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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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2
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Arponen O, McLean MA, Nanaa M, Manavaki R, Baxter GC, Gill AB, Riemer F, Kennerley AJ, Woitek R, Kaggie JD, Brackenbury WJ, Gilbert FJ. 23Na MRI: inter-reader reproducibility of normal fibroglandular sodium concentration measurements at 3 T. Eur Radiol Exp 2024; 8:75. [PMID: 38853182 PMCID: PMC11162986 DOI: 10.1186/s41747-024-00465-x] [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: 10/27/2023] [Accepted: 04/08/2024] [Indexed: 06/11/2024] Open
Abstract
BACKGROUND To study the reproducibility of 23Na magnetic resonance imaging (MRI) measurements from breast tissue in healthy volunteers. METHODS Using a dual-tuned bilateral 23Na/1H breast coil at 3-T MRI, high-resolution 23Na MRI three-dimensional cones sequences were used to quantify total sodium concentration (TSC) and fluid-attenuated sodium concentration (FASC). B1-corrected TSC and FASC maps were created. Two readers manually measured mean, minimum and maximum TSC and mean FASC values using two sampling methods: large regions of interest (LROIs) and small regions of interest (SROIs) encompassing fibroglandular tissue (FGT) and the highest signal area at the level of the nipple, respectively. The reproducibility of the measurements and correlations between density, age and FGT apparent diffusion coefficient (ADC) values were evaluatedss. RESULTS Nine healthy volunteers were included. The inter-reader reproducibility of TSC and FASC using SROIs and LROIs was excellent (intraclass coefficient range 0.945-0.979, p < 0.001), except for the minimum TSC LROI measurements (p = 0.369). The mean/minimum LROI TSC and mean LROI FASC values were lower than the respective SROI values (p < 0.001); the maximum LROI TSC values were higher than the SROI TSC values (p = 0.009). TSC correlated inversely with age but not with FGT ADCs. The mean and maximum FGT TSC and FASC values were higher in dense breasts in comparison to non-dense breasts (p < 0.020). CONCLUSIONS The chosen sampling method and the selected descriptive value affect the measured TSC and FASC values, although the inter-reader reproducibility of the measurements is in general excellent. RELEVANCE STATEMENT 23Na MRI at 3 T allows the quantification of TSC and FASC sodium concentrations. The sodium measurements should be obtained consistently in a uniform manner. KEY POINTS • 23Na MRI allows the quantification of total and fluid-attenuated sodium concentrations (TSC/FASC). • Sampling method (large/small region of interest) affects the TSC and FASC values. • Dense breasts have higher TSC and FASC values than non-dense breasts. • The inter-reader reproducibility of TSC and FASC measurements was, in general, excellent. • The results suggest the importance of stratifying the sodium measurements protocol.
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Affiliation(s)
- Otso Arponen
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK.
| | - Mary A McLean
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | - Muzna Nanaa
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | - Roido Manavaki
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | - Gabrielle C Baxter
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | - Andrew B Gill
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | - Frank Riemer
- Department of Radiology, Mohn Medical Imaging and Visualization Centre (MMIV), Haukeland University Hospital, Bergen, Norway
| | - Aneurin J Kennerley
- York Biomedical Research Institute, University of York, York, UK
- Department of Sports and Exercise Science, Institute of Sport, Manchester Metropolitan University, Manchester, UK
| | - Ramona Woitek
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Research Center for Medical Image Analysis and AI (MIAAI), Danube Private University, Krems, Austria
| | - Joshua D Kaggie
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | - William J Brackenbury
- York Biomedical Research Institute, University of York, York, UK
- Department of Biology, University of York, York, UK
| | - Fiona J Gilbert
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
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Skwierawska D, Laun FB, Wenkel E, Kapsner LA, Janka R, Uder M, Ohlmeyer S, Bickelhaupt S. Diffusion-Weighted Imaging for Skin Pathologies of the Breast-A Feasibility Study. Diagnostics (Basel) 2024; 14:934. [PMID: 38732348 PMCID: PMC11083106 DOI: 10.3390/diagnostics14090934] [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: 03/07/2024] [Revised: 04/19/2024] [Accepted: 04/24/2024] [Indexed: 05/13/2024] Open
Abstract
Several breast pathologies can affect the skin, and clinical pathways might differ significantly depending on the underlying diagnosis. This study investigates the feasibility of using diffusion-weighted imaging (DWI) to differentiate skin pathologies in breast MRIs. This retrospective study included 88 female patients who underwent diagnostic breast MRI (1.5 or 3T), including DWI. Skin areas were manually segmented, and the apparent diffusion coefficients (ADCs) were compared between different pathologies: inflammatory breast cancer (IBC; n = 5), benign skin inflammation (BSI; n = 11), Paget's disease (PD; n = 3), and skin-involved breast cancer (SIBC; n = 11). Fifty-eight women had healthy skin (H; n = 58). The SIBC group had a significantly lower mean ADC than the BSI and IBC groups. These differences persisted for the first-order features of the ADC (mean, median, maximum, and minimum) only between the SIBC and BSI groups. The mean ADC did not differ significantly between the BSI and IBC groups. Quantitative DWI assessments demonstrated differences between various skin-affecting pathologies, but did not distinguish clearly between all of them. More extensive studies are needed to assess the utility of quantitative DWI in supplementing the diagnostic assessment of skin pathologies in breast imaging.
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Affiliation(s)
- Dominika Skwierawska
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054 Erlangen, Germany
| | - Frederik B. Laun
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054 Erlangen, Germany
| | - Evelyn Wenkel
- Radiologie München, Burgstraße 7, 80331 München, Germany
- Medical Faculty, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany
| | - Lorenz A. Kapsner
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054 Erlangen, Germany
- Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Wetterkreuz 15, 91058 Erlangen-Tennenlohe, Germany
| | - Rolf Janka
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054 Erlangen, Germany
| | - Michael Uder
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054 Erlangen, Germany
| | - Sabine Ohlmeyer
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054 Erlangen, Germany
| | - Sebastian Bickelhaupt
- Institute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054 Erlangen, Germany
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Liu K, Yang W, Tian H, Li Y, He J. Association between programmed cell death ligand-1 expression in patients with cervical cancer and apparent diffusion coefficient values: a promising tool for patient´s immunotherapy selection. Eur Radiol 2024:10.1007/s00330-024-10759-8. [PMID: 38637428 DOI: 10.1007/s00330-024-10759-8] [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: 11/23/2023] [Revised: 03/21/2024] [Accepted: 04/07/2024] [Indexed: 04/20/2024]
Abstract
OBJECTIVE To investigate the associations between apparent diffusion coefficient (ADC) values extracted from three different region of interest (ROI) position approaches and programmed cell death ligand-1 (PD-L1) expression, and evaluate the performance of the nomogram established based on ADC values and clinicopathological parameters in predicting PD-L1 expression in cervical cancer (CC) patients. METHODS Through retrospective recruitment, a training cohort of 683 CC patients was created, and a validation cohort of 332 CC patients was prospectively recruited. ROIs were delineated using three different methods to measure the mean ADC (ADCmean), single-section ADC (ADCss), and the minimum ADC of tumors (ADCmin). Logistic regression was employed to identify independent factors related to PD-L1 expression. A nomogram was drawn based on ADC values combined with clinicopathological features, its discrimination and calibration performances were estimated using the area under the curve (AUC) of receiver operating characteristic and calibration curve. The clinical benefits were evaluated by decision curve analysis. RESULTS The ADCmin independently correlated with PD-L1 expression. The nomogram constructed with ADCmin and other independent clinicopathological-related factors: FIGO staging, pathological grade, parametrial invasion, and lymph node status demonstrated excellent diagnostic performance (AUC = 0.912 and 0.903, respectively), good calibration capacities, and greater net benefits compared to the clinicopathological model in both the training and validation cohorts. CONCLUSION ADCmin independently correlated PD-L1 expression, and the nomogram established with ADCmin and clinicopathological independent prognostic factors had a strong predictive performance for PD-L1 expression, thereby serving as a promising tool for selecting cases eligible for immunotherapy. CLINICAL RELEVANCE STATEMENT The minimum ADC can serve as a reliable imaging biomarker related to PD-L1 expression; the established nomogram combines the minimum ADC and clinicopathological factors that can assist clinical immunotherapy decisions.
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Affiliation(s)
- Kaihui Liu
- College of Clinical Medicine, Ningxia Medical University, Yinchuan, P.R. China
| | - Wei Yang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, P.R. China.
| | - Haiping Tian
- Department of Pathology, General Hospital of Ningxia Medical University, Yinchuan, P.R. China
| | - Yunxia Li
- Department of Medical Oncology, General Hospital of Ningxia Medical University, Yinchuan, P.R. China
| | - Jianli He
- Department of Radiotherapy, General Hospital of Ningxia Medical University, Yinchuan, P.R. China
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Gao W, Yang Q, Li X, Zhang Y, He T, Liang W, Wei X, Yang M, Gao B, Zhang G, Zhang S. Quantitative Assessment of Breast Tumor: Comparison of Four Methods of Positioning Region of Interest for Synthetic Relaxometry and Diffusion Measurement. Acad Radiol 2024:S1076-6332(24)00135-1. [PMID: 38508932 DOI: 10.1016/j.acra.2024.02.045] [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: 01/28/2024] [Revised: 02/22/2024] [Accepted: 02/24/2024] [Indexed: 03/22/2024]
Abstract
RATIONALE AND OBJECTIVES To compare the differences in apparent diffusion coefficient (ADC) and synthetic magnetic resonance (MR) measurements of four region of interest (ROI) placement methods for breast tumor and to investigate their diagnostic performance. METHODS 110 (70 malignant, 40 benign) newly diagnosed breast tumors were evaluated. The patients underwent 3.0 T MR examinations including diffusion-weighted imaging and synthetic MR. Two radiologists independently measured ADCs, T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) using four ROI methods: round, square, freehand, and whole-tumor volume (WTV). The interclass correlation coefficient (ICC) was used to assess their measurement reliability. Diagnostic performance was evaluated using multivariate logistic regression analysis and the receiver operating characteristic (ROC) curves. RESULTS The mean values of all ROI methods showed good or excellent interobserver reproducibility (0.79-0.99) and showed the best diagnostic performance compared to the minimum and maximum values. The square ROI exhibited superior performance in differentiating between benign from malignant breast lesions, followed by the freehand ROI. T2, PD, and ADC values were significantly lower in malignant breast lesions compared to benign ones for all ROI methods (p < 0.05). Multiparameters of T2 + ADC demonstrated the highest AUC values (0.82-0.95), surpassing the diagnostic efficacy of ADC or T2 alone (p < 0.05). CONCLUSION ROI placement significantly influences ADC and synthetic MR values measured in breast tumors. Square ROI and mean values showed superior performance in differentiating benign and malignant breast lesions. The multiparameters of T2 + ADC surpassed the diagnostic efficacy of a single parameter.
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Affiliation(s)
- Weibo Gao
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Quanxin Yang
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xiaohui Li
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Yanyan Zhang
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Tuo He
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Wenbin Liang
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | | | - Ming Yang
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Bo Gao
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Guirong Zhang
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Shuqun Zhang
- Department of Oncology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
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Ahmadinejad N, Azizinik F, Khosravi P, Torabi A, Mohajeri A, Arian A. Evaluation of Features in Probably Benign and Malignant Nonmass Enhancement in Breast MRI. Int J Breast Cancer 2024; 2024:6661849. [PMID: 38523651 PMCID: PMC10959584 DOI: 10.1155/2024/6661849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 12/08/2023] [Accepted: 02/27/2024] [Indexed: 03/26/2024] Open
Abstract
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a highly sensitive breast imaging modality in detecting breast carcinoma. Nonmass enhancement (NME) is uniquely seen on MRI of the breast. The correlation between NME features and pathologic results has not been extensively explored. Our goal was to evaluate the characteristics of probably benign and suspicious NME lesions in MRI and determine which features are more associated with malignancy. We performed a retrospective research after approval by the hospital ethics committee on women who underwent breast MRI from March 2017 to March 2020 and identified 63 lesions of all 400 NME that were categorized as probably benign or suspicious according to the BI-RADS classification (version 2013). MRI features of NME findings including the location, size, distribution and enhancement pattern, kinetic curve, diffusion restriction, and also pathology result or 6-12-month follow-up MRI were evaluated and analyzed in each group (probably benign or suspicious NME). Vacuum-guided biopsies (VAB) were performed under mammographic or sonographic guidance and confirmed with MRI by visualization of the inserted clips. Segmental distribution and clustered ring internal enhancement were significantly associated with malignancy (p value<0.05), while linear distribution or homogeneous enhancement patterns were associated with benignity (p value <0.05). Additionally, the plateau and washout types in the dynamic curve were only seen in malignant lesions (p value <0.05). The presence of DWI restriction in NME lesions was also found to be a statistically important factor. Understanding the imaging findings of malignant NME is helpful to determine when biopsy is indicated. The correlation between NME features and pathologic results is critical in making appropriate management.
