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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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Wang L, Wang X, Jiang F, Cao Y, Liu S, Chen H, Yang J, Zhang X, Yu T, Xu H, Lin M, Wu Y, Zhang J. Adding quantitative T1rho-weighted imaging to conventional MRI improves specificity and sensitivity for differentiating malignant from benign breast lesions. Magn Reson Imaging 2024; 108:98-103. [PMID: 38331054 DOI: 10.1016/j.mri.2024.02.005] [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: 06/13/2023] [Revised: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 02/10/2024]
Abstract
OBJECTIVES To investigate the feasibility of T1rho-weighted imaging in differentiating malignant from benign breast lesions and to explore the additional value of T1rho to conventional MRI. MATERIALS AND METHODS We prospectively enrolled consecutive women with breast lesions who underwent preoperative T1rho-weighted imaging, diffusion-weighted imaging, and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) between November 2021 and July 2023. The T1rho, apparent diffusion coefficient (ADC), and semi-quantitative parameters from DCE-MRI were obtained and compared between benign and malignant groups. The diagnostic performance was analyzed and compared using receiver operating characteristic (ROC) curves and the Delong Test. RESULTS This study included 113 patients (74 malignant and 39 benign lesions). The mean T1rho value in the benign group (92.61 ± 22.10 ms) was significantly higher than that in the malignant group (72.18 ± 16.37 ms) (P < 0.001). The ADC value and time to peak (TTP) value in the malignant group (1.13 ± 0.45 and 269.06 ± 106.01, respectively) were lower than those in the benign group (1.57 ± 0.45 and 388.30 ± 81.13, respectively) (all P < 0.001). T1rho combined with ADC and TTP showed good diagnostic performance with an area under the curve (AUC) of 0.896, a sensitivity of 81.0%, and a specificity of 87.1%. The specificity and sensitivity of the combination of T1rho, ADC, and TTP were significantly higher than those of the combination of ADC and TTP (87.1% vs. 84.6%, P < 0.005; 81.0% vs. 77.0%, P < 0.001). CONCLUSION T1rho-weighted imaging was a feasible MRI sequence for differentiating malignant from benign breast lesions. The combination of T1rho, ADC and TTP could achieve a favorable diagnostic performance with improved specificity and sensitivity, T1rho could serve as a supplementary approach to conventional MRI.
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Affiliation(s)
- Lu Wang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Xiaoxia Wang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Fujie Jiang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Ying Cao
- School of Medicine, Chongqing University, Chongqing 400030, China
| | - Shuling Liu
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Huifang Chen
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Jing Yang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | | | - Tao Yu
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Hanshan Xu
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Meng Lin
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Yongzhong Wu
- Radiation Oncology Center, Chongqing University, Chongqing 400030, China
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China.
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Danzer MF, Eveslage M, Görlich D, Noto B. A statistical framework for planning and analysing test-retest studies of repeatability. Stat Methods Med Res 2024; 33:295-308. [PMID: 38298010 DOI: 10.1177/09622802241227959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
There is an increasing number of potential quantitative biomarkers that could allow for early assessment of treatment response or disease progression. However, measurements of such biomarkers are subject to random variability. Hence, differences of a biomarker in longitudinal measurements do not necessarily represent real change but might be caused by this random measurement variability. Before utilizing a quantitative biomarker in longitudinal studies, it is therefore essential to assess the measurement repeatability. Measurement repeatability obtained from test-retest studies can be quantified by the repeatability coefficient, which is then used in the subsequent longitudinal study to determine if a measured difference represents real change or is within the range of expected random measurement variability. The quality of the point estimate of the repeatability coefficient, therefore, directly governs the assessment quality of the longitudinal study. Repeatability coefficient estimation accuracy depends on the case number in the test-retest study, but despite its pivotal role, no comprehensive framework for sample size calculation of test-retest studies exists. To address this issue, we have established such a framework, which allows for flexible sample size calculation of test-retest studies, based upon newly introduced criteria concerning assessment quality in the longitudinal study. This also permits retrospective assessment of prior test-retest studies.
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Affiliation(s)
- Moritz Fabian Danzer
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Maria Eveslage
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Dennis Görlich
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Benjamin Noto
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
- Clinic for Radiology, University Hospital Münster, Münster, Germany
- Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
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Hu Y, Hu Q, Zhan C, Yin T, Ai T. Intraobserver and Interobserver Reproducibility of Breast Diffusion-Weighted Imaging Quantitative Parameters: Readout-Segmented vs. Single-Shot Echo-Planar Imaging. J Magn Reson Imaging 2023; 58:1725-1736. [PMID: 36807457 DOI: 10.1002/jmri.28655] [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: 11/23/2022] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 02/23/2023] Open
Abstract
BACKGROUND The recommended technique for breast diffusion-weighted imaging (DWI) acquisitions is not sufficiently standardized in clinical practice. PURPOSE To investigate the intraobserver and interobserver reproducibility of DWI measurements, diffusion-kurtosis imaging (DKI) parameters, and image quality evaluation in breast lesions between single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI). STUDY TYPE Prospective. POPULATION A total of 295 women with 209 malignant and 86 benign breast lesions. FIELD STRENGTH/SEQUENCE A 3-T; fat-saturated T2-weighted MR imaging (T2WI); multi-b-value DWI with both ss-EPI and rs-EPI readouts; T1-weighted dynamic contrast-enhanced MRI (DCE-MRI). ASSESSMENT Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were measured for each lesion on ss-EPI and rs-EPI, respectively. Image quality was visually evaluated regarding image sharpness, geometric distortion, lesion conspicuity, visualization of anatomic structures, and overall quality. Quantitative and qualitative analyses were performed twice with a time interval of 2 weeks. STATISTICAL TESTS Intraobserver and interobserver reproducibility were evaluated using intra-class correlation coefficients (ICC), within-subject coefficient of variation (wCV), and Bland-Altman plots. RESULTS MK, MD, and ADC quantitative parameters for breast lesions showed excellent intraobserver and interobserver reproducibility, with ICCs >0.75 and wCV values ranging from 2.51% to 7.08% for both sequences. The wCV values in both intraobserver and interobserver measurements were higher in the ss-EPI sequence (3.63%-7.08%) than that of the rs-EPI sequence (2.51%-3.62%). The wCV values differed in subgroups with different histopathological types of lesions, breast density, lesion morphology, and lesion sizes, respectively. Furthermore, rs-EPI (ICCs, 0.76-0.97; wCV values, 2.41%-6.04%) had better intraobserver and interobserver reproducibility than ss-EPI (ICCs, 0.54-0.90; wCV values, 6.18%-13.69%) with regard to image quality. DATA CONCLUSION Compared to the ss-EPI, the rs-EPI sequence showed higher intraobserver and interobserver reproducibility for quantitative diffusion-related parameters and image quality assessments measured in breast DWI and DKI. EVIDENCE LEVEL 2. TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- Yiqi Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qilan Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Chenao Zhan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ting Yin
- MR Collaborations, Siemens Healthineers Ltd., Shanghai, China
| | - Tao Ai
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Fang S, Yang Y, Tao J, Yin Z, Liu Y, Duan Z, Liu W, Wang S. Intratumoral Heterogeneity of Fibrosarcoma Xenograft Models: Whole-Tumor Histogram Analysis of DWI and IVIM. Acad Radiol 2023; 30:2299-2308. [PMID: 36481126 DOI: 10.1016/j.acra.2022.11.016] [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: 07/27/2022] [Revised: 11/08/2022] [Accepted: 11/14/2022] [Indexed: 12/12/2022]
Abstract
RATIONAL AND OBJECTIVE To explore the correlations of histogram parameters from diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) with the heterogeneous features in a nude mouse model of fibrosarcoma. MATERIALS AND METHODS A total of 44 fibrosarcoma xenograft models were established by inoculating HT-1080 cells on the right thigh of mice and subjected tumors to DWI and IVIM imaging with 3.0 T MRI. Whole-tumor histogram parameters were calculated on apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f). Heterogeneous features, including necrosis rate, cell density, Ki-67 labeling index (LI), and microvascular density (MVD) were measured. Intraclass correlation coefficients (ICC), Pearson or Spearman correlation tests, and receiver operating characteristics (ROC) were performed. RESULTS The 90th percentile, skewness and kurtosis of ADC and D histograms showed correlations with necrosis rate, and the highest correlation coefficient was found for D90th (r = 0.485). ADC and D histogram parameters showed correlations with cell density and Ki-67 LI; D90th showed the highest correlation coefficient with cell density (r = -0.504); and Dmedian showed the most significant correlation with Ki-67 LI (r = -0.525). D*skewness, D*kurtosis, D*90th, fmean, and fmedian showed correlations with MVD. ADC90th, ADCskewness, ADCkurtosis, D90th, and Dskewness showed significant differences between the low necrosis and high necrosis groups, and the combination model showed the best diagnostic ability (AUC = 0.882), with 97% sensitivity, and 72.7% specificity. CONCLUSION Whole-tumor histogram parameters of DWI and IVIM were correlated with heterogeneous features in nude murine models of fibrosarcoma.
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Affiliation(s)
- Shaobo Fang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Yanyu Yang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Juan Tao
- Department of Pathology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Zhenzhen Yin
- Department of Radiology, Suzhou Hospital of Anhui Medical University, Anhui, China
| | - Yajie Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Zhiqing Duan
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Wenyu Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian 116027, 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: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics.
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Affiliation(s)
- Ashley M. Mendez
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Lauren K. Fang
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Claire H. Meriwether
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Summer J. Batasin
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Stéphane Loubrie
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Ana E. Rodríguez-Soto
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Rebecca A. Rakow-Penner
- Department of Radiology, University of California San Diego, La Jolla, CA, United States,Department of Bioengineering, University of California San Diego, La Jolla, CA, United States,*Correspondence: Rebecca A. Rakow-Penner,
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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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Cho E, Baek HJ, Szczepankiewicz F, An HJ, Jung EJ, Lee HJ, Lee J, Gho SM. Clinical experience of tensor-valued diffusion encoding for microstructure imaging by diffusional variance decomposition in patients with breast cancer. Quant Imaging Med Surg 2022; 12:2002-2017. [PMID: 35284250 PMCID: PMC8899958 DOI: 10.21037/qims-21-870] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 12/13/2021] [Indexed: 08/28/2023]
Abstract
BACKGROUND Diffusion-weighted imaging plays a key role in magnetic resonance imaging (MRI) of breast tumors. However, it remains unclear how to interpret single diffusion encoding with respect to its link with tissue microstructure. The purpose of this retrospective cross-sectional study was to use tensor-valued diffusion encoding to investigate the underlying microstructure of invasive ductal carcinoma (IDC) and evaluate its potential value in a clinical setting. METHODS We retrospectively reviewed biopsy-proven breast cancer patients who underwent preoperative breast MRI examination from July 2020 to March 2021. We reviewed the MRI of 29 patients with 30 IDCs, including analysis by diffusional variance decomposition enabled by tensor-valued diffusion encoding. The diffusion parameters of mean diffusivity (MD), total mean kurtosis (MKT), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), macroscopic fractional anisotropy (FA), and microscopic fractional anisotropy (µFA) were estimated. The parameter differences were compared between IDC and normal fibroglandular breast tissue (FGBT), as well as the association between the diffusion parameters and histopathologic items. RESULTS The mean value of MD in IDCs was significantly lower than that of normal FGBT (1.07±0.27 vs. 1.34±0.29, P<0.001); however, MKT, MKA, MKI, FA, and µFA were significantly higher (P<0.005). Among all the diffusion parameters, MKI was positively correlated with the tumor size on both MRI and pathological specimen (rs=0.38, P<0.05 vs. rs=0.54, P<0.01), whereas MKT had a positive correlation with the tumor size in the pathological specimen only (rs=0.47, P<0.02). In addition, the lymph node (LN) metastasis group had significantly higher MKT, MKA, and µFA compared to the metastasis negative group (P<0.05). CONCLUSIONS Tensor-valued diffusion encoding enables a useful non-invasive method for characterizing breast cancers with information on tissue microstructures. Particularly, µFA could be a potential imaging biomarker for evaluating breast cancers prior to surgery or chemotherapy.
