Comparison of fitting methods and b‐value sampling strategies for intravoxel incoherent motion in breast cancer

Abstract

Purpose To compare fitting methods and sampling strategies, including the implementation of an optimized b-value selection for improved estimation of intravoxel incoherent motion (IVIM) parameters in breast cancer. Methods Fourteen patients (age, 48.4 ± 14.27 years) with cancerous lesions underwent 3 Tesla breast MRI examination for a HIPAA-compliant, institutional review board approved diffusion MR study. IVIM biomarkers were calculated using “free” versus “segmented” fitting for conventional or optimized (repetitions of key b-values) b-value selection. Monte Carlo simulations were performed over a range of IVIM parameters to evaluate methods of analysis. Relative bias values, relative error, and coefficients of variation (CV) were obtained for assessment of methods. Statistical paired t-tests were used for comparison of experimental mean values and errors from each fitting and sampling method. Results Comparison of the different analysis/sampling methods in simulations and experiments showed that the “segmented” analysis and the optimized method have higher precision and accuracy, in general, compared with “free” fitting of conventional sampling when considering all parameters. Regarding relative bias, IVIM parameters fp and Dt differed significantly between “segmented” and “free” fitting methods. Conclusion: IVIM analysis may improve using optimized selection and “segmented” analysis, potentially enabling better differentiation of breast cancer subtypes and monitoring of treatment.

A Simplified Model for Intravoxel Incoherent Motion Perfusion Imaging of the Brain

“…The simplified linear fitting procedure has been applied in other organ systems. 4,5,12,13,15 However, only 2 very limited studies have applied this method to brain imaging. 25,27 In the first, f linear was compared with f biexponential for normal brain tissue but not for clinical pathology.…”

“…19 In principle, this method allows estimation of IVIM parameters using as few as 2 nonzero bvalues. Linear fitting has been applied for imaging of the liver, 13 kidneys, 15 pancreas, 5 prostate, 12 and breast, 4 and in the evaluation of head and neck malignancies. 14,17 To our knowledge, there has been no systematic comparison of simplified linear fitting with standard biexponential fitting for the evaluation of brain pathology.…”

“…While early investigations were hampered by various technical limitations, 3 advances in field strength, gradient hardware, and echo-planar and parallel imaging technology have led to a resurgent interest in IVIM for a wide range of clinical applications. [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] Brain imaging with IVIM is particularly challenging due to the low blood volume fractions of cerebral tissues [19][20][21] and CSF partial volume contamination. 22 Nonetheless, IVIM has now been validated for quantitative evaluation of brain perfusion using clinically available hardware and pulse sequences.…”

Spatially constrained incoherent motion method improves diffusion‐weighted MRI signal decay analysis in the liver and spleen

“…To achieve more robust parameter estimates with the independent voxel-wise fitting of the IVIM model, we used a two-phase approach as follows. We used the segmented least-squares method 22,23 to obtain initial estimates of the IVIM model parameters by applying the following 3 steps: 1. the value of the D parameter was estimated using the monoexponential function fitted to SI of b-values 200-800 s/mm 2 , 2. then, the value of the parameter f was estimated by extrapolating SI to b = 0 s/mm 2 and calculating the relative difference between the extrapolated and measured signal at b-value = 0 s/mm 2 , 3. the value of the D * parameter was calculated by fitting the biexponential model to the observed data with D and f values fixed. Next, we used the initial estimates to initialize the BOBYQA nonlinear solver 24 that fit the biexponential model to the data for D, D * , and f simultaneously.…”

Comparison of methods for estimation of the intravoxel incoherent motion (IVIM) diffusion coefficient (D) and perfusion fraction (f)

“…Multiple studies concerning approaches for fitting the IVIM model have been conducted, e.g., [16,17,20]. However, evaluation of approaches for estimating D and f only is, to our knowledge, limited to a subanalysis in a single study [16].…”