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Affiliation(s)
- Nasrin Ahmadinejad
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Imam Khomeini Hospital, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Fahimeh Azizinik
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Imam Khomeini and Yas Hospital, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Pershang Khosravi
- Department of Radiology, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Ala Torabi
- Department of Radiology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Arvin Arian
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Imam Khomeini Hospital, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
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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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Bickel H, Clauser P, Pinker K, Helbich T, Biondic I, Brkljacic B, Dietzel M, Ivanac G, Krug B, Moschetta M, Neuhaus V, Preidler K, Baltzer P. Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database. Eur Radiol 2023; 33:5400-5410. [PMID: 37166495 PMCID: PMC10326122 DOI: 10.1007/s00330-023-09675-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 02/27/2023] [Accepted: 03/14/2023] [Indexed: 05/12/2023]
Abstract
OBJECTIVES To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria. METHODS This was a multicentric, retrospective analysis of 11 independently conducted institutional review board-approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant. RESULTS A total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10-3 mm2/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p < .001). The following ADC-B categories were identified: ADC-B0-ADC cannot be assessed; ADC-B1-no contrast-enhancing lesion; ADC-B2-ADC ≥ 1.9 (cumulative malignancy rate < 0.1%); ADC-B3-ADC 1.5 to < 1.9 (0.1-1.7%); ADC-B4-ADC 1.0 to < 1.5 (10-24.5%); and ADC-B5-ADC < 1.0 (> 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94-0.97) for invasive versus non-invasive breast carcinomas was reached. CONCLUSIONS The breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI. CLINICAL RELEVANCE STATEMENT The ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes. KEY POINTS • The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making.
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Affiliation(s)
- Hubert Bickel
- Dpt. of Biomedical Imaging and Image Guided Therapy, Medical University Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
- Diagnosezentrum Meidling, Meidlinger Hauptstr. 7 - 9, 1120, Vienna, Austria
| | - Paola Clauser
- Dpt. of Biomedical Imaging and Image Guided Therapy, Medical University Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Katja Pinker
- Evelyn H. Lauder Breast Center, Memorial Sloan Kettering Cancer Center, 300 East 66th Street, New York, NY, 10065, USA
| | - Thomas Helbich
- Dpt. of Biomedical Imaging and Image Guided Therapy, Medical University Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Iva Biondic
- Dpt. of Diagnostic and Interventional Radiology, University Hospital Dubrava, University of Zagreb School of Medicine, Avenija Gojka Šuška 6, 10 000, Zagreb, Croatia
| | - Boris Brkljacic
- Dpt. of Diagnostic and Interventional Radiology, University Hospital Dubrava, University of Zagreb School of Medicine, Avenija Gojka Šuška 6, 10 000, Zagreb, Croatia
| | - Matthias Dietzel
- Dpt. of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Gordana Ivanac
- Dpt. of Diagnostic and Interventional Radiology, University Hospital Dubrava, University of Zagreb School of Medicine, Avenija Gojka Šuška 6, 10 000, Zagreb, Croatia
| | - Barbara Krug
- Dpt. of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany
| | - Marco Moschetta
- Dpt. of Emergency and Organ Transplantation-Breast Care Unit, Aldo Moro University of Bari Medical School, Piazza Giulio Cesare 11, 70124, Bari, Italy
| | - Victor Neuhaus
- Dpt. of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany
| | - Klaus Preidler
- Diagnosezentrum Meidling, Meidlinger Hauptstr. 7 - 9, 1120, Vienna, Austria
| | - Pascal Baltzer
- Dpt. of Biomedical Imaging and Image Guided Therapy, Medical University Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
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Láinez Ramos-Bossini AJ, Ruiz Santiago F, Moraleda Cabrera B, López Zúñiga D, Ariza Sánchez A. Imaging of low-energy vertebral fractures. RADIOLOGIA 2023; 65:239-250. [PMID: 37268366 DOI: 10.1016/j.rxeng.2023.01.006] [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: 10/06/2022] [Accepted: 01/01/2023] [Indexed: 06/04/2023]
Abstract
Low-energy vertebral fractures pose a diagnostic challenge for the radiologist due to their often-inadvertent nature and often subtle imaging semiology. However, the diagnosis of this type of fractures can be decisive, not only because it allows targeted treatment to prevent complications, but also because of the possibility of diagnosing systemic pathologies such as osteoporosis or metastatic disease. Pharmacological treatment in the first case has been shown to prevent the development of other fractures and complications, while percutaneous treatments and various oncological therapies can be an alternative in the second case. Therefore, it is necessary to know the epidemiology and typical imaging findings of this type of fractures. The objective of this work is to review the imaging diagnosis of low-energy fractures, with special emphasis on the characteristics that should be outlined in the radiological report to guide a specific diagnosis that favours and optimizes the treatment of patients suffering of low energy fractures.
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Affiliation(s)
- A J Láinez Ramos-Bossini
- Sección de Radiología Musculoesquelética, Servicio de Radiodiagnóstico, Hospital Universitario Virgen de las Nieves, Granada, Spain; Instituto Biosanitario de Granada (ibs.GRANADA), Granada, Spain; Programa de doctorado en Medicina Clínica y Salud Pública, Universidad de Granada, Granada, Spain; Departamento de Psiquiatría, Facultad de Medicina, Universidad de Granada, Granada, Spain
| | - F Ruiz Santiago
- Sección de Radiología Musculoesquelética, Servicio de Radiodiagnóstico, Hospital Universitario Virgen de las Nieves, Granada, Spain; Instituto Biosanitario de Granada (ibs.GRANADA), Granada, Spain; Departamento de Medicina Física y Rehabilitación, Facultad de Medicina, Universidad de Granada, Granada, Spain.
| | - B Moraleda Cabrera
- Sección de Radiología Musculoesquelética, Servicio de Radiodiagnóstico, Hospital Universitario Virgen de las Nieves, Granada, Spain; Instituto Biosanitario de Granada (ibs.GRANADA), Granada, Spain
| | - D López Zúñiga
- Sección de Radiología Musculoesquelética, Servicio de Radiodiagnóstico, Hospital Universitario Virgen de las Nieves, Granada, Spain; Instituto Biosanitario de Granada (ibs.GRANADA), Granada, Spain
| | - A Ariza Sánchez
- Sección de Radiología Musculoesquelética, Servicio de Radiodiagnóstico, Hospital Universitario Virgen de las Nieves, Granada, Spain; Instituto Biosanitario de Granada (ibs.GRANADA), Granada, Spain
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Kazerouni AS, Rahbar H, Partridge SC. Is NME the enemy of breast DWI? Eur J Radiol 2023; 159:110648. [PMID: 36571925 PMCID: PMC10601596 DOI: 10.1016/j.ejrad.2022.110648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 12/09/2022] [Indexed: 12/23/2022]
Affiliation(s)
- Anum S Kazerouni
- Department of Radiology, University of Washington, Seattle, WA, United States
| | - Habib Rahbar
- Department of Radiology, University of Washington, Seattle, WA, United States
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Láinez Ramos-Bossini A, Ruiz Santiago F, Moraleda Cabrera B, López Zúñiga D, Ariza Sánchez A. Diagnóstico por imagen de las fracturas vertebrales de baja energía. RADIOLOGIA 2023. [DOI: 10.1016/j.rx.2023.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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12
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Si L, Liu X, Li X, Yang K, Wang L. Diffusion kurtosis imaging and intravoxel incoherent motion imaging parameters in breast lesions: Effect of radiologists' experience and region-of-interest selection. Eur J Radiol 2023; 158:110633. [PMID: 36470051 DOI: 10.1016/j.ejrad.2022.110633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 11/14/2022] [Accepted: 11/24/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE To investigate the influence of ROI placement methods and radiologists' experience on diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) parameters' diagnostic performance in differentiating benign and malignant lesions based on the mass and non-mass enhancement (NME). METHODS We evaluated 138 lesions in 131 patients retrospectively. The IVIM and DKI parameter values were measured by three radiologists with different experiences independently using two different ROI placement methods. IVIM parameters include diffusion coefficient (ADCstand), true diffusion coefficient (ADCslow), pseudo-diffusion coefficient (ADCfast) and perfusion fraction (f). DKI parameters include mean diffusivity (MD) and mean kurtosis (MK). Each radiologist measured the lesions twice with a 3-month interval. We utilized intra-class correlation (ICC) to determine the inter- and intra-reader agreement for mass and NME, respectively. ROC analysis compared the diagnostic performance of parameters between different radiologists, ROI methods, and between mass and NME. RESULTS In mass lesions, inter- and intra-observer agreement were perfect for all parameters (ICC: 0.800-989). In NME, the inter-observer agreement was substantial to perfect for all parameters(ICC: 0.703-877), the intra-observer agreement of the senior and intermediate radiologists was substantial to perfect(ICC: 0.748-931) and the intra-observer agreement of the junior radiologist was moderate to substantial(ICC: 0.569-784). The diagnostic performance of ADCslow (Z = 2.209, P = 0.023), MD (mean diffusivity) (Z = 2.887, P = 0.004), and MK (mean kurtosis) (Z = 2.080, P = 0.038) in the small ROI measured by the senior radiologist was better than that of the junior radiologist for NME. The diagnostic performance of ADCslow in the large ROI measured by the senior radiologist (Z = 2.281, P = 0.023) and intermediate radiologist (Z = 2.867, P = 0.0041) was better than the junior radiologist for mass lesions. The diagnostic performance of ADCslow, ADCstand, MD, and MK did not show a significant difference between the two ROI placement methods (P > 0.05). CONCLUSION The observers' experience can influence the ROI selection and the diagnostic performance of ADCslow, ADCstand, MD, and MK measured using different methods show equal diagnostic performance.
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Affiliation(s)
- Lifang Si
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, People's Republic of China
| | - Xiaojuan Liu
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, People's Republic of China.
| | - Xinyue Li
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, People's Republic of China
| | - Kaiyan Yang
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, People's Republic of China
| | - Li Wang
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, People's Republic of China
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13
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Holopainen E, Lahtinen O, Könönen M, Anttila M, Vanninen R, Lindgren A. Greater increases in intratumoral apparent diffusion coefficients after chemoradiotherapy predict better overall survival of patients with cervical cancer. PLoS One 2023; 18:e0285786. [PMID: 37167301 PMCID: PMC10174495 DOI: 10.1371/journal.pone.0285786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 04/28/2023] [Indexed: 05/13/2023] Open
Abstract
PURPOSE To evaluate whether 1) the intratumoral apparent diffusion coefficients (ADCs) change during cervical cancer treatment and 2) the pretreatment ADC values or their change after treatment predict the treatment outcome or overall survival of patients with cervical cancer. METHODS We retrospectively enrolled 52 patients with inoperable cervical cancer treated with chemoradiotherapy, who had undergone diffusion weighted MRI before treatment and post external beam radiotherapy (EBRT) and concurrent chemotherapy. A subgroup of patients (n = 28) underwent altogether six consecutive diffusion weighted MRIs; 1) pretreatment, 2) post-EBRT and concurrent chemotherapy; 3-5) during image-guided brachytherapy (IGBT) and 6) after completing the whole treatment course. To assess interobserver and intertechnique reproducibility two observers independently measured the ADCs by drawing freehand a large region of interest (L-ROI) covering the whole tumor and three small ROIs (S-ROIs) in areas with most restricted diffusion. RESULTS Reproducibility was equally good for L-ROIs and S-ROIs. The pretreatment ADCs were higher in L-ROIs (883 mm2/s) than in S-ROIs (687 mm2/s, P < 0.001). The ADCs increased significantly between the pretreatment and post-EBRT scans (L-ROI: P < 0.001; S-ROI: P = 0.001). The ADCs remained significantly higher than pretreatment values during the whole IGBT. Using S-ROIs, greater increases in ADCs between pretreatment and post-EBRT MRI predicted better overall survival (P = 0.018). CONCLUSION ADC values significantly increase during cervical cancer treatment. Greater increases in ADC values between pretreatment and post-EBRT predicted better overall survival using S-ROIs. Standardized methods for timing and delineation of ADC measurements are advocated in future studies.
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Affiliation(s)
- Erikka Holopainen
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
| | - Olli Lahtinen
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
| | - Mervi Könönen
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
- Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland
| | - Maarit Anttila
- Department of Gynecology and Obstetrics, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Obstetrics and Gynecology, University of Eastern Finland, Kuopio, Finland
| | - Ritva Vanninen
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
| | - Auni Lindgren
- Department of Gynecology and Obstetrics, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Obstetrics and Gynecology, University of Eastern Finland, Kuopio, Finland
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Meng L, Zhao X, Guo J, Lu L, Cheng M, Xing Q, Shang H, Wang K, Zhang B, Lei D, Zhang X. Evaluation of the differentiation of benign and malignant breast lesions using synthetic relaxometry and the Kaiser score. Front Oncol 2022; 12:964078. [PMID: 36303839 PMCID: PMC9595598 DOI: 10.3389/fonc.2022.964078] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 09/26/2022] [Indexed: 12/24/2022] Open
Abstract
Objective To investigate whether there is added value of quantitative parameters from synthetic magnetic resonance imaging (SyMRI) as a complement to the Kaiser score (KS) to differentiate benign and malignant breast lesions. Materials and methods In this single-institution study, 122 patients who underwent breast MRI from March 2020 to May 2021 were retrospectively analyzed. SyMRI and dynamic contrast-enhanced MRI were performed using a 3.0-T system. Two experienced radiologists independently assigned the KS and measured the quantitative values of T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) from SyMRI. Pathology was regarded as the gold standard. The diagnostic values were compared using the appropriate statistical tests. Results There were 122 lesions (86 malignant and 36 benign) in 122 women. The T1 value was identified as the only independent factor for the differentiation of malignant and benign lesions. The diagnostic accuracy of incorporating the T1 into the KS protocol (T1+KS) was 95.1% and 92.1% for all lesions (ALL) and The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions, respectively, which was significantly higher than that of either T1 (ALL: 82.8%, P = 0.0001; BI-RADS 4: 78.9%, P = 0.002) or KS (ALL: 90.2%, P = 0.031; BI-RADS 4: 84.2%, P = 0.031) alone. The sensitivity and specificity of T1+KS were also higher than those of the T1 or KS alone. The combined diagnosis could have avoided another 15.6% biopsies compared with using KS alone. Conclusions Incorporating T1 into the KS protocol improved both the sensitivity and specificity to differentiate benign and malignant breast lesions, thus avoiding unnecessary invasive procedures.
