (mean CCC difference, 0.11; 95% confidence interval, 0.04-0.26). For normal tissue, reader agreement was lower than for lesions and did not differ based on software tools (mean CCC difference, 0.00; 95% confidence interval, -0.14 to 0.13). CONCLUSIONS A semiautomated voxel selection tool can improve interreader reproducibility of breast lesion ADC measures.
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Affiliation(s)
- Habib Rahbar
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109–1023, USA
| | - Brenda F. Kurland
- Fred Hutchinson Cancer Research Center, Clinical Research Division, 1100 Fairview Avenue North, P.O. Box 19024, Seattle, WA 98109-1024
| | - Matthew L. Olson
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109–1023, USA
| | - Averi E. Kitsch
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109–1023, USA
| | - John R Scheel
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109–1023, USA
| | - Xiaoyu Chai
- Fred Hutchinson Cancer Research Center, Clinical Research Division, 1100 Fairview Avenue North, P.O. Box 19024, Seattle, WA 98109-1024
| | - Joshua Usoro
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109–1023, USA
| | - Constance D. Lehman
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109–1023, USA
| | - Savannah C. Partridge
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109–1023, USA
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Zhao J, Guan H, Li M, Gu H, Qin J, Wu X. Significance of the ADC ratio in the differential diagnosis of breast lesions. Acta Radiol 2016; 57:422-9. [PMID: 26071495 DOI: 10.1177/0284185115590286] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2014] [Accepted: 05/11/2015] [Indexed: 12/21/2022]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) has high sensitivity but low specificity for breast cancer, and consequently, new techniques to improve the specificity of breast MRI in diagnosing breast cancer are under development. PURPOSE To assess the ability of the apparent diffusion coefficient (ADC) compared with the ADC ratio (ADCr) to differentially diagnose benign compared with malignant breast lesions. MATERIAL AND METHODS Forty-eight women with breast lesions (average age, 45 years) underwent MRI scanning including T1-weighted dynamic contrast-enhanced (DCE) scanning and diffusion-weighted imaging (DWI). The average ADC and ADCr values for both lesions and pectoralis major muscles (ADCrmuscle and ADCrmuscle) were measured in patients with malignant (n = 25) and benign (n = 23) breast lesions. The ADCr of the contralateral breast (ADCr contralateral) was also evaluated. All histology was confirmed by pathological analysis of biopsied tissue. ADC and ADCr values were analyzed using receiver-operating characteristic (ROC) curves. RESULTS For benign lesions compared with malignant lesions, lesion-side ADC was 1.45 vs. 1.05, respectively (P < 0.001), normal-side ADC was 1.82 vs.1.64 (P = 0.002), ADCrmuscle was 1.35 vs. 0.9 (P < 0.001), and ADCrcontralateral was 0.79 vs. 0.64 (P = 0.001). ADCrmuscle showed higher sensitivity (82.61%) and specificity (96.00%) than ADCrcontralateral (60.87% and 92.00%, respectively) and ADC (69.57% and 96.00%) for discriminating malignant from benign lesions. The AUC using ADCrmuscle had higher discriminatory power (0.92, P < 0.001) for malignant versus benign breast lesions compared with either ADC (0.82, P < 0.001) or ADCrcontralateral (0.78, P = 0.001). CONCLUSION The ADCrmuscle value showed higher sensitivity and specificity and improved diagnostic accuracy compared with either ADC or ADCrcontralateral in differentiating benign from malignant breast lesions.
