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基于信息论的 3T 下宫颈癌活体组织内洛伦兹、高斯、Voigt 和对称的 α-稳定模型的反转横向弛豫评估。

Information theoretic evaluation of Lorentzian, Gaussian, Voigt, and symmetric alpha-stable models of reversible transverse relaxation in cervical cancer in vivo at 3 T.

机构信息

Department of Biomedical Engineering, Faculty of Engineering, Akdeniz University, A305, 07070, Antalya, Türkiye.

出版信息

MAGMA. 2023 Feb;36(1):119-133. doi: 10.1007/s10334-022-01035-1. Epub 2022 Aug 4.

DOI:10.1007/s10334-022-01035-1
PMID:35925432
Abstract

OBJECTS

To better characterize cervical cancer at 3 T. MRI transverse relaxation patterns hold valuable biophysical information about cellular scale microstructure. Lorentzian modeling is typically used to represent intravoxel frequency distributions, resulting in mono-exponential decay of reversible transverse relaxation. However, deviations from mono-exponential decay are expected theoretically and observed experimentally.

MATERIALS AND METHODS

We compared the information content of four models of signal attenuation with reversible transverse relaxation. Biological phantoms and six women with cervical squamous cell carcinoma were imaged using a gradient-echo sampling of the spin-echo (GESSE) sequence. Lorentzian, Gaussian, Voigt, and Symmetric α-Stable (SAS) models were ranked using Akaike's Information Criterion (AIC), and the model retaining the highest information content was identified at each voxel as the best model.

RESULTS

The Lorentzian model resulted in information loss in large fractions of the phantoms and cervix. Gaussian and SAS models frequently had higher information content than the Lorentzian in much of the areas of interest. The Voigt model rarely surpassed the three other models in terms of information content.

DISCUSSION

Gaussian and SAS models provide better fitting of data in much of the human cervix at 3 T. Minimizing information loss through improved tissue modeling may have important implications for identifying reliable biomarkers of tumor hypoxia and iron deposition.

摘要

目的

更好地描述 3T 下的宫颈癌。MRI 横向弛豫模式提供了有关细胞尺度微观结构的有价值的生物物理信息。洛伦兹ian 模型通常用于表示体素内频率分布,导致可逆横向弛豫的单指数衰减。然而,理论上和实验上都预期会出现偏离单指数衰减的情况。

材料和方法

我们比较了四种与可逆横向弛豫相关的信号衰减模型的信息含量。使用梯度回波采样自旋回波(GESSE)序列对生物仿体和 6 名患有宫颈鳞状细胞癌的女性进行成像。使用赤池信息量准则(AIC)对洛伦兹ian、高斯、Voigt 和对称α稳定(SAS)模型进行排名,并在每个体素中确定保留最高信息量的模型作为最佳模型。

结果

洛伦兹ian 模型导致大部分生物仿体和宫颈的信息丢失。在大部分感兴趣区域中,高斯和 SAS 模型的信息含量通常高于洛伦兹ian 模型。Voigt 模型在信息含量方面很少超过其他三个模型。

讨论

在 3T 下,高斯和 SAS 模型在人体宫颈的大部分区域提供了更好的数据拟合。通过改进组织建模来最小化信息丢失,可能对识别肿瘤缺氧和铁沉积的可靠生物标志物具有重要意义。

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Voxel-wise Optimization of Pseudo Voigt Profile (VOPVP) for Z-spectra fitting in chemical exchange saturation transfer (CEST) MRI.
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