Online citations, reference lists, and bibliographies.
Please confirm you are human
(Sign Up for free to never see this)
← Back to Search

Intravoxel Incoherent Motion MR Imaging For Breast Lesions: Comparison And Correlation With Pharmacokinetic Evaluation From Dynamic Contrast-enhanced MR Imaging

C. Liu, K. Wang, Q. Chan, Zaiyi Liu, Jine Zhang, H. He, Shuixing Zhang, Changhong Liang
Published 2016 · Medicine

Save to my Library
Download PDF
Analyze on Scholarcy
AbstractObjectivesTo compare diagnostic performance for breast lesions by quantitative parameters derived from intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and to explore whether correlations exist between these parameters.MethodsIVIM and DCE MRI were performed on a 1.5-T MRI scanner in patients with suspicious breast lesions. Thirty-six breast cancers and 23 benign lesions were included in the study. Quantitative parameters from IVIM (D, f and D*) and DCE MRI (Ktrans, Kep, Ve and Vp) were calculated and compared between malignant and benign lesions. Spearman correlation test was used to evaluate correlations between them.ResultsD, f, D* from IVIM and Ktrans, Kep, Vp from DCE MRI were statistically different between breast cancers and benign lesions (p < 0.05, respectively) and D demonstrated the largest area under the receiver-operating characteristic curve (AUC = 0.917) and had the highest specificity (83 %). The f value was moderately statistically correlated with Vp (r = 0.692) and had a poor correlation with Ktrans (r = 0.456).ConclusionsIVIM MRI is useful in the differentiation of breast lesions. Significant correlations were found between perfusion-related parameters from IVIM and DCE MRI. IVIM may be a useful adjunctive tool to standard MRI in diagnosing breast cancer.Key Points• IVIM provided diffusion as well as perfusion information • IVIM could help differential diagnosis of breast lesions • Correlations were found between perfusion-related parameters from IVIM and DCE MRI
This paper references
Liver cirrhosis: intravoxel incoherent motion MR imaging--pilot study.
A. Luciani (2008)
Quantitative Non-Gaussian Diffusion and Intravoxel Incoherent Motion Magnetic Resonance Imaging: Differentiation of Malignant and Benign Breast Lesions
M. Iima (2015)
Head and neck tumours: combined MRI assessment based on IVIM and TIC analyses for the differentiation of tumors of different histological types
M. Sumi (2013)
Estimating kinetic parameters from dynamic contrast‐enhanced t1‐weighted MRI of a diffusable tracer: Standardized quantities and symbols
P. Tofts (1999)
Perfusion-related parameters in intravoxel incoherent motion MR imaging compared with CBV and CBF measured by dynamic susceptibility-contrast MR technique
R. Wirestam (2001)
IHM, Zuithoff NPA et al (2008)Metaanalysis of MR imaging in the diagnosis of breast lesions
Peters NHGM (2008)
Intravoxel incoherent motion MR imaging of the kidney: pilot study.
Per Eckerbom (2013)
Quantitative analysis of 3-Tesla magnetic resonance imaging in the differential diagnosis of breast lesions
Zhen-Shen Ma (2015)
Cancer statistics, 2012
R. Siegel (2012)
Predicting pathologic response to neoadjuvant chemotherapy in breast cancer by using MR imaging and quantitative 1H MR spectroscopy.
H. Baek (2009)
Initial experience of correlating parameters of intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging at 3.0 T in nasopharyngeal carcinoma
Qian-jun Jia (2014)
Meta-analysis of quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesions
X. Chen (2010)
Diffusion weighted imaging (DWI) of the breast: ready for clinical practice?
C. Lehman (2012)
Intravoxel incoherent motion MRI: emerging applications for nasopharyngeal carcinoma at the primary site
S. Zhang (2014)
Intravoxel incoherent motion diffusion‐weighted MRI at 3.0 T differentiates malignant breast lesions from benign lesions and breast parenchyma
L. Bokacheva (2014)
Imaging and cancer: research strategy of the American College of Radiology Imaging Network.
D. Aberle (2005)
Assessment of tumor blood perfusion by high‐resolution dynamic contrast‐enhanced MRI: A preclinical study of human melanoma xenografts
Ilana C Benjaminsen (2004)
Use of Intravoxel Incoherent Motion MR Imaging to Assess Placental Perfusion in a Murine Model of Placental Insufficiency
M. Alison (2013)
Meta-analysis of MR imaging in the diagnosis of breast lesions.
