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Kratochvíla J, Jiřík R, Bartoš M, Standara M, Starčuk Z, Taxt T. Blind deconvolution decreases requirements on temporal resolution of DCE-MRI: Application to 2nd generation pharmacokinetic modeling. Magn Reson Imaging 2024; 109:238-248. [PMID: 38508292 DOI: 10.1016/j.mri.2024.03.019] [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: 08/07/2023] [Revised: 03/08/2024] [Accepted: 03/16/2024] [Indexed: 03/22/2024]
Abstract
PURPOSE Dynamic Contrast-Enhanced (DCE) MRI with 2nd generation pharmacokinetic models provides estimates of plasma flow and permeability surface-area product in contrast to the broadly used 1st generation models (e.g. the Tofts models). However, the use of 2nd generation models requires higher frequency with which the dynamic images are acquired (around 1.5 s per image). Blind deconvolution can decrease the demands on temporal resolution as shown previously for one of the 1st generation models. Here, the temporal-resolution requirements achievable for blind deconvolution with a 2nd generation model are studied. METHODS The 2nd generation model is formulated as the distributed-capillary adiabatic-tissue-homogeneity (DCATH) model. Blind deconvolution is based on Parker's model of the arterial input function. The accuracy and precision of the estimated arterial input functions and the perfusion parameters is evaluated on synthetic and real clinical datasets with different levels of the temporal resolution. RESULTS The estimated arterial input functions remained unchanged from their reference high-temporal-resolution estimates (obtained with the sampling interval around 1 s) when increasing the sampling interval up to about 5 s for synthetic data and up to 3.6-4.8 s for real data. Further increasing of the sampling intervals led to systematic distortions, such as lowering and broadening of the 1st pass peak. The resulting perfusion-parameter estimation error was below 10% for the sampling intervals up to 3 s (synthetic data), in line with the real data perfusion-parameter boxplots which remained unchanged up to the sampling interval 3.6 s. CONCLUSION We show that use of blind deconvolution decreases the demands on temporal resolution in DCE-MRI from about 1.5 s (in case of measured arterial input functions) to 3-4 s. This can be exploited in increased spatial resolution or larger organ coverage.
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Affiliation(s)
- Jiří Kratochvíla
- Czech Academy of Sciences, Institute of Scientific Instruments, Královopolská 147, 612 64 Brno, Czech Republic.
| | - Radovan Jiřík
- Czech Academy of Sciences, Institute of Scientific Instruments, Královopolská 147, 612 64 Brno, Czech Republic
| | - Michal Bartoš
- Czech Academy of Sciences, Institute of Information Technology and Automation, Pod Vodárenskou věží 4, 182 08 Praha 8, Czech Republic
| | - Michal Standara
- Department of Radiology, Masaryk Memorial Cancer Institute, Žlutý kopec 7, 656 53 Brno, Czech Republic
| | - Zenon Starčuk
- Czech Academy of Sciences, Institute of Scientific Instruments, Královopolská 147, 612 64 Brno, Czech Republic
| | - Torfinn Taxt
- Department of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen, Norway
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Xie T, Zhao Q, Fu C, Grimm R, Dominik Nickel M, Hu X, Yue L, Peng W, Gu Y. Quantitative analysis from ultrafast dynamic contrast-enhanced breast MRI using population-based versus individual arterial input functions, and comparison with semi-quantitative analysis. Eur J Radiol 2024; 176:111501. [PMID: 38788607 DOI: 10.1016/j.ejrad.2024.111501] [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: 05/22/2023] [Revised: 04/27/2024] [Accepted: 05/06/2024] [Indexed: 05/26/2024]
Abstract
PURPOSE To evaluate the value of inline quantitative analysis of ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using a population-based arterial input function (P-AIF) compared with offline quantitative analysis with an individual AIF (I-AIF) and semi-quantitative analysis for diagnosing breast cancer. METHODS This prospective study included 99 consecutive patients with 109 lesions (85 malignant and 24 benign). Model-based parameters (Ktrans, kep, and ve) and model-free parameters (washin and washout) were derived from CAIPIRINHA-Dixon-TWIST-VIBE (CDTV) DCE-MRI. Univariate analysis and multivariate logistic regression analysis with forward stepwise covariate selection were performed to identify significant variables. The AUC and F1 score were assessed for semi-quantitative and two quantitative analyses. RESULTS kep from inline quantitative analysis with P-AIF for diagnosing breast cancer provided an AUC similar to kep from offline quantitative analysis with I-AIF (0.782 vs 0.779, p = 0.954), higher compared to washin from semi-quantitative analysis (0.782 vs 0.630, p = 0.034). Furthermore, the inline quantitative analysis with P-AIF achieved the larger F1 score (0.920) compared with offline quantitative analysis with I-AIF (0.780) and semi-quantitative analysis (0.480). There were no statistically significant differences for kep values between the two quantitative analysis schemes (p = 0.944). CONCLUSION The inline quantitative analysis with P-AIF from CDTV in characterizing breast lesions could offer similar diagnostic accuracy to offline quantitative analysis with I-AIF, and higher diagnostic accuracy to semi-quantitative analysis.
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Affiliation(s)
- Tianwen Xie
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Qiufeng Zhao
- Department of Radiology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Caixia Fu
- MR Applications Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | - Robert Grimm
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Xiaoxin Hu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Lei Yue
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Weijun Peng
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
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Sherminie LPG, Jayatilake ML. Fractal Dimension Analysis of Pixel Dynamic Contrast Enhanced-Magnetic Resonance Imaging Pharmacokinetic Parameters for Discrimination of Benign and Malignant Breast Lesions. JCO Clin Cancer Inform 2023; 7:e2200101. [PMID: 36745858 DOI: 10.1200/cci.22.00101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
PURPOSE Breast cancer is the most frequent cancer in women worldwide. However, its diagnosis mostly depends on visual examination of radiologic images, leading to an overdiagnosis with substantial costs. Therefore, a quantitative approach such as dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) through pharmacokinetic (PK) modeling is required for reliable analysis. As PK parameters lack information on parameter heterogeneity, texture-based analysis is required to quantify PK parameter heterogeneity. Therefore, this study focused on determining the usefulness of fractal dimension (FD) as a potential imaging biomarker of tumor heterogeneity for discriminating benign and malignant breast lesions. METHODS Parametric maps for PK parameters, extravasation rate of contrast agent from blood plasma to extravascular extracellular space (Ktrans) and volume fraction of extravascular extracellular space (ve), were generated for the regions of interest (ROIs) under the standard model using 18 lesions. Then, tumor ROI and pixel DCE-MRI time-course data were analyzed to extract pixel values of Ktrans and ve. For each ROI, FD values of Ktrans and ve were computed using the blanket method. RESULTS The FD values of Ktrans for benign and malignant lesions varied from 2.96 to 3.49 and from 2.37 to 3.16, respectively, whereas FD values of ve for benign and malignant lesions varied from 3.01 to 5.15 and 2.42 to 3.44, respectively. There were significant differences in FD values derived from Ktrans parametric maps (P = .0053) and ve parametric maps (P = .0271) between benign and malignant lesions according to the statistical analysis. CONCLUSION Incorporating texture heterogeneity changes in breast lesions captured by FD with quantitative DCE-MRI parameters generated under the standard model is a potential marker for prediction of malignant lesions.
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Affiliation(s)
- Lahanda Purage G Sherminie
- Department of Nuclear Science, Faculty of Science, University of Colombo, Colombo, Sri Lanka.,Department of Radiography/Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka
| | - Mohan L Jayatilake
- Department of Radiography/Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka
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Altabella L, Benetti G, Camera L, Cardano G, Montemezzi S, Cavedon C. Machine learning for multi-parametric breast MRI: radiomics-based approaches for lesion classification. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac7d8f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 06/30/2022] [Indexed: 11/11/2022]
Abstract
Abstract
In the artificial intelligence era, machine learning (ML) techniques have gained more and more importance in the advanced analysis of medical images in several fields of modern medicine. Radiomics extracts a huge number of medical imaging features revealing key components of tumor phenotype that can be linked to genomic pathways. The multi-dimensional nature of radiomics requires highly accurate and reliable machine-learning methods to create predictive models for classification or therapy response assessment.
Multi-parametric breast magnetic resonance imaging (MRI) is routinely used for dense breast imaging as well for screening in high-risk patients and has shown its potential to improve clinical diagnosis of breast cancer. For this reason, the application of ML techniques to breast MRI, in particular to multi-parametric imaging, is rapidly expanding and enhancing both diagnostic and prognostic power. In this review we will focus on the recent literature related to the use of ML in multi-parametric breast MRI for tumor classification and differentiation of molecular subtypes. Indeed, at present, different models and approaches have been employed for this task, requiring a detailed description of the advantages and drawbacks of each technique and a general overview of their performances.
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Wang PN, Velikina JV, Bancroft LCH, Samsonov AA, Kelcz F, Strigel RM, Holmes JH. The Influence of Data-Driven Compressed Sensing Reconstruction on Quantitative Pharmacokinetic Analysis in Breast DCE MRI. Tomography 2022; 8:1552-1569. [PMID: 35736876 PMCID: PMC9227412 DOI: 10.3390/tomography8030128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 06/07/2022] [Accepted: 06/09/2022] [Indexed: 11/25/2022] Open
Abstract
Radial acquisition with MOCCO reconstruction has been previously proposed for high spatial and temporal resolution breast DCE imaging. In this work, we characterize MOCCO across a wide range of temporal contrast enhancement in a digital reference object (DRO). Time-resolved radial data was simulated using a DRO with lesions in different PK parameters. The under sampled data were reconstructed at 5 s temporal resolution using the data-driven low-rank temporal model for MOCCO, compressed sensing with temporal total variation (CS-TV) and more conventional low-rank reconstruction (PCB). Our results demonstrated that MOCCO was able to recover curves with Ktrans values ranging from 0.01 to 0.8 min−1 and fixed Ve = 0.3, where the fitted results are within a 10% bias error range. MOCCO reconstruction showed less impact on the selection of different temporal models than conventional low-rank reconstruction and the greater error was observed with PCB. CS-TV showed overall underestimation in both Ktrans and Ve. For the Monte-Carlo simulations, MOCCO was found to provide the most accurate reconstruction results for curves with intermediate lesion kinetics in the presence of noise. Initial in vivo experiences are reported in one patient volunteer. Overall, MOCCO was able to provide reconstructed time-series data that resulted in a more accurate measurement of PK parameters than PCB and CS-TV.
