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Abstract

Background

Intravoxel incoherent motion (IVIM) tissue parameters depend on the threshold b-value.

Purpose

To explore how threshold b-value impacts PF (f), D_slow (D), and D_fast (D*) values and their performance for liver fibrosis detection.

Material and Methods

Fifteen healthy volunteers and 33 hepatitis B patients were included. With a 1.5-T magnetic resonance (MR) scanner and respiration gating, IVIM data were acquired with ten b-values of 10, 20, 40, 60, 80, 100, 150, 200, 400, and 800 s/mm². Signal measurement was performed on the right liver. Segmented-unconstrained analysis was used to compute IVIM parameters and six threshold b-values in the range of 40–200 s/mm² were compared. PF, D_slow, and D_fast values were placed along the x-axis, y-axis, and z-axis, and a plane was defined to separate volunteers from patients.

Results

Higher threshold b-values were associated with higher PF measurement; while lower threshold b-values led to higher D_slow and D_fast measurements. The dependence of PF, D_slow, and D_fast on threshold b-value differed between healthy livers and fibrotic livers; with the healthy livers showing a higher dependence. Threshold b-value = 60 s/mm² showed the largest mean distance between healthy liver datapoints vs. fibrotic liver datapoints, and a classification and regression tree showed that a combination of PF (PF < 9.5%), D_slow (D_slow < 1.239 × 10^–3 mm²/s), and D_fast (D_fast < 20.85 × 10^–3 mm²/s) differentiated healthy individuals and all individual fibrotic livers with an area under the curve of logistic regression (AUC) of 1.

Conclusion

For segmented-unconstrained analysis, the selection of threshold b-value = 60 s/mm² improves IVIM differentiation between healthy livers and fibrotic livers.

Keywords

Magnetic resonance imaging (MRI)intravoxel incoherent motion (IVIM)diffusion perfusion liver fibrosis

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Dependence of intravoxel incoherent motion diffusion MR threshold b -value selection for separating perfusion and diffusion compartments and liver fibrosis diagnostic performance

Abstract

Background

Purpose

Material and Methods

Results

Conclusion

Keywords

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References

Supplementary Material