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Loubrie S, Zou J, Rodriguez-Soto AE, Lim J, Andreassen MMS, Cheng Y, Batasin SJ, Ebrahimi S, Fang LK, Conlin CC, Seibert TM, Hahn ME, Dialani V, Wei CJ, Karimi Z, Kuperman J, Dale AM, Ojeda-Fournier H, Pisano E, Rakow-Penner R. Discrimination Between Benign and Malignant Lesions With Restriction Spectrum Imaging MRI in an Enriched Breast Cancer Screening Cohort. J Magn Reson Imaging 2024. [PMID: 39291552 DOI: 10.1002/jmri.29599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 08/16/2024] [Accepted: 08/20/2024] [Indexed: 09/19/2024] Open
Abstract
BACKGROUND Breast cancer screening with dynamic contrast-enhanced MRI (DCE-MRI) is recommended for high-risk women but has limitations, including variable specificity and difficulty in distinguishing cancerous (CL) and high-risk benign lesions (HRBL) from average-risk benign lesions (ARBL). Complementary non-invasive imaging techniques would be useful to improve specificity. PURPOSE To evaluate the performance of a previously-developed breast-specific diffusion-weighted MRI (DW-MRI) model (BS-RSI3C) to improve discrimination between CL, HRBL, and ARBL in an enriched screening population. STUDY TYPE Prospective. SUBJECTS Exactly 187 women, either with mammography screening recommending additional imaging (N = 49) or high-risk individuals undergoing routine breast MRI (N = 138), before the biopsy. FIELD STRENGTH/SEQUENCE Multishell DW-MRI echo planar imaging sequence with a reduced field of view at 3.0 T. ASSESSMENT A total of 72 women had at least one biopsied lesion, with 89 lesions categorized into ARBL, HRBL, CL, and combined CLs and HRBLs (CHRLs). DW-MRI data were processed to produce apparent diffusion coefficient (ADC) maps, and estimate signal contributions (C1, C2, and C3-restricted, hindered, and free diffusion, respectively) from the BS-RSI3C model. Lesion regions of interest (ROIs) were delineated on DW images based on suspicious DCE-MRI findings by two radiologists; control ROIs were drawn in the contralateral breast. STATISTICAL TESTS One-way ANOVA and two-sided t-tests were used to assess differences in signal contributions and ADC values among groups. P-values were adjusted using the Bonferroni method for multiple testing, P = 0.05 was used for the significance level. Receiver operating characteristics (ROC) curves and intra-class correlations (ICC) were also evaluated. RESULTS C1, √C1C2, andlog C 1 C 2 C 3 $$ \log \left(\frac{{\mathrm{C}}_1{\mathrm{C}}_2}{{\mathrm{C}}_3}\right) $$ were significantly different in HRBLs compared with ARBLs (P-values < 0.05). Thelog C 1 C 2 C 3 $$ \log \left(\frac{{\mathrm{C}}_1{\mathrm{C}}_2}{{\mathrm{C}}_3}\right) $$ had the highest AUC (0.821) in differentiating CHRLs from ARBLs, performing better than ADC (0.696), especially in non-mass enhancement (0.776 vs. 0.517). DATA CONCLUSION This study demonstrated the BS-RSI3C could differentiate HRBLs from ARBLs in a screening population, and separate CHRLs from ARBLs better than ADC. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE 2.