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Affiliation(s)
- Ping Ni Wang
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, USA; (P.N.W.); (R.M.S.)
| | - Julia V. Velikina
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, USA; (J.V.V.); (L.C.H.B.); (A.A.S.); (F.K.)
| | - Leah C. Henze Bancroft
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, USA; (J.V.V.); (L.C.H.B.); (A.A.S.); (F.K.)
| | - Alexey A. Samsonov
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, USA; (J.V.V.); (L.C.H.B.); (A.A.S.); (F.K.)
| | - Frederick Kelcz
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, USA; (J.V.V.); (L.C.H.B.); (A.A.S.); (F.K.)
| | - Roberta M. Strigel
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, USA; (P.N.W.); (R.M.S.)
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, USA; (J.V.V.); (L.C.H.B.); (A.A.S.); (F.K.)
- Carbone Cancer Center, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, USA
| | - James H. Holmes
- Department of Radiology, University of Iowa, 169 Newton Road, Iowa City, IA 52333, USA
- Holden Comprehensive Cancer Center, University of Iowa, 169 Newton Road, Iowa City, IA 52333, USA
- Correspondence:
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Xie T, Zhao Q, Fu C, Grimm R, Gu Y, Peng W. Improved value of whole-lesion histogram analysis on DCE parametric maps for diagnosing small breast cancer (≤ 1 cm). Eur Radiol 2021; 32:1634-1643. [PMID: 34505195 DOI: 10.1007/s00330-021-08244-7] [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: 02/23/2021] [Revised: 07/21/2021] [Accepted: 08/03/2021] [Indexed: 12/27/2022]
Abstract
OBJECTIVES To determine if whole-lesion histogram analysis on dynamic contrast-enhanced (DCE) parametric maps help to improve the diagnostic accuracy of small suspicious breast lesions (≤ 1 cm). METHODS This retrospective study included 99 female patients with 114 lesions (40 malignant and 74 benign lesions) suspicious on magnetic resonance imaging (MRI).Two radiologists reviewed all lesions and descripted the morphologic and kinetic characteristics according to BI-RADS by consensus. Whole lesions were segmented on DCE parametric maps (washin and washout), and quantitative histogram features were extracted. Univariate analysis and multivariate logistic regression analysis with forward stepwise covariate selection were performed to identify significant variables. Diagnostic performance was assessed and compared with that of qualitative BI-RADS assessment and quantitative histogram analysis by ROC analysis. RESULTS For malignancy defined as a washout or plateau pattern, the qualitative kinetic pattern showed a significant difference between the two groups (p = 0.023), yielding an AUC of 0.603 (95% confidence interval [CI]: 0.507, 0.694). The mean and median of washout were independent quantitative predictors of malignancy (p = 0.002, 0.010), achieving an AUC of 0.796 (95% CI: 0. 709, 0.865). The AUC of the quantitative model was better than that of the qualitative model (p < 0.001). CONCLUSIONS Compared with the qualitative BI-RADS assessment, quantitative whole-lesion histogram analysis on DCE parametric maps was better to discriminate between small benign and malignant breast lesions (≤ 1 cm) initially defined as suspicious on DCE-MRI. KEY POINTS • For malignancy defined as a washout or plateau, the kinetic pattern may provide information to diagnose small breast cancer. • The mean and median of washout map were significantly lower for small malignant breast lesions than for benign lesions. • Quantitative histogram analysis on MRI parametric maps improves diagnostic accuracy for small breast cancer, which may obviate unnecessary biopsy.
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Affiliation(s)
- Tianwen Xie
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270 Dong'an Road, Shanghai, 200032, People's Republic of China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Qiufeng Zhao
- Department of Radiology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China
| | - Caixia Fu
- MR Applications Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, People's Republic of China
| | - Robert Grimm
- MR Application Predevelopment, Siemens Healthcare, Erlangen, Germany
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270 Dong'an Road, Shanghai, 200032, People's Republic of China. .,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China.
| | - Weijun Peng
- Department of Radiology, Fudan University Shanghai Cancer Center, No. 270 Dong'an Road, Shanghai, 200032, People's Republic of China. .,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China.
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Li K, Machireddy A, Tudorica A, Moloney B, Oh KY, Jafarian N, Partridge SC, Li X, Huang W. Discrimination of Malignant and Benign Breast Lesions Using Quantitative Multiparametric MRI: A Preliminary Study. ACTA ACUST UNITED AC 2021; 6:148-159. [PMID: 32548291 PMCID: PMC7289240 DOI: 10.18383/j.tom.2019.00028] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
We aimed to compare diagnostic performance in discriminating malignant and benign breast lesions between two intravoxel incoherent motion (IVIM) analysis methods for diffusion-weighted magnetic resonance imaging (DW-MRI) data and between DW- and dynamic contrast-enhanced (DCE)-MRI, and to determine if combining DW- and DCE-MRI further improves diagnostic accuracy. DW-MRI with 12 b-values and DCE-MRI were performed on 26 patients with 28 suspicious breast lesions before biopsies. The traditional biexponential fitting and a 3-b-value method were used for independent IVIM analysis of the DW-MRI data. Simulations were performed to evaluate errors in IVIM parameter estimations by the two methods across a range of signal-to-noise ratio (SNR). Pharmacokinetic modeling of DCE-MRI data was performed. Conventional radiological MRI reading yielded 86% sensitivity and 21% specificity in breast cancer diagnosis. At the same sensitivity, specificity of individual DCE- and DW-MRI markers improved to 36%–57% and that of combined DCE- or combined DW-MRI markers to 57%–71%, with DCE-MRI markers showing better diagnostic performance. The combination of DCE- and DW-MRI markers further improved specificity to 86%–93% and the improvements in diagnostic accuracy were statistically significant (P < .05) when compared with standard clinical MRI reading and most individual markers. At low breast DW-MRI SNR values (<50), like those typically seen in clinical studies, the 3-b-value approach for IVIM analysis generates markers with smaller errors and with comparable or better diagnostic performances compared with biexponential fitting. This suggests that the 3-b-value method could be an optimal IVIM-MRI method to be combined with DCE-MRI for improved diagnostic accuracy.
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Affiliation(s)
- Kurt Li
- International School of Beaverton, Aloha, OR
| | - Archana Machireddy
- Center for Spoken Language Understanding, Oregon Health & Science University, Portland, OR
| | - Alina Tudorica
- Department of Diagnostic Radiology, Oregon Health & Science University, Portland, OR
| | - Brendan Moloney
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR; and
| | - Karen Y Oh
- Department of Diagnostic Radiology, Oregon Health & Science University, Portland, OR
| | - Neda Jafarian
- Department of Diagnostic Radiology, Oregon Health & Science University, Portland, OR
| | | | - Xin Li
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR; and
| | - Wei Huang
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR; and
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Blood Oxygenation Level Dependent Magnetic Resonance Imaging (MRI), Dynamic Contrast Enhanced MRI, and Diffusion Weighted MRI for Benign and Malignant Breast Cancer Discrimination: A Preliminary Experience. Cancers (Basel) 2021; 13:cancers13102421. [PMID: 34067721 PMCID: PMC8155852 DOI: 10.3390/cancers13102421] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 04/24/2021] [Accepted: 05/13/2021] [Indexed: 11/22/2022] Open
Abstract
Simple Summary The aim of the study is to combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. The results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D. Abstract Purpose. To combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. Methods. Thirty-seven breast lesions (11 benign and 21 malignant lesions) pathologically proven were included in this retrospective preliminary study. Pharmaco-kinetic parameters including Ktrans, kep, ve, and vp were extracted by DCE-MRI; BOLD parameters were estimated by basal signal S0 and the relaxation rate R2*; and diffusion and perfusion parameters were derived by DW-MRI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp), and tissue diffusivity (Dt)). The correlation coefficient, Wilcoxon-Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were calculated and area under the ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis and decision tree) with balancing technique and leave one out cross validation approach were considered. Results. R2* and D had a significant negative correlation (−0.57). The mean value, standard deviation, Skewness and Kurtosis values of R2* did not show a statistical significance between benign and malignant lesions (p > 0.05) confirmed by the ‘poor’ diagnostic value of ROC analysis. For DW-MRI derived parameters, the univariate analysis, standard deviation of D, Skewness and Kurtosis values of D* had a significant result to discriminate benign and malignant lesions and the best result at the univariate analysis in the discrimination of benign and malignant lesions was obtained by the Skewness of D* with an AUC of 82.9% (p-value = 0.02). Significant results for the mean value of Ktrans, mean value, standard deviation value and Skewness of kep, mean value, Skewness and Kurtosis of ve were obtained and the best AUC among DCE-MRI extracted parameters was reached by the mean value of kep and was equal to 80.0%. The best diagnostic performance in the discrimination of benign and malignant lesions was obtained at the multivariate analysis considering the DCE-MRI parameters alone with an AUC = 0.91 when the balancing technique was considered. Conclusions. Our results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D.