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Affiliation(s)
- Eun Cho
- Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
| | - Hye Jin Baek
- Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
- Department of Radiology, Institute of Health Sciences, Gyeongsang National University School of Medicine, Jinju-daero, Jinju, Republic of Korea
| | - Filip Szczepankiewicz
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Klinikgatan, Sweden
| | - Hyo Jung An
- Department of Pathology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
| | - Eun Jung Jung
- Department of Surgery, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - Ho-Joon Lee
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-gu, Busan, Republic of Korea
| | | | - Sung-Min Gho
- MR Clinical Solutions & Research Collaborations, GE Healthcare, Seoul, Republic of Korea
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Yin H, Jiang Y, Xu Z, Huang W, Chen T, Lin G. Apparent Diffusion Coefficient-Based Convolutional Neural Network Model Can Be Better Than Sole Diffusion-Weighted Magnetic Resonance Imaging to Improve the Differentiation of Invasive Breast Cancer From Breast Ductal Carcinoma In Situ. Front Oncol 2022; 11:805911. [PMID: 35096609 PMCID: PMC8795910 DOI: 10.3389/fonc.2021.805911] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 12/24/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND PURPOSE Breast ductal carcinoma in situ (DCIS) has no metastatic potential, and has better clinical outcomes compared with invasive breast cancer (IBC). Convolutional neural networks (CNNs) can adaptively extract features and may achieve higher efficiency in apparent diffusion coefficient (ADC)-based tumor invasion assessment. This study aimed to determine the feasibility of constructing an ADC-based CNN model to discriminate DCIS from IBC. METHODS The study retrospectively enrolled 700 patients with primary breast cancer between March 2006 and June 2019 from our hospital, and randomly selected 560 patients as the training and validation sets (ratio of 3 to 1), and 140 patients as the internal test set. An independent external test set of 102 patients during July 2019 and May 2021 from a different scanner of our hospital was selected as the primary cohort using the same criteria. In each set, the status of tumor invasion was confirmed by pathologic examination. The CNN model was constructed to discriminate DCIS from IBC using the training and validation sets. The CNN model was evaluated using the internal and external tests, and compared with the discriminating performance using the mean ADC. The area under the curve (AUC), sensitivity, specificity, and accuracy were calculated to evaluate the performance of the previous model. RESULTS The AUCs of the ADC-based CNN model using the internal and external test sets were larger than those of the mean ADC (AUC: 0.977 vs. 0.866, P = 0.001; and 0.926 vs. 0.845, P = 0.096, respectively). Regarding the internal test set and external test set, the ADC-based CNN model yielded sensitivities of 0.893 and 0.873, specificities of 0.929 and 0.894, and accuracies of 0.907 and 0.902, respectively. Regarding the two test sets, the mean ADC showed sensitivities of 0.845 and 0.818, specificities of 0.821 and 0.829, and accuracies of 0.836 and 0.824, respectively. Using the ADC-based CNN model, the prediction only takes approximately one second for a single lesion. CONCLUSION The ADC-based CNN model can improve the differentiation of IBC from DCIS with higher accuracy and less time.
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Affiliation(s)
- Haolin Yin
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Yu Jiang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Zihan Xu
- Lung Cancer Center, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Wenjun Huang
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Tianwu Chen
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Guangwu Lin
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
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Curcean S, Cheng L, Picchia S, Tunariu N, Collins D, Blackledge M, Popat S, O'Brien M, Minchom A, Leach MO, Koh DM. Early Response to Chemotherapy in Malignant Pleural Mesothelioma Evaluated Using Diffusion-Weighted Magnetic Resonance Imaging: Initial Observations. JTO Clin Res Rep 2021; 2:100253. [PMID: 34870249 PMCID: PMC8626584 DOI: 10.1016/j.jtocrr.2021.100253] [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: 08/03/2021] [Revised: 10/22/2021] [Accepted: 10/27/2021] [Indexed: 11/28/2022] Open
Abstract
Introduction We compared the magnetic resonance imaging total tumor volume (TTV) and median apparent diffusion coefficient (ADC) of malignant pleural mesothelioma (MPM) before and at 4 weeks after chemotherapy, to evaluate whether these are potential early markers of treatment response. Methods Diffusion-weighted magnetic resonance imaging was performed in 23 patients with MPM before and after 4 weeks of chemotherapy. The TTV was measured by semiautomatic segmentation (GrowCut) and transferred onto ADC maps to record the median ADC. Test-retest repeatability of TTV and ADC was evaluated in eight patients. TTV and median ADC changes were compared between responders and nonresponders, defined using modified Response Evaluation Criteria In Solid Tumors on computed tomography (CT) at 12 weeks after treatment. TTV and median ADC were also correlated with CT size measurement and disease survival. Results The test-retest 95% limits of agreement for TTV were -13.9% to 16.2% and for median ADC -1.2% to 3.3%. A significant increase in median ADC in responders was observed at 4 weeks after treatment (p = 0.02). Correlation was found between CT tumor size change at 12 weeks and median ADC changes at 4 weeks post-treatment (r = -0.560, p = 0.006). An increase in median ADC greater than 5.1% at 4 weeks has 100% sensitivity and 90% specificity for responders (area under the curve = 0.933, p < 0.001). There was also moderate correlation between median tumor ADC at baseline and overall survival (r = 0.45, p = 0.03). Conclusions Diffusion-weighted magnetic resonance imaging measurements of TTV and median ADC in MPM have good measurement repeatability. Increase in ADC at 4 weeks post-treatment has the potential to be an early response biomarker.
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Affiliation(s)
- Sebastian Curcean
- Department of Radiation Oncology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.,Department of Radiation Oncology, Ion Chiricuta Institute of Oncology, Cluj-Napoca, Romania.,Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Lin Cheng
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom
| | - Simona Picchia
- Department of Radiology, Bordet Institute, Bruxelles, Belgium
| | - Nina Tunariu
- Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - David Collins
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom
| | - Matthew Blackledge
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom
| | - Sanjay Popat
- Department of Medical Oncology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Mary O'Brien
- Department of Medical Oncology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Anna Minchom
- Department of Medical Oncology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Martin O Leach
- Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom.,Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom
| | - Dow-Mu Koh
- Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom.,Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom
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11
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Newitt DC, Amouzandeh G, Partridge SC, Marques HS, Herman BA, Ross BD, Hylton NM, Chenevert TL, Malyarenko DI. Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial. ACTA ACUST UNITED AC 2021; 6:177-185. [PMID: 32548294 PMCID: PMC7289237 DOI: 10.18383/j.tom.2020.00008] [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] [Indexed: 12/26/2022]
Abstract
Mean tumor apparent diffusion coefficient (ADC) of breast cancer showed excellent repeatability but only moderate predictive power for breast cancer therapy response in the ACRIN 6698 multicenter imaging trial. Previous single-center studies have shown improved predictive performance for alternative ADC histogram metrics related to low ADC dense tumor volume. Using test/retest (TT/RT) 4 b-value diffusion-weighted imaging acquisitions from pretreatment or early-treatment time-points on 71 ACRIN 6698 patients, we evaluated repeatability for ADC histogram metrics to establish confidence intervals and inform predictive models for future therapy response analysis. Histograms were generated using regions of interest (ROIs) defined separately for TT and RT diffusion-weighted imaging. TT/RT repeatability and intra- and inter-reader reproducibility (on a 20-patient subset) were evaluated using wCV and Bland–Altman limits of agreement for histogram percentiles, low-ADC dense tumor volumes, and fractional volumes (normalized to total histogram volume). Pearson correlation was used to reveal connections between metrics and ROI variability across the sample cohort. Low percentiles (15th and 25th) were highly repeatable and reproducible, wCV < 8.1%, comparable to mean ADC values previously reported. Volumetric metrics had higher wCV values in all cases, with fractional volumes somewhat better but at least 3 times higher than percentile wCVs. These metrics appear most sensitive to ADC changes around a threshold of 1.2 μm2/ms. Volumetric results were moderately to strongly correlated with ROI size. In conclusion, Lower histogram percentiles have comparable repeatability to mean ADC, while ADC-thresholded volumetric measures currently have poor repeatability but may benefit from improvements in ROI techniques.
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Affiliation(s)
- David C Newitt
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
| | | | | | - Helga S Marques
- Brown University-Center for Statistical Sciences, ECOG-ACRIN Biostatistics Center, Providence, RI
| | - Benjamin A Herman
- Brown University-Center for Statistical Sciences, ECOG-ACRIN Biostatistics Center, Providence, RI
| | - Brian D Ross
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - Nola M Hylton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
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12
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Anjari M, Guha A, Burd C, Varela M, Goh V, Connor S. Apparent diffusion coefficient agreement and reliability using different region of interest methods for the evaluation of head and neck cancer post chemo-radiotherapy. Dentomaxillofac Radiol 2021; 50:20200579. [PMID: 33956510 PMCID: PMC8474130 DOI: 10.1259/dmfr.20200579] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Objectives: Post chemoradiotherapy (CRT) interval changes in apparent diffusion coefficient (ADC) have prognostic value in head and neck squamous cell cancer (HNSCC). The impact of using different region of interest (ROI) methods on interobserver agreement and their ability to reliably detect the changes in the ADC values was assessed. Methods: Following ethical approval, 25 patients (mean age 59.5 years, 21 male) with stage 3–4 HNSCC undergoing CRT were recruited for this prospective cohort study. Diffusion weighted MRI (DW-MRI) was performed pre-treatment and at 6 and 12 weeks following CRT. Two radiologists independently delineated ROIs using whole volume (ROIv), largest area (ROIa) or representative area (ROIr) methods at primary tumour (n = 22) and largest nodal (n = 24) locations and recorded the ADCmean. When no clear focus of increased DWI signal was evident at follow-up, a standardised ROI was placed (non-measurable or NM). Bland-Altman plots and interclass correlation coefficient (ICC) were assessed. Paired t-tests evaluated interval changes in pre- and post-treatment ADCmean at each location, which were compared to the smallest detectable difference (SDD). Results: Excellent agreement was obtained for all ROI methods at pre-treatment (ICC 0.94–0.98) and 6-week post-treatment (ICC 0.94–0.98). At 12-week post-treatment, agreement was excellent (ICC 0.91–0.94) apart from ROIr (ICC 0.86) and the NM nodal disease (ICC 0.87). There were significant interval increases in ADCmean between pre-treatment and post-treatment studies, which were greater than the SDD for all ROIs. Conclusions: ADCmean values can be reproducibly obtained in HNSCC using the different ROI techniques on pre- and post-CRT MRI, and this reliably detects the interval changes.
