Watzenboeck Martin L, Heidinger Benedikt H, Rainer Julian, Schmidbauer Victor, Ulm Barbara, Rubesova Erika, Prayer Daniela, Kasprian Gregor, Prayer Florian
Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
Department of Obstetrics and Gynecology, Medical University of Vienna, Spitalgasse 23, Währinger Gürtel 18-20, 1090, Vienna, Austria.
Insights Imaging. 2023 Feb 8;14(1):31. doi: 10.1186/s13244-023-01376-y.
To investigate the reproducibility of radiomics features extracted from two-dimensional regions of interest (2D ROIs) versus whole lung (3D) ROIs in repeated in-vivo fetal magnetic resonance imaging (MRI) acquisitions.
Thirty fetal MRI scans including two axial T2-weighted acquisitions of the lungs were analysed. 2D (lung at the level of the carina) and 3D (whole lung) ROIs were manually segmented using ITK-Snap. Ninety-five radiomics features were extracted from 2 and 3D ROIs in initial and repeat acquisitions using Pyradiomics. Radiomics feature intra-class correlation coefficients (ICC) were calculated between 2 and 3D ROIs in the initial acquisition, and between 2 and 3D ROIs in repeated acquisitions, respectively.
MRI data of 11 (36.7%) female and 19 (63.3%) male fetuses acquired at a median 25 + 0 gestational weeks plus days (GW) (interquartile range [IQR] 23 + 4 - 27 + 0 GW) were assessed. Median radiomics feature ICC between 2 and 3D ROIs in the initial MRI acquisition was 0.733 (IQR 0.313-0.814, range 0.018-0.970). ICCs between radiomics features extracted using 3D ROIs in initial and repeat acquisitions (median 0.908 [IQR 0.824-0.929, range 0.335-0.996]) were significantly higher compared to 2D ROIs (0.771 [0.699-0.835, 0.048-0.965]) (p < 0.001).
Fetal MRI radiomics features extracted from 3D whole lung segmentation masks showed significantly higher reproducibility across repeat acquisitions compared to 2D ROIs. Therefore, fetal MRI whole lung radiomics features are robust diagnostic and potentially prognostic tools in the image-based in-vivo quantitative assessment of lung development.
研究在重复的体内胎儿磁共振成像（MRI）采集中，从二维感兴趣区域（2D ROI）与全肺（3D）ROI提取的放射组学特征的可重复性。
分析了30例胎儿MRI扫描，包括两次肺部轴向T2加权采集。使用ITK-Snap手动分割2D（隆突水平的肺）和3D（全肺）ROI。在初次和重复采集中，使用Pyradiomics从2D和3D ROI中提取95个放射组学特征。分别计算初次采集中2D和3D ROI之间以及重复采集中2D和3D ROI之间的放射组学特征组内相关系数（ICC）。
评估了11例（36.7%）女性和19例（63.3%）男性胎儿的MRI数据，中位孕周为25+0孕周加天数（GW）（四分位间距[IQR]为23+4 - 27+0 GW）。初次MRI采集中2D和3D ROI之间的放射组学特征ICC中位数为0.733（IQR为0.313 - 0.814，范围为0.018 - 0.970）。与2D ROI（0.771[0.699 - 0.835，0.048 - 0.965]）相比，初次和重复采集中使用3D ROI提取的放射组学特征的ICC（中位数为0.908[IQR为0.824 - 0.929，范围为0.335 - 0.996]）显著更高（p<0.001）。
与2D ROI相比，从3D全肺分割掩码中提取的胎儿MRI放射组学特征在重复采集中显示出显著更高的可重复性。因此，胎儿MRI全肺放射组学特征是基于图像的体内肺发育定量评估中强大的诊断和潜在的预后工具。