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Affiliation(s)
- Lingsong Meng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jinxia Guo
- General Electric (GE) Healthcare, MR Research China, Beijing, China
| | - Lin Lu
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Meiying Cheng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qingna Xing
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Honglei Shang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kaiyu Wang
- General Electric (GE) Healthcare, MR Research China, Beijing, China
| | - Bohao Zhang
- Henan Key Laboratory of Child Brain Injury, Institute of Neuroscience and the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Dongmei Lei
- Department of Pathology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoan Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Xiaoan Zhang,
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15
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Mürtz P, Tsesarskiy M, Sprinkart AM, Block W, Savchenko O, Luetkens JA, Attenberger U, Pieper CC. Simplified intravoxel incoherent motion DWI for differentiating malignant from benign breast lesions. Eur Radiol Exp 2022; 6:48. [PMID: 36171532 PMCID: PMC9519819 DOI: 10.1186/s41747-022-00298-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 07/27/2022] [Indexed: 11/27/2022] Open
Abstract
Background To evaluate simplified intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for differentiating malignant versus benign breast lesions as (i) stand-alone tool and (ii) add-on to dynamic contrast-enhanced magnetic resonance imaging. Methods 1.5-T DWI data (b = 0, 50, 250, 800 s/mm2) were retrospectively analysed for 126 patients with malignant or benign breast lesions. Apparent diffusion coefficient (ADC) ADC (0, 800) and IVIM-based parameters D1′ = ADC (50, 800), D2′ = ADC (250, 800), f1′ = f (0, 50, 800), f2′ = f (0, 250, 800) and D*′ = D* (0, 50, 250, 800) were voxel-wise calculated without fitting procedures. Regions of interest were analysed in vital tumour and perfusion hot spots. Beside the single parameters, the combined use of D1′ with f1′ and D2′ with f2′ was evaluated. Lesion differentiation was investigated for lesions (i) with hyperintensity on DWI with b = 800 s/mm2 (n = 191) and (ii) with suspicious contrast-enhancement (n = 135). Results All lesions with suspicious contrast-enhancement appeared also hyperintense on DWI with b = 800 s/mm2. For task (i), best discrimination was reached for the combination of D1′ and f1′ using perfusion hot spot regions-of-interest (accuracy 93.7%), which was higher than that of ADC (86.9%, p = 0.003) and single IVIM parameters D1′ (88.0%) and f1′ (87.4%). For task (ii), best discrimination was reached for single parameter D1′ using perfusion hot spot regions-of-interest (92.6%), which were slightly but not significantly better than that of ADC (91.1%) and D2′ (88.1%). Adding f1′ to D1′ did not improve discrimination. Conclusions IVIM analysis yielded a higher accuracy than ADC. If stand-alone DWI is used, perfusion analysis is of special relevance.
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Affiliation(s)
- Petra Mürtz
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
| | - Mark Tsesarskiy
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Alois M Sprinkart
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Wolfgang Block
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Department of Radiotherapy and Radiation Oncology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Department of Neuroradiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Oleksandr Savchenko
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Julian A Luetkens
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Ulrike Attenberger
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Claus C Pieper
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
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Zhong M, Yang Z, Chen X, Huang R, Wang M, Fan W, Dai Z, Chen X. Readout-Segmented Echo-Planar Diffusion-Weighted MR Imaging Improves the Differentiation of Breast Cancer Receptor Statuses Compared With Conventional Diffusion-Weighted Imaging. J Magn Reson Imaging 2022; 56:691-699. [PMID: 35038210 PMCID: PMC9542110 DOI: 10.1002/jmri.28065] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/04/2022] [Accepted: 01/05/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Readout-segmented echo-planar diffusion-weighted imaging (RS-EPI) can improve image quality and signal-to-noise ratio, the resulting apparent diffusion coefficient (ADC) value acts as a more sensitive biomarker to characterize tumors. However, data regarding the differentiation of breast cancer (BC) receptor statuses using RS-EPI are limited. PURPOSE To determine whether RS-EPI improves the differentiation of receptor statuses compared with conventional single-shot (SS) EPI in breast MRI. STUDY TYPE Retrospective. POPULATION A total of 151 BC women with the mean age of 50.6 years. FIELD STRENGTH/SEQUENCE A 3 T/ RS-EPI and SS-EPI. ASSESSMENT The ADCs of the lesion and normal background tissue from the two sequences were collected by two radiologists with 15 years of experience working of breast MRI (M.H.Z. and X.F.C.), and a normalized ADC was calculated by dividing the mean ADC value of the lesion by the mean ADC value of the normal background tissue. STATISTICAL TESTS Agreement between the ADC measurements from the two sequences was assessed using the Pearson correlation coefficient and Bland-Altman plots. One-way analysis of variance, Kruskal-Wallis test, and median difference were used to compare the ADC measurements for all lesions and different receptor statuses. A P value less than 0.05 indicated a significant result. RESULTS The ADC measurements of all lesions and normal background tissues were significantly higher on RS-EPI than on SS-EPI (1.82 ± 0.33 vs. 1.55 ± 0.30 and 0.83 ± 0.11 vs. 0.79 ± 0.10). The normalized ADC was lower on RS-EPI than on SS-EPI (0.47 ± 0.11 vs. 0.53 ± 0.12, a median difference of -0.04 [95% CI: -0.256 to 0.111]). For both diffusion methods, only the ADC measurement of RS-EPI was higher for human epidermal growth factor receptor-2 (HER-2)-positive tumors than for HER-2-negative tumors (0.87 ± 0.10 vs. 0.81 ± 0.11), and this measurement was associated with HER-2 positive status (adjusted odds ratio [OR] = 654.4); however, similar results were not observed for the ADC measurement of SS-EPI (0.80 ± 0.10 vs. 0.78 ± 0.11 with P = 0.199 and adjusted OR = 0.21 with P = 0.464, respectively). DATA CONCLUSION RS-EPI can improve the distinction between HER-2-positive and HER-2-negative breast cancer, complementing the clinical application of diffusion imaging. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Minghao Zhong
- Department of Radiology, Meizhou People's HospitalMeizhou514031China
| | - Zhiqi Yang
- Department of Radiology, Meizhou People's Hospital, Meizhou, 514031 China
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, 514031 China
| | - Xiaofeng Chen
- Department of Radiology, Meizhou People's HospitalMeizhou514031China
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka PopulationMeizhou514031China
| | - Ruibin Huang
- Department of RadiologyFirst Affiliated Hospital of Shantou University Medical CollegeShantou515000China
| | - Mengzhu Wang
- MR Scientific Marketing, Siemens HealthineersGuangzhou510620China
| | - Weixiong Fan
- Department of Radiology, Meizhou People's HospitalMeizhou514031China
| | - Zhuozhi Dai
- Department of Radiology, Shantou Central Hospital, Shantou, Guangdong, 515041 China
| | - Xiangguang Chen
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, 514031 China
- Department of Radiology, Meizhou People's Hospital, Meizhou, 514031 China
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Can DWI provide additional value to Kaiser score in evaluation of breast lesions. Eur Radiol 2022; 32:5964-5973. [PMID: 35357535 DOI: 10.1007/s00330-022-08674-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 05/28/2021] [Accepted: 06/07/2021] [Indexed: 01/19/2023]
Abstract
OBJECTIVES To explore added value of diffusion-weighted imaging (DWI) as an adjunct to Kaiser score (KS) for differentiation of benign from malignant lesions on breast magnetic resonance imaging (MRI). METHODS Two hundred forty-six patients with 273 lesions (155 malignancies) were included in this retrospective study from January 2015 to December 2019. All lesions were proved by pathology. Two radiologists blind to pathological results evaluated lesions according to KS. Lesions with score > 4 were considered malignant. Four thresholds of ADC values -1.3 × 10-3mm2/s, 1.4 × 10-3mm2/s, 1.53 × 10-3mm2/s, and 1.6 × 10-3mm2/s were used to distinguish benign from malignant lesions. For combined diagnosis, a lesion with KS > 4 and ADC values below the preset cutoffs was considered as malignant; otherwise, it was benign. Sensitivity, specificity, and area under the curve (AUC) were compared between KS, DWI, and combined diagnosis. RESULTS The AUC of KS was significantly higher than that of DWI alone (0.941 vs 0.901, p = 0.04). The sensitivity of KS (96.8%) and DWI (97.4 - 99.4%) was comparable (p > 0.05) while the specificity of KS (83.9%) was significantly higher than that of DWI (19.5-56.8%) (p < 0.05). Adding DWI as an adjunct to KS resulted in a 0-2.5% increase of specificity and a 0.1-1.3% decrease of sensitivity; however, the difference did not reach statistical significance (p > 0.05). CONCLUSION KS showed higher diagnostic performance than DWI alone for discrimination of breast benign and malignant lesions. DWI showed no additional value to KS for characterizing breast lesions. KEY POINTS • KS showed higher diagnostic performance than DWI alone for differentiation of benign from breast malignant lesions. • DWI alone showed a high sensitivity but a low specificity for characterizing breast lesions. • Diagnostic performance did not improve using DWI as an adjunct to KS.
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Zang H, Liu HL, Zhu LY, Wang X, Wei LM, Lou JJ, Zou QG, Wang SQ, Wang SJ, Jiang YN. Diagnostic performance of DCE-MRI, multiparametric MRI and multimodality imaging for discrimination of breast non-mass-like enhancement lesions. Br J Radiol 2022; 95:20220211. [PMID: 35522775 PMCID: PMC10162064 DOI: 10.1259/bjr.20220211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 04/18/2022] [Accepted: 04/29/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE The aim of this study was to investigate and compare the diagnostic performance of dynamic contrast-enhanced (DCE)-MRI, multiparametric MRI (mpMRI), and multimodality imaging (MMI) combining mpMRI and mammography (MG) for discriminating breast non-mass-like enhancement (NME) lesions. METHODS This retrospective study enrolled 193 patients with 199 lesions who underwent 3.0 T MRI and MG from January 2017 to December 2019. The features of DCE-MRI, turbo inversion recovery magnitude (TIRM), and diffusion-weighted imaging (DWI) were assessed by two breast radiologists. Then, all lesions were divided into microcalcification and non-microcalcification groups to assess the features of MG. Comparisons were performed between groups using univariate analyses. Then, multivariate analyses were performed to construct diagnostic models for distinguishing NME lesions. Diagnostic performance was evaluated by using the area under the curve (AUC) and the differences between AUCs were evaluated by using the DeLong test. RESULTS Overall (n = 199), mpMRI outperformed DCE-MRI alone (AUCmpMRI = 0.924 vs. AUCDCE-MRI = 0.884; p = 0.007). Furthermore, MMI outperformed both mpMRI and MG (the microcalcification group [n = 140]: AUCMMI = 0.997 vs. AUCmpMRI = 0.978, p = 0.018 and AUCMMI = 0.997 vs. AUCMG = 0.912, p < 0.001; the non-microcalcification group [n = 59]: AUCMMI = 0.857 vs. AUCmpMRI = 0.768, p = 0.044 and AUCMMI = 0.857 vs. AUCMG = 0.759, p = 0.039). CONCLUSION & ADVANCES IN KNOWLEDGE DCE-MRI combined with DWI and TIRM information could improve the diagnostic performance for discriminating NME lesions compared with DCE-MRI alone. Furthermore, MMI combining mpMRI and MG showed better discrimination than both mpMRI and MG.
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Affiliation(s)
- Hui Zang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, China
| | - Hong-li Liu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, China
| | - Li-yu Zhu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, China
| | - Xiao Wang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, China
| | - Liang-min Wei
- Department of Biostatistics, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Jiangning District, Nanjing, China
| | - Jian-juan Lou
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, China
| | - Qi-gui Zou
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, China
| | - Si-qi Wang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, China
| | - Shou-ju Wang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, China
| | - Yan-ni Jiang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, China
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Mendez AM, Fang LK, Meriwether CH, Batasin SJ, Loubrie S, Rodríguez-Soto AE, Rakow-Penner RA. Diffusion Breast MRI: Current Standard and Emerging Techniques. Front Oncol 2022; 12:844790. [PMID: 35880168 PMCID: PMC9307963 DOI: 10.3389/fonc.2022.844790] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics.
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Affiliation(s)
- Ashley M. Mendez
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Lauren K. Fang
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Claire H. Meriwether
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Summer J. Batasin
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Stéphane Loubrie
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Ana E. Rodríguez-Soto
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Rebecca A. Rakow-Penner
- Department of Radiology, University of California San Diego, La Jolla, CA, United States,Department of Bioengineering, University of California San Diego, La Jolla, CA, United States,*Correspondence: Rebecca A. Rakow-Penner,
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Lv W, Zheng D, Guan W, Wu P. Contribution of Diffusion-Weighted Imaging and ADC Values to Papillary Breast Lesions. Front Oncol 2022; 12:911790. [PMID: 35847891 PMCID: PMC9279724 DOI: 10.3389/fonc.2022.911790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Accepted: 05/31/2022] [Indexed: 11/13/2022] Open
Abstract
This study aimed to evaluate the role of apparent diffusion coefficient (ADC) values obtained from diffusion-weighted imaging (DWI) in the differentiation of malignant from benign papillary breast lesions. The magnetic resonance imaging (MRI) data of 94 breast papillary lesions confirmed by pathology were retrospectively analyzed. The differences in ADC values of papillary lesions under different enhancements in MRI and different pathological types were investigated, and the ADC threshold was determined by the receiver operating characteristic curve for its potential diagnostic value. The mean ADC values in borderline and malignant lesions (1.01 ± 0.20 × 10-3 mm2/s) were significantly lower compared to benign lesions (1.21 ± 0.27 × 10-3 mm2/s) (P < 0.05). The optimal threshold of the ADC value could be 1.00 × 10-3 mm2/s. The ADC values were statistically significant in differentiating between benign and malignant papillary lesions whether in mass or non-mass enhancement (P < 0.05). However, there were no statistical differences in the ADC values among borderline or any other histological subtypes of malignant lesions (P > 0.05). Measuring ADC values from DWI can be used to identify benign and malignant breast papillary lesions. The diagnostic performance of the ADC value in identifying benign and malignant breast lesions is not affected by the way of lesion enhancement. However, it shows no use for differential diagnosis among malignant lesion subtypes for now. The ADC value of 1.00 × 10-3 mm2/s can be used as the most appropriate threshold for distinguishing between benign and malignant breast papillary lesions.