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Affiliation(s)
- Mustafa Anjari
- Department of Radiology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Amrita Guha
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Department of Radio Diagnosis, Tata Memorial Hospital, Mumbai, India.,Homi Bhabha National Institute, Mumbai, India
| | - Christian Burd
- Department of Radiology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Marta Varela
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Vicky Goh
- Department of Radiology, Guy's and St Thomas' NHS Foundation Trust, London, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Steve Connor
- Department of Radiology, Guy's and St Thomas' NHS Foundation Trust, London, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Neuroradiology Department, King's College Hospital, London, UK
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13
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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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14
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Qualitative characterization of breast tumors with diffusion-weighted imaging has comparable accuracy to quantitative analysis. Clin Imaging 2021; 77:17-24. [PMID: 33639496 DOI: 10.1016/j.clinimag.2021.02.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 01/22/2021] [Accepted: 02/10/2021] [Indexed: 11/20/2022]
Abstract
PURPOSE To evaluate the applicability and accuracy of a new qualitative diffusion-weighted imaging (DWI) assessment method in the characterization of breast tumors compared to quantitative ADC measurement and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS After review board approval, MRIs of 216 consecutive women with final diagnoses (131 malignant, 85 benign) were retrospectively analyzed. Two radiologists independently scored DWI and dynamic contrast-enhanced MRI (DCE-MRI) according to malignancy probability. Qualitative assessments were performed by combined analysis of tumor morphology and diffusion signal. Quantitative data was obtained from apparent diffusion coefficient (ADC) measurements. Lastly, descriptive DWI features were evaluated and recorded. Cohen's kappa, receiver operating characteristic and multivariate analyzes were applied. RESULTS Of malignant tumors, 97% were visible on DWI. Qualitative and quantitative DWI assessments provided comparable sensitivities of 89-94% and 88-92% and specificities of 51-61% and 59-67%, respectively. There was no statistical difference between the accuracies of qualitative and quantitative DWI (p ≥ 0.105). Best diagnostic values were obtained with DCE-MRI (sensitivity, 99-100%; specificity, 69-71%). Inter-reader agreement was moderate (kappa = 0.597) for qualitative DWI and substantial (kappa = 0.689) for DCE-MRI (p < 0.001). Agreement between qualitative DWI and DCE-MRI scores was moderate (kappa = 0.536 and 0.442). Visual diffusion signal, mass margin and shape were the most predictive features of malignancy on multivariate analysis of qualitative assessment. CONCLUSION Qualitative characterization of breast tumors on DWI has comparable accuracy to quantitative ADC analysis. This method might be used to make DWI more widely available with eliminating the need to a predetermined ADC threshold in tumor characterization. However, lower accuracy and inter-reader agreement of it compared to DCE-MRI should be considered.
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15
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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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16
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Transarterial chemoembolization of colorectal cancer liver metastasis: improved tumor response by DSM-TACE versus conventional TACE, a prospective, randomized, single-center trial. Eur Radiol 2020; 31:2242-2251. [PMID: 32960329 DOI: 10.1007/s00330-020-07253-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 07/26/2020] [Accepted: 08/31/2020] [Indexed: 01/17/2023]
Abstract
OBJECTIVES To prospectively evaluate the therapy response of third-line TACE with DSM or lipiodol in the treatment of CRLM using MRI. METHODS In this prospective, randomized, single-center trial, patients were randomly assigned to receive TACE therapy with either lipiodol or DSM as the embolization agent. Therapy response was evaluated using MRI. Local tumor response was determined according to RECIST 1.1, and survival data was analyzed using the Kaplan-Meier estimator. RESULTS Fifty patients (35 male, 15 female) were randomized and included in the survival analysis, whereas 31 patients completed therapy and were considered for evaluation of tumor responses (cTACE: n = 13, DSM-TACE: n = 18). In the cTACE group, PR was observed in 23%, SD in 15%, and PD in 62%. In the DSM-TACE-group, PR was observed in 22% of patients, SD in 56%, and PD in 22% (p = 0.047). In addition, the DSM-TACE group showed statistically significant tumor volume reduction (p = 0.006). Median apparent diffusion coefficient values were not significantly different between both groups at baseline (p = 0.26) and study endpoint (p = 0.83). Median survival in the cTACE group was 13 months (95% confidence interval, range 5-40 months) compared to 16 months (95% confidence interval, range 1-48 months) in the DSM-TACE group, exhibiting no statistically significant difference (p = 0.75). CONCLUSION DSM-TACE showed a significant difference reducing tumor volume and in tumor response according to RECIST 1.1 compared to cTACE. Thus, patients with CRLM might not only benefit from short embolization effect of DSM-TACE but also from better tumor responses. Apparent diffusion coefficients were not significantly different between both groups and cannot be used as a biomarker for monitoring for therapeutic effect of TACE. KEY POINTS • To our knowledge, this is the first prospective study that directly compared cTACE and DSM-TACE in patients with CRLM. • DSM-TACE showed a significant difference reducing tumor volume (p = 0.006) and in tumor response according to RECIST 1.1 (p = 0.047) compared to cTACE. • Survival analysis showed a median survival of 13 months in the cTACE group compared to 16 months in the DSM-TACE group (p = 0.75).
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17
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Vairavan R, Abdullah O, Retnasamy PB, Sauli Z, Shahimin MM, Retnasamy V. A Brief Review on Breast Carcinoma and Deliberation on Current Non Invasive Imaging Techniques for Detection. Curr Med Imaging 2020; 15:85-121. [PMID: 31975658 DOI: 10.2174/1573405613666170912115617] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Revised: 08/27/2017] [Accepted: 08/29/2017] [Indexed: 12/22/2022]
Abstract
BACKGROUND Breast carcinoma is a life threatening disease that accounts for 25.1% of all carcinoma among women worldwide. Early detection of the disease enhances the chance for survival. DISCUSSION This paper presents comprehensive report on breast carcinoma disease and its modalities available for detection and diagnosis, as it delves into the screening and detection modalities with special focus placed on the non-invasive techniques and its recent advancement work done, as well as a proposal on a novel method for the application of early breast carcinoma detection. CONCLUSION This paper aims to serve as a foundation guidance for the reader to attain bird's eye understanding on breast carcinoma disease and its current non-invasive modalities.
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Affiliation(s)
- Rajendaran Vairavan
- School of Microelectronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
| | - Othman Abdullah
- Hospital Sultan Abdul Halim, 08000 Sg. Petani, Kedah, Malaysia
| | | | - Zaliman Sauli
- School of Microelectronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
| | - Mukhzeer Mohamad Shahimin
- Department of Electrical and Electronic Engineering, Faculty of Engineering, National Defence University of Malaysia (UPNM), Kem Sungai Besi, 57000 Kuala Lumpur, Malaysia
| | - Vithyacharan Retnasamy
- School of Microelectronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
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18
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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: 233] [Impact Index Per Article: 46.6] [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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19
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Munhoz L, Nishimura DA, Hisatomi M, Yanagi Y, Asaumi J, Arita ES. Application of diffusion-weighted magnetic resonance imaging in the diagnosis of odontogenic lesions: a systematic review. Oral Surg Oral Med Oral Pathol Oral Radiol 2019; 130:85-100.e1. [PMID: 32007494 DOI: 10.1016/j.oooo.2019.11.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 11/10/2019] [Accepted: 11/15/2019] [Indexed: 11/29/2022]
Abstract
OBJECTIVES This systematic literature review addresses the use of diffusion-weighted magnetic resonance imaging (DWI) and apparent diffusion coefficient (ADC) for the evaluation of benign maxillomandibular odontogenic lesions. STUDY DESIGN Databases were searched, and original research studies or case report manuscripts up to April 2019 were included, using the keyword "diffusion," combined with the keywords "maxillofacial pathology," "oral pathology," "odontogenic tumors," "dental tissue neoplasms," "odontogenic cysts," and the histologic denomination of benign odontogenic lesions, according to the World Health Organization classification. Only English language articles and studies pertaining to DWI were selected. RESULTS Fifteen investigations (11 original articles and 4 case reports) of distinct benign odontogenic lesions were included. Most studies did not include exclusively odontogenic lesions in their samples. CONCLUSIONS It is too early to reach a conclusion that DWI and ADC can provide useful information in the differentiation of the histologic type of some benign odontogenic lesions on the basis of available data in the literature.
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Affiliation(s)
- Luciana Munhoz
- Department of Stomatology, School of Dentistry, São Paulo University, São Paulo, Brazil.
| | | | - Miki Hisatomi
- Department of Dentomaxillofacial Radiology and Oral Diagnosis, Okayama University Hospital, Okayama, Japan
| | - Yoshinobu Yanagi
- Department of Dentomaxillofacial Radiology and Oral Diagnosis, Okayama University Hospital, Okayama, Japan
| | - Junich Asaumi
- Department of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Emiko Saito Arita
- Department of Stomatology, School of Dentistry, São Paulo University, São Paulo, Brazil
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Munhoz L, Ramos EADA, Im DC, Hisatomi M, Yanagi Y, Asaumi J, Arita ES. Application of diffusion-weighted magnetic resonance imaging in the diagnosis of salivary gland diseases: a systematic review. Oral Surg Oral Med Oral Pathol Oral Radiol 2019; 128:280-310. [DOI: 10.1016/j.oooo.2019.02.020] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 02/16/2019] [Accepted: 02/22/2019] [Indexed: 01/02/2023]
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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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Goto M, Le Bihan D, Yoshida M, Sakai K, Yamada K. Adding a Model-free Diffusion MRI Marker to BI-RADS Assessment Improves Specificity for Diagnosing Breast Lesions. Radiology 2019; 292:84-93. [PMID: 31112086 DOI: 10.1148/radiol.2019181780] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Background The apparent diffusion coefficient (ADC) is a commonly used quantitative diffusion-weighted (DW) imaging marker in breast lesion assessment; however, reported ADC values to distinguish malignant and benign lesions show wide variability. Purpose To investigate the diagnostic performance of a tissue signature index (S-index) as a model-free diffusion marker to differentiate malignant and benign breast lesions. Materials and Methods This was a single-institution retrospective study of patients who underwent breast MRI from April 2017 to September 2018. Dynamic contrast-enhanced (DCE) MRI and DW imaging were performed with a 3-T MRI system. For DW imaging, three b values (0, 200, and 1500 sec/mm2) were used for Breast Imaging Reporting and Data Systems (BI-RADS) scoring and to calculate the S-index and a shifted ADC. The diagnostic performances of S-index, shifted ADC, and BI-RADS scoring were evaluated by using receiver operating coefficient analysis. Results The study involved 99 women (mean age, 54 years ± 14 [standard deviation]) with 69 malignant and 38 benign lesions. The S-index was higher for malignant lesions (mean, 75.9 ± 17.4) than for benign lesions (mean, 31.6 ± 21.0; P < .001). Overall diagnostic performance was identical for S-index and shifted ADC (area under the receiver operating characteristic curve [AUC], 0.95; 95% confidence interval [CI]: 0.91, 0.99) and slightly higher than for BI-RADS (AUC, 0.91; 95% CI: 0.87, 0.96; P = .22). The AUC of S-index combined with BI-RADS reached 0.98 (95% CI: 0.96, 1.00), higher than for BI-RADS alone (P < .001), yielding high sensitivity (65 of 69 [94%]; 95% CI: 85%, 98%) and specificity (36 of 38 [95%]; 95% CI: 81%, 99%). Significant differences were identified with the S-index for progesterone receptor and human epidermal growth factor receptor type 2 status (P = .003 and P < .001, respectively). Conclusion The signature index has the potential to enable classification of breast lesion types with high accuracy, especially in combination with dynamic contrast-enhanced MRI and correlates with histologic prognostic factors in invasive breast cancer. © RSNA, 2019 Online supplemental material is available for this article.