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Ucar EA, Durur-Subasi I, Yilmaz KB, Arikok AT, Hekimoglu B. Quantitative perfusion parameters of benign inflammatory breast pathologies: A descriptive study. Clin Imaging 2020; 68:249-256. [PMID: 32911313 DOI: 10.1016/j.clinimag.2020.08.024] [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: 03/23/2020] [Revised: 07/07/2020] [Accepted: 08/24/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE With this study, we evaluated the perfusion magnetic resonance imaging (MRI) features of benign inflammatory breast lesions for the first time and compared their Ktrans, Kep, Ve values and contrast kinetic curves to benign masses and invasive ductal carcinoma (IDC). MATERIALS AND METHODS Perfusion MRIs of the benign masses (n = 42), inflammatory lesions (n = 25), and IDCs (n = 16) were evaluated retrospectively in terms of Ktrans, Kep, Ve values and contrast kinetic curves and compared by the Kruskal-Wallis, Mann-Whitney U, chi-square tests statistically. Cronbach α test was used to measure intraobserver and interobserver reliability. RESULTS Mean Ktrans values were 0.052 for benign masses, 0.086 for inflammatory lesions and 0.101 for IDC (p < 0.001). Mean Kep values were 0.241 for benign masses, 0.435 for inflammatory lesions and 0.530 for IDC (p < 0.001). Mean Ve values were 0.476 for benign masses, 0.318 for inflammatory lesions and 0.310 for IDC (p = 0.067). For inflammatory and IDC lesions, Ktrans and Kep values were found to be higher and Ve values were lower than benign masses (p = 0.001 for Ktrans, p = 0.001 for Kep, p = 0.045 for Ve). There were excellent or good intra-interobserver reliabilities. For the kinetic curve pattern, most of the benign lesions showed progressive (81%), inflammatory lesions progressive (64%) and IDC lesions plateau (75%) patterns (p < 0.001). CONCLUSIONS On T1 perfusion MRI, similar to IDC lesions, inflammatory lesions demonstrate higher Ktrans and Kep and lower Ve values than benign masses. Quantitative perfusion parameters are not helpful in differentiating them from IDC lesions.
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Affiliation(s)
- Elif Ayse Ucar
- Bor Public Hospital, Clinic of Radiology, Nigde, Turkey; University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Clinic of Radiology, Ankara, Turkey.
| | - Irmak Durur-Subasi
- University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Clinic of Radiology, Ankara, Turkey; Istanbul Medipol University, Faculty of Medicine, Department of Radiology, Istanbul, Turkey
| | - Kerim Bora Yilmaz
- University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Clinic of General Surgery, Ankara, Turkey
| | - Ata Turker Arikok
- University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Clinic of Pathology, Ankara, Turkey
| | - Baki Hekimoglu
- University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Clinic of Radiology, Ankara, Turkey
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Image quality of the CAIPIRINHA-Dixon-TWIST-VIBE technique for ultra-fast breast DCE-MRI: Comparison with the conventional GRE technique. Eur J Radiol 2020; 129:109108. [PMID: 32563961 DOI: 10.1016/j.ejrad.2020.109108] [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: 11/07/2019] [Revised: 04/20/2020] [Accepted: 05/29/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE The aim of this study was to evaluate image quality of the CAIPIRINHA-Dixon-TWIST-Volume-Interpolated Breath-hold Examination (CDT-VIBE) technique for ultra-fast breast dynamic contrast enhanced (DCE) MRI with respect to conventional Gradient-Recalled Echo (GRE) technique. METHODS A total of 58 patients underwent a DCE-MRI based on CDT-VIBE sequence (temporal resolution: 11.9 s), immediately followed by 1 phase of a conventional T1 weighted GRE sequence (acquisition time: 68 s). The Signal-to-Noise Ratio (SNR) on phantom images, lesion/parenchyma signal ratio (LPSR), image quality, and morphological characterization were compared between the last phase of CDT-VIBE and conventional GRE images. The image quality was assessed by visual grading analysis (VGA). Reader agreement was assessed using Kappa analysis. RESULTS There was no significant difference in SNR (phantom) or LPSR (patient) between CDT-VIBE and conventional GRE images (P > 0.05). Significant parallel acquisition technique (PAT) noise and mild blurriness was observed on CDT-VIBE images. Visual grading analysis (VGA) confirmed significantly worse ratings for CDT-VIBE compared to the conventional GRE sequence in terms of PAT noise, lesion's internal feature clarity, and therefore overall image quality (area under contrast curve [AUC] values: 0.578 ‒ 0.764, P < 0.05), but edge sharpness and lesion conspicuity were equivalent (P > 0.05). Kappa analysis revealed good agreement on image quality scores (к = 0.725 ‒ 0.908) and on morphologic terms (к = 0.745-1.000). CONCLUSION The CDT-VIBE sequence provides excellent spatial resolution and adequate image quality in ultra-fast breast DCE-MRI. Further improvement in PAT noise and internal structure blurriness may be necessary.
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Zhang Q, Peng Y, Liu W, Bai J, Zheng J, Yang X, Zhou L. Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions. J Magn Reson Imaging 2020; 52:596-607. [PMID: 32061014 DOI: 10.1002/jmri.27098] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 02/04/2020] [Accepted: 02/05/2020] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND MRI-based radiomics has been used to diagnose breast lesions; however, little research combining quantitative pharmacokinetic parameters of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion kurtosis imaging (DKI) exists. PURPOSE To develop and validate a multimodal MRI-based radiomics model for the differential diagnosis of benign and malignant breast lesions and analyze the discriminative abilities of different MR sequences. STUDY TYPE Retrospective. POPULATION In all, 207 female patients with 207 histopathology-confirmed breast lesions (95 benign and 112 malignant) were included in the study. Then 159 patients were assigned to the training group, and 48 patients comprised the validation group. FIELD STRENGTH/SEQUENCE T2 -weighted (T2 W), T1 -weighted (T1 W), diffusion-weighted MR imaging (b-values = 0, 500, 800, and 2000 seconds/mm2 ) and quantitative DCE-MRI were performed on a 3.0T MR scanner. ASSESSMENT Radiomics features were extracted from T2 WI, T1 WI, DKI, apparent diffusion coefficient (ADC) maps, and DCE pharmacokinetic parameter maps in the training set. Models based on each sequence or combinations of sequences were built using a support vector machine (SVM) classifier and used to differentiate benign and malignant breast lesions in the validation set. STATISTICAL TESTS Optimal feature selection was performed by Spearman's rank correlation coefficients and the least absolute shrinkage and selection operator algorithm (LASSO). Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the radiomics models in the validation set. RESULTS The area under the ROC curve (AUC) of the optimal radiomics model, including T2 WI, DKI, and quantitative DCE-MRI parameter maps was 0.921, with an accuracy of 0.833. The AUCs of the models based on T1 WI, T2 WI, ADC map, DKI, and DCE pharmacokinetic parameter maps were 0.730, 0.791, 0.770, 0.788, and 0.836, respectively. DATA CONCLUSION The model based on radiomics features from T2 WI, DKI, and quantitative DCE pharmacokinetic parameter maps has a high discriminatory ability for benign and malignant breast lesions. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:596-607.
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Affiliation(s)
- Qian Zhang
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yunsong Peng
- Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
| | - Wei Liu
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jiayuan Bai
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jian Zheng
- Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
| | - Xiaodong Yang
- Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
| | - Lijuan Zhou
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
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12
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Whole-lesion histogram and texture analyses of breast lesions on inline quantitative DCE mapping with CAIPIRINHA-Dixon-TWIST-VIBE. Eur Radiol 2019; 30:57-65. [PMID: 31372782 DOI: 10.1007/s00330-019-06365-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 06/17/2019] [Accepted: 07/10/2019] [Indexed: 01/01/2023]
Abstract
PURPOSE To investigate the diagnostic capability of whole-lesion (WL) histogram and texture analysis of dynamic contrast-enhanced (DCE) MRI inline-generated quantitative parametric maps using CAIPIRINHA-Dixon-TWIST-VIBE (CDTV) to differentiate malignant from benign breast lesions and breast cancer subtypes. MATERIALS AND METHODS From February 2018 to November 2018, DCE MRI using CDTV was performed on 211 patients. The inline-generated parametric maps included Ktrans, kep, Ve, and IAUGC60. Histogram and texture features were extracted from the above parametric maps respectively based on a WL analysis. Student's t tests, one-way ANOVAs, Mann-Whitney U tests, Jonckheere-Terpstra tests, and ROC curves were used for statistical analysis. RESULTS Compared with benign breast lesions, malignant breast lesions showed significantly higher Ktrans_median, 5th percentile, entropy, and diff-entropy, IAUGC60_median, 5th percentile, entropy, and diff-entropy, kep_mean, median, 5th percentile, entropy, and diff-entropy, and Ve_95th percentile, diff-variance, and contrast, and significantly lower kep_skewness and Ve_SD, entropy, diff-entropy, and skewness (all p ≤ 0.011). The combination of all the extracted parameters yielded an AUC of 0.85 (sensitivity 76%, specificity 86%). kep_contrast showed a significant difference among different subtypes of breast cancer (p = 0.006). kep_skewness showed a significant difference between lymph node-positive and lymph node-negative breast cancer (p = 0.007). The IAGC60_5th percentile had an AUC of 0.71 (sensitivity 50%, specificity 91%) for differentiating between high- and low-proliferation groups of breast cancer. CONCLUSIONS The WL histogram and texture analyses of CDTV-DCE-derived parameters may give additional information for further evaluation of breast cancer. KEY POINTS • Inline DCE mapping with CDTV is effective and time-saving. • WL histogram and texture-extracted features could distinguish breast cancer from benign lesions accurately. • kep_contrast, kep_skewness, and IAUGC60_5th percentile could predict breast cancer subtypes, lymph node metastasis, and proliferation abilities, respectively.