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Affiliation(s)
- Jinli Zhao
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, PR China
| | - Haitao Guan
- Department of Ultrasound, The Third People's Hospital of Nantong, Nantong, Jiangsu Province, PR China
| | - Minda Li
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, PR China
| | - Hongmei Gu
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, PR China
| | - Jufeng Qin
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, PR China
| | - Xianhua Wu
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, PR China
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Bickelhaupt S, Laun FB, Tesdorff J, Lederer W, Daniel H, Stieber A, Delorme S, Schlemmer HP. Fast and Noninvasive Characterization of Suspicious Lesions Detected at Breast Cancer X-Ray Screening: Capability of Diffusion-weighted MR Imaging with MIPs. Radiology 2016; 278:689-97. [DOI: 10.1148/radiol.2015150425] [Citation(s) in RCA: 92] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Rahbar H, Parsian S, Lam DL, Dontchos BN, Andeen NK, Rendi MH, Lehman CD, Partridge SC. Can MRI biomarkers at 3 T identify low-risk ductal carcinoma in situ? Clin Imaging 2015; 40:125-9. [PMID: 26365872 DOI: 10.1016/j.clinimag.2015.07.026] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Accepted: 07/21/2015] [Indexed: 11/28/2022]
Abstract
OBJECTIVE The objective was to explore whether 3-T magnetic resonance imaging (MRI) can identify low-risk ductal carcinoma in situ (DCIS). METHODS Dynamic contrast-enhanced and diffusion-weighted (DWI) MRI features of 36 DCIS lesions [8 low risk, Van Nuys Pathologic Classification (VNPC) 1; 28 high risk, VNPC 2/3] were reviewed. An MRI model that best identified low-risk DCIS was determined using multivariate logistic regression. RESULTS Low-risk DCIS exhibited different DWI properties [i.e., higher contrast-to-noise ratio (P=.02) and lower normalized apparent diffusion coefficients (P=.04)] than high-risk DCIS. A model combining these DWI features provided best performance (area under receiver operating characteristic curve =0.86). CONCLUSIONS DWI may help identify DCIS lesions requiring less therapy.
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Affiliation(s)
- Habib Rahbar
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109-1023, USA.
| | - Sana Parsian
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109-1023, USA
| | - Diana L Lam
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109-1023, USA
| | - Brian N Dontchos
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109-1023, USA
| | - Nicole K Andeen
- University of Washington Department of Anatomic Pathology, 1959 NE Pacific St., Box 357470, Seattle, WA 98195, USA
| | - Mara H Rendi
- University of Washington Department of Anatomic Pathology, 1959 NE Pacific St., Box 357470, Seattle, WA 98195, USA
| | - Constance D Lehman
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109-1023, USA
| | - Savannah C Partridge
- University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109-1023, USA
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Fat suppression techniques (STIR vs. SPAIR) on diffusion-weighted imaging of breast lesions at 3.0 T: preliminary experience. Radiol Med 2015; 120:705-13. [PMID: 25665796 DOI: 10.1007/s11547-015-0508-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2013] [Accepted: 05/19/2014] [Indexed: 12/24/2022]
Abstract
PURPOSE The aim of this work was to perform a qualitative and quantitative comparison of the performance of two fat suppression techniques on breast diffusion-weighted imaging (DWI). MATERIALS AND METHODS Fifty-one women underwent clinical breast magnetic resonance imaging, including DWI with short TI inversion recovery (STIR) and spectral attenuated inversion recovery (SPAIR). Four were excluded from the analysis due to image artefacts. Rating of fat suppression uniformity and lesion visibility were performed. Agreement between the two sequences was evaluated. Additionally, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values for normal gland, benign and malignant lesions were compared. Receiver operating characteristic analysis was also performed. RESULTS From the 52 lesions found, 47 were detected by both sequences. DWI-STIR evidenced more homogeneous fat suppression (p = 0.03). Although these lesions were seen with both techniques, DWI-SPAIR evidenced higher score for lesion visibility in nine of them. SNR and CNR were comparable, except for SNR in benign lesions (p < 0.01), which was higher for DWI-SPAIR. Mean ADC values for lesions were similar. ADC for normal fibroglandular tissue was higher when using DWI-STIR (p = 0.006). Sensitivity, specificity, accuracy and area under the curve values were alike: 84.0 % for both; 77.3, 71.4 %; 80.9, 78.3 %; 82.5, 81.3 % for DWI-SPAIR and DWI-STIR, respectively. CONCLUSION DWI-STIR showed superior fat suppression homogeneity. No differences were found for SNR and CNR, except for SNR in benign lesions. ADCs for lesions were comparable. Findings in this study are consistent with previous studies at 1.5 T, meaning that both fat suppression techniques are appropriate for breast DWI at 3.0 T.