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Affiliation(s)
- Mariko Goto
- From the Department of Radiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajiicho, Kawaramachi Hirokoji, Kamigyoku, Kyoto 602-8566, Japan (M.G., M.Y., K.S., K.Y.); and NeuroSpin, Gif-sur-Yvette, France (D.L.B.)
| | - Denis Le Bihan
- From the Department of Radiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajiicho, Kawaramachi Hirokoji, Kamigyoku, Kyoto 602-8566, Japan (M.G., M.Y., K.S., K.Y.); and NeuroSpin, Gif-sur-Yvette, France (D.L.B.)
| | - Mariko Yoshida
- From the Department of Radiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajiicho, Kawaramachi Hirokoji, Kamigyoku, Kyoto 602-8566, Japan (M.G., M.Y., K.S., K.Y.); and NeuroSpin, Gif-sur-Yvette, France (D.L.B.)
| | - Koji Sakai
- From the Department of Radiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajiicho, Kawaramachi Hirokoji, Kamigyoku, Kyoto 602-8566, Japan (M.G., M.Y., K.S., K.Y.); and NeuroSpin, Gif-sur-Yvette, France (D.L.B.)
| | - Kei Yamada
- From the Department of Radiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 465 Kajiicho, Kawaramachi Hirokoji, Kamigyoku, Kyoto 602-8566, Japan (M.G., M.Y., K.S., K.Y.); and NeuroSpin, Gif-sur-Yvette, France (D.L.B.)
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Threshold Isocontouring on High b-Value Diffusion-Weighted Images in Magnetic Resonance Mammography. J Comput Assist Tomogr 2019; 43:434-442. [PMID: 31082949 DOI: 10.1097/rct.0000000000000868] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Motivated by the similar appearance of malignant breast lesions in high b-value diffusion-weighted imaging (DWI) and positron emission tomography, the purpose of this work was to evaluate the applicability of a threshold isocontouring approach commonly used in positron emission tomography to analyze DWI data acquired from female human breasts with minimal interobserver variability. METHODS Twenty-three female participants (59.4 ± 10.0 years) with 23 lesions initially classified as suggestive of cancers in x-ray mammography screening were subsequently imaged on a 1.5-T magnetic resonance imaging scanner. Diffusion-weighted imaging was performed prior to biopsy with b values of 0, 100, 750, and 1500 s/mm. Isocontouring with different threshold levels was performed on the highest b-value image to determine the voxels used for subsequent evaluation of diffusion metrics. The coefficient of variation was computed by specifying 4 different regions of interest drawn around the lesion. Additionally, a receiver operating statistical analysis was performed. RESULTS Using a relative threshold level greater than or equal to 0.85 almost completely suppresses the intra-individual and inter-individual variability. Among 4 studied diffusion metrics, the diffusion coefficients from the intravoxel incoherent motion model returned the highest area under curve value of 0.9. The optimal cut-off diffusivity was found to be 0.85 μm/ms with a sensitivity of 87.5% and specificity of 90.9%. CONCLUSION Threshold isocontouring on high b-value maps is a viable approach to reliably evaluate DWI data of suspicious focal lesions in magnetic resonance mammography.
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Camps-Herrero J. Diffusion-weighted imaging of the breast: current status as an imaging biomarker and future role. BJR Open 2019; 1:20180049. [PMID: 33178933 PMCID: PMC7592470 DOI: 10.1259/bjro.20180049] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Revised: 02/07/2019] [Accepted: 02/12/2019] [Indexed: 12/13/2022] Open
Abstract
Diffusion-weighted imaging (DWI) of the breast is a MRI sequence that shows several advantages when compared to the dynamic contrast-enhanced sequence: it does not need intravenous contrast, it is relatively quick and easy to implement (artifacts notwithstanding). In this review, the current applications of DWI for lesion characterization and prognosis as well as for response evaluation are analyzed from the point of view of the necessary steps to become a useful surrogate of underlying biological processes (tissue architecture and cellularity): from the proof of concept, to the proof of mechanism, the proof of principle and finally the proof of effectiveness. Future applications of DWI in screening, DWI modeling and radiomics are also discussed.
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Affiliation(s)
- Julia Camps-Herrero
- Head of Radiology Department, Breast Unit. Hospital Universitario de la Ribera, Alzira, Spain
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Munhoz L, Abdala Júnior R, Arita ES. The value of the apparent diffusion coefficient calculated from diffusion-weighted magnetic resonance imaging scans in the differentiation of maxillary sinus inflammatory diseases. Oral Surg Oral Med Oral Pathol Oral Radiol 2018; 127:433-443. [PMID: 30600171 DOI: 10.1016/j.oooo.2018.11.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Revised: 10/12/2018] [Accepted: 11/23/2018] [Indexed: 12/24/2022]
Abstract
OBJECTIVES This study examined the value of the apparent diffusion coefficient (ADC) calculated by using diffusion-weighted imaging (DWI) in the differentiation of inflammatory lesions of the maxillary sinus. STUDY DESIGN Sixty-five maxillary sinus magnetic resonance imaging (MRI) scans with findings suggestive of inflammatory lesions were qualitatively categorized into 4 distinct groups by using T2-weighted images: group 1: presence of mucosal thickening; group 2: presence of sinonasal polyps or mucous retention cysts; group 3: presence of fluid identified by air-fluid levels with a homogeneous signal intensity; and group 4: presence of fluid identified by air-fluid levels with a heterogeneous signal intensity. The ADC of each imaging finding was measured by using a 5-mm area of interest. Statistical differences between the groups were determined by using nonparametric tests with a 5% significance level. RESULTS Statistically significant differences were observed between group 1 and the other groups. Mucosal thickening was associated with lower ADC values compared with the other inflammatory lesions. CONCLUSIONS The ADC can be useful in differentiating mucosal thickening from other inflammatory alterations in the maxillary sinuses. Mucosal thickening had more restricted water diffusion compared with the other inflammatory lesions.
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Affiliation(s)
- Luciana Munhoz
- Department of Stomatology, School of Dentistry, São Paulo University, São Paulo, SP, Brazil.
| | - Reinaldo Abdala Júnior
- Department of Stomatology, School of Dentistry, São Paulo University, São Paulo, SP, Brazil
| | - Emiko Saito Arita
- Department of Stomatology, School of Dentistry, São Paulo University, São Paulo, SP, Brazil
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26
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Munhoz L, Abdala Júnior R, Abdala R, Arita ES. Diffusion-weighted magnetic resonance imaging of the paranasal sinuses: A systematic review. Oral Surg Oral Med Oral Pathol Oral Radiol 2018; 126:521-536. [PMID: 30143461 DOI: 10.1016/j.oooo.2018.07.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Revised: 06/29/2018] [Accepted: 07/07/2018] [Indexed: 01/05/2023]
Abstract
OBJECTIVES This was a systematic review of studies on the use of diffusion-weighted imaging (DWI) for paranasal sinus diseases. The applications of DWI were analyzed along with the main results, and conclusions were obtained by the investigators. STUDY DESIGN Databases were searched using the keyword "diffusion" combined with "sinonasal," "paranasal sinus," "maxillary sinus," "frontal sinus," "ethmoid sinus," and "sphenoid sinus," including only articles that were published from 2008 to 2018. Only original English language studies with sinonasal disease samples were selected. RESULTS Sixteen studies about various sinonasal diseases were included. The main objectives of most of the studies were related to the use of the apparent diffusion coefficient (ADC) in the differentiation of benign lesions and malignant neoplasms. We concluded that the ADC for malignant neoplasms is lower. Histologic features of samples evaluated in the studies were heterogeneous. CONCLUSIONS The ADC may improve the quality of the diagnostic hypothesis, particularly in differentiating benign and malignant diseases. Furthermore, the differences between certain types of lesions could be determined by using the ADC. However, further studies focusing on inflammatory diseases should be performed. Overall, DWI and the ADC are promising methods that can be incorporated into routine evaluations.
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Affiliation(s)
- Luciana Munhoz
- Department of Stomatology, School of Dentistry, São Paulo University, São Paulo, SP, Brazil.