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13
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Chen Y, Wu B, Liu H, Wang D, Gu Y. Feasibility study of dual parametric 2D histogram analysis of breast lesions with dynamic contrast-enhanced and diffusion-weighted MRI. J Transl Med 2018; 16:325. [PMID: 30470241 PMCID: PMC6260880 DOI: 10.1186/s12967-018-1698-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 11/16/2018] [Indexed: 01/01/2023] Open
Abstract
Background This study aimed to investigate the diagnostic value of a dual-parametric 2D histogram classification method for breast lesions. Methods This study included 116 patients with 72 malignant and 44 benign breast lesions who underwent CAIPIRINHA-Dixon-TWIST-VIBE dynamic contrast-enhanced (CDT-VIBE DCE) and readout-segmented diffusion-weighted magnetic resonance examination. The volume of interest (VOI), which encompassed the entire lesion, was segmented from the last phase of DCE images. For each VOI, a 1D histogram analysis (mean, median, 10th percentile, 90th percentile, kurtosis and skewness) was performed on apparent diffusion coefficient (ADC) and volume transfer constant (Ktrans) maps; a 2D histogram image (Ktrans-ADC) was generated from the pixelwise aligned maps, and its kurtosis and skewness were calculated. Each parameter was correlated with pathological results using the Mann–Whitney test and receiver operating characteristic curve analysis. Results For the Ktrans histogram, the area under the curve (AUC) of the mean, median, 90th percentile and kurtosis had statistically diagnostic values (mean: 0.760; median: 0.661; 90th percentile: 0.781; and kurtosis: 0.620). For the ADC histogram, the AUC of the mean, median, 10th percentile, skewness and kurtosis had statistically diagnostic values (mean: 0.661; median: 0.677; 10th percentile: 0.656; skewness: 0.664; and kurtosis: 0.620). For the 2D Ktrans-ADC histogram, the skewness and kurtosis had statistically higher diagnostic values (skewness: 0.831, kurtosis: 0.828) than those of the 1D histogram (all P < 0.05). Conclusions The dual-parametric 2D histogram analysis revealed better diagnostic accuracy for breast lesions than single parametric histogram analysis of either Ktrans or ADC maps.
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Affiliation(s)
- Yanqiong Chen
- Fudan University Shanghai Cancer Center, No. 270, Dong'an Rd, Shanghai, 200032, China
| | - Bin Wu
- Fudan University Shanghai Cancer Center, No. 270, Dong'an Rd, Shanghai, 200032, China
| | - Hui Liu
- Imaging Technology (Shanghai), Shanghai, China
| | - Dan Wang
- Fudan University Shanghai Cancer Center, No. 270, Dong'an Rd, Shanghai, 200032, China
| | - Yajia Gu
- Fudan University Shanghai Cancer Center, No. 270, Dong'an Rd, Shanghai, 200032, China.
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14
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Shukla-Dave A, Obuchowski NA, Chenevert TL, Jambawalikar S, Schwartz LH, Malyarenko D, Huang W, Noworolski SM, Young RJ, Shiroishi MS, Kim H, Coolens C, Laue H, Chung C, Rosen M, Boss M, Jackson EF. Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials. J Magn Reson Imaging 2018; 49:e101-e121. [PMID: 30451345 DOI: 10.1002/jmri.26518] [Citation(s) in RCA: 199] [Impact Index Per Article: 33.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 09/06/2018] [Accepted: 09/06/2018] [Indexed: 12/14/2022] Open
Abstract
Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.
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Affiliation(s)
- Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Nancy A Obuchowski
- Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Thomas L Chenevert
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Sachin Jambawalikar
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - Lawrence H Schwartz
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - Dariya Malyarenko
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Wei Huang
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Susan M Noworolski
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Robert J Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Mark S Shiroishi
- Division of Neuroradiology, Department of Radiology, University of Southern California, Los Angeles, California, USA
| | - Harrison Kim
- Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Catherine Coolens
- Department of Radiation Oncology, Princess Margaret Cancer Centre, Toronto, Canada
| | | | - Caroline Chung
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas, USA
| | - Mark Rosen
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michael Boss
- Applied Physics Division, National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Edward F Jackson
- Departments of Medical Physics, Radiology, and Human Oncology, University of Wisconsin School of Medicine, Madison, Wisconsin, USA
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15
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Sagawa H, Kataoka M, Kanao S, Onishi N, Nickel MD, Toi M, Togashi K. Impact of the Number of Iterations in Compressed Sensing Reconstruction on Ultrafast Dynamic Contrast-enhanced Breast MR Imaging. Magn Reson Med Sci 2018; 18:200-207. [PMID: 30416179 PMCID: PMC6630053 DOI: 10.2463/mrms.mp.2018-0015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Purpose: To assess the impact of the number of iterations of compressed sensing (CS) reconstruction on the kinetic parameters and image quality in dynamic contrast-enhanced (DCE)-MRI of the breast, with prospectively undersampled CS-accelerated scans. Materials and Methods: Breast examinations including ultrafast DCE-MRI using CS were conducted for 21 patients. Images were reconstructed with different numbers of iterations. The peak enhancement ratio of the aorta and wash-in slope, initial area under the curve, and Ktrans of the breast lesions were measured. The root mean square error and structural similarity between the images using 50 iterations and images with a lower number of iterations were evaluated as criterion for quantitative image evaluation. Results: Using an insufficient number of iterations, the contrast-enhanced effect was highly underestimated. In all semi-quantitative parameters, the number of iterations that stabilized the parameters in malignant lesions was higher than that in benign lesions. At least 15 iterations were needed for semi-quantitative parameters. For Ktrans, there were no significant differences between 10 and 50 iterations in both malignant and benign lesions. Conclusion: The kinetic parameters using ultrafast DCE-MRI with CS are affected by the number of iterations, especially in malignant lesions. However, if the images are reconstructed with an adequate number of iterations, ultrafast DCE-MRI with CS can be a powerful technique having high temporal and spatial resolution.
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Affiliation(s)
- Hajime Sagawa
- Division of Clinical Radiology Service, Kyoto University Hospital
| | - Masako Kataoka
- Division of Clinical Radiology Service, Kyoto University Hospital
| | - Shotaro Kanao
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine
| | - Natsuko Onishi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine
| | | | - Masakazu Toi
- Department of Breast Surgery, Kyoto University Graduate School of Medicine
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine
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16
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Patella F, Franceschelli G, Petrillo M, Sansone M, Fusco R, Pesapane F, Pompili G, Ierardi AM, Saibene AM, Moneghini L, Biglioli F, Carrafiello G. A multiparametric analysis combining DCE-MRI- and IVIM -derived parameters to improve differentiation of parotid tumors: a pilot study. Future Oncol 2018; 14:2893-2903. [PMID: 29425058 DOI: 10.2217/fon-2017-0655] [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] [Indexed: 12/25/2022] Open
Abstract
AIM To evaluate dynamic contrast-enhanced (DCE)-MRI and diffusion weighted (DW)-MRI diagnostic value to differentiate Warthin tumors (WT) by pleomorphic adenomas (PA). MATERIALS & METHODS Seven WT and seven PA were examined. DCE- and DW-MRI parameters were extracted from volumes of interest; volume of interest-based averages and standard deviations were calculated. Statistical analysis included: linear discriminant analysis, receiver operating characteristic curves, sensitivity and specificity. RESULTS No single feature was able to differentiate WT by PA (p > 0.05); linear discriminant analysis analysis showed that a combination of all features or combinations of feature pairs (namely: Ktrans(std) & f(std), Ktrans(std) & D(std), kep(std) & D(std), MRE(av) & TTP(av)) might achieve sensitivity (SENS), specificity (SPEC) = 100%, with a slight reduction after cross-validation analysis (SENS = 0.875; SPEC = 1). CONCLUSION Although preliminary and not conclusive, our results suggest that differentiation between WT and PA is possible through a multiparametric approach based on combination of DCE- and DW-MRI parameters.
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Affiliation(s)
- Francesca Patella
- Postgraduation School of Radiodiagnostic of Milan, Università degli Studi di Milano, Milan, Italy
| | | | - Mario Petrillo
- Diagnostic & Interventional Radiology Service, San Paolo Hospital, Milan, Italy
| | - Mario Sansone
- Department of Electrical Engineering & Information Technologies, University "Federico II" of Naples, Via Claudio, Naples, Italy
| | - Roberta Fusco
- Radiology Unit, "Dipartimento di supporto ai percorsi oncologici Area Diagnostica, Istituto Nazionale Tumori - IRCCS - Fondazione G Pascale", Via Mariano Semmola, Naples, Italy
| | - Filippo Pesapane
- Postgraduation School of Radiodiagnostic of Milan, Università degli Studi di Milano, Milan, Italy
| | - Giovanni Pompili
- Diagnostic & Interventional Radiology Service, San Paolo Hospital, Milan, Italy
| | - Anna Maria Ierardi
- Diagnostic & Interventional Radiology Service, San Paolo Hospital, Milan, Italy
| | - Alberto Maria Saibene
- Otolaryngology Unit, ASST Santi Paolo e Carlo, Department of Health Sciences, Università degli Studi di Milano, Milan, Italy
| | - Laura Moneghini
- Department of Health Sciences, Division of Pathology, University of Milan, AO Santi Paolo e Carlo, 20142 Milan, Italy
| | - Federico Biglioli
- Maxillofacial Surgery Unit, ASST Santi Paolo e Carlo, Università degli Studi di Milano, Milan, Italy
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17
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Sorace AG, Partridge SC, Li X, Virostko J, Barnes SL, Hippe DS, Huang W, Yankeelov TE. Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial. J Med Imaging (Bellingham) 2018; 5:011019. [PMID: 29392160 DOI: 10.1117/1.jmi.5.1.011019] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 12/18/2017] [Indexed: 01/10/2023] Open
Abstract
Comparative preliminary analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data collected in the International Breast MR Consortium 6883 multicenter trial was performed to distinguish benign and malignant breast tumors. Prebiopsy DCE-MRI data from 45 patients with suspicious breast lesions were obtained. Semiquantitative mean signal-enhancement ratio ([Formula: see text]) was calculated for all lesions, and quantitative pharmacokinetic, parameters [Formula: see text], [Formula: see text], and [Formula: see text], were calculated for the subset with available [Formula: see text] maps ([Formula: see text]). Diagnostic performance was estimated for DCE-MRI parameters and compared to standard clinical MRI assessment. Quantitative and semiquantitative metrics discriminated benign and malignant lesions, with receiver operating characteristic area under the curve (AUC) values of 0.71, 0.70, and 0.82 for [Formula: see text], [Formula: see text], and [Formula: see text], respectively ([Formula: see text]). At equal 94% sensitivity, the specificity and positive predictive value of [Formula: see text] (53% and 63%, respectively) and Ktrans (42% and 58%) were higher than clinical MRI assessment (32% and 54%). A multivariable model combining [Formula: see text] and clinical MRI assessment had an AUC value of 0.87. Quantitative pharmacokinetic and semiquantitative analyses of DCE-MRI improves discrimination of benign and malignant breast tumors, with our findings suggesting higher diagnostic accuracy using [Formula: see text]. [Formula: see text] has potential to help reduce unnecessary biopsies resulting from routine breast imaging.
