A Modified Tri-Exponential Model for Multi--value Diffusion-Weighted Imaging: A Method to Detect the Strictly Diffusion-Limited Compartment in Brain.

To present a new modified tri-exponential model for diffusion-weighted imaging (DWI) to detect the strictly diffusion-limited compartment, and to compare it with the conventional bi- and tri-exponential models. Multi--value diffusion-weighted imaging (DWI) with 17 -values up to 8,000 s/mm were performed on six volunteers. The corrected Akaike information criterions (AICc) and squared predicted errors (SPE) were calculated to compare these three models. The mean values were ranging 11.9-18.7% in white matter ROIs and 1.2-2.7% in gray matter ROIs. In all white matter ROIs: the AICcs of the modified tri-exponential model were the lowest ( < 0.05 for five ROIs), indicating the new model has the best fit among these models; the SPEs of the bi-exponential model were the highest ( < 0.05), suggesting the bi-exponential model is unable to predict the signal intensity at ultra-high -value. The mean values were extremely low in white matter (1-7 × 10 mm/s), but not in gray matter (251-445 × 10 mm/s), indicating that the conventional tri-exponential model fails to represent a special compartment. The strictly diffusion-limited compartment may be an important component in white matter. The new model fits better than the other two models, and may provide additional information.