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Bickel H, Pinker-Domenig K, Bogner W, Spick C, Bagó-Horváth Z, Weber M, Helbich T, Baltzer P. Quantitative Apparent Diffusion Coefficient as a Noninvasive Imaging Biomarker for the Differentiation of Invasive Breast Cancer and Ductal Carcinoma In Situ. Invest Radiol 2015; 50:95-100. [DOI: 10.1097/rli.0000000000000104] [Citation(s) in RCA: 76] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Çabuk G, Nass Duce M, Özgür A, Apaydın FD, Polat A, Orekici G. The diagnostic value of diffusion-weighted imaging and the apparent diffusion coefficient values in the differentiation of benign and malignant breast lesions. J Med Imaging Radiat Oncol 2015; 59:141-8. [PMID: 25564776 DOI: 10.1111/1754-9485.12273] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2014] [Accepted: 11/20/2014] [Indexed: 11/26/2022]
Abstract
INTRODUCTION The goal of our study was to evaluate the diagnostic efficacy of diffusion-weighted imaging (DWI) in the differentiation of benign and malignant breast lesions. METHODS Between June 2012 and March 2013, 60 patients with 63 lesions (age range 29-70 years, mean age 48.6 years) were included in our study. All lesions, except complicated cysts and intra-mammary lymph nodes, were confirmed histopathologically. The patients were evaluated with a 1.5 Tesla MR scanner using dedicated bilateral breast coil. DWI images were obtained by echo planar imaging sequence and 'b' values were selected as 200, 600 and 1000 s/mm(2). Apparent diffusion coefficient (ADC) values of both breast lesions and the normal fibroglandular tissue of the contralateral breast were calculated and statistically compared using Shapiro-Wilk test, Student's t-test, Mann-Whitney U test, chi-square test and the receiver operating curve. RESULTS Of 63 lesions, 22 were malignant and 41 were benign. In malignant lesions, the mean ADC values were 1.40 ± 0.41 × 10(-3) mm(2)/s for b = 200, 1.05 ± 0.28 × 10(-3) mm(2)/s for b = 600 and 0.91 ± 0.20 × 10(-3) mm(2)/s for b = 1000 and in benign lesions, the mean ADC values were 2.13 ± 0.85 × 10(-3) mm(2)/s for b = 200, 1.64 ± 0.47 × 10(-3) mm(2)/s for b = 600 and 1.40 ± 0.43 × 10(-3) mm(2)/s for b = 1000. The success of ADC values in differentiation of benign and malignant lesions was statistically significant (P = 0.0001). The threshold values were determined to be 1.50 × 10(-3) mm(2)/s for b = 200, 1.22 × 10(-3) mm(2)/s for b = 600 and 0.98 × 10(-3) mm(2)/s for b = 1000 (P < 0.05). CONCLUSION DWI can be an effective radiological method in the differentiation of benign and malignant breast lesions.
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Affiliation(s)
- Gonca Çabuk
- Department of Radiology, School of Medicine, Mersin University, Mersin, Turkey
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Nogueira L, Brandão S, Nunes RG, Ferreira HA, Loureiro J, Ramos I. Breast DWI at 3 T: influence of the fat-suppression technique on image quality and diagnostic performance. Clin Radiol 2014; 70:286-94. [PMID: 25555315 DOI: 10.1016/j.crad.2014.11.012] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2014] [Revised: 11/12/2014] [Accepted: 11/19/2014] [Indexed: 10/24/2022]
Abstract
AIM To evaluate two fat-suppression techniques: short tau inversion recovery (STIR) and spectral adiabatic inversion recovery (SPAIR) regarding image quality and diagnostic performance in diffusion-weighted imaging (DWI) of breast lesions at 3 T. MATERIALS AND METHODS Ninety-two women (mean age 48 ± 12.1 years; range 21-78 years) underwent breast MRI. Two DWI pulse sequences, with b-values (50 and 1000 s/mm(2)) were performed with STIR and SPAIR. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), suppression homogeneity, and apparent diffusion coefficient (ADC) values were quantitatively assessed for each technique. Values were compared between techniques and lesion type. Receiver operating characteristics (ROC) analysis was used to evaluate lesion discrimination. RESULTS One hundred and fourteen lesions were analysed (40 benign and 74 malignant). SNR and CNR were significantly higher for DWI-SPAIR; fat-suppression uniformity was better for DWI-STIR (p < 1 × 10(-4)). ADC values for benign and malignant lesions and normal tissue were 1.92 × 10(-3), 1.18 × 10(-3), 1.86 × 10(-3) s/mm(2) for DWI-STIR and 1.80 × 10(-3), 1.11 × 10(-3), 1.79 × 10(-3) s/mm(2) for SPAIR, respectively. Comparison between fat-suppression techniques showed significant differences in mean ADC values for benign (p = 0.013) and malignant lesions (p = 0.001). DWI-STIR and -SPAIR ADC cut-offs were 1.42 × 10(-3) and 1.46 × 10(-3) s/mm(2), respectively. Diagnostic performance for DWI-STIR versus SPAIR was: accuracy (81.6 versus 83.3%), area under curve (87.7 versus 89.2%), sensitivity (79.7 versus 85.1%), and specificity (85 versus 80%). Positive predictive value was similar. CONCLUSION The fat-saturation technique used in the present study may influence image quality and ADC quantification. Nevertheless, STIR and SPAIR techniques showed similar diagnostic performances, and therefore, both are suitable for use in clinical practice.