N. Peters (2008)
Biexponential Signal Attenuation Analysis of Diffusion-weighted Imaging of Breast.
T. Tamura (2010)
Intravoxel incoherent motion diffusion-weighted MR imaging in differentiation of lung cancer from obstructive lung consolidation: comparison and correlation with pharmacokinetic analysis from dynamic contrast-enhanced MR imaging
L. Wang (2014)
Efficient method for calculating kinetic parameters using T1‐weighted dynamic contrast‐enhanced magnetic resonance imaging
K. Murase (2004)
Diffusion weighted magnetic resonance imaging of the breast: protocol optimization, interpretation, and clinical applications.
S. Partridge (2013)
Intravoxel incoherent motion MR imaging for prostate cancer: An evaluation of perfusion fraction and diffusion coefficient derived from different b‐value combinations
Y. Pang (2013)
Differential diagnosis of mammographically and clinically occult breast lesions on diffusion‐weighted MRI
S. Partridge (2010)
Modeling tracer kinetics in dynamic Gd‐DTPA MR imaging
P. Tofts (1997)
Correlation of perfusion parameters on dynamic contrast‐enhanced MRI with prognostic factors and subtypes of breast cancers
H. R. Koo (2012)
1997)Modeling tracer kinetics in dynamic Gd-DTPAMR imaging
PS Tofts (1997)
Intravoxel incoherent motion diffusion-weighted imaging in nonalcoholic fatty liver disease: a 3.0-T MR study.
B. Guiu (2012)
Intravoxel incoherent motion (IVIM) in evaluation of breast lesions: comparison with conventional DWI.
C. Liu (2013)
Intravoxel incoherent motion imaging of tumor microenvironment in locally advanced breast cancer
E. Sigmund (2011)
Diffusion-weighted Imaging Improves the Diagnostic Accuracy of Conventional 3.0-T
R. Khouli (2010)
Salivary gland tumors: use of intravoxel incoherent motion MR imaging for assessment of diffusion and perfusion for the differentiation of benign from malignant tumors.
M. Sumi (2012)
Comparisons of multi b‐value DWI signal analysis with pathological specimen of breast cancer
T. Tamura (2012)
Diffusion weighted MRI of the breast: Protocol optimization, guidelines for interpretation, and potential clinical applications
S. Partridge (2013)
The Histogram Analysis of Diffusion-Weighted Intravoxel Incoherent Motion (IVIM) Imaging for Differentiating the Gleason grade of Prostate Cancer
Y. Zhang (2014)
Normalization of Tumor Vasculature: An Emerging Concept in Antiangiogenic Therapy
R. Jain (2005)
MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders.
D. Le Bihan (1986)
Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging: a modest proposal with tremendous potential.
W. T. Dixon (1988)
Imaging and Cancer: Research Strategy of the American College of Radiology Imaging NetworkAberle DR, Chiles C, Gatsonis C, et al (Univ of California, Los Angeles; Wake Forest Univ, Winston-Salem, NC; Brown Univ, Providence, RI; et al) Radiology 235:741–751, 2005§
C. Maynard (2006)

This paper is referenced by
Comments on "Intravoxel incoherent motion diffusion-weighted imaging as an adjunct to dynamic contrast-enhanced MRI to improve accuracy of the differential diagnosis of benign and malignant breast lesions".
S. Zhou (2018)
Intravoxel Incoherent Motion Combined With Dynamic Contrast‐Enhanced Perfusion MRI of Early Cervical Carcinoma: Correlations Between Multimodal Parameters and HIF‐1α Expression
Xiangsheng Li (2019)
Value of intravoxel incoherent motion diffusion-weighted MR imaging in differentiating malignant from benign pulmonary lesions : a meta analysis
Xiliang Chen (2017)
Innovation in Breast Cancer Radiology
R. Rahim (2017)
Histogram Analysis Comparison of Monoexponential, Advanced Diffusion‐Weighted Imaging, and Dynamic Contrast‐Enhanced MRI for Differentiating Borderline From Malignant Epithelial Ovarian Tumors
Mengge He (2020)
Assessment of Correlation between Intravoxel Incoherent Motion Diffusion Weighted MR Imaging and Dynamic Contrast-Enhanced MR Imaging of Sacroiliitis with Ankylosing Spondylitis
Yinghua Zhao (2017)
Role of intravoxel incoherent motion MRI in preoperative evaluation of DNA mismatch repair status in rectal cancers.