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Affiliation(s)
- Wenjie Lv
- Department of Breast Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dawen Zheng
- Department of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenbin Guan
- Department of Pathology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ping Wu
- Department of Breast Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Ping Wu,
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21
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Le NN, Li W, Onishi N, Newitt DC, Gibbs JE, Wilmes LJ, Kornak J, Partridge SC, LeStage B, Price ER, Joe BN, Esserman LJ, Hylton NM. Effect of Inter-Reader Variability on Diffusion-Weighted MRI Apparent Diffusion Coefficient Measurements and Prediction of Pathologic Complete Response for Breast Cancer. Tomography 2022; 8:1208-1220. [PMID: 35645385 PMCID: PMC9149942 DOI: 10.3390/tomography8030099] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/13/2022] [Accepted: 04/15/2022] [Indexed: 11/16/2022] Open
Abstract
This study evaluated the inter-reader agreement of tumor apparent diffusion coefficient (ADC) measurements performed on breast diffusion-weighted imaging (DWI) for assessing treatment response in a multi-center clinical trial of neoadjuvant chemotherapy (NAC) for breast cancer. DWIs from 103 breast cancer patients (mean age: 46 ± 11 years) acquired at baseline and after 3 weeks of treatment were evaluated independently by two readers. Three types of tumor regions of interests (ROIs) were delineated: multiple-slice restricted, single-slice restricted and single-slice tumor ROIs. Compared to tumor ROIs, restricted ROIs were limited to low ADC areas of enhancing tumor only. We found excellent agreement (intraclass correlation coefficient [ICC] ranged from 0.94 to 0.98) for mean ADC. Higher ICCs were observed in multiple-slice restricted ROIs (range: 0.97 to 0.98) than in other two ROI types (both in the range of 0.94 to 0.98). Among the three ROI types, the highest area under the receiver operating characteristic curves (AUCs) were observed for mean ADC of multiple-slice restricted ROIs (0.65, 95% confidence interval [CI]: 0.52–0.79 and 0.67, 95% CI: 0.53–0.81 for Reader 1 and Reader 2, respectively). In conclusion, mean ADC values of multiple-slice restricted ROI showed excellent agreement and similar predictive performance for pathologic complete response between the two readers.
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Affiliation(s)
- Nu N. Le
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94158, USA; (N.N.L.); (N.O.); (D.C.N.); (J.E.G.); (L.J.W.); (E.R.P.); (B.N.J.); (N.M.H.)
| | - Wen Li
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94158, USA; (N.N.L.); (N.O.); (D.C.N.); (J.E.G.); (L.J.W.); (E.R.P.); (B.N.J.); (N.M.H.)
- Correspondence:
| | - Natsuko Onishi
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94158, USA; (N.N.L.); (N.O.); (D.C.N.); (J.E.G.); (L.J.W.); (E.R.P.); (B.N.J.); (N.M.H.)
| | - David C. Newitt
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94158, USA; (N.N.L.); (N.O.); (D.C.N.); (J.E.G.); (L.J.W.); (E.R.P.); (B.N.J.); (N.M.H.)
| | - Jessica E. Gibbs
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94158, USA; (N.N.L.); (N.O.); (D.C.N.); (J.E.G.); (L.J.W.); (E.R.P.); (B.N.J.); (N.M.H.)
| | - Lisa J. Wilmes
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94158, USA; (N.N.L.); (N.O.); (D.C.N.); (J.E.G.); (L.J.W.); (E.R.P.); (B.N.J.); (N.M.H.)
| | - John Kornak
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA;
| | | | | | - Elissa R. Price
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94158, USA; (N.N.L.); (N.O.); (D.C.N.); (J.E.G.); (L.J.W.); (E.R.P.); (B.N.J.); (N.M.H.)
| | - Bonnie N. Joe
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94158, USA; (N.N.L.); (N.O.); (D.C.N.); (J.E.G.); (L.J.W.); (E.R.P.); (B.N.J.); (N.M.H.)
| | - Laura J. Esserman
- Department of Surgery and Radiology, University of California, San Francisco, CA 94143, USA;
| | - Nola M. Hylton
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94158, USA; (N.N.L.); (N.O.); (D.C.N.); (J.E.G.); (L.J.W.); (E.R.P.); (B.N.J.); (N.M.H.)
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22
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Geng X, Zhang D, Suo S, Chen J, Cheng F, Zhang K, Zhang Q, Li L, Lu Y, Hua J, Zhuang Z. Using the apparent diffusion coefficient histogram analysis to predict response to neoadjuvant chemotherapy in patients with breast cancer: comparison among three region of interest selection methods. ANNALS OF TRANSLATIONAL MEDICINE 2022; 10:323. [PMID: 35433990 PMCID: PMC9011214 DOI: 10.21037/atm-22-1078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 03/18/2022] [Indexed: 11/06/2022]
Abstract
Background The apparent diffusion coefficient (ADC) value using histogram analysis is helpful to predict responses to neoadjuvant chemotherapy (NAC) in breast cancer. However, the measurement method has not reached a consensus. This study was to assess the diagnostic performance of the ADC histogram analysis at predicting patient response prior to NAC in breast cancer patients using different region of interest (ROI) selection methods. Methods A total of 75 patients who underwent diffusion weighted imaging (DWI) prior to NAC were retrospectively enrolled from February 2017 to December 2019. Images were measured using small 2-dimensional (2D) ROI, large 2D ROI, and volume ROI methods. The measurement time and ROI size were recorded. Histopathologic responses were acquired using the Miller-Payne grading system after surgery. The inter- and intra-observer repeatability was analyzed and the ADC histogram values from the three ROI methods were compared. The efficacy of each method at predicting patient response prior to NAC was assessed using the area under the receiver operating characteristic curve (AUC) for the whole study population and subgroups according to molecular subtype. Results Among the 75 enrolled patients, 26 (34.67%) were responsive to NAC therapy. The ADC histogram values were significantly different among the three ROI methods (P≤0.038). Inter- and intra-observer repeatability of the large 2D ROI method and the volume ROI method was generally greater than that observed with the 2D ROI method. The 10% ADC value of the large 2D ROI method showed the greatest AUC (0.701) in the whole study population and in the luminal subgroup (AUC 0.804). The volume ROI method required significantly more time than the other two ROI methods (P<0.001). Conclusions The small 2D ROI method is not appropriate for predicting response prior to NAC in breast cancer patients due to the poor repeatability. When choosing the ROI method and the histogram parameters for predicting response prior to NAC in breast cancer patients using ADC-derived histogram analysis, 10% of the large 2D ROI method is recommended, especially in luminal A subtype patients.
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Affiliation(s)
- Xiaochuan Geng
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dandan Zhang
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shiteng Suo
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Chen
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fang Cheng
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kebei Zhang
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qing Zhang
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lan Li
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yang Lu
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jia Hua
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiguo Zhuang
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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23
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Jeong S, Kim TH. Diffusion-weighted imaging of breast invasive lobular carcinoma: comparison with invasive carcinoma of no special type using a histogram analysis. Quant Imaging Med Surg 2022; 12:95-105. [PMID: 34993063 DOI: 10.21037/qims-21-355] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 06/03/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND To investigate the imaging findings and visibility of breast invasive lobular carcinoma (ILC) on diffusion-weighted imaging (DWI) and compare quantitative apparent diffusion coefficient (ADC) metrics of ILC and invasive carcinoma of no special type (NST) using a histogram analysis. METHODS We performed an observational retrospective study of 629 consecutive women with pathologically proven ILC and invasive ductal carcinoma of NST, who underwent 3-T MRI including DWI, between January 2017 and August 2020. RESULTS After propensity score matching, 71 women were allocated to each group. On DWI, 9 (12.7%) lesions of ILC and 4 (5.6%) invasive carcinomas of the NST were not visualized. For the tumor visibility on DWI, tumor size, tumor ADC value, and background diffusion grade were significantly associated with the visibility score in both groups (all P<0.05), whereas the mean background ADC value was not significant (P>0.05). The mean ADC (1.226×10-3 vs. 1.052×10-3 mm2/s, P<0.001), median ADC (1.222×10-3 vs. 1.051×10-3 mm2/s, P=0.002), maximum ADC (1.758×10-3 vs. 1.504×10-3 mm2/s, P<0.001), minimum ADC (0.717×10-3 vs. 0.649×10-3 mm2/s, P=0.003), 90th percentile ADC (1.506×10-3 vs. 1.292×10-3 mm2/s, P<0.001) and 10th percentile ADC (0.956×10-3 vs. 0.818×10-3 mm2/s, P=0.008) were higher in ILC than in invasive carcinoma of NST. Additionally, the ADC difference value of the ILC was higher than that of invasive carcinoma of NST (1.04×10-3 vs. 0.855×10-3 mm2/s, P=0.027). CONCLUSIONS On DWI, the visibility of ILC was lower compared to invasive carcinoma of NST. ILC showed higher quantitative ADC values and higher ADC difference values.
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Affiliation(s)
- Seongkyun Jeong
- Department of Human Intelligence Robot Engineering, Sangmyung University, Cheonan, Republic of Korea
| | - Tae Hee Kim
- Department of Radiology, Ajou University School of Medicine and Graduate School of Medicine, Suwon, Republic of Korea
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24
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Meng L, Zhao X, Lu L, Xing Q, Wang K, Guo Y, Shang H, Chen Y, Huang M, Sun Y, Zhang X. A Comparative Assessment of MR BI-RADS 4 Breast Lesions With Kaiser Score and Apparent Diffusion Coefficient Value. Front Oncol 2021; 11:779642. [PMID: 34926290 PMCID: PMC8675081 DOI: 10.3389/fonc.2021.779642] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 11/10/2021] [Indexed: 12/24/2022] Open
Abstract
Objectives To investigate the diagnostic performance of the Kaiser score and apparent diffusion coefficient (ADC) to differentiate Breast Imaging Reporting and Data System (BI-RADS) Category 4 lesions at dynamic contrast-enhanced (DCE) MRI. Methods This was a single-institution retrospective study of patients who underwent breast MRI from March 2020 to June 2021. All image data were acquired with a 3-T MRI system. Kaiser score of each lesion was assigned by an experienced breast radiologist. Kaiser score+ was determined by combining ADC and Kaiser score. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of Kaiser score+, Kaiser score, and ADC. The area under the curve (AUC) values were calculated and compared by using the Delong test. The differences in sensitivity and specificity between different indicators were determined by the McNemar test. Results The study involved 243 women (mean age, 43.1 years; age range, 18-67 years) with 268 MR BI-RADS 4 lesions. Overall diagnostic performance for Kaiser score (AUC, 0.902) was significantly higher than for ADC (AUC, 0.81; p = 0.004). There were no significant differences in AUCs between Kaiser score and Kaiser score+ (p = 0.134). The Kaiser score was superior to ADC in avoiding unnecessary biopsies (p < 0.001). Compared with the Kaiser score alone, the specificity of Kaiser score+ increased by 7.82%, however, at the price of a lower sensitivity. Conclusion For MR BI-RADS category 4 breast lesions, the Kaiser score was superior to ADC mapping regarding the potential to avoid unnecessary biopsies. However, the combination of both indicators did not significantly contribute to breast cancer diagnosis of this subgroup.
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Affiliation(s)
- Lingsong Meng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lin Lu
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qingna Xing
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kaiyu Wang
- Magnetic Resonance (MR) Research China, General Electric (GE) Healthcare, Beijing, China
| | - Yafei Guo
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Honglei Shang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yan Chen
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mengyue Huang
- Department of Magnetic Resonance Imaging (MRI), The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yongbing Sun
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoan Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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25
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van der Hoogt KJJ, Schipper RJ, Winter-Warnars GA, Ter Beek LC, Loo CE, Mann RM, Beets-Tan RGH. Factors affecting the value of diffusion-weighted imaging for identifying breast cancer patients with pathological complete response on neoadjuvant systemic therapy: a systematic review. Insights Imaging 2021; 12:187. [PMID: 34921645 PMCID: PMC8684570 DOI: 10.1186/s13244-021-01123-1] [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: 10/14/2021] [Accepted: 11/06/2021] [Indexed: 12/18/2022] Open
Abstract
This review aims to identify factors causing heterogeneity in breast DWI-MRI and their impact on its value for identifying breast cancer patients with pathological complete response (pCR) on neoadjuvant systemic therapy (NST). A search was performed on PubMed until April 2020 for studies analyzing DWI for identifying breast cancer patients with pCR on NST. Technical and clinical study aspects were extracted and assessed for variability. Twenty studies representing 1455 patients/lesions were included. The studies differed with respect to study population, treatment type, DWI acquisition technique, post-processing (e.g., mono-exponential/intravoxel incoherent motion/stretched exponential modeling), and timing of follow-up studies. For the acquisition and generation of ADC-maps, various b-value combinations were used. Approaches for drawing regions of interest on longitudinal MRIs were highly variable. Biological variability due to various molecular subtypes was usually not taken into account. Moreover, definitions of pCR varied. The individual areas under the curve for the studies range from 0.50 to 0.92. However, overlapping ranges of mean/median ADC-values at pre- and/or during and/or post-NST were found for the pCR and non-pCR groups between studies. The technical, clinical, and epidemiological heterogeneity may be causal for the observed variability in the ability of DWI to predict pCR accurately. This makes implementation of DWI for pCR prediction and evaluation based on one absolute ADC threshold for all breast cancer types undesirable. Multidisciplinary consensus and appropriate clinical study design, taking biological and therapeutic variation into account, is required for obtaining standardized, reliable, and reproducible DWI measurements for pCR/non-pCR identification.
