Radiomics of fetal magnetic resonance imaging in congenital diaphragmatic hernia

Author:

Syrkashev E. M.1ORCID,Burov A. A.2ORCID,Podurovskaya Yu. L.2ORCID,Kadyrberdiyeva F. Z.2ORCID,Ikryannikov E. O.3ORCID,Semenov D. S.3ORCID,Sharova D. E.3ORCID,Vasilev Yu. A.3ORCID,Gus A. I.2ORCID

Affiliation:

1. Research Center for Obstetrics, Gynecology and Perinatology named by V.I. Kulakov of the Ministry of Healthcare of the Russian Federation; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of Moscow Healthcare Department

2. Research Center for Obstetrics, Gynecology and Perinatology named by V.I. Kulakov of the Ministry of Healthcare of the Russian Federation

3. Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of Moscow Healthcare Department

Abstract

Objectives. Analysis of possibilities of radiomics as a source of additional diagnostic information about the structural maturity of the lungsMaterials and methods. A retrospective study included 72 pregnant women: 35 with congenital fetal diaphragmatic hernia (group 1) and 37 without fetal lung pathology (group 2). Frontal or co-frontal T2 images (T2 FSE) were obtained. Segmentation of regions of interest at the fetal lung level was performed manually with ITK-Snap. A total of 107 radiomic features were extracted using pyradiomics. The statistical analysis was performed using the STATISTICA 10 statistical analysis package (USA) to detect correlation between trait values and the target variable (presence of lung pathology in CDH), and to show differences in the comparison groups according to the detected parameters.Results. Statistically significant features were identified for 2D and 3D segmentations (p < 0.05). For 2D and 3D segmentations, the number of significant features was 14 and 73, respectively. After exclusion of features with cross-correlations, their number decreased to 6 and 8 for single slices and 3D images, respectively. Correlation coefficients between the features and the presence of lung pathology were also calculated. In the case of 3D images, the number of features with significant correlation coefficients (r > 0.4, p < 0.05) equaled 20, while for single-slice images this number was 3.Conclusion. The data obtained allow to conclude that it is reasonable to use texture analysis of the 3D MRI images as a source of additional diagnostic information concerning the structural maturity of the lungs.

Publisher

Vidar, Ltd.

Subject

Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

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