| | - Reinaldo Abdala Júnior
- Department of Stomatology, School of Dentistry, São Paulo University, São Paulo, SP, Brazil
| | - Rogério Abdala
- CDB - Centro de Diagnósticos Brasil, São Paulo, SP, Brazil
| | - Emiko Saito Arita
- Department of Stomatology, School of Dentistry, São Paulo University, São Paulo, SP, Brazil
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Stahle JA, Larson MM, Rossmeisl JH, Dervisis N, Neelis D. Diffusion weighted magnetic resonance imaging is a feasible method for characterizing regional lymph nodes in canine patients with head and neck disease. Vet Radiol Ultrasound 2018; 60:176-183. [DOI: 10.1111/vru.12694] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2017] [Revised: 08/06/2018] [Accepted: 08/09/2018] [Indexed: 12/24/2022] Open
Affiliation(s)
- Jessica A. Stahle
- Department of Radiology; Red Bank Veterinary Hospital; Mount Laurel NJ 08054
| | - Martha M. Larson
- Small Animal Clinical Sciences; Virginia Polytechnic and State University; Blacksburg VA 24061
| | - John H. Rossmeisl
- Small Animal Clinical Sciences; Virginia Polytechnic and State University; Blacksburg VA 24061
| | - Nick Dervisis
- Small Animal Clinical Sciences; Virginia Polytechnic and State University; Blacksburg VA 24061
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Newitt DC, Zhang Z, Gibbs JE, Partridge SC, Chenevert TL, Rosen MA, Bolan PJ, Marques HS, Aliu S, Li W, Cimino L, Joe BN, Umphrey H, Ojeda-Fournier H, Dogan B, Oh K, Abe H, Drukteinis J, Esserman LJ, Hylton NM. Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial. J Magn Reson Imaging 2018; 49:1617-1628. [PMID: 30350329 DOI: 10.1002/jmri.26539] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Revised: 09/20/2018] [Accepted: 09/22/2018] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Quantitative diffusion-weighted imaging (DWI) MRI is a promising technique for cancer characterization and treatment monitoring. Knowledge of the reproducibility of DWI metrics in breast tumors is necessary to apply DWI as a clinical biomarker. PURPOSE To evaluate the repeatability and reproducibility of breast tumor apparent diffusion coefficient (ADC) in a multi-institution clinical trial setting, using standardized DWI protocols and quality assurance (QA) procedures. STUDY TYPE Prospective. SUBJECTS In all, 89 women from nine institutions undergoing neoadjuvant chemotherapy for invasive breast cancer. FIELD STRENGTH/SEQUENCE DWI was acquired before and after patient repositioning using a four b-value, single-shot echo-planar sequence at 1.5T or 3.0T. ASSESSMENT A QA procedure by trained operators assessed artifacts, fat suppression, and signal-to-noise ratio, and determine study analyzability. Mean tumor ADC was measured via manual segmentation of the multislice tumor region referencing DWI and contrast-enhanced images. Twenty cases were evaluated multiple times to assess intra- and interoperator variability. Segmentation similarity was assessed via the Sørenson-Dice similarity coefficient. STATISTICAL TESTS Repeatability and reproducibility were evaluated using within-subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), agreement index (AI), and repeatability coefficient (RC). Correlations were measured by Pearson's correlation coefficients. RESULTS In all, 71 cases (80%) passed QA evaluation: 44 at 1.5T, 27 at 3.0T; 60 pretreatment, 11 after 3 weeks of taxane-based treatment. ADC repeatability was excellent: wCV = 4.8% (95% confidence interval [CI] 4.0, 5.7%), ICC = 0.97 (95% CI 0.95, 0.98), AI = 0.83 (95% CI 0.76, 0.87), and RC = 0.16 * 10-3 mm2 /sec (95% CI 0.13, 0.19). The results were similar across field strengths and timepoint subgroups. Reproducibility was excellent: interreader ICC = 0.92 (95% CI 0.80, 0.97) and intrareader ICC = 0.91 (95% CI 0.78, 0.96). DATA CONCLUSION Breast tumor ADC can be measured with excellent repeatability and reproducibility in a multi-institution setting using a standardized protocol and QA procedure. Improvements to DWI image quality could reduce loss of data in clinical trials. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1617-1628.
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Affiliation(s)
- David C Newitt
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Zheng Zhang
- Department of Biostatistics, Brown University, Providence, Rhode Island, USA.,Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA.,American College of Radiology Imaging Network (ACRIN), Philadelphia, Pennsylvania, USA
| | - Jessica E Gibbs
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | | | - Thomas L Chenevert
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Mark A Rosen
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Patrick J Bolan
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Helga S Marques
- Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA.,American College of Radiology Imaging Network (ACRIN), Philadelphia, Pennsylvania, USA
| | - Sheye Aliu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Wen Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Lisa Cimino
- American College of Radiology & ECOG-ACRIN Cancer Research Group, Philadelphia, Pennsylvania, USA
| | - Bonnie N Joe
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Heidi Umphrey
- Department of Radiology, University of Alabama, Birmingham, Alabama, USA
| | | | - Basak Dogan
- Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Department of Diagnostic Radiology, University of Texas Southwestern Medical Center, Houston, Texas, USA
| | - Karen Oh
- Department of Radiology, Oregon Health & Science University, Portland, Oregon, USA
| | - Hiroyuki Abe
- Department of Radiology, University of Chicago, Chicago, Illinois, USA
| | - Jennifer Drukteinis
- H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.,Department of Women's Imaging, St. Joseph's Women's Hospital, Tampa, Florida, USA
| | - Laura J Esserman
- Department of Surgery, University of California, San Francisco, California, USA
| | - Nola M Hylton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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Histogram analysis of apparent diffusion coefficient maps in the prognosis of patients with locally advanced head and neck squamous cell carcinoma: Comparison of different region of interest selection methods. Eur J Radiol 2018; 106:7-13. [DOI: 10.1016/j.ejrad.2018.07.004] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Revised: 05/24/2018] [Accepted: 07/03/2018] [Indexed: 11/23/2022]
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Association among T2 signal intensity, necrosis, ADC and Ki-67 in estrogen receptor-positive and HER2-negative invasive ductal carcinoma. Magn Reson Imaging 2018; 54:176-182. [PMID: 30172938 DOI: 10.1016/j.mri.2018.08.017] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2018] [Revised: 08/13/2018] [Accepted: 08/27/2018] [Indexed: 12/23/2022]
Abstract
PURPOSE To determine whether T2 signal intensity, necrosis, and ADC values are associated with Ki-67 in patients with Estrogen Receptor (ER)-positive and Human epidermal growth factor receptor type 2 (HER2)-negative invasive ductal carcinoma (IDC). MATERIALS AND METHODS Between March 2012 and February 2013, one hundred eighty seven women with ER-positive and HER2-negative IDC who underwent breast MRI and subsequent surgery were included. Intratumoral signal intensity was evaluated based on a combination of T2-weighted (low or equal, high, or very high) and contrast-enhanced MR images (enhancement or not). Necrosis was defined as very high T2 and no enhancement. Using the analysis of variance and pairwise t-test, a model based on intratumoral signal intensity was developed to assess Ki-67 of the surgical specimen. Inter-observer agreement for the developed model was analyzed. Conventional mean and minimum apparent diffusion coefficient (ADC) measurements were performed and correlated with Ki-67. RESULTS As the grade of the developed model increased (Grade I: low or equal T2, Grade II: high T2, or necrosis < 50%, Grade III: necrosis ≥ 50%), mean Ki-67 significantly increased (Grade I to III: 12.5%, 17.6%, 45.0%, respectively; P < 0.001). Good inter-observer agreement was found for the model (κ = 0.846, P < 0.001). ADC did not show significant correlations with Ki-67 (Pearson's correlation coefficient, 0.140 [P = 0.057] for mean ADC; -0.079 [P = 0.284] for minimum ADC). CONCLUSION Intratumoral signal intensity but not ADC was associated with Ki-67 in patients with ER-positive and HER2-negative IDC.
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Munhoz L, Abdala Júnior R, Abdala R, Asaumi J, Arita ES. Diffusion-Weighted Magnetic Resonance Imaging in Maxillary Sinuses Inflammatory Diseases: Report of Three Cases and Literature Review. EJOURNAL OF ORAL MAXILLOFACIAL RESEARCH 2018; 9:e4. [PMID: 30116516 PMCID: PMC6090247 DOI: 10.5037/jomr.2018.9204] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 06/25/2018] [Indexed: 01/15/2023]
Abstract
Background Magnetic resonance imaging is considered a preferable imaging examination in the diagnosis of inflammatory maxillary sinus disease and can provide precise sinonasal characterization. Diffusion-weighted magnetic resonance imaging and apparent diffusion coefficient are complementary magnetic resonance imaging tools that can be applied to the differentiation of sinus diseases. In this report, 3 cases of inflammatory maxillary sinus diseases imaging findings considering diffusion-weighted magnetic resonance imaging features were described. Additionally, a literature review considering the use of diffusion-weighted magnetic resonance imaging in inflammatory lesions is provided. Methods The cases reported were: presence of air-fluid levels, mucosal thickening and a mucous retention cyst. Conventional magnetic resonance imaging and apparent diffusion coefficient (ADC) maps, with ADC values were demonstrated. In the literature review, the studies considering inflammatory lesions were detailed, as well as ADC values established by investigators. Results ADC values for presence of air-fluid levels, mucosal thickening and mucous retention cyst were respectively: 1.99 x 10-3 mm2/s; 1.83 x 10-3 mm2/s; 2.05 x 10-3 mm2/s. Conclusions It was observed that apparent diffusion coefficient values from the inflammatory lesions described in this report were different and apparent diffusion coefficient may be useful in the differentiation of these maxillary sinus alterations. Further larger sample investigations considering apparent diffusion coefficient values focusing in inflammatory lesions are recommended. The lack of studies considering the use of diffusion-weighted magnetic resonance imaging on inflammatory diseases diagnostic was the major limitation to the literature review.
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Affiliation(s)
- Luciana Munhoz
- Department of Stomatology, School of Dentistry, São Paulo University, São PauloBrazil
| | | | | | - Junichi Asaumi
- Departament of Oral and Maxillofacial Radiology, Okayama University, OkayamaJapan
| | - Emiko Saito Arita
- Department of Stomatology, School of Dentistry, São Paulo University, São PauloBrazil
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Sorace AG, Wu C, Barnes SL, Jarrett AM, Avery S, Patt D, Goodgame B, Luci JJ, Kang H, Abramson RG, Yankeelov TE, Virostko J. Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting. J Magn Reson Imaging 2018; 48:10.1002/jmri.26011. [PMID: 29570895 PMCID: PMC6151298 DOI: 10.1002/jmri.26011] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 03/02/2018] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Quantitative diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) have the potential to impact patient care by providing noninvasive biological information in breast cancer. PURPOSE/HYPOTHESIS To quantify the repeatability, reproducibility, and accuracy of apparent diffusion coefficient (ADC) and T1 -mapping of the breast in community radiology practices. STUDY TYPE Prospective. SUBJECTS/PHANTOM Ice-water DW-MRI and T1 gel phantoms were used to assess accuracy. Normal subjects (n = 3) and phantoms across three sites (one academic, two community) were used to assess reproducibility. Test-retest analysis at one site in normal subjects (n = 12) was used to assess repeatability. FIELD STRENGTH/SEQUENCE 3T Siemens Skyra MRI quantitative DW-MRI and T1 -mapping. ASSESSMENT Quantitative DW-MRI and T1 -mapping parametric maps of phantoms and fibroglandular and adipose tissue of the breast. STATISTICAL TESTS Average values of breast tissue were quantified and Bland-Altman analysis was performed to assess the repeatability of the MRI techniques, while the Friedman test assessed reproducibility. RESULTS ADC measurements were reproducible across sites, with an average difference of 1.6% in an ice-water phantom and 7.0% in breast fibroglandular tissue. T1 measurements in gel phantoms had an average difference of 2.8% across three sites, whereas breast fibroglandular and adipose tissue had 8.4% and 7.5% average differences, respectively. In the repeatability study, we found no bias between first and second scanning sessions (P = 0.1). The difference between repeated measurements was independent of the mean for each MRI metric (P = 0.156, P = 0.862, P = 0.197 for ADC, T1 of fibroglandular tissue, and T1 of adipose tissue, respectively). DATA CONCLUSION Community radiology practices can perform repeatable, reproducible, and accurate quantitative T1 -mapping and DW-MRI. This has the potential to dramatically expand the number of sites that can participate in multisite clinical trials and increase clinical translation of quantitative MRI techniques for cancer response assessment. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.
