基于解剖MRI的大脑皮质表面影像组学重建方法研究

Research on radiomics reconstruction from cerebral cortex surface based on anatomical magnetic resonance imaging

目的 设计一种脑皮质表面影像组学计算方法,为脑影像研究提供丰富的、可靠的脑区局部特征。材料与方法 基于21组重复测量健康被试与222例多动症相关被试的大脑T1WI磁共振数据集提取皮层厚度、灰质体积、平均曲率与皮层表面积四种表面形态指数。使用Desikan-Killiany(DK)脑图谱和球面局部投影,实现三维皮层表面脑区的二维平面化。利用Pyradiomics对四个形态指数分别提取968个二维影像组学特征。结合重复测量数据集与组内相关系数(intra-class correlation coefficient, ICC),以ICC信度值作为影像组学特征评估的标准,综合评价不同形态指数、不同影像组学特征类型与不同脑区间的复测信度差异。结合多动症数据集,预测患者的注意力缺陷指数、过动指数两种症状指标。结果 对于不同形态指标,灰质体积、皮层表面积的影像组学特征可重复性较好,与皮层厚度与平均曲率组差异具有统计学意义(P<0.05)。对于不同类型影像组学特征,基于皮层厚度的一阶特征和灰度共生矩阵特征与其他类型特征差异具有统计学意义(P<0.05)。对于不同脑区,左右脑内嗅皮层、左右脑颞极与右脑额极提取的特征相较其他区域复测性降低(P<0.05)。总体而言本研究提出的表面重建方法所提取的脑影像组学特征均具有较高的可重测性(ICC均值>0.76)。在对多动症两种症状指标的预测中发现,左脑海马旁回、额上回与颞上回与多动症症状显著相关(|r|=0.33~0.52,P<0.05)。结论 基于DK脑图谱与表面形态学指数构建脑影像组学特征是可行的,所提取的新型特征具有良好的可重复性,并在注意力预测等研究中具有一定的临床价值。

Objective:To design a computational method of cortical surface radiomics,to provide rich and reliable local features of brain regions for brain imaging research.Materials and Methods:Based on the T1WI magnetic resonance data sets of 21 groups of repeated measurements of healthy subjects and 222 attention deficit hyperactivity disorder(ADHD)-related subjects,four surface morphological indices including cortical thickness,gray matter volume,mean curvature and cortical surface area were extracted.Using the Desikan-Killiany(DK)brain atlas and spherical local projection,the brain area is flattened from the three-dimensional cortical surface to two-dimensional.Pyradiomics was used to extract 968 two-dimensional radiomics features for each of the four morphological indices.Combining repeated measurement data set and intra-class correlation coefficients(ICC),the ICC value was used as the standard for evaluating radiomics features to comprehensively evaluate the differences in test-retest reliability among different morphological indices,different radiomics feature types and different brain regions.And based on the ADHD dataset,we predict the patient's attention deficit index and hyperactivity index.Results:For different morphological indicators,the radiomics features of gray matter volume and cortical surface area have better reproducibility,and are significantly different from the cortical thickness and average curvature groups(P<0.05).For different types of radiomics features,the first-order features and gray-level co-occurrence matrix features based on cortical thickness showed significant differences from other types of features(P<0.05).For different brain regions,the features extracted from the left and right entorhinal cortex,the left and right temporal poles,and the right frontal pole have lower retest retestability than other regions(P<0.05).However,in general,the brain radiomics features extracted by the surface reconstruction method proposed in this study have high reproducibility(mean ICC>0.76).In the prediction tasks of the two symptom indicators of attention deficit hyperactivity disorder(ADHD),it was found that the left hippocampal gyrus,superior frontal gyrus and superior temporal gyrus were significantly correlated with ADHD symptoms(|r|=0.33-0.52,P<0.05).Conclusions:It is feasible to construct brain radiomics features based on DK brain atlas and surface morphology index.The extracted new features have good repeatability and have certain clinical value in attention prediction and other studies.