C. Yan (2019)
Quantitative dynamic contrast-enhanced MR imaging for differentiating benign, borderline, and malignant ovarian tumors
Hai-ming Li (2018)
Use of diffusion kurtosis imaging and quantitative dynamic contrast‐enhanced MRI for the differentiation of breast tumors
T. Li (2018)
The volumetric-tumour histogram-based analysis of intravoxel incoherent motion and non-Gaussian diffusion MRI: association with prognostic factors in HER2-positive breast cancer
C. You (2019)
Diffusion-weighted imaging and diffusion kurtosis imaging for early evaluation of the response to docetaxel in rat epithelial ovarian cancer
Su-juan Yuan (2018)
Intravoxel Incoherent Motion Diffusion-Weighted Imaging Used to Detect Prostate Cancer and Stratify Tumor Grade: A Meta-Analysis
Ni He (2020)
Differentiation Between Luminal-A and Luminal-B Breast Cancer Using Intravoxel Incoherent Motion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging.
H. Kawashima (2017)
Intravoxel incoherent motion diffusion‐weighted MRI of invasive breast cancer: Correlation with prognostic factors and kinetic features acquired with computer‐aided diagnosis
S. Song (2019)
Differentiating the lung lesions using Intravoxel incoherent motion diffusion-weighted imaging: a meta-analysis
Jianye Liang (2020)
Intravoxel Incoherent Motion Diffusion-Weighted Imaging Versus Dynamic Contrast-Enhanced Magnetic Resonance Imaging: Comparison of the Diagnostic Performance of Perfusion-Related Parameters in Breast
L. Jiang (2018)
Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Quantitative Differentiation of Breast Tumors: A Meta-Analysis
J. Liang (2020)
New Segmentation Models for the Radiologic Characterization of Polycystic Kidney Disease Patients from MR and CT Images
D. Turco (2017)
Differential diagnosis and clinicopathological study of single index IVIM, DWI, and DKI models in benign and malignant breast lesions
Huiyang Wang (2020)
Intravoxel Incoherent Motion MR Imaging in the Differentiation of Benign and Malignant Sinonasal Lesions: Comparison with Conventional Diffusion-Weighted MR Imaging
Z. Xiao (2018)
Standard diffusion-weighted, diffusion kurtosis and intravoxel incoherent motion MR imaging of sinonasal malignancies: correlations with Ki-67 proliferation status
Z. Xiao (2017)
Correlation Between Intravoxel Incoherent Motion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Parameters in Rectal Cancer.
H. Sun (2019)
Comparison of Intravoxel incoherent motion imaging and multiecho dynamic contrast‐based MRI in rectal cancer
K. M. Bakke (2019)
Relative Enhanced Diffusivity in Prostate Cancer: Protocol Optimization and Diagnostic Potential
Daniel C Billdal (2019)
Discrimination of Malignant and Benign Breast Lesions Using Quantitative Multiparametric MRI: A Preliminary Study
Kurt Li (2020)
The potential of multiparametric MRI of the breast.
K. Pinker (2017)
Evaluation of myocardial microcirculation using intravoxel incoherent motion imaging
Anna Mou (2017)
Application of dynamic contrast enhanced MRI in the diagnosis of brucellar spondylitis
P. Zhao (2019)
Intravoxel incoherent motion magnetic resonance imaging for breast cancer: A comparison with benign lesions and evaluation of heterogeneity in different tumor regions with prognostic factors and molecular classification
M. Zhao (2018)
Can whole-tumor apparent diffusion coefficient histogram analysis be helpful to evaluate breast phyllode tumor grades?
Y. Guo (2019)
Diffusion MRI of the breast: Current status and future directions
M. Iima (2019)
Intravoxel incoherent motion MR imaging for differentiating malignant lesions in spine: A pilot study.
Yan-jun Chen (2019)
See more
Semantic Scholar Logo Some data provided by SemanticScholar