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Affiliation(s)
- Anna G. Sorace
- Department of Diagnostic Medicine, University of Texas at Austin, Austin, Texas, USA
- Livestrong Cancer Institutes, University of Texas at Austin, Austin, Texas, USA
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
| | - Chengyue Wu
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
| | - Stephanie L. Barnes
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
- Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA
| | - Angela M. Jarrett
- Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA
| | - Sarah Avery
- Austin Radiological Association, Austin, Texas, USA
| | | | - Boone Goodgame
- Seton Hospital, Austin, Texas, USA
- Department of Internal Medicine, University of Texas at Austin, Austin, Texas, USA
| | - Jeffery J. Luci
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
- Department of Neuroscience, University of Texas at Austin, Austin, Texas, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Richard G. Abramson
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Thomas E. Yankeelov
- Department of Diagnostic Medicine, University of Texas at Austin, Austin, Texas, USA
- Livestrong Cancer Institutes, University of Texas at Austin, Austin, Texas, USA
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
- Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA
| | - John Virostko
- Department of Diagnostic Medicine, University of Texas at Austin, Austin, Texas, USA
- Livestrong Cancer Institutes, University of Texas at Austin, Austin, Texas, USA
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Sasaki T, Kim J, Moritani T, Capizzano AA, Sato SP, Sato Y, Kirby P, Ishitoya S, Oya A, Toda M, Yuzawa S, Takahashi K. Roles of the apparent diffusion coefficient and tumor volume in predicting tumor grade in patients with choroid plexus tumors. Neuroradiology 2018; 60:479-486. [DOI: 10.1007/s00234-018-2008-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Accepted: 02/27/2018] [Indexed: 12/24/2022]
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Iima M, Kataoka M, Kanao S, Kawai M, Onishi N, Koyasu S, Murata K, Ohashi A, Sakaguchi R, Togashi K. Variability of non-Gaussian diffusion MRI and intravoxel incoherent motion (IVIM) measurements in the breast. PLoS One 2018; 13:e0193444. [PMID: 29494639 PMCID: PMC5832256 DOI: 10.1371/journal.pone.0193444] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 02/12/2018] [Indexed: 01/12/2023] Open
Abstract
We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0–2500 s/mm2 with one number of excitations [NEX]) and five b-values (0–2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
- The Hakubi Center for Advanced Research, Kyoto University, Kyoto, Japan
- * E-mail:
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Shotaro Kanao
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Makiko Kawai
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Natsuko Onishi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Sho Koyasu
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | | | - Akane Ohashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Rena Sakaguchi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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deSouza NM, Winfield JM, Waterton JC, Weller A, Papoutsaki MV, Doran SJ, Collins DJ, Fournier L, Sullivan D, Chenevert T, Jackson A, Boss M, Trattnig S, Liu Y. Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives. Eur Radiol 2018; 28:1118-1131. [PMID: 28956113 PMCID: PMC5811587 DOI: 10.1007/s00330-017-4972-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Revised: 05/24/2017] [Accepted: 06/28/2017] [Indexed: 12/18/2022]
Abstract
For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology. KEY POINTS • Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing "precision" of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research.
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Affiliation(s)
- N. M. deSouza
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - J. M. Winfield
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - J. C. Waterton
- Manchester Academic Health Sciences Institute, University of Manchester, Manchester, UK
| | - A. Weller
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - M.-V. Papoutsaki
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - S. J. Doran
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - D. J. Collins
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - L. Fournier
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Radiology Department, Université Paris Descartes Sorbonne Paris Cité, Paris, France
| | - D. Sullivan
- Duke Comprehensive Cancer Institute, Durham, NC USA
| | - T. Chenevert
- Department of Radiology, University of Michigan Health System, Ann Arbor, MI USA
| | - A. Jackson
- Manchester Academic Health Sciences Institute, University of Manchester, Manchester, UK
| | - M. Boss
- Applied Physics Division, National Institute of Standards and Technology (NIST), Boulder, CO USA
| | - S. Trattnig
- Department of Biomedical Imaging and Image guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Y. Liu
- European Organisation for Research and Treatment of Cancer, Headquarters, Brussels, Belgium
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Moreau B, Iannessi A, Hoog C, Beaumont H. How reliable are ADC measurements? A phantom and clinical study of cervical lymph nodes. Eur Radiol 2018; 28:3362-3371. [PMID: 29476218 PMCID: PMC6028847 DOI: 10.1007/s00330-017-5265-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 12/11/2017] [Accepted: 12/20/2017] [Indexed: 12/11/2022]
Abstract
Objective To assess the reliability of ADC measurements in vitro and in cervical lymph nodes of healthy volunteers. Methods We used a GE 1.5 T MRI scanner and a first ice-water phantom according to recommendations released by the Quantitative Imaging Biomarker Alliance (QIBA) for assessing ADC against reference values. We analysed the target size effect by using a second phantom made of six inserted spheres with diameters ranging from 10 to 37 mm. Thirteen healthy volunteers were also scanned to assess the inter- and intra-observer reproducibility of volumetric ADC measurements of cervical lymph nodes. Results On the ice-water phantom, the error in ADC measurements was less than 4.3 %. The spatial bias due to the non-linearity of gradient fields was found to be 24 % at 8 cm from the isocentre. ADC measure reliability decreased when addressing small targets due to partial volume effects (up to 12.8 %). The mean ADC value of cervical lymph nodes was 0.87.10-3 ± 0.12.10-3 mm2/s with a good intra-observer reliability. Inter-observer reproducibility featured a bias of -5.5 % due to segmentation issues. Conclusion ADC is a potentially important imaging biomarker in oncology; however, variability issues preclude its broader adoption. Reliable use of ADC requires technical advances and systematic quality control. Key Points • ADC is a promising quantitative imaging biomarker. • ADC has a fair inter-reader variability and good intra-reader variability. • Partial volume effect, post-processing software and non-linearity of scanners are limiting factors. • No threshold values for detecting cervical lymph node malignancy can be drawn. Electronic supplementary material The online version of this article (10.1007/s00330-017-5265-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Bastien Moreau
- Department of Radiology, Centre Antoine Lacassagne, 06100, Nice, France
| | - Antoine Iannessi
- Department of Radiology, Centre Antoine Lacassagne, 06100, Nice, France
| | - Christopher Hoog
- Department of Radiology, Centre Antoine Lacassagne, 06100, Nice, France
| | - Hubert Beaumont
- Research and Development Department, Median Technologies, Les deux arcs - 1800 route des crêtes - Bat. B, 06560, Valbonne, France.
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Newitt DC, Malyarenko D, Chenevert TL, Quarles CC, Bell L, Fedorov A, Fennessy F, Jacobs MA, Solaiyappan M, Hectors S, Taouli B, Muzi M, Kinahan PE, Schmainda KM, Prah MA, Taber EN, Kroenke C, Huang W, Arlinghaus LR, Yankeelov TE, Cao Y, Aryal M, Yen YF, Kalpathy-Cramer J, Shukla-Dave A, Fung M, Liang J, Boss M, Hylton N. Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network. J Med Imaging (Bellingham) 2018; 5:011003. [PMID: 29021993 PMCID: PMC5633866 DOI: 10.1117/1.jmi.5.1.011003] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Accepted: 09/12/2017] [Indexed: 12/26/2022] Open
Abstract
Diffusion weighted MRI has become ubiquitous in many areas of medicine, including cancer diagnosis and treatment response monitoring. Reproducibility of diffusion metrics is essential for their acceptance as quantitative biomarkers in these areas. We examined the variability in the apparent diffusion coefficient (ADC) obtained from both postprocessing software implementations utilized by the NCI Quantitative Imaging Network and online scan time-generated ADC maps. Phantom and in vivo breast studies were evaluated for two ([Formula: see text]) and four ([Formula: see text]) [Formula: see text]-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and in vivo [Formula: see text], with relative biases [Formula: see text] ([Formula: see text]) and [Formula: see text] (phantom [Formula: see text]) but with higher deviations in ADC at the lowest phantom ADC values. In vivo [Formula: see text] concordance was good, with typical biases of [Formula: see text] to 3% but higher for online maps. Multiple b-value ADC implementations were separated into two groups determined by the fitting algorithm. Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for [Formula: see text] in vivo data. Some higher deviations were found for individual implementations and online parametric maps. Despite generally good concordance, implementation biases in ADC measures are sometimes significant and may be large enough to be of concern in multisite studies.
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Affiliation(s)
- David C. Newitt
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, United States
| | - Dariya Malyarenko
- University of Michigan, Department of Radiology, Ann Arbor, Michigan, United States
| | - Thomas L. Chenevert
- University of Michigan, Department of Radiology, Ann Arbor, Michigan, United States
| | - C. Chad Quarles
- Barrow Neurological Institute, Division of Imaging Research, Phoenix, Arizona, United States
| | - Laura Bell
- Barrow Neurological Institute, Division of Imaging Research, Phoenix, Arizona, United States
| | - Andriy Fedorov
- Harvard Medical School, Brigham and Women’s Hospital, Department of Radiology, Boston, Massachusetts, United States
| | - Fiona Fennessy
- Harvard Medical School, Brigham and Women’s Hospital, Department of Radiology, Boston, Massachusetts, United States
| | - Michael A. Jacobs
- The Johns Hopkins School of Medicine, Russell H. Morgan Department of Radiology and Radiological Science and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland, United States
| | - Meiyappan Solaiyappan
- The Johns Hopkins School of Medicine, Russell H. Morgan Department of Radiology and Radiological Science and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland, United States
| | - Stefanie Hectors
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, United States
| | - Bachir Taouli
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, United States
| | - Mark Muzi
- University of Washington, Department of Radiology, Neurology, and Radiation Oncology, Seattle, Washington, United States
| | - Paul E. Kinahan
- University of Washington, Department of Radiology, Neurology, and Radiation Oncology, Seattle, Washington, United States
| | - Kathleen M. Schmainda
- Medical College of Wisconsin, Department of Radiology, Milwaukee, Wisconsin, United States
| | - Melissa A. Prah
- Medical College of Wisconsin, Department of Radiology, Milwaukee, Wisconsin, United States
| | - Erin N. Taber
- Oregon Health and Science University, Advanced Imaging Research Center, Portland, Oregon, United States
| | - Christopher Kroenke
- Oregon Health and Science University, Advanced Imaging Research Center, Portland, Oregon, United States
| | - Wei Huang
- Oregon Health and Science University, Advanced Imaging Research Center, Portland, Oregon, United States
| | - Lori R. Arlinghaus
- Vanderbilt University Medical Center, Vanderbilt University Institute of Imaging Science, Nashville, Tennessee, United States
| | - Thomas E. Yankeelov
- The University of Texas at Austin, Institute for Computational and Engineering Sciences, Department of Biomedical Engineering and Diagnostic Medicine, Austin, Texas, United States
| | - Yue Cao
- University of Michigan, Radiation Oncology, Radiology, and Biomedical Engineering, Ann Arbor, Michigan, United States
| | - Madhava Aryal
- University of Michigan, Radiation Oncology, Radiology, and Biomedical Engineering, Ann Arbor, Michigan, United States
| | - Yi-Fen Yen
- Harvard Medical School, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Jayashree Kalpathy-Cramer
- Harvard Medical School, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Amita Shukla-Dave
- Memorial Sloan-Kettering Cancer Center, Department of Medical Physics and Radiology, New York, New York, United States
| | - Maggie Fung
- Memorial Sloan-Kettering Cancer Center, GE Healthcare, New York, New York, United States
| | | | - Michael Boss
- National Institute of Standards and Technology, Applied Physics Division, Boulder, Colorado, United States
- University of Colorado Boulder, Department of Physics, Boulder, Colorado, United States
| | - Nola Hylton
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, United States
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Short tau inversion recovery in breast diffusion-weighted imaging: signal-to-noise ratio and apparent diffusion coefficients using a breast phantom in comparison with spectral attenuated inversion recovery. Radiol Med 2017; 123:296-304. [PMID: 29230679 DOI: 10.1007/s11547-017-0840-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 11/30/2017] [Indexed: 12/25/2022]
Abstract
OBJECTIVE This study aimed to compare the signal-to-noise ratios (SNRs) and apparent diffusion coefficients (ADCs) obtained using two fat suppression techniques in breast diffusion-weighted imaging (DWI) of a phantom. MATERIALS AND METHODS The breast phantom comprised agar gels with four different concentrations of granulated sugar (samples 1, 2, 3, and 4). DWI with short tau inversion recovery (STIR-DWI) and that with spectral attenuated inversion recovery (SPAIR-DWI) were performed using 3.0-T magnetic resonance imaging, and the obtained SNRs and ADCs were compared. ADCs were also compared between the right and left breast phantoms. RESULTS For samples 3 and 4, SNRs obtained using STIR-DWI were lower than those obtained using SPAIR-DWI. For samples 2, 3, and 4, overall ADCs obtained using STIR-DWI were significantly higher than those obtained using SPAIR-DWI (p < 0.001 for all), although no significant difference was observed for sample 1 (p = 0.62). STIR-DWI shows a positive bias and wide limits of agreement in Bland-Altman plot. The coefficients of variance of overall ADCs were good in STIR-DWI and SPAIR-DWI. For all samples, STIR-DWI demonstrated slightly larger percentage differences in ADCs between the right and left phantoms than SPAIR-DWI. CONCLUSION SNRs and ADCs obtained using STIR-DWI are influenced by the T 1 value; a shorter T 1 value decreases SNRs, overestimates ADCs, and induces the measurement error in ADCs. STIR-DWI showed a larger difference in ADCs between the right and left phantoms than SPAIR-DWI.
