Bailey Colleen, Collins David J, Tunariu Nina, Orton Matthew R, Morgan Veronica A, Feiweier Thorsten, Hawkes David J, Leach Martin O, Alexander Daniel C, Panagiotaki Eleftheria
Centre for Medical Image Computing, University College London, London, United Kingdom.
Department of Radiation Oncology, Odette Cancer Centre, Toronto, Canada.
Front Oncol. 2018 Feb 16;8:26. doi: 10.3389/fonc.2018.00026. eCollection 2018.
To examine the usefulness of rich diffusion protocols with high -values and varying diffusion time for probing microstructure in bone metastases. Analysis techniques including biophysical and mathematical models were compared with the clinical apparent diffusion coefficient (ADC).
Four patients were scanned using 13 -values up to 3,000 s/mm and diffusion times ranging 18-52 ms. Data were fitted to mono-exponential ADC, intravoxel incoherent motion (IVIM), Kurtosis and Vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) models. Parameters from the models were compared using correlation plots.
ADC and IVIM did not fit the data well, failing to capture the signal at high -values. The Kurtosis model best explained the data in many voxels, but in voxels exhibiting a more time-dependent signal, the VERDICT model explained the data best. The ADC correlated significantly ( < 0.004) with the intracellular diffusion coefficient ( = 0.48), intracellular volume fraction ( = -0.21), and perfusion fraction ( = 0.46) parameters from VERDICT, suggesting that these factors all contribute to ADC contrast. The mean kurtosis correlated with the intracellular volume fraction parameter ( = 0.26) from VERDICT, consistent with the hypothesis that kurtosis relates to cellularity, but also correlated weakly with the intracellular diffusion coefficient ( = 0.18) and cell radius ( = 0.16) parameters, suggesting that it may be difficult to attribute physical meaning to kurtosis.
Both Kurtosis and VERDICT explained the diffusion signal better than ADC and IVIM, primarily due to poor fitting at high -values in the latter two models. The Kurtosis and VERDICT models captured information at high using parameters (Kurtosis or intracellular volume fraction and radius) that do not have a simple relationship with ADC and that may provide additional microstructural information in bone metastases.
研究具有高值和不同扩散时间的丰富扩散协议在探测骨转移瘤微观结构方面的实用性。将包括生物物理和数学模型在内的分析技术与临床表观扩散系数（ADC）进行比较。
对4例患者进行扫描，使用高达3000 s/mm²的13个值以及18 - 52 ms的扩散时间。数据拟合到单指数ADC、体素内不相干运动（IVIM）、峰度和肿瘤细胞计数的血管、细胞外及受限扩散（VERDICT）模型。使用相关图比较模型的参数。
ADC和IVIM对数据拟合不佳，未能在高值时捕捉到信号。峰度模型在许多体素中能最好地解释数据，但在表现出更多时间依赖性信号的体素中，VERDICT模型对数据解释最佳。ADC与VERDICT模型的细胞内扩散系数（r = 0.48）、细胞内体积分数（r = -0.21）和灌注分数（r = 0.46）参数显著相关（P < 0.004），表明这些因素均对ADC对比度有贡献。平均峰度与VERDICT模型的细胞内体积分数参数（r = 0.26）相关，这与峰度与细胞密度相关的假设一致，但也与细胞内扩散系数（r = 0.18）和细胞半径（r = 0.16）参数弱相关，表明可能难以赋予峰度物理意义。
峰度和VERDICT模型比ADC和IVIM能更好地解释扩散信号，主要是因为后两种模型在高值时拟合不佳。峰度和VERDICT模型利用与ADC没有简单关系且可能在骨转移瘤中提供额外微观结构信息的参数（峰度或细胞内体积分数和半径）在高值时捕捉信息。
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