scholarly journals Texture features and pharmacokinetic parameters in differentiating benign and malignant breast lesions by dynamic contrast enhanced magnetic resonance imaging

2018 ◽  
Author(s):  
Qingliang Niu ◽  
Xiaomei Jiang ◽  
Qin Li ◽  
Zhaolong Zheng ◽  
Hanwang Du ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Texture Features ◽  
Pharmacokinetic Parameters ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Malignant Breast

The value of dynamic contrast-enhanced magnetic resonance imaging combined with apparent diffusion coefficient in the differentiation of benign and malignant diseases of the breast

2021 ◽  
pp. 028418512110240
Author(s):  
Feng Ao ◽  
Yi Yan ◽  
Zi-Li Zhang ◽  
Sheng Li ◽  
Wen-Jing Li ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Lesion Group ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Apparent Diffusion ◽  
Malignant Breast ◽  
Diagnostic Criterion

Background The value of combined dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coefficient (ADC) histogram analysis for the diagnosis of breast cancer has not been evaluated in previous studies. Purpose To investigate the diagnostic value of DCE-MRI combined with ADC in benign and malignant breast lesions. Material and Methods The clinicopathological imaging data included 168 patients (177 lesions) with breast lesions who underwent convention breast MRI, DCE-MRI, and diffusion-weighted imaging (DWI); they were divided into the benign lesion group (n = 39) and malignant lesion group (n = 129) based on pathology. Results Using the type III outflow curve as a diagnostic criterion for malignant breast lesions, the diagnostic sensitivity was 76.9%, the specificity was 80%, the correct rate was 72.2%, and its area under the curve (AUC) was 0.823. Using an enhancement ratio > 100% as a diagnostic criterion for malignant breast lesions, the sensitivity was 61.5%, specificity was 80%, and AUC was 0.723. Using > 3 ipsilateral vessels as a diagnostic criterion for malignant lesions in the breast resulted in a diagnostic sensitivity of 81.6%, a specificity of 80.8%, and an AUC of 0.805. Conclusion The type of time intensity curve DCE-MRI, the early enhancement rate in the first phase, the number of ipsilateral vessels, and the ADC full volume histogram of the blood supply score and DWI are valuable in the diagnosis of benign and malignant breast lesions.

scholarly journals Accelerated Brain DCE-MRI Using Iterative Reconstruction With Total Generalized Variation Penalty for Quantitative Pharmacokinetic Analysis: A Feasibility Study

2016 ◽  
Vol 16 (4) ◽  
pp. 446-460 ◽  
Author(s):  
Chunhao Wang ◽  
Fang-Fang Yin ◽  
John P. Kirkpatrick ◽  
Zheng Chang
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Region Of Interest ◽  
Pharmacokinetic Analysis ◽  
Pharmacokinetic Parameters ◽  
Resonance Imaging ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Generalized Variation ◽  
Undersampled Data

Purpose: To investigate the feasibility of using undersampled k-space data and an iterative image reconstruction method with total generalized variation penalty in the quantitative pharmacokinetic analysis for clinical brain dynamic contrast-enhanced magnetic resonance imaging. Methods: Eight brain dynamic contrast-enhanced magnetic resonance imaging scans were retrospectively studied. Two k-space sparse sampling strategies were designed to achieve a simulated image acquisition acceleration factor of 4. They are (1) a golden ratio–optimized 32-ray radial sampling profile and (2) a Cartesian-based random sampling profile with spatiotemporal-regularized sampling density constraints. The undersampled data were reconstructed to yield images using the investigated reconstruction technique. In quantitative pharmacokinetic analysis on a voxel-by-voxel basis, the rate constant Ktrans in the extended Tofts model and blood flow FB and blood volume VB from the 2-compartment exchange model were analyzed. Finally, the quantitative pharmacokinetic parameters calculated from the undersampled data were compared with the corresponding calculated values from the fully sampled data. To quantify each parameter’s accuracy calculated using the undersampled data, error in volume mean, total relative error, and cross-correlation were calculated. Results: The pharmacokinetic parameter maps generated from the undersampled data appeared comparable to the ones generated from the original full sampling data. Within the region of interest, most derived error in volume mean values in the region of interest was about 5% or lower, and the average error in volume mean of all parameter maps generated through either sampling strategy was about 3.54%. The average total relative error value of all parameter maps in region of interest was about 0.115, and the average cross-correlation of all parameter maps in region of interest was about 0.962. All investigated pharmacokinetic parameters had no significant differences between the result from original data and the reduced sampling data. Conclusion: With sparsely sampled k-space data in simulation of accelerated acquisition by a factor of 4, the investigated dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic parameters can accurately estimate the total generalized variation-based iterative image reconstruction method for reliable clinical application.

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