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Affiliation(s)
- Anna G Sorace
- University of Texas at Austin, Department of Diagnostic Medicine, Austin, Texas, United States.,University of Texas at Austin, Livestrong Cancer Institutes, Austin, Texas, United States.,University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas, United States
| | - Savannah C Partridge
- University of Washington, Department of Radiology, Seattle, Washington, United States
| | - Xia Li
- GE Global Research, Niskayuna, New York, United States
| | - Jack Virostko
- University of Texas at Austin, Department of Diagnostic Medicine, Austin, Texas, United States.,University of Texas at Austin, Livestrong Cancer Institutes, Austin, Texas, United States
| | - Stephanie L Barnes
- University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas, United States.,University of Texas at Austin, Institute for Computational and Engineering Sciences, Austin, Texas, United States
| | - Daniel S Hippe
- University of Washington, Department of Radiology, Seattle, Washington, United States
| | - Wei Huang
- Oregon Health and Science University, Advanced Imaging Research Center, Portland, Oregon, United States.,Oregon Health and Science University, Knight Cancer Institute, Portland, Oregon, United States
| | - Thomas E Yankeelov
- University of Texas at Austin, Department of Diagnostic Medicine, Austin, Texas, United States.,University of Texas at Austin, Livestrong Cancer Institutes, Austin, Texas, United States.,University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas, United States.,University of Texas at Austin, Institute for Computational and Engineering Sciences, Austin, Texas, United States
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18
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Heacock L, Lewin AA, Gao Y, Babb JS, Heller SL, Melsaether AN, Bagadiya N, Kim SG, Moy L. Feasibility analysis of early temporal kinetics as a surrogate marker for breast tumor type, grade, and aggressiveness. J Magn Reson Imaging 2017; 47:1692-1700. [PMID: 29178258 DOI: 10.1002/jmri.25897] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Accepted: 10/30/2017] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Screening breast MRI has been shown to preferentially detect high-grade ductal carcinoma in situ (DCIS) and invasive carcinoma, likely due to increased angiogenesis resulting in early initial uptake of contrast. As interest grows in abbreviated screening breast MRI (AB-MRI), markers of early contrast washin that can predict tumor grade and potential aggressiveness are of clinical interest. PURPOSE To evaluate the feasibility of using the initial enhancement ratio (IER) as a surrogate marker for tumor grade, hormone receptor status, and prognostic markers, as an initial step to being incorporated into AB-MRI. STUDY TYPE Retrospective. SUBJECTS In all, 162 women (mean 55.0 years, range 32.8-87.7 years) with 187 malignancies imaged January 2012-November 2015. FIELD STRENGTH/SEQUENCE Images were acquired at 3.0T with a T1 -weighted gradient echo fat-suppressed-volume interpolated breath-hold sequence. ASSESSMENT Subjects underwent dynamic contrast-enhanced breast MRI with a 7-channel breast coil. IER (% signal increase over baseline at the first postcontrast acquisition) was assessed and correlated with background parenchymal enhancement, washout curves, stage, and final pathology. STATISTICAL TESTS Chi-square test, Spearman rank correlation, Mann-Whitney U-tests, Bland-Altman analysis, and receiver operating characteristic curve analysis. RESULTS IER was higher for invasive cancer than for DCIS (R1/R2, P < 0.001). IER increased with tumor grade (R1: r = 0.56, P < 0.001, R2: r = 0.50, P < 0.001), as ki-67 increased (R1: r = 0.35, P < 0.001; R2 r = 0.35, P < 0.001), and for node-positive disease (R1/R2, P = 0.001). IER was higher for human epidermal growth factor receptor two-positive and triple negative cancers than for estrogen receptor-positive / progesterone receptor-positive tumors (R1 P < 0.001-0.002; R2 P = 0.0.001-0.011). IER had higher sensitivity (80.6% vs. 75.5%) and specificity (55.8% vs. 48.1%) than washout curves for positive nodes, higher specificity (48.1% vs. 36.5%) and positive predictive value (70.2% vs. 66.7%) for high ki-67, and excellent interobserver agreement (intraclass correlation coefficient = 0.82). DATA CONCLUSION IER, a measurement of early contrast washin, is associated with higher-grade malignancies and tumor aggressiveness and might be potentially incorporated into an AB-MRI protocol. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1692-1700.
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Affiliation(s)
- Laura Heacock
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Alana A Lewin
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Yiming Gao
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - James S Babb
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Samantha L Heller
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Amy N Melsaether
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2 R), New York University School of Medicine, New York, New York, USA
| | - Neeti Bagadiya
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Sungheon G Kim
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2 R), New York University School of Medicine, New York, New York, USA
| | - Linda Moy
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2 R), New York University School of Medicine, New York, New York, USA
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19
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Xu T, Zhang L, Xu H, Kang S, Xu Y, Luo X, Hua T, Tang G. Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis. Oncotarget 2017; 8:114360-114370. [PMID: 29371992 PMCID: PMC5768409 DOI: 10.18632/oncotarget.22267] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 07/26/2017] [Indexed: 12/17/2022] Open
Abstract
Purpose This study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis. Materials and Methods Approval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis. Results Low-risk tumors showed significantly lower Ktrans and Kepvalues (t = 2.065, P = 0.043 and t = 3.548, P = 0.001, respectively) and higher ADC value (t = 4.713, P = 0.000) than non-low-risk breast cancers. Our results revealed no significant differences in clinic data and conventional imaging findings between the two breast cancer subtypes. Adding the quantitative DCE-MRI parameters and ADC values to conventional MRI improved the diagnostic performance of MRI: The area under the ROC improved from 0.63 to 0.91. Low-risk breast cancers showed significantly lower matrix metalloproteinase (MMP)-2 expression (P = 0.000), lower MMP-9 expression (P = 0.001), and lower microvessel density (MVD) values (P = 0.008) compared with non-low-risk breast cancers. Ktrans and Kep values were positively correlated with pathological biomarkers. The ADC value showed a significant inverse correlation with pathological biomarkers. Conclusions The prediction parameter using Ktrans, Kep, and ADC obtained on DCE-MRI and diffusion-weighted imaging could facilitate the identification of low-risk breast cancers. Decreased biological factors, including MVD, vascular endothelial growth factor, MMP-2, and MMP-9, may explain the possible pathological basis.
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Affiliation(s)
- Tingting Xu
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Lin Zhang
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Hong Xu
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Sifeng Kang
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Yali Xu
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Xiaoyu Luo
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Ting Hua
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Guangyu Tang
- Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
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Li Z, Ai T, Hu Y, Yan X, Nickel MD, Xu X, Xia L. Application of whole-lesion histogram analysis of pharmacokinetic parameters in dynamic contrast-enhanced MRI of breast lesions with the CAIPIRINHA-Dixon-TWIST-VIBE technique. J Magn Reson Imaging 2017; 47:91-96. [PMID: 28577335 DOI: 10.1002/jmri.25762] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Accepted: 04/26/2017] [Indexed: 12/23/2022] Open
Abstract
PURPOSE To investigate the application of whole-lesion histogram analysis of pharmacokinetic parameters for differentiating malignant from benign breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS In all, 92 women with 97 breast lesions (26 benign and 71 malignant lesions) were enrolled in this study. Patients underwent dynamic breast MRI at 3T using a prototypical CAIPIRINHA-Dixon-TWIST-VIBE (CDT-VIBE) sequence and a subsequent surgery or biopsy. Inflow rate of the agent between plasma and interstitium (Ktrans ), outflow rate of agent between interstitium and plasma (Kep ), extravascular space volume per unit volume of tissue (ve ) including mean value, 25th/50th/75th/90th percentiles, skewness, and kurtosis were then calculated based on the whole lesion. A single-sample Kolmogorov-Smirnov test, paired t-test, and receiver operating characteristic curve (ROC) analysis were used for statistical analysis. RESULTS Malignant breast lesions had significantly higher Ktrans , Kep , and lower ve in mean values, 25th/50th/75th/90th percentiles, and significantly higher skewness of ve than benign breast lesions (all P < 0.05). There was no significant difference in kurtosis values between malignant and benign breast lesions (all P > 0.05). The 90th percentile of Ktrans , the 90th percentile of Kep , and the 50th percentile of ve showed the greatest areas under the ROC curve (AUC) for each pharmacokinetic parameter derived from DCE-MRI. The 90th percentile of Kep achieved the highest AUC value (0.927) among all histogram-derived values. CONCLUSION The whole-lesion histogram analysis of pharmacokinetic parameters can improve the diagnostic accuracy of breast DCE-MRI with the CDT-VIBE technique. The 90th percentile of Kep may be the best indicator in differentiation between malignant and benign breast lesions. LEVEL OF EVIDENCE 4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2018;47:91-96.
