Apparent diffusion coefficient-dependent voxelwise computed diffusion-weighted imaging: An approach for improving SNR and reducing T2 shine-through effects.

Purpose: To introduce and evaluate a method for signal-to-noise ratio (SNR) improvement and T2 shine-through effect reduction in diffusion-weighted magnetic resonance imaging (DWI).

Materials And Methods: The proposed method uses quantitative information given by the voxel apparent diffusion coefficient (ADC) to derive voxelwise-computed DWI (vcDWI). Behavior of signal intensity variations was simulated and correlated with measurements using a dedicated phantom for DWI allowing for independent adjustment of T2 -relaxivity and diffusivity. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were measured and compared to the method of computed DWI (cDWI). Image signal was correlated with ADCs to appreciate the extent of T2 shine-through effects. Additionally, the proposed method was retrospectively applied to whole-body DWI data of 20 patients with metastatic malignancies. vcDWI was compared to cDWI and measured DWI with respect to image quality, lesion detectability, and lesion diffusivity assessment.

Results: Theoretically predicted signal intensity variations showed a high correlation with measured phantom data (r > 0.96). The proposed method yielded lower background signal intensity variation and higher contrast (+144%) and CNR (+358%) for diffusion-restricted phantom compartments than cDWI. Signal intensities of vcDWI showed an increased inverse correlation with phantom ADC values compared to cDWI (r = -0.86 vs. r = -0.73). Application to patient data showed higher image quality (P < 0.001) and lesion detectability (P = 0.011) using vcDWI compared to cDWI, and higher confidence for the correct identification of diffusion-restricted lesions compared to measured DWI (80/80 vs. 60/81; P = 0.013).

Conclusion: vcDWI is a promising approach for the reduction of T2 shine-through effects and improvement of SNR and CNR in DWI. The clinical significance of these improvements, especially regarding lesion detection, needs to be evaluated in larger prospective clinical studies.