Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer at 3.0 tesla: Comparison of different curve-fitting methods.

Published on Aug 1, 2015in Journal of Magnetic Resonance Imaging4.813
· DOI :10.1002/JMRI.24799
Shiteng Suo14
Estimated H-index: 14
(SJTU: Shanghai Jiao Tong University),
Naier Lin1
Estimated H-index: 1
(SJTU: Shanghai Jiao Tong University)
+ 5 AuthorsJianrong Xu37
Estimated H-index: 37
(SJTU: Shanghai Jiao Tong University)
Background: To compare three different curve-fitting methods for intravoxel incoherent motion (IVIM) analysis in breast cancer. Methods: Diffusion-weighted imaging was acquired in 30 patients with breast cancer using seven b-values (0–800 s/ mm 2 ). Three curve-fitting methods were used for biexponential IVIM analysis: a. Direct estimation of D (diffusion coefficient), D* (pseudodiffusion coefficient) and f (perfusion fraction) (Method 1), b. Estimation of D first and then D* and f (Method 2), c. Estimation of D and f first and then D* (Method 3). Goodness-of-fit, parameter precision (coefficient of variance [CV]), parameter difference and correlation with relative enhancement ratio (RER) and initial area under the curve (IAUC) from dynamic contrast-enhanced (DCE) MRI of the three methods were determined and compared. Results: Among the three biexponential methods, Method 1 best described most of the pixels (63.20% based on R 2 ;4 4.52% based on Akaike Information Criteria). The CV of D calculated from Method 2/3 (14.95%/13.90%), the CV of D* from Method 2 (77.04%) and the CV of f from Method 3 (80.87%) were the lowest among the three methods. Significant difference was observed for each IVIM-derived parameter calculated from all the three methods (P 50.000–0.005). Only the perfusion-related f value calculated from Method 2 was correlated with RER (r 50.548; P 50.002) or IAUC (r 50.561; P 50.001). Conclusion: IVIM-derived parameters differ depending on the calculation methods. The two-step fitting method with D value estimation first was correlated with DCE MRI perfusion. J. MAGN. RESON. IMAGING 2014;00:000–000.
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