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Affiliation(s)
- Kay J J van der Hoogt
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands. .,GROW School of Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands.
| | - Robert J Schipper
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Gonneke A Winter-Warnars
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Leon C Ter Beek
- Department of Medical Physics, The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Amsterdam, The Netherlands
| | - Claudette E Loo
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Ritse M Mann
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,GROW School of Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands.,Danish Colorectal Cancer Unit South, Institute of Regional Health Research, Vejle University Hospital, University of Southern Denmark, Odense, Denmark
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Prakash S, Sangeetha K. An Early Breast Cancer Detection System Using Recurrent Neural Network (RNN) with Animal Migration Optimization (AMO) Based Classification Method. JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS 2021. [DOI: 10.1166/jmihi.2021.3885] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Breast cancer can be detected using early signs of it mammograms and digital mammography. For Computer Aided Detection (CAD), algorithms can be developed using this opportunities. Early detection is assisted by self-test and periodical check-ups and it can enhance the survival chance
significantly. Due the need of breast cancer’s early detection and false diagnosis impact on patients, made researchers to investigate Deep Learning (DL) techniques for mammograms. So, it requires a non-invasive cancer detection system, which is highly effective, accurate, fast as well
as robust. Proposed work has three steps, (i) Pre-processing, (ii) Segmentation, and (iii) Classification. Firstly, preprocessing stage removing noise from images by using mean and median filtering algorithms are used, while keeping its features intact for better understanding and recognition,
then edge detection by using canny edge detector. It uses Gaussian filter for smoothening image. Gaussian smoothening is used for enhancing image analysis process quality, result in blurring of fine-scaled image edges. In the next stage, image representation is changed into something, which
makes analyses process as a simple one. Foreground and background subtraction is used for accurate breast image detection in segmentation. After completion of segmentation stage, the remove unwanted image in input image dataset. Finally, a novel RNN forclassifying and detecting breast cancer
using Auto Encoder (AE) based RNN for feature extraction by integrating Animal Migration Optimization (AMO) for tuning the parameters of RNN model, then softmax classifier use RNN algorithm. Experimental results are conducted using Mini-Mammographic (MIAS) dataset of breast cancer. The classifiers
are measured through measures like precision, recall, f-measure and accuracy.
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Affiliation(s)
- S. Prakash
- Computer Science and Engineering Department, Sri Shakthi Institute of Engineering and Technology, Coimbatore 641062, Tamil Nadu, India
| | - K. Sangeetha
- Computer Science and Engineering Department, SNS College of Technology, Coimbatore 641035, India
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Comparison of different ROI analysis methods for liver lesion characterization with simplified intravoxel incoherent motion (IVIM). Sci Rep 2021; 11:22752. [PMID: 34815436 PMCID: PMC8610969 DOI: 10.1038/s41598-021-01108-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 10/08/2021] [Indexed: 01/20/2023] Open
Abstract
This study investigated the impact of different ROI placement and analysis methods on the diagnostic performance of simplified IVIM-DWI for differentiating liver lesions. 1.5/3.0-T DWI data from a respiratory-gated MRI sequence (b = 0, 50, 250, 800 s/mm2) were analyzed in patients with malignant (n = 74/54) and benign (n = 35/19) lesions. Apparent diffusion coefficient ADC = ADC(0,800) and IVIM parameters D1' = ADC(50,800), D2' = ADC(250,800), f1' = f(0,50,800), f2' = f(0,250,800), and D*' = D*(0,50,250,800) were calculated voxel-wise. For each lesion, a representative 2D-ROI, a 3D-ROI whole lesion, and a 3D-ROI from "good" slices were placed, including and excluding centrally deviating areas (CDA) if present, and analyzed with various histogram metrics. The diagnostic performance of 2D- and 3D-ROIs was not significantly different; e.g. AUC (ADC/D1'/f1') were 0.958/0.902/0.622 for 2D- and 0.942/0.892/0.712 for whole lesion 3D-ROIs excluding CDA at 1.5 T (p > 0.05). For 2D- and 3D-ROIs, AUC (ADC/D1'/D2') were significantly higher, when CDA were excluded. With CDA included, AUC (ADC/D1'/D2'/f1'/D*') improved when low percentiles were used instead of averages, and was then comparable to the results of average ROI analysis excluding CDA. For lesion differentiation the use of a representative 2D-ROI is sufficient. CDA should be excluded from ROIs by hand or automatically using low percentiles of diffusion coefficients.
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28
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Kapetas P, Clauser P, Milos RI, Vigano S, Bernathova M, Helbich TH, Baltzer PAT. Microstructural breast tissue characterization: A head-to-head comparison of Diffusion Weighted Imaging and Acoustic Radiation Force Impulse elastography with clinical implications. Eur J Radiol 2021; 143:109926. [PMID: 34438330 DOI: 10.1016/j.ejrad.2021.109926] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 08/12/2021] [Accepted: 08/14/2021] [Indexed: 01/08/2023]
Abstract
PURPOSE Head-to-head comparison of Diffusion Weighted Imaging (DWI) and Acoustic Radiation Force Impulse (ARFI) elastography regarding the characterization of breast lesions in an assessment setting. METHOD Patients undergoing an ultrasound examination including ARFI and an MRI protocol including DWI for the characterization of a BI-RADS 3-5 breast lesion between 06/2013 and 10/2016 were eligible for inclusion in this retrospective, IRB-approved study. 60 patients (30-84 years, median 50) with a median lesion size of 16 mm (range 5-55 mm) were included. The maximum shear wave velocity (SWVmax) and mean apparent diffusion coefficient (ADCmean) for each lesion were retrospectively evaluated by a radiologist experienced in the technique. Histology was the reference standard. Diagnostic performances of ARFI and DWI were assessed using ROC curve analysis. Spearman's rank correlation coefficient and multivariate logistic regression were used to investigate the independence of both tests regarding their diagnostic information to distinguish benign from malignant lesions. RESULTS Corresponding areas under the ROC curve for differentiation of benign (n = 16) and malignant (n = 49) lesions were 0.822 (ARFI) and 0.871 (DWI, p-value = 0.48). SWVmax and ADCmean values showed a significant negative correlation (ρ = -0.501, p-value < 0.001). In multivariate analysis, combination of ARFI and DWI did not improve the results of each single modality, thus no significant independent diagnostic information was present. CONCLUSION Significant correlation between quantitative findings of ARFI and DWI in breast lesions exists. Thus, ARFI provides similar diagnostic information as a DWI-including protocol of an additional "problem-solving" MRI for the characterization of a sonographically evident breast lesion, improving the immediate patient management in the assessment setting.
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Affiliation(s)
- Panagiotis Kapetas
- Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Waehringer Guertel 18-20, 1090 Vienna, Austria.
| | - Paola Clauser
- Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Waehringer Guertel 18-20, 1090 Vienna, Austria.
| | - Ruxandra-Iulia Milos
- Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Waehringer Guertel 18-20, 1090 Vienna, Austria.
| | - Sara Vigano
- Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via della Commenda 10, 20122 Milan, Italy
| | - Maria Bernathova
- Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Waehringer Guertel 18-20, 1090 Vienna, Austria.
| | - Thomas H Helbich
- Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Waehringer Guertel 18-20, 1090 Vienna, Austria.
| | - Pascal A T Baltzer
- Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Waehringer Guertel 18-20, 1090 Vienna, Austria.
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Wang H, van der Velden BHM, Ragusi MAA, Veldhuis WB, Viergever MA, Verburg E, Gilhuijs KGA. Toward Computer-Assisted Triaging of Magnetic Resonance Imaging-Guided Biopsy in Preoperative Breast Cancer Patients. Invest Radiol 2021; 56:442-449. [PMID: 33851810 DOI: 10.1097/rli.0000000000000759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Incidental MR-detected breast lesions (ie, additional lesions to the index cancer) pose challenges in the preoperative workup of patients with early breast cancer. We pursue computer-assisted triaging of magnetic resonance imaging (MRI)-guided breast biopsy of additional lesions at high specificity. MATERIALS AND METHODS We investigated 316 consecutive female patients (aged 26 to 76 years; mean, 54 years) with early breast cancer who received preoperative multiparametric breast MRI between 2013 and 2016. In total, 82 (26%) of 316 patients had additional breast lesions on MRI. These 82 patients had 101 additional lesions in total, 51 were benign and 50 were malignant. We collected 4 clinical features and 46 MRI radiomic features from T1-weighted dynamic contrast-enhanced imaging, high-temporal-resolution dynamic contrast-enhanced imaging, T2-weighted imaging, and diffusion-weighted imaging. A multiparametric computer-aided diagnosis (CAD) model using 10-fold cross-validated ridge regression was constructed. The sensitivities were calculated at operating points corresponding to 98%, 95%, and 90% specificity. The model calibration performance was evaluated by calibration plot analysis and goodness-of-fit tests. The model was tested in an independent testing cohort of 187 consecutive patients from 2017 and 2018 (aged 35 to 76 years; mean, 59 years). In this testing cohort, 45 (24%) of 187 patients had 55 additional breast lesions in total, 23 were benign and 32 were malignant. RESULTS The multiparametric CAD model correctly identified 48% of the malignant additional lesions with a specificity of 98%. At specificity 95% and 90%, the sensitivity was 62% and 72%, respectively. Calibration plot analysis and goodness-of-fit tests indicated that the model was well fitted.In the independent testing cohort, the specificity was 96% and the sensitivity 44% at the 98% specificity operating point of the training set. At operating points 95% and 90%, the specificity was 83% at 69% sensitivity and the specificity was 78% at 81% sensitivity, respectively. CONCLUSIONS The multiparametric CAD model showed potential to identify malignant disease extension with near-perfect specificity in approximately half the population of preoperative patients originally indicated for a breast biopsy. In the other half, patients would still proceed to MRI-guided biopsy to confirm absence of malignant disease. These findings demonstrate the potential to triage MRI-guided breast biopsy.
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Affiliation(s)
- Hui Wang
- From the Image Sciences Institute
| | | | | | - Wouter B Veldhuis
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
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Dietzel M, Krug B, Clauser P, Burke C, Hellmich M, Maintz D, Uder M, Bickel H, Helbich T, Baltzer PAT. A Multicentric Comparison of Apparent Diffusion Coefficient Mapping and the Kaiser Score in the Assessment of Breast Lesions. Invest Radiol 2021; 56:274-282. [PMID: 33122603 DOI: 10.1097/rli.0000000000000739] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
MATERIALS AND METHODS In this multicentric study, individual patient data from 3 different centers were analyzed. Consecutive patients receiving standardized multiparametric breast magnetic resonance imaging for standard nonscreening indications were included. At each center, 2 experienced radiologists with more than 5 years of experience retrospectively interpreted the examinations in consensus and applied the KS to every histologically verified lesion. The corresponding mean ADC of each lesion was measured using a Wielema type 4 region of interest. According to established methods, the KS and ADC were combined, yielding the KS+ score. Diagnostic accuracy was evaluated by the area under the receiver operating characteristics curve (AUROC) and compared between the KS, ADC, and KS+ (DeLong test). Likewise, the potential to help avoid unnecessary biopsies was compared between the KS, ADC, and KS+ based on established high sensitivity thresholds (McNemar test). RESULTS A total of 450 lesions in 414 patients (mean age, 51.5 years; interquartile range, 42-60.8 years) were included, with 219 lesions being malignant (48.7%; 95% confidence interval [CI], 44%-53.4%). The performance of the KS (AUROC, 0.915; CI, 0.886-0.939) was significantly better than that of the ADC (AUROC, 0.848; CI, 0.811-0.880; P < 0.001). The largest difference between these parameters was observed when assessing subcentimeter lesions (AUROC, 0.909 for KS; CI, 0.849-0.950 vs 0.811 for ADC; CI, 0.737-0.871; P = 0.02).The use of the KS+ (AUROC, 0.918; CI, 0.889-0.942) improved the performance slightly, but without any significant difference relative to a single KS or ADC reading (P = 0.64).When applying high sensitivity thresholds for avoiding unnecessary biopsies, the KS and ADC achieved equal sensitivity (97.7% for both; cutoff values, >4 for KS and ≤1.4 × 10-3 mm2/s for ADC). However, the rate of potentially avoidable biopsies was higher when using the KS (specificity: 65.4% for KS vs 32.9% for ADC; P < 0.0001). The KS was superior to the KS+ in avoiding unnecessary biopsies. CONCLUSIONS Both the KS and ADC may be used to distinguish benign from malignant breast lesions. However, KS proved superior in this task including, most of all, when assessing small lesions less than 1 cm. Using the KS may avoid twice as many unnecessary biopsies, and the combination of both the KS and ADS does not improve diagnostic performance.
