Optimization of intra‐voxel incoherent motion measurement in diffusion‐weighted imaging of breast cancer

Abstract

PurposeThe purpose of this study was to optimize intra‐voxel incoherent motion (IVIM) measurement in diffusion‐weighted imaging (DWI) of breast cancer by separating perfusion and diffusion effects through the determination of an optimal threshold b‐value, thus benign and cancerous breast tissues can be accurately differentiated using IVIM‐derived diffusion and perfusion parameters.Materials and MethodsTwenty‐eight patients, with biopsy‐confirmed breast cancers, were studied with a 3T MRI scanner, using T1‐weighted dynamic contrast‐enhanced MRI images, and diffusion‐weighted images with nine b‐values, ranging from 0 to 1000 s/mm². IVIM‐derived parameter maps for tissue diffusion coefficients D, perfusion fraction f, and pseudo‐diffusion coefficients D* were computed using the segmented fitting method with optimized threshold b‐value, and the sum of squared residuals (SSR) were calculated for IVIM‐derived parameters in different breast lesions.ResultsThe IVIM analysis method developed in this work can separate perfusion and diffusion effects with the optimal threshold b‐value of 300 s/mm², and the results of diffusion and perfusion parameters from IVIM analysis can be used to differentiate pathological changes in breast tissues. It was found that the averages and standard deviations of the diffusion and perfusion parameters, D, f, D*, are the following, for malignant, benign and normal breast tissues respectively: D (0.813 ± 0.225 × 10−3 mm2/s, 1.437 ± 0.538 × 10−3 mm2/s, 1.838 ± 0.213 × 10−3 mm2/s), f (10.73 ± 3.44%, 7.86 ± 3.70%, 8.92 ± 3.72%), D* (15.23 ± 12.17×10−3 mm²/s, 12.02 ± 3.19 × 10−3 mm2/s, 12.03 ± 7.21 × 10−3 mm2/s).Conclusion IVIM‐derived diffusion and perfusion parameter maps depend highly on the choice of threshold b‐value. Using the methodology developed in this work, and with the optimized threshold b‐value, the diffusion and perfusion parameters of breast tissues can be accurately assessed, making IVIM MRI a technique of choice for differential diagnosis of breast cancer.

DW-MRI of the breast: a pictorial review

“…Studies discovered a considerable vascular influence in both DCIS and invasive breast lesions (Fig. 11) [18].

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B-Value Optimization in the Estimation of Intravoxel Incoherent Motion Parameters in Patients with Cervical Cancer

“…This multi-step process requires a b-value threshold to be selected, and several studies have demonstrated the importance of choosing an appropriate threshold (22,39). However, it was also found that the threshold is dependent on the organs, with values ranging from 20 s/mm 2 in the healthy liver (19) to 300 s/mm 2 in breast cancer (23). In the present study, we found that the optimal threshold for SCC was 40 s/mm 2 and 100 s/mm 2 for adenocarcinoma, which was similar to a previous report (20).…”

“…Due to the multistep estimation process of estimating IVIM parameters, the choice of b-value threshold in the initial estimation of the pure diffusion coefficient (D) and perfusion fraction (f) affects the final fitting (19,20). Furthermore, the optimal b-value distribution (BVD) and choice of the b-value threshold are organ-specific (19)(20)(21)(22)(23).…”

Optimization of b‐value schemes for estimation of the diffusion coefficient and the perfusion fraction with segmented intravoxel incoherent motion model fitting

“…Optimal choices of b‐values and the number of repeated acquisitions of each b‐value have been studied extensively for the monoexponential diffusion model, mainly using error propagation or similar techniques . Some studies have performed similar work with the IVIM model . However, these studies on the IVIM model have focused on minimizing the error of parameters estimated simultaneously from the biexponential model and not the segmented procedure nor for estimation of only D and f .…”

“…[17][18][19] Some studies have performed similar work with the IVIM model. 9,[20][21][22][23][24] However, these studies on the IVIM model have focused on minimizing the error of parameters estimated simultaneously from the biexponential model and not the segmented procedure nor for estimation of only D and f. Optimization of acquisition of data for segmented model fitting is to our knowledge hitherto limited to choice of intermediate b-value in three-b-value protocols. 11,25 The aim of this work was to develop a framework for optimization of b-value schemes for diffusion-weighted imaging data used to estimate IVIM parameters D and f with segmented model fitting.…”