Utilizing multicompartmental restriction spectrum magnetic resonance imaging for liver fibrosis characterization in a mouse model.

Medical physics Pub Date : 2024-05-16 DOI:10.1002/mp.17126

Yeyu Cai, Jiayi Liu, HaiTao Yang, Liyun Zheng, Dongmei Wu, Enhua Xiao, Yongming Dai

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Abstract

Background: Currently, an advanced imaging method may be necessary for magnetic resonance imaging (MRI) to diagnosis and quantify liver fibrosis (LF).

Purpose: To evaluate the feasibility of the multicompartmental restriction spectrum imaging (RSI) model to characterize LF in a mouse model.

Methods: Thirty mice with carbon tetrachloride (CCl₄)-induced LF and eight control mice were investigated using multi-b-value (ranging from 0 to 2000 s/mm²) diffusion-weighted imaging (DWI) on a 3T scanner. DWI data were processed using RSI model (2-5 compartments) with the Bayesian Information Criterion (BIC) determining the optimal model. Conventional ADC value and signal fraction of each compartment in the optimal RSI model were compared across groups. Receiver operating characteristics (ROC) curve analysis was performed to determine the diagnosis performances of different parameters, while Spearman correlation analysis was employed to investigate the correlation between different tissue compartments and the stage of LF.

Results: According to BIC results, a 4-compartment RSI model (RSI₄) with optimal ADCs of 0.471 × 10^-3, 1.653 × 10^-3, 9.487 × 10^-3, and > 30 × 10^-3, was the optimal model to characterize LF. Significant differences in signal contribution fraction of the C₁ and C₃ compartments were observed between LF and control groups (P = 0.018 and 0.003, respectively). ROC analysis showed that RSI₄-C₃ was the most effective single diffusion parameter for characterizing LF (AUC = 0.876, P = 0.003). Furthermore, the combination of ADC values and RSI₄-C₃ value increased the diagnosis performance significantly (AUC = 0.894, P = 0.002).

Conclusion: The 4-compartment RSI model has the potential to distinguish LF from the control group based on diffusion parameters. RSI₄-C₃ showed the highest diagnostic performance among all the parameters. The combination of ADC and RSI₄-C₃ values further improved the discrimination performance.

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在小鼠模型中利用多室限制频谱磁共振成像分析肝纤维化特征。

背景：目前，磁共振成像（MRI）诊断和量化肝纤维化可能需要一种先进的成像方法：目的：评估多室限制谱成像（RSI）模型表征小鼠肝纤维化的可行性：方法：在3T扫描仪上使用多b值（范围从0到2000 s/mm2）扩散加权成像（DWI）对30只四氯化碳（CCl4）诱导的LF小鼠和8只对照小鼠进行了研究。DWI 数据使用 RSI 模型（2-5 个区室）进行处理，并由贝叶斯信息标准（BIC）确定最佳模型。各组之间比较了最佳 RSI 模型中每个分区的常规 ADC 值和信号分数。通过接收者操作特征（ROC）曲线分析来确定不同参数的诊断性能，同时采用斯皮尔曼相关性分析来研究不同组织分区与 LF 分期之间的相关性：根据 BIC 结果，4 区室 RSI 模型（RSI4）的最佳 ADC 分别为 0.471 × 10-3、1.653 × 10-3、9.487 × 10-3 和 > 30 × 10-3，是表征 LF 的最佳模型。在 LF 组和对照组之间，C1 和 C3 区间的信号贡献率存在显著差异（P = 0.018 和 0.003）。ROC 分析显示，RSI4-C3 是表征 LF 最有效的单一扩散参数（AUC = 0.876，P = 0.003）。此外，结合 ADC 值和 RSI4-C3 值可显著提高诊断性能（AUC = 0.894，P = 0.002）：结论：4 室 RSI 模型具有根据弥散参数区分 LF 和对照组的潜力。在所有参数中，RSI4-C3 的诊断性能最高。ADC 和 RSI4-C3 值的组合进一步提高了鉴别性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Medical physics

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