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Affiliation(s)
- Zhiwei Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Tao Ai
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Yiqi Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Xu Yan
- MR Collaboration NE Asia, Siemens Healthcare, Shanghai, P.R. China
| | | | - Xiao Xu
- GE Healthcare Life Science, Shanghai, P.R. China
| | - Liming Xia
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
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Heacock L, Gao Y, Heller SL, Melsaether AN, Babb JS, Block TK, Otazo R, Kim SG, Moy L. Comparison of conventional DCE-MRI and a novel golden-angle radial multicoil compressed sensing method for the evaluation of breast lesion conspicuity. J Magn Reson Imaging 2016; 45:1746-1752. [PMID: 27859874 DOI: 10.1002/jmri.25530] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 10/10/2016] [Indexed: 12/25/2022] Open
Abstract
PURPOSE To compare a novel multicoil compressed sensing technique with flexible temporal resolution, golden-angle radial sparse parallel (GRASP), to conventional fat-suppressed spoiled three-dimensional (3D) gradient-echo (volumetric interpolated breath-hold examination, VIBE) MRI in evaluating the conspicuity of benign and malignant breast lesions. MATERIALS AND METHODS Between March and August 2015, 121 women (24-84 years; mean, 49.7 years) with 180 biopsy-proven benign and malignant lesions were imaged consecutively at 3.0 Tesla in a dynamic contrast-enhanced (DCE) MRI exam using sagittal T1-weighted fat-suppressed 3D VIBE in this Health Insurance Portability and Accountability Act-compliant, retrospective study. Subjects underwent MRI-guided breast biopsy (mean, 13 days [1-95 days]) using GRASP DCE-MRI, a fat-suppressed radial "stack-of-stars" 3D FLASH sequence with golden-angle ordering. Three readers independently evaluated breast lesions on both sequences. Statistical analysis included mixed models with generalized estimating equations, kappa-weighted coefficients and Fisher's exact test. RESULTS All lesions demonstrated good conspicuity on VIBE and GRASP sequences (4.28 ± 0.81 versus 3.65 ± 1.22), with no significant difference in lesion detection (P = 0.248). VIBE had slightly higher lesion conspicuity than GRASP for all lesions, with VIBE 12.6% (0.63/5.0) more conspicuous (P < 0.001). Masses and nonmass enhancement (NME) were more conspicuous on VIBE (P < 0.001), with a larger difference for NME (14.2% versus 9.4% more conspicuous). Malignant lesions were more conspicuous than benign lesions (P < 0.001) on both sequences. CONCLUSION GRASP DCE-MRI, a multicoil compressed sensing technique with high spatial resolution and flexible temporal resolution, has near-comparable performance to conventional VIBE imaging for breast lesion evaluation. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;45:1746-1752.
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Affiliation(s)
- Laura Heacock
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Yiming Gao
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Samantha L Heller
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Amy N Melsaether
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York, USA
| | - James S Babb
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Tobias K Block
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York, USA
| | - Ricardo Otazo
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York, USA
| | - Sungheon G Kim
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York, USA
| | - Linda Moy
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York, USA
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Fusco R, Sansone M, Petrillo M, Setola SV, Granata V, Botti G, Perdonà S, Borzillo V, Muto P, Petrillo A. Multiparametric MRI for prostate cancer detection: Preliminary results on quantitative analysis of dynamic contrast enhanced imaging, diffusion-weighted imaging and spectroscopy imaging. Magn Reson Imaging 2016; 34:839-45. [PMID: 27071309 DOI: 10.1016/j.mri.2016.04.001] [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: 01/31/2016] [Accepted: 04/03/2016] [Indexed: 10/22/2022]
Abstract
INTRODUCTION Early promising data suggest that combined use of both morphological and functional MRI (multi-parametric MR, mpMRI) including MRSI, DWI and DCE may be of additional value for prostate cancer localization and its local staging. The objective of this paper is to evaluate the diagnostic performance of mpMRI in the detection of prostate cancer. METHODS Thirty-one consecutive male patients were screened to be enrolled in a single center prospective observational study. All eligible patients underwent multi-parametric MRI and TRUS (Trans Rectal Ultra Sound) guided prostate biopsies. A register, approved by the Institutional Ethics Committee, included patients enrolled in this study. All patients who decided to undergo the MRI examination signed an explicit informed consensus. MRI data were aligned on a common spatial grid and several functional parameters (perfusion, diffusion and metabolic parameters) were computed. Statistical analysis was conducted in order to compare mpMRI with biopsy-based analysis. RESULTS Statistically significant differences between median values in high Gleason score (≥5) and low Gleason score (<5) to Wilcox on rank sum test were obtained for MRSI parameters and for plasma fraction (Tofts model) of DCE-MRI. The area under curve obtained with ROC analysis showed that the best-performing single-parameter was vp (plasma fraction of Tofts model), while the best parameters combination to discriminate the area with high Gleason score were (Cho+Cr)/Cit and Cho+Cr. Linear Discrimination Analysis showed that the best results were obtained considering the linear combination of all MRSI parameters and the linear combination of all features (perfusion, diffusion and metabolic parameters). CONCLUSIONS In conclusion, our findings showed that by combining morphological MRI, DWI, DCE-MRI and MRSI, an increase in sensitivity and specificity correlated to biopsy Gleason grade could be obtained. Furthermore, morphological and functional MRI could have a diagnostic role in patients with prostate cancer, identifying those patients who will have a negative work-up and those patients at high risk for a high Gleason score cancer of the prostate.
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Affiliation(s)
- Roberta Fusco
- Department of Diagnostic Imaging, Radiant and Metabolic Therapy, "Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS", Via Mariano Semmola, 80131, Naples, Italy.
| | - Mario Sansone
- Department of Electrical Engineering and Information Technologies, University "Federico II" of Naples, Via Claudio 21, 80125, Naples, Italy
| | - Mario Petrillo
- Department of Diagnostic Imaging, Radiant and Metabolic Therapy, "Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS", Via Mariano Semmola, 80131, Naples, Italy
| | - Sergio Venanzio Setola
- Department of Diagnostic Imaging, Radiant and Metabolic Therapy, "Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS", Via Mariano Semmola, 80131, Naples, Italy
| | - Vincenza Granata
- Department of Diagnostic Imaging, Radiant and Metabolic Therapy, "Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS", Via Mariano Semmola, 80131, Naples, Italy
| | - Gerardo Botti
- Department of Pathology, "Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS", Via Mariano Semmola, 80131, Naples, Italy
| | - Sisto Perdonà
- Department of Urology, "Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS", Via Mariano Semmola, 80131, Naples, Italy
| | - Valentina Borzillo
- Department of Diagnostic Imaging, Radiant and Metabolic Therapy, "Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS", Via Mariano Semmola, 80131, Naples, Italy
| | - Paolo Muto
- Department of Diagnostic Imaging, Radiant and Metabolic Therapy, "Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS", Via Mariano Semmola, 80131, Naples, Italy
| | - Antonella Petrillo
- Department of Diagnostic Imaging, Radiant and Metabolic Therapy, "Istituto Nazionale Tumori Fondazione Giovanni Pascale - IRCCS", Via Mariano Semmola, 80131, Naples, Italy
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Magnetic Resonance Imaging: Advanced Applications in Breast Cancer. CURRENT RADIOLOGY REPORTS 2016. [DOI: 10.1007/s40134-016-0142-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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25
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Prediction of low-risk breast cancer using perfusion parameters and apparent diffusion coefficient. Magn Reson Imaging 2016; 34:67-74. [DOI: 10.1016/j.mri.2015.10.028] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Accepted: 10/21/2015] [Indexed: 11/20/2022]
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Khalifa F, Soliman A, El-Baz A, Abou El-Ghar M, El-Diasty T, Gimel'farb G, Ouseph R, Dwyer AC. Models and methods for analyzing DCE-MRI: a review. Med Phys 2015; 41:124301. [PMID: 25471985 DOI: 10.1118/1.4898202] [Citation(s) in RCA: 194] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches. METHODS DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases. RESULTS Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors. CONCLUSIONS Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.
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Affiliation(s)
- Fahmi Khalifa
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, Kentucky 40292 and Electronics and Communication Engineering Department, Mansoura University, Mansoura 35516, Egypt
| | - Ahmed Soliman
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, Kentucky 40292
| | - Ayman El-Baz
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, Kentucky 40292
| | - Mohamed Abou El-Ghar
- Radiology Department, Urology and Nephrology Center, Mansoura University, Mansoura 35516, Egypt
| | - Tarek El-Diasty
- Radiology Department, Urology and Nephrology Center, Mansoura University, Mansoura 35516, Egypt
| | - Georgy Gimel'farb
- Department of Computer Science, University of Auckland, Auckland 1142, New Zealand
| | - Rosemary Ouseph
- Kidney Transplantation-Kidney Disease Center, University of Louisville, Louisville, Kentucky 40202
| | - Amy C Dwyer
- Kidney Transplantation-Kidney Disease Center, University of Louisville, Louisville, Kentucky 40202
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Integration of DCE-MRI and DW-MRI Quantitative Parameters for Breast Lesion Classification. BIOMED RESEARCH INTERNATIONAL 2015; 2015:237863. [PMID: 26339597 PMCID: PMC4538369 DOI: 10.1155/2015/237863] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2014] [Accepted: 04/15/2015] [Indexed: 12/21/2022]
Abstract
OBJECTIVE The purpose of our study was to evaluate the diagnostic value of an imaging protocol combining dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) in patients with suspicious breast lesions. MATERIALS AND METHODS A total of 31 breast lesions (15 malignant and 16 benign proved by histological examination) in 26 female patients were included in this study. For both DCE-MRI and DW-MRI model free and model based parameters were computed pixel by pixel on manually segmented ROIs. Statistical procedures included conventional linear analysis and more advanced techniques for classification of lesions in benign and malignant. RESULTS Our findings indicated no strong correlation between DCE-MRI and DW-MRI parameters. Results of classification analysis show that combining of DCE parameters or DW-MRI parameter, in comparison of single feature, does not yield a dramatic improvement of sensitivity and specificity of the two techniques alone. The best performance was obtained considering a full combination of all features. Moreover, the classification results combining all features are dominated by DCE-MRI features alone. CONCLUSION The combination of DWI and DCE-MRI does not show a potential to dramatically increase the sensitivity and specificity of breast MRI. DCE-MRI alone gave the same performance as in combination with DW-MRI.
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Kratochvíla J, Jiřík R, Bartoš M, Standara M, Starčuk Z, Taxt T. Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI. Magn Reson Med 2015; 75:1355-65. [PMID: 25865576 DOI: 10.1002/mrm.25619] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2014] [Revised: 12/01/2014] [Accepted: 12/24/2014] [Indexed: 12/21/2022]
Abstract
PURPOSE One of the main challenges in quantitative dynamic contrast-enhanced (DCE) MRI is estimation of the arterial input function (AIF). Usually, the signal from a single artery (ignoring contrast dispersion, partial volume effects and flow artifacts) or a population average of such signals (also ignoring variability between patients) is used. METHODS Multi-channel blind deconvolution is an alternative approach avoiding most of these problems. The AIF is estimated directly from the measured tracer concentration curves in several tissues. This contribution extends the published methods of multi-channel blind deconvolution by applying a more realistic model of the impulse residue function, the distributed capillary adiabatic tissue homogeneity model (DCATH). In addition, an alternative AIF model is used and several AIF-scaling methods are tested. RESULTS The proposed method is evaluated on synthetic data with respect to the number of tissue regions and to the signal-to-noise ratio. Evaluation on clinical data (renal cell carcinoma patients before and after the beginning of the treatment) gave consistent results. An initial evaluation on clinical data indicates more reliable and less noise sensitive perfusion parameter estimates. CONCLUSION Blind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup.