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Affiliation(s)
- Stephane Loubrie
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Jingjing Zou
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Ana E Rodriguez-Soto
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Jihe Lim
- Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Gyeonggi-do, Republic of Korea
| | - Maren M S Andreassen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research and Innovation, Vestre Viken, Drammen, Norway
| | - Yuwei Cheng
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Summer J Batasin
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Sheida Ebrahimi
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Lauren K Fang
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Christopher C Conlin
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Tyler M Seibert
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Radiation Medicine, University of California San Diego, La Jolla, California, USA
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Michael E Hahn
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Vandana Dialani
- Department of Radiology, Beth Israel Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Catherine J Wei
- Department of Radiology, Mass General Brigham - Salem Hospital, Salem, Massachusetts, USA
| | - Zahra Karimi
- Department of Radiology, Beth Israel Hospital, Boston, Massachusetts, USA
| | - Joshua Kuperman
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Haydee Ojeda-Fournier
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Etta Pisano
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- American College of Radiology, Reston, Virginia, USA
| | - Rebecca Rakow-Penner
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
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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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Fan W, Wang X, Zhang X, Liu M, Meng Q, Chen Z. Investigating Optimal Echo Times for Quantitative Susceptibility Mapping of Basal Ganglia Nuclei in the Healthy Brain. Curr Med Imaging 2021; 16:991-996. [PMID: 33081660 DOI: 10.2174/1573405615666191219102044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2019] [Revised: 11/21/2019] [Accepted: 12/02/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) technique had been used to measure the magnetic susceptibility of brain tissue in clinical practice. However, QSM presented echo-time (TE) dependence, and an appropriate number of echo-times (nTEs) for QSM became more important to obtain the reliable susceptibility value. OBJECTIVE The aim of the study was to explore the optimal nTEs for quantitative susceptibility mapping (QSM) measurements of basal ganglia nuclei in the healthy brain. METHODS 3D multi-echo enhanced gradient recalled echo T2 star weighted angiography (ESWAN) sequence was acquired on a 3.0T MR scanner for QSM analysis. Regions of interests (ROIs) were drawn along the margin of the head of the caudate nucleus (HCN), putamen (Pu) and globus pallidus (GP). The mean susceptibility value and standard deviation of the ROIs were derived from the pixels within each region. RESULTS CV analysis demonstrated that TE6, TE8 and TE14 ESWAN sequences presented consistent lower CV value (< 1) for QSM measure of HCN, Pu and GP. ANOVA identified that susceptibility value showed no significant difference between TE6 and TE8 in HCN, Pu and GP (P > 0.05). ICC analysis demonstrated that the susceptibility value of TE6-TE8 had the highest ICC value as compared with TE6-TE14 and TE8-TE14 in HCN, Pu and GP. Combined with the timeefficiency of MRI scanning, TE6 sequence could not only provide the reliable QSM measurement but also short imaging time. CONCLUSION The current study identified that the optimal nTEs of ESWAN were 6 TEs (2.9ms ~ 80.9ms) for QSM measurement of basal ganglia nuclei in the healthy brain.
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Affiliation(s)
- Wenping Fan
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - Xue Wang
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - Xingwen Zhang
- Department of Neurology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
| | - Mengqi Liu
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China,Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
| | - Qinglin Meng
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - Zhiye Chen
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China,Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
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Quantitative Measures of Background Parenchymal Enhancement Predict Breast Cancer Risk. AJR Am J Roentgenol 2021; 217:64-75. [PMID: 32876474 PMCID: PMC9801515 DOI: 10.2214/ajr.20.23804] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND. Higher categories of background parenchymal enhancement (BPE) increase breast cancer risk. However, current clinical BPE categorization is subjective. OBJECTIVE. Using a semiautomated segmentation algorithm, we calculated quantitative BPE measures and investigated the utility of individual features and feature pairs in significantly predicting subsequent breast cancer risk compared with radiologist-assigned BPE category. METHODS. In this retrospective case-control study, we identified 95 women at high risk of breast cancer but without a personal history of breast cancer who underwent breast MRI. Of these women, 19 subsequently developed breast cancer and were included as cases. Each case was age matched to four control patients (76 control patients total). Sociodemographic characteristics were compared between the cases and matched control patients using the Mann-Whitney U test. From each dynamic contrast-enhanced MRI examination, quantitative fibroglandular tissue and BPE measures were computed by averaging enhancing voxels above enhancement ratio thresholds (0-100%), totaling the enhancing volume above thresholds (BPE volume in cm3), and estimating the percentage of enhancing tissue above thresholds relative to total breast volume (BPE%) on each gadolinium-enhanced phase. For the 91 imaging features generated, we compared predictive performance using conditional logistic regression with 80:20 hold-out cross validation and ROC curve analysis. ROC AUC was the figure of merit. Sensitivity, specificity, PPV, and NPV were also computed. All feature pairs were exhaustively searched to identify those with the highest AUC and Youden index. A DeLong test was used to compare predictive performance (AUCs). RESULTS. Women subsequently diagnosed with breast cancer were more likely to have mild, moderate, or marked BPE (odds ratio, 3.0; 95% CI, 0.9-10.0; p = .07). According to ROC curve analysis, a BPE category threshold greater than minimal resulted in a maximized AUC (0.62) in distinguishing cases from control patients. Compared with BPE category, the first gadolinium-enhanced (phase 1) BPE% at the 30% and 40% enhancement ratio thresholds yielded significantly higher AUC values of 0.85 (p = .0007) and 0.84 (p = .0004), respectively. Feature combinations showed similar AUC values with improved sensitivity. CONCLUSION. Preliminary data indicate that quantitative BPE measures may outperform radiologist-assigned category in breast cancer risk prediction. CLINICAL IMPACT. Future risk prediction models that incorporate quantitative measures warrant additional investigation.
