Abstract
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. Diffusion-weighted images were acquired with a 3T scanner using a respiratory-triggered echo-planar sequence and 16 b-values (0-800s/mm2 ). 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=200s/mm2 ). With the signal of all scans averaged, bi-exponential model full fitting showed Dslow =1.14×10-3 mm2 /s, Dfast =193.6×10-3 mm2 /s, and perfusion fraction (PF)=16.9%, and segmented fitting showed Dslow =0.98×10-3 mm2 /s, Dfast =42.2×10-3 mm2 /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 mm2 /s; F'slow =76.4 or 76.6%), fast (D'fast =15.1 or 15.4×10-3 mm2 /s; F'fast =11.8 or 11.7%) and very fast (D'Vfast =445.0 or 448.8×10-3 mm2 /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 Dfast ; 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. For healthy liver, tri-exponential modeling is preferred to bi-exponential modeling. For the bi-exponential model, segmented fitting underestimates Dfast , but offers a more accurate estimation of Dslow .
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call