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Affiliation(s)
- Jiří Kratochvíla
- Department of Biomedical Engineering, Brno University of Technology, Brno, Czech Republic.,Institute of Scientific Instruments of the Academy of Sciences of the Czech Republic, Brno, Czech Republic
| | - Radovan Jiřík
- Institute of Scientific Instruments of the Academy of Sciences of the Czech Republic, Brno, Czech Republic
| | - Michal Bartoš
- Department of Biomedical Engineering, Brno University of Technology, Brno, Czech Republic.,Institute of Information Technology and Automation of the Academy of Sciences of the Czech Republic, Praha, Czech Republic
| | | | - Zenon Starčuk
- Institute of Scientific Instruments of the Academy of Sciences of the Czech Republic, Brno, Czech Republic
| | - Torfinn Taxt
- Department of Biomedicine, University of Bergen, Bergen, Norway
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Standardized Index of Shape (SIS): a quantitative DCE-MRI parameter to discriminate responders by non-responders after neoadjuvant therapy in LARC. Eur Radiol 2015; 25:1935-45. [PMID: 25577525 DOI: 10.1007/s00330-014-3581-3] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2014] [Revised: 12/15/2014] [Accepted: 12/19/2014] [Indexed: 01/02/2023]
Abstract
OBJECTIVES To investigate the potential of DCE-MRI to discriminate responders from non-responders after neoadjuvant chemo-radiotherapy (CRT) for locally advanced rectal cancer (LARC). We investigated several shape parameters for the time-intensity curve (TIC) in order to identify the best combination of parameters between two linear parameter classifiers. METHODS Seventy-four consecutive patients with LARC were enrolled in a prospective study approved by our ethics committee. Each patient gave written informed consent. After surgery, pathological TNM and tumour regression grade (TRG) were estimated. DCE-MRI semi-quantitative analysis (sqMRI) was performed to identify the best parameter or parameter combination to discriminate responders from non-responders in response monitoring to CRT. Percentage changes of TIC shape descriptors from the baseline to the presurgical scan were assessed and correlated with TRG. Receiver operating characteristic analysis and linear classifier were applied. RESULTS Forty-six patients (62.2%) were classified as responders, while 28 subjects (37.8%) were considered as non-responders. sqMRI reached a sensitivity of 93.5% and a specificity of 82.1% combining the percentage change in Maximum Signal Difference (ΔMSD) and Wash-out Slope (ΔWOS), the Standardized Index of Shape (SIS). CONCLUSIONS SIS obtains the best result in discriminating responders from non-responders after CRT in LARC, with a cut-off value of -3.0%. KEY POINTS • DCE-MRI shape descriptors are investigated to assess preoperative CRT response in LARC. • Identification of the best TIC shape descriptors combination through a linear classifier. • Identification of a single MRI index to predict neoadjuvant treatment response.
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Hao W, Zhao B, Wang G, Wang C, Liu H. Influence of scan duration on the estimation of pharmacokinetic parameters for breast lesions: a study based on CAIPIRINHA-Dixon-TWIST-VIBE technique. Eur Radiol 2014; 25:1162-71. [DOI: 10.1007/s00330-014-3451-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2014] [Revised: 07/24/2014] [Accepted: 09/23/2014] [Indexed: 12/28/2022]
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Payne A, Todd N, Minalga E, Wang Y, Diakite M, Hadley R, Merrill R, Factor R, Neumayer L, Parker DL. In vivo evaluation of a breast-specific magnetic resonance guided focused ultrasound system in a goat udder model. Med Phys 2014; 40:073302. [PMID: 23822456 DOI: 10.1118/1.4811103] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
PURPOSE This work further evaluates the functionality, efficacy, and safety of a new breast-specific magnetic resonance guided high intensity focused ultrasound (MRgFUS) system in an in vivo goat udder model. METHODS Eight female goats underwent an MRgFUS ablation procedure using the breast-specific MRgFUS system. Tissue classification was achieved through the 3D magnetic resonance imaging (MRI) acquisition of several contrasts (T1w, T2w, PDw, 3-point Dixon). The MRgFUS treatment was performed with a grid trajectory executed in one or two planes within the glandular tissue of the goat udder. Temperature was monitored using a 3D proton resonance frequency (PRF) MRI technique. Delayed contrast enhanced-MR images were acquired immediately and 14 days post MRgFUS treatment. A localized tissue excision was performed in one animal and histological analysis was performed. Animals were available for adoption at the conclusion of the study. RESULTS The breast-specific MRgFUS system was able to ablate regions ranging in size from 0.4 to 3.6 cm(3) in the goat udder model. Tissue damage was confirmed through the correlation of thermal dose measurements obtained with realtime 3D MR thermometry to delayed contrast enhanced-MR images immediately after the treatment and 14 days postablation. In general, lesions were longer in the ultrasound propagation direction, which is consistent with the dimensions of the ultrasound focal spot. Thermal dose volumes had better agreement with nonenhancing areas of the DCE-MRI images obtained 14 days after the MRgFUS treatment. CONCLUSIONS The system was able to successfully ablate lesions up to 3.6 cm(3). The thermal dose volume was found to correlate better with the 14-day postablation nonenhancing delayed contrast enhanced-MR image volumes. While the goat udder is not an ideal model for the human breast, this study has proven the feasibility of using this system on a wide variety of udder shapes and sizes, demonstrating the flexibility that would be required in order to treat human subjects.
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Affiliation(s)
- A Payne
- Utah Center for Advanced Imaging Research, University of Utah, 729 Arapeen Drive, Salt Lake City, Utah 84108, USA.
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Furman-Haran E, Feinberg MS, Badikhi D, Eyal E, Zehavi T, Degani H. Standardization of radiological evaluation of dynamic contrast enhanced MRI: application in breast cancer diagnosis. Technol Cancer Res Treat 2013; 13:445-54. [PMID: 24000989 PMCID: PMC4527468 DOI: 10.7785/tcrtexpress.2013.600263] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Dynamic contrast enhanced MRI is applied as an adjuvant tool for breast cancer detection, diagnosis, and follow-up of therapy. Despite improvements through the years in achieving higher spatial and temporal resolution, it still suffers from lack of scanning and processing standardization, and consequently, high variability in the radiological evaluation, particularly differentiating malignant from benign lesions. We describe here a hybrid method for achieving standardization of the radiological evaluation of breast dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) protocols, based on integrating the model based three time point (3TP) method with principal component analysis (PCA). The scanning and image processing procedures consisted of three main steps: 1. 3TP standardization of the MRI acquisition parameters according to a kinetic model, 2. Applying PCA to test cases and constructing an eigenvectors' base related to the contrast-enhancement kinetics and 3. Projecting all new cases on the eigenvectors' base and evaluating the clinical outcome. Datasets of overall 96 malignant and 26 benign breast lesions were recorded on 1.5T and 3T scanners, using three different MRI acquisition parameters optimized by the 3TP method. The final radiological evaluation showed similar detection and diagnostic ability for the three different MRI acquisition parameters. The area under the curve of receiver operating characteristic analysis yielded a value of 0.88 ± 0.034 for differentiating malignant from benign lesions. This 3TP + PCA hybrid method is fast and can be readily applied as a computer aided diagnostic tool of breast cancer. The underlying principles of this method can be extended to standardize the evaluation of malignancies in other organs.
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Pharmacokinetic Approach for Dynamic Breast MRI to Indicate Signal Intensity Time Curves of Benign and Malignant Lesions by Using the Tumor Flow Residence Time. Invest Radiol 2013; 48:69-78. [DOI: 10.1097/rli.0b013e31827d29cf] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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Stoutjesdijk MJ, Zijp M, Boetes C, Karssemeijer N, Barentsz JO, Huisman H. Computer aided analysis of breast MRI enhancement kinetics using mean shift c lustering and multifeature iterative region of interest selection. J Magn Reson Imaging 2012; 36:1104-12. [DOI: 10.1002/jmri.23746] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2011] [Accepted: 06/01/2012] [Indexed: 12/26/2022] Open
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A feasible high spatiotemporal resolution breast DCE-MRI protocol for clinical settings. Magn Reson Imaging 2012; 30:1257-67. [PMID: 22770687 DOI: 10.1016/j.mri.2012.04.009] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2012] [Revised: 04/07/2012] [Accepted: 04/18/2012] [Indexed: 11/23/2022]
Abstract
Three dimensional bilateral imaging is the standard for most clinical breast dynamic contrast-enhanced (DCE) MRI protocols. Because of high spatial resolution (sRes) requirement, the typical 1-2 min temporal resolution (tRes) afforded by a conventional full-k-space-sampling gradient echo (GRE) sequence precludes meaningful and accurate pharmacokinetic analysis of DCE time-course data. The commercially available, GRE-based, k-space undersampling and data sharing TWIST (time-resolved angiography with stochastic trajectories) sequence was used in this study to perform DCE-MRI exams on thirty one patients (with 36 suspicious breast lesions) before their biopsies. The TWIST DCE-MRI was immediately followed by a single-frame conventional GRE acquisition. Blinded from each other, three radiologist readers assessed agreements in multiple lesion morphology categories between the last set of TWIST DCE images and the conventional GRE images. Fleiss' κ test was used to evaluate inter-reader agreement. The TWIST DCE time-course data were subjected to quantitative pharmacokinetic analyses. With a four-channel phased-array breast coil, the TWIST sequence produced DCE images with 20 s or less tRes and ~ 1.0×1.0×1.4 mm(3) sRes. There were no significant differences in signal-to-noise (P=.45) and contrast-to-noise (P=.51) ratios between the TWIST and conventional GRE images. The agreements in morphology evaluations between the two image sets were excellent with the intra-reader agreement ranging from 79% for mass margin to 100% for mammographic density and the inter-reader κ value ranging from 0.54 (P<.0001) for lesion size to 1.00 (P<.0001) for background parenchymal enhancement. Quantitative analyses of the DCE time-course data provided higher breast cancer diagnostic accuracy (91% specificity at 100% sensitivity) than the current clinical practice of morphology and qualitative kinetics assessments. The TWIST sequence may be used in clinical settings to acquire high spatiotemporal resolution breast DCE-MRI images for both precise lesion morphology characterization and accurate pharmacokinetic analysis.