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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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Evaluation of primary breast cancers using dedicated breast PET and whole-body PET. Sci Rep 2020; 10:21930. [PMID: 33318514 PMCID: PMC7736887 DOI: 10.1038/s41598-020-78865-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 11/17/2020] [Indexed: 01/06/2023] Open
Abstract
Metabolic imaging of the primary breast tumor with 18F-fluorodeoxyglucose ([18F]FDG) PET may assist in predicting treatment response in the neoadjuvant chemotherapy (NAC) setting. Dedicated breast PET (dbPET) is a high-resolution imaging modality with demonstrated ability in highlighting intratumoral heterogeneity and identifying small lesions in the breast volume. In this study, we characterized similarities and differences in the uptake of [18F]FDG in dbPET compared to whole-body PET (wbPET) in a cohort of ten patients with biopsy-confirmed, locally advanced breast cancer at the pre-treatment timepoint. Patients received bilateral dbPET and wbPET following administration of 186 MBq and 307 MBq [18F]FDG on separate days, respectively. [18F]FDG uptake measurements and 20 radiomic features based on morphology, tumor intensity, and texture were calculated and compared. There was a fivefold increase in SULpeak for dbPET (median difference (95% CI): 4.0 mL−1 (1.8–6.4 mL−1), p = 0.006). Additionally, spatial heterogeneity features showed statistically significant differences between dbPET and wbPET. The higher [18F]FDG uptake in dbPET highlighted the dynamic range of this breast-specific imaging modality. Combining with the higher spatial resolution, dbPET may be able to detect treatment response in the primary tumor during NAC, and future studies with larger cohorts are warranted.
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van der Velden BH, van Rijssel MJ, Lena B, Philippens ME, Loo CE, Ragusi MA, Elias SG, Sutton EJ, Morris EA, Bartels LW, Gilhuijs KG. Harmonization of Quantitative Parenchymal Enhancement in T 1 -Weighted Breast MRI. J Magn Reson Imaging 2020; 52:1374-1382. [PMID: 32491246 PMCID: PMC7687185 DOI: 10.1002/jmri.27244] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 05/19/2020] [Accepted: 05/20/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Differences in imaging parameters influence computer-extracted parenchymal enhancement measures from breast MRI. PURPOSE To investigate the effect of differences in dynamic contrast-enhanced MRI acquisition parameter settings on quantitative parenchymal enhancement of the breast, and to evaluate harmonization of contrast-enhancement values with respect to flip angle and repetition time. STUDY TYPE Retrospective. PHANTOM/POPULATIONS We modeled parenchymal enhancement using simulations, a phantom, and two cohorts (N = 398 and N = 302) from independent cancer centers. SEQUENCE FIELD/STRENGTH 1.5T dynamic contrast-enhanced T1 -weighted spoiled gradient echo MRI. Vendors: Philips, Siemens, General Electric Medical Systems. ASSESSMENT We assessed harmonization of parenchymal enhancement in simulations and phantom by varying the MR parameters that influence the amount of T1 -weighting: flip angle (8°-25°) and repetition time (4-12 msec). We calculated the median and interquartile range (IQR) of the enhancement values before and after harmonization. In vivo, we assessed overlap of quantitative parenchymal enhancement in the cohorts before and after harmonization using kernel density estimations. Cohort 1 was scanned with flip angle 20° and repetition time 8 msec; cohort 2 with flip angle 10° and repetition time 6 msec. STATISTICAL TESTS Paired Wilcoxon signed-rank-test of bootstrapped kernel density estimations. RESULTS Before harmonization, simulated enhancement values had a median (IQR) of 0.46 (0.34-0.49). After harmonization, the IQR was reduced: median (IQR): 0.44 (0.44-0.45). In