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Affiliation(s)
- Luisa Nogueira
- Department of Radiology, School of Health Technology of Porto/Polytechnic Institute of Porto (ESTSP/IPP), Rua Valente Perfeito, 4400-330, Vila Nova de Gaia, Portugal; Department of Radiology, Hospital de São João/Faculty of Medicine of Porto University (FMUP), Alameda Prof. Hernâni Monteiro, 4200-319 Porto, Portugal.
| | - Sofia Brandão
- MRI Unit, Department of Radiology, Hospital de São João, Alameda Prof. Hernani Monteiro, 4200-319 Porto, Portugal
| | - Rita G Nunes
- Institute of Biophysics and Biomedical Engineering (IBEB), Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016, Lisboa, Portugal
| | - Hugo Alexandre Ferreira
- Institute of Biophysics and Biomedical Engineering (IBEB), Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016, Lisboa, Portugal
| | - Joana Loureiro
- MRI Unit, Department of Radiology, Hospital de São João, Alameda Prof. Hernani Monteiro, 4200-319 Porto, Portugal
| | - Isabel Ramos
- Department of Radiology, Hospital de São João/Faculty of Medicine of Porto University (FMUP), Alameda Prof. Hernâni Monteiro, 4200-319 Porto, Portugal
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Suo S, Lin N, Wang H, Zhang L, Wang R, Zhang S, Hua J, Xu J. Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer at 3.0 tesla: Comparison of different curve-fitting methods. J Magn Reson Imaging 2014; 42:362-70. [PMID: 25407944 DOI: 10.1002/jmri.24799] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2014] [Accepted: 10/24/2014] [Indexed: 11/09/2022] Open
Affiliation(s)
- Shiteng Suo
- Department of Radiology; Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University; Shanghai China
| | - Naier Lin
- Department of Radiology; Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University; Shanghai China
| | - He Wang
- Philips Research China; Shanghai China
| | - Liangbin Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University; Shanghai China
| | - Rui Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University; Shanghai China
| | - Su Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University; Shanghai China
| | - Jia Hua
- Department of Radiology; Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University; Shanghai China
| | - Jianrong Xu
- Department of Radiology; Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University; Shanghai China
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Breast Cancer Detection Using Double Reading of Unenhanced MRI Including T1-Weighted, T2-Weighted STIR, and Diffusion-Weighted Imaging: A Proof of Concept Study. AJR Am J Roentgenol 2014; 203:674-81. [DOI: 10.2214/ajr.13.11816] [Citation(s) in RCA: 74] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Belli P, Costantini M, Bufi E, Giardina GG, Rinaldi P, Franceschini G, Bonomo L. Diffusion magnetic resonance imaging in breast cancer characterisation: correlations between the apparent diffusion coefficient and major prognostic factors. Radiol Med 2014; 120:268-76. [PMID: 25096888 DOI: 10.1007/s11547-014-0442-8] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2013] [Accepted: 03/26/2014] [Indexed: 12/16/2022]
Abstract
PURPOSE This study was done to investigate the correlation between the apparent diffusion coefficient (ADC) and prognostic factors of breast cancer. MATERIALS AND METHODS From January 2008 to June 2011, all consecutive patients with breast cancer who underwent breast magnetic resonance imaging (MRI) and subsequent surgery in our hospital were enrolled in our study. The MRI protocol included a diffusion-weighted imaging sequence with b values of 0 and 1,000 s/mm(2). For each target lesion in the breast, the ADC value was compared with regard to major prognostic factors: histology, tumour grade, tumour size, lymph node status, and age. RESULTS A total of 289 patients with a mean age of 53.49 years were included in the study. The mean ADC value of malignant lesions was 1.02 × 10(-3) mm(2)/s. In situ carcinomas, grade 1 lesions, and tumours without lymph nodal involvement had mean ADC values that were significantly higher than those of invasive carcinomas (p = 0.009), grade 2/3 lesions (p < 0.001), and tumours with nodal metastases (p = 0.001). No significant differences were observed in ADC values among tumours of different sizes or among patient age groups. CONCLUSIONS ADC values appear to correlate with tumour grade and some major prognostic factors.