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Fluckiger JU, Schabel MC, Dibella EVR. The effect of temporal sampling on quantitative pharmacokinetic and three-time-point analysis of breast DCE-MRI. Magn Reson Imaging 2012; 30:934-43. [PMID: 22513074 DOI: 10.1016/j.mri.2012.02.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2011] [Revised: 02/15/2012] [Accepted: 02/17/2012] [Indexed: 01/28/2023]
Abstract
The effects of temporal sampling on the previously published three-time-point (3TP) method are compared with those of a Tofts-Kety model using an arterial input function from the alternating minimization with model (AMM) method. Computer simulations are done to estimate the expected error in both the 3TP and Tofts-Kety models as a function of the temporal sampling rate of the data. The error in the 3TP model parameters remained essentially constant with respect to temporal sampling. The Tofts-Kety model showed a linear increase in parameter error with respect to temporal sampling. Both analysis methods were also applied to 87 clinically acquired breast scans. These scans were downsampled in time by a factor of 2 and 4, and the methods were reapplied. The spatial resolution was held constant throughout this study. At temporal resolutions less than 19.4 s, the Tofts-Kety model outperformed the 3TP model using receiver operating characteristic curve analysis (area under the ROC curve [AUC] of 0.94 compared to 0.91). As the temporal sampling rate decreased, the 3TP model outperformed the Tofts-Kety model (AUC of 0.89 versus 0.85). When the temporal sampling rate of the data was less than 20 s, the Tofts-Kety model with the AMM method had lower parameter error than the 3TP method.
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Affiliation(s)
- Jacob U Fluckiger
- Department of Radiology, Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, UT 84108, USA
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Li X, Welch EB, Arlinghaus LR, Chakravarthy AB, Xu L, Farley J, Loveless ME, Mayer IA, Kelley MC, Meszoely IM, Means-Powell JA, Abramson VG, Grau AM, Gore JC, Yankeelov TE. A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer. Phys Med Biol 2011; 56:5753-69. [PMID: 21841212 DOI: 10.1088/0031-9155/56/17/018] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Quantitative analysis of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data requires the accurate determination of the arterial input function (AIF). A novel method for obtaining the AIF is presented here and pharmacokinetic parameters derived from individual and population-based AIFs are then compared. A Philips 3.0 T Achieva MR scanner was used to obtain 20 DCE-MRI data sets from ten breast cancer patients prior to and after one cycle of chemotherapy. Using a semi-automated method to estimate the AIF from the axillary artery, we obtain the AIF for each patient, AIF(ind), and compute a population-averaged AIF, AIF(pop). The extended standard model is used to estimate the physiological parameters using the two types of AIFs. The mean concordance correlation coefficient (CCC) for the AIFs segmented manually and by the proposed AIF tracking approach is 0.96, indicating accurate and automatic tracking of an AIF in DCE-MRI data of the breast is possible. Regarding the kinetic parameters, the CCC values for K(trans), v(p) and v(e) as estimated by AIF(ind) and AIF(pop) are 0.65, 0.74 and 0.31, respectively, based on the region of interest analysis. The average CCC values for the voxel-by-voxel analysis are 0.76, 0.84 and 0.68 for K(trans), v(p) and v(e), respectively. This work indicates that K(trans) and v(p) show good agreement between AIF(pop) and AIF(ind) while there is a weak agreement on v(e).
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Affiliation(s)
- Xia Li
- Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA
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Huang W, Tudorica LA, Li X, Thakur SB, Chen Y, Morris EA, Tagge IJ, Korenblit ME, Rooney WD, Koutcher JA, Springer CS. Discrimination of benign and malignant breast lesions by using shutter-speed dynamic contrast-enhanced MR imaging. Radiology 2011; 261:394-403. [PMID: 21828189 DOI: 10.1148/radiol.11102413] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
PURPOSE To assess the accuracy of the shutter-speed approach compared with standard approach dynamic contrast material-enhanced magnetic resonance (MR) imaging pharmacokinetic analysis for breast cancer diagnosis. MATERIALS AND METHODS This study was approved by the institutional review board and was HIPAA compliant. Informed consent was obtained from 89 high-risk women (age range, 28-83 years) who had 92 suspicious lesions with negative findings at mammography (but visible at MR imaging). Each underwent a research dynamic contrast-enhanced MR imaging examination just prior to a clinical MR imaging-guided interventional procedure. Tumor region of interest (ROI) averaged and (for some) pixel-by-pixel dynamic contrast-enhanced time-course data, together with mean arterial input function, were subjected to serial standard and shutter-speed approach analyses to extract pharmacokinetic parameters, including rate constant for passive contrast reagent transfer between plasma and interstitium (K(trans)) and interstitial space volume fraction, or v(e). Pathologic findings were used as reference standards. Diagnostic accuracy was assessed with receiver operating characteristic analyses. RESULTS The pathologic analyses revealed 20 malignant and 72 benign lesions. Positive predictive value of the institutional clinical breast MR imaging protocol was 22%. At 100% sensitivity, ROI-averaged shutter-speed approach K(trans) had significantly (P = .008) higher diagnostic specificity than standard approach K(trans): 86.1% versus 77.8%. The difference in the ROI-averaged K(trans) parameter value, or ΔK(trans) (≡ K(trans) [shutter-speed approach] - K(trans) [standard approach]), had even higher specificity (88.9%). Combined use of ROI analysis and pixel-by-pixel mapping of ΔK(trans) achieved 98.6% specificity at 100% sensitivity. CONCLUSION The use of the shutter-speed dynamic contrast-enhanced MR imaging method has the potential to improve breast cancer diagnostic accuracy and reduce putatively unnecessary biopsy procedures that yield benign pathologic findings. SUPPLEMENTAL MATERIAL http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11102413/-/DC1.
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Affiliation(s)
- Wei Huang
- W. M. Keck Foundation High-Field MRI Laboratory-Advanced Imaging Research Center, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR 97239, USA.
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De Naeyer D, Debergh I, De Deene Y, Ceelen WP, Segers P, Verdonck P. First order correction for T2*-relaxation in determining contrast agent concentration from spoiled gradient echo pulse sequence signal intensity. J Magn Reson Imaging 2011; 34:710-5. [PMID: 21769976 DOI: 10.1002/jmri.22681] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2010] [Accepted: 05/23/2011] [Indexed: 11/10/2022] Open
Abstract
PURPOSE To investigate the accuracy of a method neglecting T(2)*-relaxation, for the conversion of spoiled gradient echo pulse sequence signal intensity to contrast agent (CA) concentration, in dynamic contrast enhanced MRI studies. In addition a new closed form conversion expression is proposed that accounts for a first order approximation of T(2)*-relaxation. MATERIALS AND METHODS The accuracy of both conversion methods is compared theoretically by means of simulations for four pulse sequences from literature. Both methods are tested in vivo against the numerical conversion method for measuring the arterial input function in mice. RESULTS Simulations show that the T(2)*-neglecting method underestimates typical tissue CA concentrations (0 mM to 2 mM) up to 6%, while the errors for arterial concentrations (0 mM to 10 mM) range up to 43%. The results from our first order method are numerically indistinguishable from the simulation input values in tumor tissue, while for arterial concentrations the error is reduced up to a factor 10. In vivo, peak Gd-DOTA concentration is underestimated up to 14% with the T(2)*-neglecting method and up to 0.9% with our first order method. CONCLUSION Our conversion method reduces the underestimation of CA concentration severely in a broad physiological concentration range and is easy to perform in any clinical setting.
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Affiliation(s)
- Dieter De Naeyer
- Institute Biomedical Technology (IBiTech), Department of Civil Engineering, Ghent University, Belgium.
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Leung TK, Huang PJ, Lee CM, Chen CS, Wu CH, Chao JS. Can breast magnetic resonance imaging demonstrate characteristic findings of preoperative ductal carcinoma in situ in Taiwanese women? Asian J Surg 2010; 33:143-9. [PMID: 21163412 DOI: 10.1016/s1015-9584(10)60024-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/14/2010] [Indexed: 12/01/2022] Open
Abstract
OBJECTIVE Magnetic resonance imaging (MRI) is more sensitive than mammography and sonography for breast cancer detection, but its diagnostic specificity is still being debated, and standardised criteria are lacking. METHODS This study used a dedicated breast MRI system with a Spiral RODEO pulse sequence, and applied postprocessing techniques including multiplanar reformation (MPR) with ductal orientation, early subtracted phase (ESP) and a postcontrast kinetic curve. We discuss the possible MRI/pathology correlations based on pathogenetic concepts. We retrospectively collected data from 13 cases of benign intraductal and early-stage malignant lesions to observe the capability of MPR, ESP and kinetic curve techniques to diagnose early lesions differentially. MRI features and pathological findings for these cases were collected. RESULTS Thirteen cases of ductal carcinoma in situ with MRI characteristics and pathological findings were identified. We analysed early ductal lesions, such as intraductal epithelial hyperplasia, intraductal papilloma, ductal carcinoma in situ and small focal invasive ductal carcinoma. Using MRI with MPR to demonstrate ductal orientation, we found 12 cases with a ductogram appearance and 6 with crossing-over glandular tissue. The tumour size estimated by MRI was accurate in 6 cases, but overestimated in seven. CONCLUSION Dedicated breast MRI with MPR, ESP and kinetic curve analyses might be helpful in defining some characteristics of early-stage malignant lesions.
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Affiliation(s)
- Ting-Kai Leung
- Department of Diagnostic Radiology, Taipei Medical University Hospital, No. 2523 Wu Hsing Street, Taipei 110, Taiwan.
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