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Affiliation(s)
- Matthias Dietzel
- From the Department of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Barbara Krug
- Department of Diagnostic and Interventional Radiology, University Hospital Cologne
| | - Paola Clauser
- Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Christina Burke
- Department of Diagnostic and Interventional Radiology, University Hospital Cologne
| | - Martin Hellmich
- Institute of Medical Statistics and Bioinformatics, University Cologne, Cologne, Germany
| | - David Maintz
- Department of Diagnostic and Interventional Radiology, University Hospital Cologne
| | - Michael Uder
- From the Department of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Hubert Bickel
- Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Thomas Helbich
- Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Pascal A T Baltzer
- Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
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Suh J, Kim JH, Kim SY, Cho N, Kim DH, Kim R, Kim ES, Jang MJ, Ha SM, Lee SH, Chang JM, Moon WK. Noncontrast-Enhanced MR-Based Conductivity Imaging for Breast Cancer Detection and Lesion Differentiation. J Magn Reson Imaging 2021; 54:631-645. [PMID: 33894088 DOI: 10.1002/jmri.27655] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 04/01/2021] [Accepted: 04/01/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND There is increasing interest in noncontrast-enhanced MRI due to safety concerns for gadolinium contrast agents. PURPOSE To investigate the clinical feasibility of MR-based conductivity imaging for breast cancer detection and lesion differentiation. STUDY TYPE Prospective. SUBJECTS One hundred and ten women, with 112 known cancers and 17 benign lesions (biopsy-proven), scheduled for preoperative MRI. FIELD STRENGTH/SEQUENCE Non-fat-suppressed T2-weighted turbo spin-echo sequence (T2WI), dynamic contrast-enhanced MRI and diffusion-weighted imaging (DWI) at 3T. ASSESSMENT Cancer detectability on each imaging modality was qualitatively evaluated on a per-breast basis: the conductivity maps derived from T2WI were independently reviewed by three radiologists (R1-R3). T2WI, DWI, and pre-operative digital mammography were independently reviewed by three other radiologists (R4-R6). Conductivity and apparent diffusion coefficient (ADC) measurements (mean, minimum, and maximum) were performed for 112 cancers and 17 benign lesions independently by two radiologists (R1 and R2). Tumor size was measured from surgical specimens. STATISTICAL TESTS Cancer detection rates were compared using generalized estimating equations. Multivariable logistic regression analysis was performed to identify factors associated with cancer detectability. Discriminating ability of conductivity and ADC was evaluated by using the areas under the receiver operating characteristic curve (AUC). RESULTS Conductivity imaging showed lower cancer detection rates (20%-32%) compared to T2WI (62%-71%), DWI (85%-90%), and mammography (79%-88%) (all P < 0.05). Fatty breast on MRI (odds ratio = 11.8, P < 0.05) and invasive tumor size (odds ratio = 1.7, P < 0.05) were associated with cancer detectability of conductivity imaging. The maximum conductivity showed comparable ability to the mean ADC in discriminating between cancers and benign lesions (AUC = 0.67 [95% CI: 0.59, 0.75] vs. 0.84 [0.76, 0.90], P = 0.06 (R1); 0.65 [0.56, 0.73] vs. 0.82 [0.74, 0.88], P = 0.07 (R2)). DATA CONCLUSION Although conductivity imaging showed suboptimal performance in breast cancer detection, the quantitative measurement of conductivity showed the potential for lesion differentiation. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- June Suh
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jun-Hyeong Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Soo-Yeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Nariya Cho
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Rihyeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eun Sil Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Myoung-Jin Jang
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Su Min Ha
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jung Min Chang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
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Naranjo ID, Reymbaut A, Brynolfsson P, Lo Gullo R, Bryskhe K, Topgaard D, Giri DD, Reiner JS, Thakur SB, Pinker-Domenig K. Multidimensional Diffusion Magnetic Resonance Imaging for Characterization of Tissue Microstructure in Breast Cancer Patients: A Prospective Pilot Study. Cancers (Basel) 2021; 13:1606. [PMID: 33807205 PMCID: PMC8037718 DOI: 10.3390/cancers13071606] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 03/29/2021] [Indexed: 12/19/2022] Open
Abstract
Diffusion-weighted imaging is a non-invasive functional imaging modality for breast tumor characterization through apparent diffusion coefficients. Yet, it has so far been unable to intuitively inform on tissue microstructure. In this IRB-approved prospective study, we applied novel multidimensional diffusion (MDD) encoding across 16 patients with suspected breast cancer to evaluate its potential for tissue characterization in the clinical setting. Data acquired via custom MDD sequences was processed using an algorithm estimating non-parametric diffusion tensor distributions. The statistical descriptors of these distributions allow us to quantify tissue composition in terms of metrics informing on cell densities, shapes, and orientations. Additionally, signal fractions from specific cell types, such as elongated cells (bin1), isotropic cells (bin2), and free water (bin3), were teased apart. Histogram analysis in cancers and healthy breast tissue showed that cancers exhibited lower mean values of "size" (1.43 ± 0.54 × 10-3 mm2/s) and higher mean values of "shape" (0.47 ± 0.15) corresponding to bin1, while FGT (fibroglandular breast tissue) presented higher mean values of "size" (2.33 ± 0.22 × 10-3 mm2/s) and lower mean values of "shape" (0.27 ± 0.11) corresponding to bin3 (p < 0.001). Invasive carcinomas showed significant differences in mean signal fractions from bin1 (0.64 ± 0.13 vs. 0.4 ± 0.25) and bin3 (0.18 ± 0.08 vs. 0.42 ± 0.21) compared to ductal carcinomas in situ (DCIS) and invasive carcinomas with associated DCIS (p = 0.03). MDD enabled qualitative and quantitative evaluation of the composition of breast cancers and healthy glands.
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Affiliation(s)
- Isaac Daimiel Naranjo
- Memorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA; (I.D.N.); (R.L.G.); (J.S.R.); (S.B.T.)
- Department of Radiology, Breast Imaging Service, Guy’s and St. Thomas’ NHS Trust, Great Maze Pond, London SE1 9RT, UK
| | - Alexis Reymbaut
- Random Walk Imaging AB, SE-22002 Lund, Sweden; (A.R.); (P.B.); (K.B.)
| | - Patrik Brynolfsson
- Random Walk Imaging AB, SE-22002 Lund, Sweden; (A.R.); (P.B.); (K.B.)
- NONPI Medical AB, SE-90738 Umeå, Sweden
| | - Roberto Lo Gullo
- Memorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA; (I.D.N.); (R.L.G.); (J.S.R.); (S.B.T.)
| | - Karin Bryskhe
- Random Walk Imaging AB, SE-22002 Lund, Sweden; (A.R.); (P.B.); (K.B.)
| | - Daniel Topgaard
- Department of Chemistry, Lund University, SE-22100 Lund, Sweden;
| | - Dilip D. Giri
- Memorial Sloan Kettering Cancer Center, Department of Pathology, 1275 York Ave, New York, NY 10065, USA;
| | - Jeffrey S. Reiner
- Memorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA; (I.D.N.); (R.L.G.); (J.S.R.); (S.B.T.)
| | - Sunitha B. Thakur
- Memorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA; (I.D.N.); (R.L.G.); (J.S.R.); (S.B.T.)
- Memorial Sloan Kettering Cancer Center, Department of Medical Physics, 1275 York Ave, New York, NY 10065, USA
| | - Katja Pinker-Domenig
- Memorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA; (I.D.N.); (R.L.G.); (J.S.R.); (S.B.T.)
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Wielema M, Sijens PE, Dijkstra H, De Bock GH, van Bruggen IG, Siegersma JE, Langius E, Pijnappel RM, Dorrius MD, Oudkerk M. Diffusion weighted imaging of the breast: Performance of standardized breast tumor tissue selection methods in clinical decision making. PLoS One 2021; 16:e0245930. [PMID: 33493230 PMCID: PMC7833148 DOI: 10.1371/journal.pone.0245930] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 01/08/2021] [Indexed: 12/05/2022] Open
Abstract
Objectives In breast diffusion weighted imaging (DWI) protocol standardization, it is recently shown that no breast tumor tissue selection (BTTS) method outperformed the others. The purpose of this study is to analyze the feasibility of three fixed-size breast tumor tissue selection (BTTS) methods based on the reproducibility, accuracy and time-measurement in comparison to the largest oval and manual delineation in breast diffusion weighted imaging data. Methods This study is performed with a consecutive dataset of 116 breast lesions (98 malignant) of at least 1.0 cm, scanned in accordance with the EUSOBI breast DWI working group recommendations. Reproducibility of the maximum size manual (BTTS1) and of the maximal size round/oval (BTTS2) methods were compared with three smaller fixed-size circular BTTS methods in the middle of each lesion (BTTS3, 0.12 cm3 volume) and at lowest apparent diffusion coefficient (ADC) (BTTS4, 0.12 cm3; BTTS5, 0.24 cm3). Mean ADC values, intraclass-correlation-coefficients (ICCs), area under the curve (AUC) and measurement times (sec) of the 5 BTTS methods were assessed by two observers. Results Excellent inter- and intra-observer agreement was found for any BTTS (with ICC 0.88–0.92 and 0.92–0.94, respectively). Significant difference in ADCmean between any pair of BTTS methods was shown (p = <0.001–0.009), except for BTTS2 vs. BTTS3 for observer 1 (p = 0.10). AUCs were comparable between BTTS methods, with highest AUC for BTTS2 (0.89–0.91) and lowest for BTTS4 (0.76–0.85). However, as an indicator of clinical feasibility, BTTS2-3 showed shortest measurement times (10–15 sec) compared to BTTS1, 4–5 (19–39 sec). Conclusion The performance of fixed-size BTTS methods, as a potential tool for clinical decision making, shows equal AUC but shorter ADC measurement time compared to manual or oval whole lesion measurements. The advantage of a fixed size BTTS method is the excellent reproducibility. A central fixed breast tumor tissue volume of 0.12 cm3 is the most feasible method for use in clinical practice.
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Affiliation(s)
- M. Wielema
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- * E-mail:
| | - P. E. Sijens
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - H. Dijkstra
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - G. H. De Bock
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - I. G. van Bruggen
- Department of Radiotherapy, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - J. E. Siegersma
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - E. Langius
- Department of Radiology, Isala Hospital, Zwolle, the Netherlands
| | - R. M. Pijnappel
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - M. D. Dorrius
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - M. Oudkerk
- Faculty of Medical Sciences, University of Groningen, Groningen, the Netherlands
- Institute of Diagnostic Accuracy, Groningen, the Netherlands
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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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Lee SH, Shin HJ, Moon WK. Diffusion-Weighted Magnetic Resonance Imaging of the Breast: Standardization of Image Acquisition and Interpretation. Korean J Radiol 2020; 22:9-22. [PMID: 32901461 PMCID: PMC7772373 DOI: 10.3348/kjr.2020.0093] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 05/06/2020] [Accepted: 05/09/2020] [Indexed: 12/12/2022] Open
Abstract
Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a rapid, unenhanced imaging technique that measures the motion of water molecules within tissues and provides information regarding the cell density and tissue microstructure. DW MRI has demonstrated the potential to improve the specificity of breast MRI, facilitate the evaluation of tumor response to neoadjuvant chemotherapy and can be employed in unenhanced MRI screening. However, standardization of the acquisition and interpretation of DW MRI is challenging. Recently, the European Society of Breast Radiology issued a consensus statement, which described the acquisition parameters and interpretation of DW MRI. The current article describes the basic principles, standardized acquisition protocols and interpretation guidelines, and the clinical applications of DW MRI in breast imaging.
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Affiliation(s)
- Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Hee Jung Shin
- Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.
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36
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Penn AI, Medved M, Dialani V, Pisano ED, Cole EB, Brousseau D, Karczmar GS, Gao G, Reich BD, Abe H. Discrimination of benign from malignant breast lesions in dense breasts with model-based analysis of regions-of-interest using directional diffusion-weighted images. BMC Med Imaging 2020; 20:61. [PMID: 32517657 PMCID: PMC7282088 DOI: 10.1186/s12880-020-00458-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Accepted: 05/20/2020] [Indexed: 12/03/2022] Open
Abstract
Background There is an increasing interest in non-contrast-enhanced magnetic resonance imaging (MRI) for detecting and evaluating breast lesions. We present a methodology utilizing lesion core and periphery region of interest (ROI) features derived from directional diffusion-weighted imaging (DWI) data to evaluate performance in discriminating benign from malignant lesions in dense breasts. Methods We accrued 55 dense-breast cases with 69 lesions (31 benign; 38 cancer) at a single institution in a prospective study; cases with ROIs exceeding 7.50 cm2 were excluded, resulting in analysis of 50 cases with 63 lesions (29 benign, 34 cancers). Spin-echo echo-planar imaging DWI was acquired at 1.5 T and 3 T. Data from three diffusion encoding gradient directions were exported and processed independently. Lesion ROIs were hand-drawn on DWI images by two radiologists. A region growing algorithm generated 3D lesion models on augmented apparent-diffusion coefficient (ADC) maps and defined lesion core and lesion periphery sub-ROIs. A lesion-core and a lesion-periphery feature were defined and combined into an overall classifier whose performance was compared to that of mean ADC using receiver operating characteristic (ROC) analysis. Inter-observer variability in ROI definition was measured using Dice Similarity Coefficient (DSC). Results The region-growing algorithm for 3D lesion model generation improved inter-observer variability over hand drawn ROIs (DSC: 0.66 vs 0.56 (p < 0.001) with substantial agreement (DSC > 0.8) in 46% vs 13% of cases, respectively (p < 0.001)). The overall classifier improved discrimination over mean ADC, (ROC- area under the curve (AUC): 0.85 vs 0.75 and 0.83 vs 0.74 respectively for the two readers). Conclusions A classifier generated from directional DWI information using lesion core and lesion periphery information separately can improve lesion discrimination in dense breasts over mean ADC and should be considered for inclusion in computer-aided diagnosis algorithms. Our model-based ROIs could facilitate standardization of breast MRI computer-aided diagnostics (CADx).
