Merisaari Harri, Laakso Hanne, Liljenbäck Heidi, Virtanen Helena, Aronen Hannu J, Minn Heikki, Poutanen Matti, Roivainen Anne, Liimatainen Timo, Jambor Ivan
Department of Radiology, University of Turku, Turku, Finland.
Turku Brain and Mind Center, University of Turku, Turku, Finland.
Front Oncol. 2021 May 26;11:583921. doi: 10.3389/fonc.2021.583921. eCollection 2021.
To evaluate fitting quality and repeatability of four mathematical models for diffusion weighted imaging (DWI) during tumor progression in mouse xenograft model of prostate cancer.
Human prostate cancer cells (PC-3) were implanted subcutaneously in right hind limbs of 11 immunodeficient mice. Tumor growth was followed by weekly DWI examinations using a 7T MR scanner. Additional DWI examination was performed after repositioning following the fourth DWI examination to evaluate short term repeatability. DWI was performed using 15 and 12 b-values in the ranges of 0-500 and 0-2000 s/mm, respectively. Corrected Akaike information criteria and F-ratio were used to evaluate fitting quality of each model (mono-exponential, stretched exponential, kurtosis, and bi-exponential).
Significant changes were observed in DWI data during the tumor growth, indicated by ADC, ADC, and ADC. Similar results were obtained using low as well as high b-values. No marked changes in model preference were present between the weeks 1-4. The parameters of the mono-exponential, stretched exponential, and kurtosis models had smaller confidence interval and coefficient of repeatability values than the parameters of the bi-exponential model.
Stretched exponential and kurtosis models showed better fit to DWI data than the mono-exponential model and presented with good repeatability.
评估四种扩散加权成像（DWI）数学模型在前列腺癌小鼠异种移植模型肿瘤进展过程中的拟合质量和可重复性。
将人前列腺癌细胞（PC-3）皮下植入11只免疫缺陷小鼠的右后肢。使用7T MR扫描仪每周进行DWI检查以跟踪肿瘤生长。在第四次DWI检查后重新定位后进行额外的DWI检查以评估短期可重复性。分别使用范围为0-500和0-2000 s/mm²的15个和12个b值进行DWI检查。使用校正的赤池信息准则和F比率来评估每个模型（单指数、拉伸指数、峰度和双指数）的拟合质量。
在肿瘤生长过程中，DWI数据观察到显著变化，表现为表观扩散系数（ADC）、ADC和ADC的变化。使用低b值和高b值均获得了类似结果。在第1至4周之间，模型偏好没有明显变化。单指数、拉伸指数和峰度模型的参数比双指数模型的参数具有更小的置信区间和可重复性系数值。
拉伸指数和峰度模型对DWI数据的拟合优于单指数模型，并且具有良好的可重复性。