the phantom, the IQR also decreased, median (IQR): 0.96 (0.59-1.22) before harmonization, 0.96 (0.91-1.02) after harmonization. Harmonization yielded significantly (P < 0.001) better overlap in parenchymal enhancement between the cohorts: median (IQR) was 0.46 (0.37-0.58) for cohort 1 vs. 0.37 (0.30-0.44) for cohort 2 before harmonization (57% overlap); and 0.35 (0.28-0.43) vs. .0.37 (0.30-0.44) after harmonization (85% overlap). DATA CONCLUSION The proposed practical harmonization method enables an accurate comparison between patients scanned with differences in imaging parameters. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 4.
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Affiliation(s)
- Bas H.M. van der Velden
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Michael J. van Rijssel
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Beatrice Lena
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Marielle E.P. Philippens
- Department of RadiotherapyUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Claudette E. Loo
- Department of RadiologyThe Netherlands Cancer Institute – Antoni van Leeuwenhoek HospitalAmsterdamThe Netherlands
| | - Max A.A. Ragusi
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Sjoerd G. Elias
- Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Elizabeth J. Sutton
- Department of RadiologyMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Elizabeth A. Morris
- Department of RadiologyMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Lambertus W. Bartels
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Kenneth G.A. Gilhuijs
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
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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: 245] [Impact Index Per Article: 49.0] [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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Onodera K, Hatakenaka M, Yama N, Onodera M, Saito T, Kwee TC, Takahara T. Repeatability analysis of ADC histogram metrics of the uterus. Acta Radiol 2019; 60:526-534. [PMID: 29969050 DOI: 10.1177/0284185118786062] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Recently, histogram analysis based on voxel-wise apparent diffusion coefficient (ADC) value distribution has been increasingly performed. However, few studies have been reported regarding its repeatability. PURPOSE To evaluate the repeatability of ADC histogram metrics of the uterus in clinical magnetic resonance imaging (MRI). MATERIAL AND METHODS Thirty-three female patients who underwent pelvic MRI including diffusion-weighted imaging (DWI) were prospectively included after providing informed consent. Two sequential DWI acquisitions with identical parameters and position were obtained. Regions of interest (ROIs) for histologically confirmed uterine lesions (five cervical and three endometrial cancers, and one endometrial hyperplasia) and normal appearing tissues (21 endometrium and 33 myometrium) were assigned on the first DWI dataset and then pasted onto the second DWI dataset. ADC histogram metrics within the ROIs were calculated and repeatability was evaluated by calculating within-subject coefficient of variance (%) (wCV (%)) and Bland-Altman plot (%). RESULTS ADC 10%, 25%, median, 75%, 90%, maximum, mean, and entropy showed high repeatability (wCV (%) < 7, 95% limit of agreement in Bland-Altman plot (%) < ±20), followed by ADC minimum (wCV (%) = 8.12, 95% limit of agreement in Bland-Altman plot (%) < ±30). However, ADC skewness and kurtosis showed very low repeatability in all evaluations. CONCLUSION ADC histogram metrics like ADC 10%, 25%, median, 75%, 90%, maximum, mean, and entropy are robust biomarkers and could be applicable to clinical use. However, ADC skewness and kurtosis lack robustness. Radiologists should keep these characteristics and limitations in mind when interpreting quantitative DWI.