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Affiliation(s)
- Alan I Penn
- Alan Penn & Assoc., Inc., 14 Clemson Ct, Rockville, MD, 20810, USA.
| | - Milica Medved
- Department of Radiology, The University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637, USA
| | - Vandana Dialani
- Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA, 02215, USA
| | - Etta D Pisano
- Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA, 02215, USA.,American College of Radiology, Two Liberty Place, Philadelphia, PA, 19102, USA
| | - Elodia B Cole
- American College of Radiology, Two Liberty Place, Philadelphia, PA, 19102, USA
| | - David Brousseau
- Providence Cedars-Sinai Tarzana Medical Center, 18321 Clark Street, Tarzana, CA, 91356, USA
| | - Gregory S Karczmar
- Department of Radiology, The University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637, USA
| | - Guimin Gao
- Department of Public Health Sciences, The University of Chicago, 5841 S. Maryland Ave. MC 2000, Chicago, IL, 60637, USA
| | - Barry D Reich
- Alan Penn & Assoc., Inc., 14 Clemson Ct, Rockville, MD, 20810, USA
| | - Hiroyuki Abe
- Department of Radiology, The University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637, USA
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Jiang J, Fu Y, Hu X, Cui L, Hong Q, Gu X, Yin J, Cai R, Xu G. The value of diffusion-weighted imaging based on monoexponential and biexponential models for the diagnosis of benign and malignant lung nodules and masses. Br J Radiol 2020; 93:20190400. [PMID: 32163295 PMCID: PMC10993207 DOI: 10.1259/bjr.20190400] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 02/29/2020] [Accepted: 03/09/2020] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVES The objective is to compare the efficacy of diffusion-weighted imaging (DWI) parameters of mean and minimum apparent diffusion coefficient (ADCmean and ADCmin) and intravoxel incoherent motion (IVIM) in the differentiation of benign and malignant lung nodules and masses. METHODS Lung lesions measured larger than 1.5 cm on CT were included between August 2015 and September 2018. DWI (10 b-values, 0-1000 s/mm2) scans were performed, and the data were post-processed to derive the ADCmean, ADCmin and IVIM parameters of true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f). An independent sample t-test or Mann-Whitney U test was used to compare benign and malignant parameters. Receiver operating characteristic curves were generated and a Z test was used. RESULTS 121 patients were finally enrolled, each with one lesion. Examined 121 lesions were malignant in 88 (72.7%) and benign in 33 (27.3%). The ADCmean of malignant pulmonary nodules was significantly lower than that of benign pulmonary nodules (t = 3.156, p = 0.006), whereas the other parameters revealed no significant differences (p = 0.162-0.690). Receiver operating characteristic curve analysis revealed that an ADCmean threshold value of 1.43 × 10-3 mm2/s yielded 88.57% sensitivity and 64.29% specificity. While for lung masses, the ADCmean, ADCmin, D and D* values in malignant pulmonary masses were significantly lower (P﹤0.001-0.011). Among them, the D value exhibited the best diagnostic performance when the threshold of D was 1.23 × 10-3mm2/s, which yielded a sensitivity of 90.57% and a specificity of 89.47% (Z = 2.230, 3.958, 2.877 and p = 0.026, ﹤0.001 and 0.004, respectively). CONCLUSION ADC is the most robust parameter to differentiate benign and malignant lung nodules, whereas D is the most robust parameter to differentiate benign and malignant lung masses. ADVANCES IN KNOWLEDGE This is the first study to compare all the quantitative parameters of DWI and IVIM mentioned in the literatures for assessing lung lesions; Second, we divided the lesions into lung nodules and lung masses with the size of 3 cm as the boundary.
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Affiliation(s)
- Jianqin Jiang
- Department of Radiology, Yancheng City No.1 People's
Hospital, Yancheng,
China
| | - Yigang Fu
- Department of Radiology, Yancheng City No.1 People's
Hospital, Yancheng,
China
| | - Xiaoyun Hu
- Department of Radiology, Wuxi People's Hospital,
Wuxi, China
| | - Lei Cui
- Department of Radiology, Second Affiliated Hospital of Nantong
University, Nantong,
China
| | - Qin Hong
- Department of Radiology, Yancheng City No.1 People's
Hospital, Yancheng,
China
| | - Xiaowen Gu
- Department of Radiology, Suzhou Municipal
Hospital, Suzhou,
China
| | - Jianbing Yin
- Department of Radiology, Second Affiliated Hospital of Nantong
University, Nantong,
China
| | - Rongfang Cai
- Department of Radiology, Second Affiliated Hospital of Nantong
University, Nantong,
China
| | - Gaofeng Xu
- Department of Radiology, Yancheng City No.1 People's
Hospital, Yancheng,
China
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Peng Y, Xu C, Hu X, Shen Y, Hu D, Kamel I, Li Z. Reduced Field-of-View Diffusion-Weighted Imaging in Histological Characterization of Rectal Cancer: Impact of Different Region-of-Interest Positioning Protocols on Apparent Diffusion Coefficient Measurements. Eur J Radiol 2020; 127:109028. [DOI: 10.1016/j.ejrad.2020.109028] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 03/11/2020] [Accepted: 04/14/2020] [Indexed: 01/21/2023]
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Wielema M, Dorrius MD, Pijnappel RM, De Bock GH, Baltzer PAT, Oudkerk M, Sijens PE. Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis. PLoS One 2020; 15:e0232856. [PMID: 32374781 PMCID: PMC7202642 DOI: 10.1371/journal.pone.0232856] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 04/22/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from malignant breast lesions in DWI in terms of sensitivity, specificity and area under the curve (AUC). METHODS AND FINDINGS In this systematic review and meta-analysis, adhering to the PRISMA statement, 61 studies, with 65 study subsets, in females with benign or malignant primary breast lesions (6291 lesions) were assessed. Studies on DWI, quantified by ADC, scanned on 1.5 and 3.0 Tesla and using b-values 0/50 and ≥ 800 s/mm2 were included. PubMed and EMBASE were searched for studies up to 23-10-2019 (n = 2897). Data were pooled based on four BTTS methods (by definition of measured region of interest, ROI): BTTS1: whole breast tumor tissue selection, BTTS2: subtracted whole breast tumor tissue selection, BTTS3: circular breast tumor tissue selection and BTTS4: lowest diffusion breast tumor tissue selection. BTTS methods 2 and 3 excluded necrotic, cystic and hemorrhagic areas. Pooled sensitivity, specificity and AUC of the BTTS methods were calculated. Heterogeneity was explored using the inconsistency index (I2) and considering covariables: field strength, lowest b-value, image of BTTS selection, pre-or post-contrast DWI, slice thickness and ADC threshold. Pooled sensitivity, specificity and AUC were: 0.82 (0.72-0.89), 0.79 (0.65-0.89), 0.88 (0.85-0.90) for BTTS1; 0.91 (0.89-0.93), 0.84 (0.80-0.87), 0.94 (0.91-0.96) for BTTS2; 0.89 (0.86-0.92), 0.90 (0.85-0.93), 0.95 (0.93-0.96) for BTTS3 and 0.90 (0.86-0.93), 0.84 (0.81-0.87), 0.86 (0.82-0.88) for BTTS4, respectively. Significant heterogeneity was found between studies (I2 = 95). CONCLUSIONS None of the breast tissue selection (BTTS) methodologies outperformed in differentiating benign from malignant breast lesions. The high heterogeneity of ADC data acquisition demands further standardization, such as DWI acquisition parameters and tumor tissue selection to substantially increase the reliability of DWI of the breast.
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Affiliation(s)
- M. Wielema
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - M. D. Dorrius
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - R. M. Pijnappel
- Department of Radiology, Utrecht University, University Medical Center Utrecht, Utrecht, The Netherlands
| | - G. H. De Bock
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - P. A. T. Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - M. Oudkerk
- University of Groningen, Groningen, The Netherlands
- Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - P. E. Sijens
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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Sodano C, Clauser P, Dietzel M, Kapetas P, Pinker K, Helbich TH, Gussew A, Baltzer PA. Clinical relevance of total choline (tCho) quantification in suspicious lesions on multiparametric breast MRI. Eur Radiol 2020; 30:3371-3382. [PMID: 32065286 PMCID: PMC7248046 DOI: 10.1007/s00330-020-06678-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 01/03/2020] [Accepted: 01/27/2020] [Indexed: 12/24/2022]
Abstract
Purpose To assess the additional value of quantitative tCho evaluation to diagnose malignancy and lymph node metastases in suspicious lesions on multiparametric breast MRI (mpMRI, BI-RADS 4, and BI-RADS 5). Methods One hundred twenty-one patients that demonstrated suspicious multiparametric breast MRI lesions using DCE, T2w, and diffusion-weighted (DW) images were prospectively enrolled in this IRB-approved study. All underwent single-voxel proton MR spectroscopy (1H-MRS, point-resolved spectroscopy sequence, TR 2000 ms, TE 272 ms) with and without water suppression. The total choline (tCho) amplitude was measured and normalized to millimoles/liter according to established methodology by two independent readers (R1, R2). ROC-analysis was employed to predict malignancy and lymph node status by tCho results. Results One hundred three patients with 74 malignant and 29 benign lesions had full 1H-MRS data. The area under the ROC curve (AUC) for prediction of malignancy was 0.816 (R1) and 0.809 (R2). A cutoff of 0.8 mmol/l tCho could diagnose malignancy with a sensitivity of > 95%. For prediction of lymph node metastases, tCho measurements achieved an AUC of 0.760 (R1) and 0.788 (R2). At tCho levels < 2.4 mmol/l, no metastatic lymph nodes were found. Conclusion Quantitative tCho evaluation from 1H-MRS allowed diagnose malignancy and lymph node status in breast lesions suspicious on multiparametric breast MRI. tCho therefore demonstrated the potential to downgrade suspicious mpMRI lesions and stratify the risk of lymph node metastases for improved patient management. Key Points • Quantitative tCho evaluation can distinguish benign from malignant breast lesions suspicious after multiparametric MRI assessment. • Quantitative tCho levels are associated with lymph node status in breast cancer. • Quantitative tCho levels are higher in hormonal receptor positive compared to hormonal receptor negative lesions. Electronic supplementary material The online version of this article (10.1007/s00330-020-06678-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Claudia Sodano
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender, Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, A-1090, Vienna, Austria
| | - Paola Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender, Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, A-1090, Vienna, Austria
| | - Matthias Dietzel
- Institute of Radiology, Universitätsklinikum Erlangen, Maximiliansplatz 1, 91054, Erlangen, Germany
| | - Panagiotis Kapetas
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender, Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, A-1090, Vienna, Austria
| | - Katja Pinker
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Thomas H Helbich
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender, Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, A-1090, Vienna, Austria
| | - Alexander Gussew
- Universitätsklinik und Poliklinik für Radiologie, Ernst-Grube-Str. 40, D-06120, Halle (Saale), Germany
| | - Pascal Andreas Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender, Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, A-1090, Vienna, Austria.
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Peter SC, Wenkel E, Weiland E, Dietzel M, Janka R, Hartmann A, Emons J, Uder M, Ellmann S. Combination of an ultrafast TWIST-VIBE Dixon sequence protocol and diffusion-weighted imaging into an accurate easily applicable classification tool for masses in breast MRI. Eur Radiol 2020; 30:2761-2772. [PMID: 32002644 DOI: 10.1007/s00330-019-06608-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 11/18/2019] [Accepted: 12/05/2019] [Indexed: 12/24/2022]
Abstract
OBJECTIVES This study aimed to develop a tool for the classification of masses in breast MRI, based on ultrafast TWIST-VIBE Dixon (TVD) dynamic sequences combined with DWI. TVD sequences allow to abbreviate breast MRI protocols, but provide kinetic information only on the contrast wash-in, and because of the lack of the wash-out kinetics, their diagnostic value might be hampered. A special focus of this study was thus to maintain high diagnostic accuracy in lesion classification. MATERIALS AND METHODS Sixty-one patients who received breast MRI between 02/2014 and 04/2015 were included, with 83 reported lesions (60 malignant). Our institute's standard breast MRI protocol was complemented by an ultrafast TVD sequence. ADC and peak enhancement of the TVD sequences were integrated into a generalised linear model (GLM) for malignancy prediction. For comparison, a second GLM was calculated using ADC and conventional DCE curve type. The resulting GLMs were evaluated for standard diagnostic parameters. For easy application of the GLMs, nomograms were created. RESULTS The GLM based on peak enhancement of the TVD and ADC was as equally accurate as the GLM based on conventional DCE and ADC, with no significant differences (sensitivity, 93.3%/93.3%; specificity, 91.3%/87.0%; PPV, 96.6%/94.9%; NPV, 84.0%/83.3%; all, p ≥ 0.315). CONCLUSIONS This study presents a method to integrate ultrafast TVD sequences into a breast MRI protocol, allowing a reduction of the examination time while maintaining diagnostic accuracy. A GLM based on the combination of TVD-derived peak enhancement and ADC provides high diagnostic accuracy, and can be easily applied using a nomogram. KEY POINTS • Ultrafast TWIST-VIBE Dixon sequence protocols in combination with diffusion-weighted imaging allow to shorten breast MRI examinations, while diagnostic accuracy is maintained. • Integrating peak enhancement from the TWIST-VIBE Dixon sequence and the apparent diffusion coefficient into a generalised linear model provides a comprehensible image evaluation approach. • This approach is further facilitated by nomograms.
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Affiliation(s)
- Sandra C Peter
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Evelyn Wenkel
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Elisabeth Weiland
- Siemens Healthcare GmbH, Allee am Röthelheimpark 2, 91052, Erlangen, Germany
| | - Matthias Dietzel
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Rolf Janka
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Arndt Hartmann
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), 91054, Erlangen, Germany
| | - Julius Emons
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, 91054, Erlangen, Germany
| | - Michael Uder
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany
| | - Stephan Ellmann
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054, Erlangen, Germany.