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Affiliation(s)
- Paolo Belli
- Department of Bio-Imaging and Radiological Sciences, Università Cattolica del Sacro Cuore, L.go A. Gemelli 8, 00168, Rome, Italy,
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Greenwood HI, Heller SL, Kim S, Sigmund EE, Shaylor SD, Moy L. Ductal carcinoma in situ of the breasts: review of MR imaging features. Radiographics 2014; 33:1569-88. [PMID: 24108552 DOI: 10.1148/rg.336125055] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The incidence of ductal carcinoma in situ (DCIS) has increased over the past few decades and now accounts for over 20% of newly diagnosed cases of breast cancer. Although the detection of DCIS has increased with the advent of widespread mammography screening, it is essential to have a more accurate assessment of the extent of DCIS for successful breast conservation therapy. Recent studies evaluating the detection of DCIS with magnetic resonance (MR) imaging have used high spatial resolution techniques and have increasingly been performed to screen a high-risk population as well as to evaluate the extent of disease. This work has shown that MR imaging is the most sensitive modality currently available for identifying DCIS and is more accurate than mammography in evaluating the extent of DCIS. MR imaging is particularly sensitive for identifying high-grade and intermediate-grade DCIS. DCIS may have variable morphologic features on MR images, with non-mass enhancement morphology being the most common manifestation. Less commonly, DCIS may also manifest as a mass on MR images, in which case it is most likely to be irregular. The kinetics of DCIS are also variable, with fast uptake and a plateau curve reported as the most common kinetic pattern. Additional MR imaging tools such as diffusion-weighted imaging and quantitative kinetic analysis combined with the benefit of high field strength, such as 3 T, may increase the sensitivity and specificity of breast MR imaging in the detection of DCIS.
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Affiliation(s)
- Heather I Greenwood
- Department of Radiology, New York University School of Medicine, 550 First Ave, New York, NY 10016
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Nogueira L, Brandão S, Matos E, Nunes RG, Loureiro J, Ferreira HA, Ramos I. Diffusion-weighted imaging: determination of the best pair of b-values to discriminate breast lesions. Br J Radiol 2014; 87:20130807. [PMID: 24834475 DOI: 10.1259/bjr.20130807] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVE In breast diffusion-weighted imaging (DWI), the apparent diffusion coefficient (ADC) is used to discriminate between malignant and benign lesions. As ADC estimates can be affected by the weighting factors, our goal was to determine the optimal pair of b-values for discriminating breast lesions at 3.0 T. METHODS 152 females with 157 lesions (89 malignant and 68 benign) underwent breast MRI, including a DWI sequence sampling six b-values 50, 200, 400, 600, 800 and 1000 s mm(-2). ADC values were computed from different pairs of b-values and compared with ADC obtained by fitting the six b-values using a mono-exponential diffusion model (ADCall). Cut-off ADC values were determined and diagnostic performance evaluated by receiver operating characteristic analysis using Youden statistics. Mean ADCs were determined for normal tissue and lesions. Differences were evaluated by lesion and histological types. RESULTS Considering the cut-off values 1.46 and 1.49 × 10(3)mm(2) s(-1), the pairs 50, 1000 and 200, 800 s mm(-2) showed the highest accuracy, 77.5% and 75.4% with areas under the curve 84.4% and 84.2%, respectively. The best pair for ADC quantification was 50, 1000 s mm(-2) with 38/49 true-negative and 69/89 true-positive cases respectively; mean ADCs were 1.86 ± 0.46, 1.77 ± 0.37 and 1.15 ± 0.46 × 10(-3) mm(2) s(-1) for normal, benign and malignant lesions. There were no significant differences in these ADC values when compared with ADCall (ADC calculated from the full set of b - values) [difference = 0.0075 × 10(-3) mm(2) s(-1); confidence interval 95%: (-0.0036; 0.0186); p = 0.18]. CONCLUSION The diagnostic performance in differentiating malignant and benign lesions was most accurate for the b-value pair 50, 1000 s mm(-2). ADVANCES IN KNOWLEDGE The best b-value pair for lesion discrimination and characterization through ADC quantification was 50, 1000 s mm(-2).