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Wagner F, Laun FB, Kuder TA, Mlynarska A, Maier F, Faust J, Demberg K, Lindemann L, Rivkin B, Nagel AM, Ladd ME, Maier-Hein K, Bickelhaupt S, Bach M. Temperature and concentration calibration of aqueous polyvinylpyrrolidone (PVP) solutions for isotropic diffusion MRI phantoms. PLoS One 2017; 12:e0179276. [PMID: 28628638 PMCID: PMC5476261 DOI: 10.1371/journal.pone.0179276] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Accepted: 05/27/2017] [Indexed: 12/12/2022] Open
Abstract
To use the "apparent diffusion coefficient" (Dapp) as a quantitative imaging parameter, well-suited test fluids are essential. In this study, the previously proposed aqueous solutions of polyvinylpyrrolidone (PVP) were examined and temperature calibrations were obtained. For example, at a temperature of 20°C, Dapp ranged from 1.594 (95% CI: 1.593, 1.595) μm2/ms to 0.3326 (95% CI: 0. 3304, 0.3348) μm2/ms for PVP-concentrations ranging from 10% (w/w) to 50% (w/w) using K30 polymer lengths. The temperature dependence of Dapp was found to be so strong that a negligence seems not advisable. The temperature dependence is descriptively modelled by an exponential function exp(c2 (T - 20°C)) and the determined c2 values are reported, which can be used for temperature calibration. For example, we find the value 0.02952 K-1 for 30% (w/w) PVP-concentration and K30 polymer length. In general, aqueous PVP solutions were found to be suitable to produce easily applicable and reliable Dapp-phantoms.
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Affiliation(s)
- Friedrich Wagner
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Frederik B. Laun
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Tristan A. Kuder
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Anna Mlynarska
- Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Florian Maier
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jonas Faust
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Kerstin Demberg
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Linus Lindemann
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Boris Rivkin
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Armin M. Nagel
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Mark E. Ladd
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Klaus Maier-Hein
- Medical and Biological Informatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Michael Bach
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Tsili AC, Ntorkou A, Astrakas L, Xydis V, Tsampalas S, Sofikitis N, Argyropoulou MI. Diffusion-weighted magnetic resonance imaging in the characterization of testicular germ cell neoplasms: Effect of ROI methods on apparent diffusion coefficient values and interobserver variability. Eur J Radiol 2017; 89:1-6. [DOI: 10.1016/j.ejrad.2017.01.017] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Revised: 01/09/2017] [Accepted: 01/17/2017] [Indexed: 01/08/2023]
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Priola AM, Priola SM, Gned D, Giraudo MT, Brundu M, Righi L, Veltri A. Diffusion-weighted quantitative MRI of pleural abnormalities: Intra- and interobserver variability in the apparent diffusion coefficient measurements. J Magn Reson Imaging 2017; 46:769-782. [PMID: 28117923 DOI: 10.1002/jmri.25633] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 12/28/2016] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To assess intra- and interobserver variability in the apparent diffusion coefficient (ADC) measurements of pleural abnormalities. MATERIALS AND METHODS Diffusion-weighted magnetic resonance imaging was performed in 34 patients to characterize pleural abnormalities, with a 1.5T unit at b values of 0/150/500/800 sec/mm2 . In two sessions held 3 months apart, on perfusion-free ADC maps, two independent readers measured the ADC of pleural abnormalities (two readings for each reader in each case) using different methods of region-of-interest (ROI) positioning. In three methods, freehand ROIs were drawn within tumor boundaries to encompass the entire lesion on one or more axial slices (whole tumor volume [WTV], three slices observer-defined [TSOD], single-slice [SS]), while in two methods one or more ROIs were placed on the more restricted areas (multiple small round ROI [MSR], one small round ROI [OSR]). Measurement variability between readings by each reader (intraobserver repeatability) and between readers in first reading (interobserver repeatability) were assessed using intraclass correlation coefficient (ICC) and coefficient of variation (CoV). Analysis of variance (ANOVA) was performed to compare ADC values between the different methods. The measurement time of each case for all methods in first reading was recorded and compared between methods and readers. RESULTS All methods demonstrated good (MSR, OSR) and excellent (WTV, TSOD, SS) intra- and interreader agreement, with best and worst repeatability in WTV (lower ICC, 0.977; higher CoV, 3.5%) and OSR (lower ICC, 0.625; higher CoV, 22.8%), respectively. The lower 95% confidence interval of ICC resulted in fair to moderate agreement for OSR (up to 0.379) and in excellent agreement for WTV, TSV, and SS (up to 0.918). ADC values of OSR and MSR were significantly lower compared to other methods (P < 0.001). The OSR and SS required less measurement time (10 and 21/22 sec, respectively) compared to the others (P < 0.0001), while the WTV required the longest measurement time (132/134 sec) (P < 0.0001). CONCLUSION ADC measurements of pleural abnormalities are repeatable. The SS method has excellent repeatability, similar to WTV, but requires significantly less measurement time. Thus, its use should be preferred in clinical practice. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:769-782.
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Affiliation(s)
| | - Sandro Massimo Priola
- Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
| | - Dario Gned
- Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
| | | | - Maria Brundu
- Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
| | - Luisella Righi
- Department of Pathology, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
| | - Andrea Veltri
- Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Orbassano (Torino), Italy
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Hering J, Laun FB, Lederer W, Daniel H, Kuder TA, Stieber A, Delorme S, Maier-Hein KH, Schlemmer HP, Bickelhaupt S. Applicability and discriminative value of a semiautomatic three-dimensional spherical volume for the assessment of the apparent diffusion coefficient in suspicious breast lesions—feasibility study. Clin Imaging 2016; 40:1280-1285. [DOI: 10.1016/j.clinimag.2016.08.022] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2016] [Revised: 08/02/2016] [Accepted: 08/30/2016] [Indexed: 01/01/2023]
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Spick C, Bickel H, Pinker K, Bernathova M, Kapetas P, Woitek R, Clauser P, Polanec SH, Rudas M, Bartsch R, Helbich TH, Baltzer PA. Diffusion-weighted MRI of breast lesions: a prospective clinical investigation of the quantitative imaging biomarker characteristics of reproducibility, repeatability, and diagnostic accuracy. NMR IN BIOMEDICINE 2016; 29:1445-1453. [PMID: 27553252 DOI: 10.1002/nbm.3596] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 07/08/2016] [Accepted: 07/08/2016] [Indexed: 06/06/2023]
Abstract
Diffusion-weighted MRI (DWI) provides insights into tissue microstructure by visualization and quantification of water diffusivity. Quantitative evaluation of the apparent diffusion coefficient (ADC) obtained from DWI has been proven helpful for differentiating between malignant and benign breast lesions, for cancer subtyping in breast cancer patients, and for prediction of response to neoadjuvant chemotherapy. However, to further establish DWI of breast lesions it is important to evaluate the quantitative imaging biomarker (QIB) characteristics of reproducibility, repeatability, and diagnostic accuracy. In this intra-individual prospective clinical study 40 consecutive patients with suspicious findings, scheduled for biopsy, underwent an identical 3T breast MRI protocol of the breast on two consecutive days (>24 h). Mean ADC of target lesions was assessed (two independent readers) in four separate sessions. Reproducibility, repeatability, and diagnostic accuracy between examinations (E1, E2), readers (R1, R2), and measurements (M1, M2) were assessed with intraclass correlation coefficients (ICCs), coefficients of variation (CVs), Bland-Altman plots, and receiver operating characteristic (ROC) analysis with calculation of the area under the ROC curve (AUC). The standard of reference was either histopathology (n = 38) or imaging follow-up of up to 24 months (n = 2). Eighty breast MRI examinations (median E1-E2, 2 ± 1.7 days, 95% confidence interval (CI) 1-2 days, range 1-11 days) in 40 patients (mean age 56, standard deviation (SD) ±14) were evaluated. In 55 target lesions (mean size 25.2 ± 20.8 (SD) mm, range 6-106 mm), mean ADC values were significantly (P < 0.0001) higher in benign (1.38, 95% CI 1.27-1.49 × 10(-3) mm(2) /s) compared with malignant (0.86, 95% CI 0.81-0.91 × 10(-) (3) mm(2) /s) lesions. Reproducibility and repeatability showed high agreement for repeated examinations, readers, and measurements (all ICCs >0.9, CVs 3.2-8%), indicating little variation. Bland-Altman plots demonstrated no systematic differences, and diagnostic accuracy was not significantly different in the two repeated examinations (all ROC curves >0.91, P > 0.05). High reproducibility, repeatability, and diagnostic accuracy of DWI provide reliable characteristics for its use as a potential QIB, to further improve breast lesion detection, characterization, and treatment monitoring of breast lesions.