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Affiliation(s)
- Koichi Onodera
- Department of Diagnostic Radiology, Sapporo Medical University, Sapporo, Japan
| | | | - Naoya Yama
- Department of Diagnostic Radiology, Sapporo Medical University, Sapporo, Japan
| | - Maki Onodera
- Department of Diagnostic Radiology, Sapporo Medical University, Sapporo, Japan
| | - Tsuyoshi Saito
- Department of Obstetrics and Gynecology, Sapporo Medical University, Sapporo, Japan
| | - Thomas Christian Kwee
- Department of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
| | - Taro Takahara
- Department of Biomedical Engineering, School of Engineering, Tokai University, Hiratsuka, Japan
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10
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Panda A, Chen Y, Ropella-Panagis K, Ghodasara S, Stopchinski M, Seyfried N, Wright K, Seiberlich N, Griswold M, Gulani V. Repeatability and reproducibility of 3D MR fingerprinting relaxometry measurements in normal breast tissue. J Magn Reson Imaging 2019; 50:1133-1143. [PMID: 30892807 DOI: 10.1002/jmri.26717] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 02/27/2019] [Accepted: 02/28/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The 3D breast magnetic resonance fingerprinting (MRF) technique enables T1 and T2 mapping in breast tissues. Combined repeatability and reproducibility studies on breast T1 and T2 relaxometry are lacking. PURPOSE To assess test-retest and two-visit repeatability and interscanner reproducibility of the 3D breast MRF technique in a single-institution setting. STUDY TYPE Prospective. SUBJECTS Eighteen women (median age 29 years, range, 22-33 years) underwent Visit 1 scans on scanner 1. Ten of these women underwent test-retest scan repositioning after a 10-minute interval. Thirteen women had Visit 2 scans within 7-15 days in same menstrual cycle. The remaining five women had Visit 2 scans in the same menstrual phase in next menstrual cycle. Five women were also scanned on scanner 2 at both visits for interscanner reproducibility. FIELD STRENGTH/SEQUENCE Two 3T MR scanners with the 3D breast MRF technique. ASSESSMENT T1 and T2 MRF maps of both breasts. STATISTICAL TESTS Mean T1 and T2 values for normal fibroglandular tissues were quantified at all scans. For variability, between and within-subjects coefficients of variation (bCV and wCV, respectively) were assessed. Repeatability was assessed with Bland-Altman analysis and coefficient of repeatability (CR). Reproducibility was assessed with interscanner coefficient of variation (CoV) and Wilcoxon signed-rank test. RESULTS The bCV at test-retest scans was 9-12% for T1 , 7-17% for T2 , wCV was <4% for T1 , and <7% for T2 . For two visits in same menstrual cycle, bCV was 10-15% for T1 , 13-17% for T2 , wCV was <7% for T1 and <5% for T2 . For two visits in the same menstrual phase, bCV was 6-14% for T1 , 15-18% for T2 , wCV was <7% for T1 , and <9% for T2 . For test-retest scans, CR for T1 and T2 were 130 msec and 11 msec. For two visit scans, CR was <290 msec for T1 and 10-14 msec for T2 . Interscanner CoV was 3.3-3.6% for T1 and 5.1-6.6% for T2 , with no differences between interscanner measurements (P = 1.00 for T1 , P = 0.344 for T2 ). DATA CONCLUSION 3D breast MRF measurements are repeatable across scan timings and scanners and may be useful in clinical applications in breast imaging. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1133-1143.