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Diffusion-weighted imaging with simultaneous multi-slice echo-planar technique for the diagnosis of breast magnetic resonance imaging. Jpn J Radiol 2020; 38:358-364. [DOI: 10.1007/s11604-020-00919-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Accepted: 01/03/2020] [Indexed: 10/25/2022]
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Avendano D, Marino MA, Leithner D, Thakur S, Bernard-Davila B, Martinez DF, Helbich TH, Morris EA, Jochelson MS, Baltzer PAT, Clauser P, Kapetas P, Pinker K. Limited role of DWI with apparent diffusion coefficient mapping in breast lesions presenting as non-mass enhancement on dynamic contrast-enhanced MRI. Breast Cancer Res 2019; 21:136. [PMID: 31801635 PMCID: PMC6894318 DOI: 10.1186/s13058-019-1208-y] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 10/03/2019] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Available data proving the value of DWI for breast cancer diagnosis is mainly for enhancing masses; DWI may be less sensitive and specific in non-mass enhancement (NME) lesions. The objective of this study was to assess the diagnostic accuracy of DWI using different ROI measurement approaches and ADC metrics in breast lesions presenting as NME lesions on dynamic contrast-enhanced (DCE) MRI. METHODS In this retrospective study, 95 patients who underwent multiparametric MRI with DCE and DWI from September 2007 to July 2013 and who were diagnosed with a suspicious NME (BI-RADS 4/5) were included. Twenty-nine patients were excluded for lesion non-visibility on DWI (n = 24: 12 benign and 12 malignant) and poor DWI quality (n = 5: 1 benign and 4 malignant). Two readers independently assessed DWI and DCE-MRI findings in two separate randomized readings using different ADC metrics and ROI approaches. NME lesions were classified as either benign (> 1.3 × 10-3 mm2/s) or malignant (≤ 1.3 × 10-3 mm2/s). Histopathology was the standard of reference. ROC curves were plotted, and AUCs were determined. Concordance correlation coefficient (CCC) was measured. RESULTS There were 39 malignant (59%) and 27 benign (41%) lesions in 66 (65 women, 1 man) patients (mean age, 51.8 years). The mean ADC value of the darkest part of the tumor (Dptu) achieved the highest diagnostic accuracy, with AUCs of up to 0.71. Inter-reader agreement was highest with Dptu ADC max (CCC 0.42) and lowest with the point tumor (Ptu) ADC min (CCC = - 0.01). Intra-reader agreement was highest with Wtu ADC mean (CCC = 0.44 for reader 1, 0.41 for reader 2), but this was not associated with the highest diagnostic accuracy. CONCLUSIONS Diagnostic accuracy of DWI with ADC mapping is limited in NME lesions. Thirty-one percent of lesions presenting as NME on DCE-MRI could not be evaluated with DWI, and therefore, DCE-MRI remains indispensable. Best results were achieved using Dptu 2D ROI measurement and ADC mean.
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Affiliation(s)
- Daly Avendano
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, Suite 705, 300 E 66th Street, New York, NY, 10065, USA.,Department of Breast Imaging, Breast Cancer Center TecSalud, ITESM Monterrey, Monterrey, Nuevo Leon, Mexico
| | - Maria Adele Marino
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, Suite 705, 300 E 66th Street, New York, NY, 10065, USA.,Department of Biomedical Sciences and Morphologic and Functional Imaging, University of Messina, Messina, Italy
| | - Doris Leithner
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, Suite 705, 300 E 66th Street, New York, NY, 10065, USA.,Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany
| | - Sunitha Thakur
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, 10065, USA
| | - Blanca Bernard-Davila
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, Suite 705, 300 E 66th Street, New York, NY, 10065, USA
| | - Danny F Martinez
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, Suite 705, 300 E 66th Street, New York, NY, 10065, USA
| | - Thomas H Helbich
- Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Elizabeth A Morris
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, Suite 705, 300 E 66th Street, New York, NY, 10065, USA
| | - Maxine S Jochelson
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, Suite 705, 300 E 66th Street, New York, NY, 10065, USA
| | - Pascal A T Baltzer
- Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Paola Clauser
- Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Panagiotis Kapetas
- Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Katja Pinker
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, Suite 705, 300 E 66th Street, New York, NY, 10065, USA. .,Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
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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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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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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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Andreassen MMS, Goa PE, Sjøbakk TE, Hedayati R, Eikesdal HP, Deng C, Østlie A, Lundgren S, Bathen TF, Jerome NP. Semi-automatic segmentation from intrinsically-registered 18F-FDG-PET/MRI for treatment response assessment in a breast cancer cohort: comparison to manual DCE-MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2019; 33:317-328. [PMID: 31562584 PMCID: PMC7109176 DOI: 10.1007/s10334-019-00778-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Revised: 08/27/2019] [Accepted: 09/16/2019] [Indexed: 12/21/2022]
Abstract
Objectives To investigate the reliability of simultaneous positron emission tomography and magnetic resonance imaging (PET/MRI)-derived biomarkers using semi-automated Gaussian mixture model (GMM) segmentation on PET images, against conventional manual tumor segmentation on dynamic contrast-enhanced (DCE) images. Materials and methods Twenty-four breast cancer patients underwent PET/MRI (following 18F-fluorodeoxyglucose (18F-FDG) injection) at baseline and during neoadjuvant treatment, yielding 53 data sets (24 untreated, 29 treated). Two-dimensional tumor segmentation was performed manually on DCE–MRI images (manual DCE) and using GMM with corresponding PET images (GMM–PET). Tumor area and mean apparent diffusion coefficient (ADC) derived from both segmentation methods were compared, and spatial overlap between the segmentations was assessed with Dice similarity coefficient and center-of-gravity displacement. Results No significant differences were observed between mean ADC and tumor area derived from manual DCE segmentation and GMM–PET. There were strong positive correlations for tumor area and ADC derived from manual DCE and GMM–PET for untreated and treated lesions. The mean Dice score for GMM–PET was 0.770 and 0.649 for untreated and treated lesions, respectively. Discussion Using PET/MRI, tumor area and mean ADC value estimated with a GMM–PET can replicate manual DCE tumor definition from MRI for monitoring neoadjuvant treatment response in breast cancer.
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Affiliation(s)
| | - Pål Erik Goa
- Department of Physics, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway
| | - Torill Eidhammer Sjøbakk
- Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Roja Hedayati
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Oncology, St. Olav's University Hospital, Trondheim, Norway
| | - Hans Petter Eikesdal
- Section of Oncology, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Oncology, Haukeland University Hospital, Bergen, Norway
| | - Callie Deng
- Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Agnes Østlie
- Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway
| | - Steinar Lundgren
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Oncology, St. Olav's University Hospital, Trondheim, Norway
| | - Tone Frost Bathen
- Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway
| | - Neil Peter Jerome
- Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
- Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway.
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Bajaj P, Iacconi C, Dershaw DD, Morris EA. Diffusion-Weighted MRI of the Breast in Women with a History of Mantle Radiation: Does Radiation Alter Apparent Diffusion Coefficient? JOURNAL OF BREAST IMAGING 2019; 1:212-216. [DOI: 10.1093/jbi/wbz035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Indexed: 11/13/2022]
Abstract
Abstract
Objective
Fibrosis from chest irradiation could lower the apparent diffusion coefficient (ADC) of breast tissue. ADC values of normal breast tissue in high-risk women who underwent mantle radiation before age 30 years were compared with a screening control group matched for breast fibroglandular tissue (FGT).
Methods
In this retrospective study, we reviewed 21 women with a history of mantle radiation who underwent breast MRI examinations between 2008 and 2013, and 20 nonirradiated patients (control group) imaged during the same period with matching FGT and similar age. The women were dichotomized into low FGT (10/20, 50%) and high-FGT (10/20, 50%) groups, based on BI-RADS descriptors. All MRI examinations included diffusion-weighted imaging (DWI) (b = 0, 1000); ADC maps were generated and evaluated on PACS workstations by two radiologists in agreement. Region of interest markers were placed on ADC maps in visualized breast tissue in the retroareolar region of each breast. The ADC value was averaged for the right and left breast in each patient included in the study. The Wilcoxon signed-rank test was used to compare the ADC values in the irradiated patients and the matched control patients.
Results
The median breast ADC was lower in the irradiated group (1.32 × 10-3mm2/sec) than in the control group (1.62 × 10-3mm2/sec; P = 0.0089). Low FGT in the irradiated group had a lower median ADC (1.25 × 10-3mm2/sec) than it did in the control group (1.53 × 10-3mm2/sec). Irradiated high-FGT breasts had a median ADC (1.52 × 10-3mm2/sec), as compared with nonirradiated control patients with high FGT (1.82 × 10-3mm2/sec).
Conclusion
Previously irradiated breasts have lower ADC values than do nonirradiated breasts.
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Affiliation(s)
- Punam Bajaj
- Memorial Sloan Kettering Cancer Center, Department of Breast Imaging, New York, NY
| | - Chiara Iacconi
- Memorial Sloan Kettering Cancer Center, Department of Breast Imaging, New York, NY
| | - David D Dershaw
- Memorial Sloan Kettering Cancer Center, Department of Breast Imaging, New York, NY
| | - Elizabeth A Morris
- Memorial Sloan Kettering Cancer Center, Department of Breast Imaging, New York, NY
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Senn N, Masannat Y, Husain E, Siow B, Heys SD, He J. q-Space Imaging Yields a Higher Effect Gradient to Assess Cellularity than Conventional Diffusion-weighted Imaging Methods at 3.0 T: A Pilot Study with Freshly Excised Whole-Breast Tumors. Radiol Imaging Cancer 2019; 1:e190008. [PMID: 33778671 PMCID: PMC7983771 DOI: 10.1148/rycan.2019190008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 07/16/2019] [Accepted: 07/25/2019] [Indexed: 11/29/2022]
Abstract
Purpose To determine whether q-space imaging (QSI), an advanced diffusion-weighted MRI method, provides a higher effect gradient to assess tumor cellularity than existing diffusion imaging methods, and fidelity to cellularity obtained from histologic analysis. Materials and Methods In this prospective study, diffusion-weighted images were acquired from 20 whole-breast tumors freshly excised from participants (age range, 35-78 years) by using a clinical 3.0-T MRI unit. Median and skewness values were extracted from the histogram distributions obtained from QSI, monoexponential model, diffusion kurtosis imaging (DKI), and stretched exponential model (SEM). The skewness from QSI and other diffusion models was compared by using paired t tests and relative effect gradient obtained from correlating skewness values. Results The skewness obtained from QSI (mean, 1.34 ± 0.77 [standard deviation]) was significantly higher than the skewness from monoexponential fitting approach (mean, 1.09 ± 0.67; P = .015), SEM (mean, 1.07 ± 0.70; P = .014), and DKI (mean, 0.97 ± 0.63; P = .004). QSI yielded a higher effect gradient in skewness (percentage increase) compared with monoexponential fitting approach (0.26 of 0.74; 35.1%), SEM (0.26 of 0.74; 35.1%), and DKI (0.37 of 0.63; 58.7%). The skewness and median from QSI were significantly correlated with the skewness (ρ = -0.468; P = .038) and median (ρ = -0.513; P = .021) of cellularity from histologic analysis. Conclusion QSI yields a higher effect gradient in assessing breast tumor cellularity than existing diffusion methods, and fidelity to underlying histologic structure.Keywords: Breast, MR-Diffusion Weighted Imaging, MR-Imaging, Pathology, Tissue Characterization, Tumor ResponseOnline supplemental material is available for this article.Published under a CC BY 4.0 license.
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Affiliation(s)
| | | | - Ehab Husain
- From the Institute of Medical Sciences, School of Medicine, University of Aberdeen, Aberdeen AB25 2ZD, Scotland (N.S., S.D.H., J.H.); Breast Unit (Y.M., S.D.H.) and Department of Pathology (E.H.), Aberdeen Royal Infirmary, Aberdeen, Scotland; and MRI Unit, The Francis Crick Institute, London, England (B.S.)
| | - Bernard Siow
- From the Institute of Medical Sciences, School of Medicine, University of Aberdeen, Aberdeen AB25 2ZD, Scotland (N.S., S.D.H., J.H.); Breast Unit (Y.M., S.D.H.) and Department of Pathology (E.H.), Aberdeen Royal Infirmary, Aberdeen, Scotland; and MRI Unit, The Francis Crick Institute, London, England (B.S.)
| | - Steven D. Heys
- From the Institute of Medical Sciences, School of Medicine, University of Aberdeen, Aberdeen AB25 2ZD, Scotland (N.S., S.D.H., J.H.); Breast Unit (Y.M., S.D.H.) and Department of Pathology (E.H.), Aberdeen Royal Infirmary, Aberdeen, Scotland; and MRI Unit, The Francis Crick Institute, London, England (B.S.)
| | - Jiabao He
- From the Institute of Medical Sciences, School of Medicine, University of Aberdeen, Aberdeen AB25 2ZD, Scotland (N.S., S.D.H., J.H.); Breast Unit (Y.M., S.D.H.) and Department of Pathology (E.H.), Aberdeen Royal Infirmary, Aberdeen, Scotland; and MRI Unit, The Francis Crick Institute, London, England (B.S.)
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Mongula J, Bakers F, Slangen B, van Kuijk S, Kruitwagen R, Mihl C. Evaluation of various apparent diffusion coefficient measurement techniques in pre-operative staging of early cervical carcinoma. Eur J Radiol 2019; 118:101-106. [DOI: 10.1016/j.ejrad.2019.06.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 06/21/2019] [Accepted: 06/25/2019] [Indexed: 02/08/2023]
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