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Affiliation(s)
- Claudio Spick
- 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
| | - Hubert Bickel
- 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 Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, A-1090, Vienna, Austria
| | - Maria Bernathova
- 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
| | - 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
| | - Ramona Woitek
- 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
| | - Stephan H Polanec
- 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
| | - Margaretha Rudas
- Clinical Institute of Pathology, Medical University of Vienna, Waehringer-Guertel 18-20, A-1090, Vienna, Austria
| | - Rupert Bartsch
- Department of Internal Medicine, Division of Oncology, Medical University of Vienna, Waehringer-Guertel 18-20, A-1090, Vienna, Austria
| | - 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
| | - Pascal A 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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Bickel H, Pinker K, Polanec S, Magometschnigg H, Wengert G, Spick C, Bogner W, Bago-Horvath Z, Helbich TH, Baltzer P. Diffusion-weighted imaging of breast lesions: Region-of-interest placement and different ADC parameters influence apparent diffusion coefficient values. Eur Radiol 2016; 27:1883-1892. [DOI: 10.1007/s00330-016-4564-3] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 08/11/2016] [Indexed: 01/01/2023]
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Xu XQ, Hu H, Su GY, Liu H, Shi HB, Wu FY. Diffusion Weighted Imaging for Differentiating Benign from Malignant Orbital Tumors: Diagnostic Performance of the Apparent Diffusion Coefficient Based on Region of Interest Selection Method. Korean J Radiol 2016; 17:650-6. [PMID: 27587953 PMCID: PMC5007391 DOI: 10.3348/kjr.2016.17.5.650] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2016] [Accepted: 06/10/2016] [Indexed: 12/30/2022] Open
Abstract
Objective To evaluate the differences in the apparent diffusion coefficient (ADC) measurements based on three different region of interest (ROI) selection methods, and compare their diagnostic performance in differentiating benign from malignant orbital tumors. Materials and Methods Diffusion-weighted imaging data of sixty-four patients with orbital tumors (33 benign and 31 malignant) were retrospectively analyzed. Two readers independently measured the ADC values using three different ROIs selection methods including whole-tumor (WT), single-slice (SS), and reader-defined small sample (RDSS). The differences of ADC values (ADC-ROIWT, ADC-ROISS, and ADC-ROIRDSS) between benign and malignant group were compared using unpaired t test. Receiver operating characteristic curve was used to determine and compare their diagnostic ability. The ADC measurement time was compared using ANOVA analysis and the measurement reproducibility was assessed using Bland-Altman method and intra-class correlation coefficient (ICC). Results Malignant group showed significantly lower ADC-ROIWT, ADC-ROISS, and ADC-ROIRDSS than benign group (all p < 0.05). The areas under the curve showed no significant difference when using ADC-ROIWT, ADC-ROISS, and ADC-ROIRDSS as differentiating index, respectively (all p > 0.05). The ROISS and ROIRDSS required comparable measurement time (p > 0.05), while significantly shorter than ROIWT (p < 0.05). The ROISS showed the best reproducibility (mean difference ± limits of agreement between two readers were 0.022 [-0.080–0.123] × 10-3 mm2/s; ICC, 0.997) among three ROI methods. Conclusion Apparent diffusion coefficient values based on the three different ROI selection methods can help to differentiate benign from malignant orbital tumors. The results of measurement time, reproducibility and diagnostic ability suggest that the ROISS method are potentially useful for clinical practice.
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Affiliation(s)
- Xiao-Quan Xu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China
| | - Hao Hu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China
| | - Guo-Yi Su
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China
| | - Hu Liu
- Department of Ophthalmology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China
| | - Hai-Bin Shi
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China
| | - Fei-Yun Wu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China
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Apparent diffusion coefficient measurements in diffusion-weighted magnetic resonance imaging of the anterior mediastinum: inter-observer reproducibility of five different methods of region-of-interest positioning. Eur Radiol 2016; 27:1386-1394. [DOI: 10.1007/s00330-016-4527-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Revised: 05/23/2016] [Accepted: 07/21/2016] [Indexed: 12/12/2022]
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Incidentally detected enhancing lesions found in breast MRI: analysis of apparent diffusion coefficient and T2 signal intensity significantly improves specificity. Eur Radiol 2016; 26:4361-4370. [PMID: 27114285 DOI: 10.1007/s00330-016-4326-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2015] [Revised: 02/29/2016] [Accepted: 03/08/2016] [Indexed: 12/26/2022]
Abstract
OBJECTIVES To evaluate the value of adding T2- and diffusion-weighted imaging (DWI) to the BI-RADS® classification in MRI-detected lesions. METHODS This retrospective study included 112 consecutive patients who underwent 3.0T structural breast MRI with T2- and DWI on the basis of EUSOMA recommendations. Morphological and kinetic features, T2 signal intensity (T2 SI) and apparent diffusion coefficient (ADC) findings were assessed. RESULTS Thirty-three (29.5 %) patients (mean age 57.0 ± 12.7 years) had 36 primarily MRI-detected incidental lesions of which 16 (44.4 %) proved to be malignant. No single morphological or kinetic feature was associated with malignancy. Both low T2 SI (P = 0.009) and low ADC values (≤0.87 × 10-3 mm2s-1, P < 0.001) yielded high specificity (80.0 %/80.0 %). The BI-RADS classification supplemented with information from DWI and T2-WI improved the diagnostic performance of the BI-RADS classification as sensitivity remained 100 % and specificity improved from 30 % to 65.0 %. The numbers of false positive lesions declined from 39 % (N = 14) to 19 % (N = 7). CONCLUSION MRI-detected incidental lesions may be challenging to characterize as they have few specific malignancy indicating features. The specificity of MRI can be improved by incorporating T2 SI and ADC values into the BI-RADS assessment. KEY POINTS • MRI-detected incidental lesions have few specific malignancy indicating features. • ≥ 1 suspicious morphologic or kinetic feature may warrant biopsy. • T2 signal intensity and DWI assessment are feasible in primarily MRI-detected lesions. • T2 SI and DWI assessment improve the BI-RADS specificity in MRI-detected lesions.
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Hao Y, Pan C, Chen W, Li T, Zhu W, Qi J. Differentiation between malignant and benign thyroid nodules and stratification of papillary thyroid cancer with aggressive histological features: Whole-lesion diffusion-weighted imaging histogram analysis. J Magn Reson Imaging 2016; 44:1546-1555. [PMID: 27093648 DOI: 10.1002/jmri.25290] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2016] [Accepted: 04/04/2016] [Indexed: 12/23/2022] Open
Abstract
PURPOSE To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features. MATERIALS AND METHODS This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC. RESULTS Mean ADC, median ADC, 5th percentile ADC, 25th percentile ADC, 75th percentile ADC, 95th percentile ADC (all P < 0.001), and kurtosis (P = 0.001) were significantly lower in malignant thyroid nodules, and mean ADC achieved the highest AUC (0.919) with a cutoff value of 1842.78 × 10-6 mm2 /s in differentiating malignant and benign nodules. Compared to the PTCs without extrathyroidal extension, PTCs with extrathyroidal extension showed significantly lower median ADC, 5th percentile ADC, and 25th percentile ADC. The 5th percentile ADC achieved the highest AUC (0.757) with cutoff value of 911.5 × 10-6 mm2 /s for differentiating between PTCs with and without extrathyroidal extension. CONCLUSION Whole-lesion ADC histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555.
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Affiliation(s)
- Yonghong Hao
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chu Pan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - WeiWei Chen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tao Li
- Department of Radiology, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - WenZhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - JianPin Qi
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Apparent diffusion coefficient of breast cancer and normal fibroglandular tissue in diffusion-weighted imaging: the effects of menstrual cycle and menopausal status. Breast Cancer Res Treat 2016; 157:31-40. [PMID: 27091644 DOI: 10.1007/s10549-016-3793-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2016] [Accepted: 04/07/2016] [Indexed: 10/21/2022]
Abstract
The purpose of this study was to investigate prospectively whether the apparent diffusion coefficients (ADCs) of both breast cancer and normal fibroglandular tissue vary with the menstrual cycle and menopausal status. Institutional review board approval was obtained, and informed consent was obtained from each participant. Fifty-seven women (29 premenopausal, 28 postmenopausal) with newly diagnosed breast cancer underwent diffusion-weighted imaging twice (interval 12-20 days) before surgery. Two radiologists independently measured ADC of breast cancer and normal contralateral breast tissue, and we quantified the differences according to the phases of menstrual cycle and menopausal status. With normal fibroglandular tissue, ADC was significantly lower in postmenopausal than in premenopausal women (P = 0.035). In premenopausal women, ADC did not differ significantly between proliferative and secretory phases in either breast cancer or normal fibroglandular tissue (P = 0.969 and P = 0.519, respectively). In postmenopausal women, no significant differences were found between ADCs measured at different time intervals in either breast cancer or normal fibroglandular tissue (P = 0.948 and P = 0.961, respectively). The within-subject variability of the ADC measurements was quantified using the coefficient of variation (CV) and was small: the mean CVs of tumor ADC were 2.90 % (premenopausal) and 3.43 % (postmenopausal), and those of fibroglandular tissue ADC were 4.37 % (premenopausal) and 2.55 % (postmenopausal). Both intra- and interobserver agreements were excellent for ADC measurements, with intraclass correlation coefficients in the range of 0.834-0.974. In conclusion, the measured ADCs of breast cancer and normal fibroglandular tissue were not affected significantly by menstrual cycle, and the measurements were highly reproducible both within and between observers.
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Keenan KE, Peskin AP, Wilmes LJ, Aliu SO, Jones EF, Li W, Kornak J, Newitt DC, Hylton NM. Variability and bias assessment in breast ADC measurement across multiple systems. J Magn Reson Imaging 2016; 44:846-55. [PMID: 27008431 DOI: 10.1002/jmri.25237] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2015] [Accepted: 02/29/2016] [Indexed: 12/19/2022] Open
Abstract
PURPOSE To assess the ability of a recent, anatomically designed breast phantom incorporating T1 and diffusion elements to serve as a quality control device for quantitative comparison of apparent diffusion coefficient (ADC) measurements calculated from diffusion-weighted MRI (DWI) within and across MRI systems. MATERIALS AND METHODS A bilateral breast phantom incorporating multiple T1 and diffusion tissue mimics and a geometric distortion array was imaged with DWI on 1.5 Tesla (T) and 3.0T scanners from two different manufacturers, using three different breast coils (three configurations total). Multiple measurements were acquired to assess the bias and variability of different diffusion weighted single-shot echo-planar imaging sequences on the scanner-coil systems. RESULTS The repeatability of ADC measurements was mixed: the standard deviation relative to baseline across scanner-coil-sequences ranged from low variability (0.47, 95% confidence interval [CI]: 0.22-1.00) to high variability (1.69, 95% CI: 0.17-17.26), depending on material, with the lowest and highest variability from the same scanner-coil-sequence. Assessment of image distortion showed that right/left measurements of the geometric distortion array were 1 to 16% larger on the left coil side compared with the right coil side independent of scanner-coil systems, diffusion weighting, and phase-encoding direction. CONCLUSION This breast phantom can be used to measure scanner-coil-sequence bias and variability for DWI. When establishing a multisystem study, this breast phantom may be used to minimize protocol differences (e.g., due to available sequences or shimming technique), to correct for bias that cannot be minimized, and to weigh results from each system depending on respective variability. J. Magn. Reson. Imaging 2016. J. MAGN. RESON. IMAGING 2016;44:846-855.
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Affiliation(s)
- Kathryn E Keenan
- Physical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA.
| | - Adele P Peskin
- Physical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Lisa J Wilmes
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Sheye O Aliu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Ella F Jones
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Wen Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - John Kornak
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | - David C Newitt
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Nola M Hylton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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