Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, New Territories, Hong Kong SAR.
Department of Vascular and Interventional Radiology, Image-Guided Therapy Center, François-Mitterrand University Hospital, Dijon Cedex, France.
NMR Biomed. 2019 Nov;32(11):e4155. doi: 10.1002/nbm.4155. Epub 2019 Jul 30.
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 3 T scanner using a respiratory-triggered echo-planar sequence and 16 b-values (0-800 s/mm ). 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 ).
With the signal of all scans averaged, bi-exponential model full fitting showed D = 1.14 × 10 mm /s, D = 193.6 × 10 mm /s, and perfusion fraction (PF) = 16.9%, and segmented fitting showed D = 0.98 × 10 mm /s, D = 42.2 × 10 mm /s, and PF = 23.3%. IVIM parameters derived from the tri-exponential model were similar for full fitting and segmented fitting, with slow (D' = 0.98 × 10 mm /s; F' = 76.4 or 76.6%), fast (D' = 15.1 or 15.4 × 10 mm /s; F' = 11.8 or 11.7%) and very fast (D' = 445.0 or 448.8 × 10 mm /s; F' = 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 ; 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 D , but offers a more accurate estimation of D .
确定双指数或三指数模型以及完全或分段拟合是否更适合健康肝脏的体素内不相干运动（IVIM）成像信号。
使用呼吸触发的回波平面序列和 16 个 b 值（0-800 s/mm ）在 3 T 扫描仪上采集扩散加权图像。18 名健康志愿者在同一会话中两次扫描肝脏，然后在另一次会话中扫描一次。使用双指数和三指数模型以及完全拟合和分段拟合（阈值 b 值= 200 s/mm ）对肝实质感兴趣区域的测量值进行处理。
对所有扫描的信号进行平均，双指数模型完全拟合显示 D = 1.14×10 -3 mm 2 /s，D = 193.6×10 -3 mm 2 /s，灌注分数（PF）= 16.9%，分段拟合显示 D = 0.98×10 -3 mm 2 /s，D = 42.2×10 -3 mm 2 /s，PF = 23.3%。三指数模型的 IVIM 参数的全拟合和分段拟合相似，慢扩散（D' = 0.98×10 -3 mm 2 /s；F' = 76.4 或 76.6%）、快扩散（D' = 15.1 或 15.4×10 -3 mm 2 /s；F' = 11.8 或 11.7%）和非常快扩散（D' = 445.0 或 448.8×10 -3 mm 2 /s；F' = 11.8 或 11.7%）的扩散室。与双指数模型相比，三指数模型提供了更好的整体拟合。对于双指数模型，与分段拟合相比，完全拟合在非常低和低 b 值时提供了更好的拟合，后者倾向于低估 D ；但是，分段方法在高 b 值下具有更低的信号预测误差。与完全拟合相比，三指数分段拟合提供了更好的扫描-重扫可重复性。
对于健康肝脏，三指数模型优于双指数模型。对于双指数模型，分段拟合低估了 D ，但可以更准确地估计 D 。
