Comparison of tri‐exponential decay versus bi‐exponential decay and full fitting versus segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI

Objectives To determine whether bi‐ or tri‐exponential models, and full or segmented fittings, better fit the intravoxel incoherent motion (IVIM) imaging signal of healthy livers. Methods Diffusion‐weighted images were acquired with a 3 T scanner using a respiratory‐triggered echo‐planar sequence and 16 b ‐values (0–800 s/mm 2 ). Eighteen healthy volunteers had their livers scanned twice in the same session, and then once in another session. Liver parenchyma region‐of‐interest‐based measurements were processed with bi‐exponential and tri‐exponential models, with both full fitting and segmented fitting (threshold b ‐value = 200 s/mm 2 ). Results With the signal of all scans averaged, bi‐exponential model full fitting showed D slow = 1.14 × 10 −3 mm 2 /s, D fast = 193.6 × 10 −3 mm 2 /s, and perfusion fraction (PF) = 16.9%, and segmented fitting showed D slow = 0.98 × 10 −3 mm 2 /s, D fast = 42.2 × 10 −3 mm 2 /s, and PF = 23.3%. IVIM parameters derived from the tri‐exponential model were similar for full fitting and segmented fitting, with slow ( D ' slow = 0.98 × 10 −3 mm 2 /s; F ' slow = 76.4 or 76.6%), fast ( D ' fast = 15.1 or 15.4 × 10 −3 mm 2 /s; F ' fast = 11.8 or 11.7%) and very fast ( D ' Vfast = 445.0 or 448.8 × 10 −3 mm 2 /s; F ' Vfast = 11.8 or 11.7%) diffusion compartments. The tri‐exponential model provided an overall better fit than the bi‐exponential model. For the bi‐exponential model, full fitting provided a better fit at very low and low b ‐values compared with segmented fitting, with the latter tending to underestimate D fast ; however, the segmented method demonstrated lower error in signal prediction for high b ‐values. Compared with full fitting, tri‐exponential segmented fitting offered better scan‐rescan reproducibility. Conclusion For healthy liver, tri‐exponential modeling is preferred to bi‐exponential modeling. For the bi‐exponential model, segmented fitting underestimates D fast , but offers a more accurate estimation of D slow .