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Affiliation(s)
- L Nogueira
- 1 Department of Radiology, School of Allied Health Sciences, Oporto Polytechnic Institute (ESTSP/IPP), Vila Nova de Gaia, Portugal
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Menezes GLG, Knuttel FM, Stehouwer BL, Pijnappel RM, van den Bosch MAAJ. Magnetic resonance imaging in breast cancer: A literature review and future perspectives. World J Clin Oncol 2014; 5:61-70. [PMID: 24829852 PMCID: PMC4014797 DOI: 10.5306/wjco.v5.i2.61] [Citation(s) in RCA: 93] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2014] [Revised: 03/18/2014] [Accepted: 04/17/2014] [Indexed: 02/06/2023] Open
Abstract
Early detection and diagnosis of breast cancer are essential for successful treatment. Currently mammography and ultrasound are the basic imaging techniques for the detection and localization of breast tumors. The low sensitivity and specificity of these imaging tools resulted in a demand for new imaging modalities and breast magnetic resonance imaging (MRI) has become increasingly important in the detection and delineation of breast cancer in daily practice. However, the clinical benefits of the use of pre-operative MRI in women with newly diagnosed breast cancer is still a matter of debate. The main additional diagnostic value of MRI relies on specific situations such as detecting multifocal, multicentric or contralateral disease unrecognized on conventional assessment (particularly in patients diagnosed with invasive lobular carcinoma), assessing the response to neoadjuvant chemotherapy, detection of cancer in dense breast tissue, recognition of an occult primary breast cancer in patients presenting with cancer metastasis in axillary lymph nodes, among others. Nevertheless, the development of new MRI technologies such as diffusion-weighted imaging, proton spectroscopy and higher field strength 7.0 T imaging offer a new perspective in providing additional information in breast abnormalities. We conducted an expert literature review on the value of breast MRI in diagnosing and staging breast cancer, as well as the future potentials of new MRI technologies.
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Diffusion-weighted breast imaging at 3 T: Preliminary experience. Clin Radiol 2014; 69:378-84. [DOI: 10.1016/j.crad.2013.11.005] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2013] [Revised: 10/29/2013] [Accepted: 11/07/2013] [Indexed: 12/16/2022]
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Wu LM, Chen XX, Li YL, Hua J, Chen J, Hu J, Xu JR. On the utility of quantitative diffusion-weighted MR imaging as a tool in differentiation between malignant and benign thyroid nodules. Acad Radiol 2014; 21:355-63. [PMID: 24332602 DOI: 10.1016/j.acra.2013.10.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2013] [Revised: 10/12/2013] [Accepted: 10/14/2013] [Indexed: 10/25/2022]
Abstract
RATIONALE AND OBJECTIVES To evaluate the ability of diffusion-weighted magnetic resonance imaging (DWI) in differentiating malignant thyroid nodules from benign lesions with a meta-analysis. MATERIALS AND METHODS Articles in English and Chinese language relating to the accuracy of DWI for this utility were retrieved. Pooled estimation and subgroup analysis data were obtained by statistical analysis. RESULTS A total of seven studies (17 subsets) with 358 patients, who fulfilled all of the inclusion criteria, were considered for the analysis. No publication bias was found (bias = 7.03, P > .05). Methodological quality was relatively high. DWI sensitivity was 0.91 (95% confidence interval [CI], 0.87-0.94) and specificity was 0.93 (95% CI, 0.86-0.96). Overall, positive likelihood ratio was 12.24 (95% CI, 6.47-23.20) and negative likelihood ratio was 0.99 (95% CI, 0.06-0.15). Diagnostic odds ratio was 123.78 (95% CI, 56.85-269.48). The area under the curve of the summary receiver operating characteristic was 0.94 (95% CI, 0.92-0.96). In patients with high pretest probabilities, DWI enabled confirmation of malignant thyroid lesion; in patients with low pretest probabilities, DWI enabled exclusion of malignant thyroid lesion. Worst-case-scenario (pretest probability, 50%) posttest probabilities were 92% and 9% for positive and negative DWI results, respectively. CONCLUSIONS A limited number of small studies suggests that quantitative DWI is a reliable diagnostic method for differentiation between benign and malignant thyroid lesions.
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