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Affiliation(s)
- Ananya Panda
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Yong Chen
- Department of Radiology, University of North Carolina, Chapel Hill, North Carolina, USA.,Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, North Carolina, USA
| | | | - Satyam Ghodasara
- School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Marcie Stopchinski
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Nicole Seyfried
- School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Katherine Wright
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Nicole Seiberlich
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
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11
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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: 69] [Impact Index Per Article: 11.5] [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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12
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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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13
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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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14
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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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15
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Froneman T, van den Heever D, Dellimore K. Development of a wearable support system to aid the visually impaired in independent mobilization and navigation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2017:783-786. [PMID: 29059989 DOI: 10.1109/embc.2017.8036941] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Visually impaired individuals have great difficulty in navigating unfamiliar environments. Conventional methods of obstacle detection are not always sufficient, thus a need exists for a low-cost device which could aid the visually impaired in navigating indoor environments. The aim of this study is to develop a wearable prototype support system which aids the visually impaired in independent navigation and mobilization. It utilizes ultrasonic sensors to detect obstacles and transmits feedback to the user through an array of vibration motors. The prototype device was evaluated by detecting the sensor signatures of various common static household obstacles. Trends were identified in these signatures which can be used to give feedback to the user of the type of obstacle encountered. The results show the basic feasibility of the device in static indoor obstacle detection and identification for the visually impaired. However, further refinement is needed to extend the system's functionality by detecting dynamic obstacles.
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16
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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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Ledger AEW, Scurr ED, Hughes J, Macdonald A, Wallace T, Thomas K, Wilson R, Leach MO, Schmidt MA. Comparison of Dixon Sequences for Estimation of Percent Breast Fibroglandular Tissue. PLoS One 2016; 11:e0152152. [PMID: 27011312 PMCID: PMC4806997 DOI: 10.1371/journal.pone.0152152] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Accepted: 03/09/2016] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVES To evaluate sources of error in the Magnetic Resonance Imaging (MRI) measurement of percent fibroglandular tissue (%FGT) using two-point Dixon sequences for fat-water separation. METHODS Ten female volunteers (median age: 31 yrs, range: 23-50 yrs) gave informed consent following Research Ethics Committee approval. Each volunteer was scanned twice following repositioning to enable an estimation of measurement repeatability from high-resolution gradient-echo (GRE) proton-density (PD)-weighted Dixon sequences. Differences in measures of %FGT attributable to resolution, T1 weighting and sequence type were assessed by comparison of this Dixon sequence with low-resolution GRE PD-weighted Dixon data, and against gradient-echo (GRE) or spin-echo (SE) based T1-weighted Dixon datasets, respectively. RESULTS %FGT measurement from high-resolution PD-weighted Dixon sequences had a coefficient of repeatability of ±4.3%. There was no significant difference in %FGT between high-resolution and low-resolution PD-weighted data. Values of %FGT from GRE and SE T1-weighted data were strongly correlated with that derived from PD-weighted data (r = 0.995 and 0.96, respectively). However, both sequences exhibited higher mean %FGT by 2.9% (p < 0.0001) and 12.6% (p < 0.0001), respectively, in comparison with PD-weighted data; the increase in %FGT from the SE T1-weighted sequence was significantly larger at lower breast densities. CONCLUSION Although measurement of %FGT at low resolution is feasible, T1 weighting and sequence type impact on the accuracy of Dixon-based %FGT measurements; Dixon MRI protocols for %FGT measurement should be carefully considered, particularly for longitudinal or multi-centre studies.
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Affiliation(s)
- Araminta E. W. Ledger
- CR-UK Cancer Imaging Centre, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Erica D. Scurr
- Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Julie Hughes
- Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Alison Macdonald
- Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Toni Wallace
- Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Karen Thomas
- Clinical Research and Development, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Robin Wilson
- Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Martin O. Leach
- CR-UK Cancer Imaging Centre, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Maria A. Schmidt
- CR-UK Cancer Imaging Centre, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, United Kingdom
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Giannotti E, Waugh S, Priba L, Davis Z, Crowe E, Vinnicombe S. Assessment and quantification of sources of variability in breast apparent diffusion coefficient (ADC) measurements at diffusion weighted imaging. Eur J Radiol 2015; 84:1729-36. [DOI: 10.1016/j.ejrad.2015.05.032] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Revised: 05/21/2015] [Accepted: 05/29/2015] [Indexed: 10/23/2022]
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