Texture analysis of placental MRI: can it aid in the prenatal diagnosis of placenta accreta spectrum?
Texture analysis of placental MRI: can it aid in the prenatal diagnosis of placenta accreta spectrum?
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DOI：
10.1007/s00261-019-02104-1
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发表时间：
2019-09-01
影响因子：
2.4
通讯作者：
Cai, Kejia
中科院分区：
文献类型：
--
作者：
Chen, Eric;Mar, Winnie A.;Cai, Kejia
目的探讨纹理分析能否在MRI上鉴别植入胎盘频谱(PAS)和正常胎盘。方法对80例PAS患者的影像资料进行回顾性分析，其中PAS患者46例，非PAS患者34例。以组织病理学为参考标准。分析从单一机构获得的矢状位单次激发快速自旋回波T2加权序列。在MatLab平台上使用内部软件量化胎盘的异质性，包括像素强度的标准差、变异系数、灰度共生矩阵(GLCM)、直方图定向梯度(HOG)和盒大小从2到512的分形分析。采用双尾非配对t检验，P<；0.05有统计学意义。结果PAS与像素强度的标准差和每个盒子大小的分形图分析值较高相关。方框大小为256(p=0.011)和32(p=0.021)以及像素强度标准差(p=0.023)的分形图分析具有最显著的统计学意义。PAS组256时的分形值为0.090，PAS组为0.13，PAS组像素强度标准差为3.7vs2.5。未发现PAS和GLCM、变异系数和HOG之间有统计学意义的关联。结论应用像素强度标准差和分形分析，正常组与异常组之间差异有统计学意义。
Purpose To determine if texture analysis can differentiate placenta accreta spectrum (PAS) from normal placenta on MRI. Methods We performed retrospective image analysis of 80 patients, comprised of 46 patients with PAS and 34 patients without PAS. Histopathology was used as the reference standard. Sagittal single shot fast spin echo T2-weighted MRI sequences acquired from a single institution were analyzed. Placental heterogeneity was quantified using in-house software on a Matlab platform, including the standard deviation of pixel intensity, coefficient of variation, gray-level co-occurrence matrices (GLCM), histogram-oriented gradients (HOG), and fractal analysis with box sizes from 2 to 512. Two-tailed unpaired Student's t test was used with statistical significance of p < 0.05. Results PAS was associated with higher values for standard deviation of pixel intensity and fractal analysis at every box size. Fractal analysis at box sizes 256 (p = 0.011) and 32 (p = 0.021), and standard deviation of pixel intensity (p = 0.023) were the most statistically significant. Fractal values at box size 256 for PAS was 0.13 versus 0.090 for patients without PAS, while standard deviation of pixel intensity was 3.7 for PAS versus 2.5 for patients without PAS. No statistically significant association between PAS and GLCM, coefficient of variation, and HOG was found. Conclusion Statistically significant differences were found between normal and abnormal groups using standard deviation of pixel intensity and fractal analysis.