PURPOSE: Routine ultrasound screening to predict gestational age is important for risk assessment of pregnancy complications among pregnant women. We explored a quantitative method for sonographic analysis of placental texture, with the objective of reproducible measurement. METHODS: We studied 151 pregnant women; the gestational ages of their fetuses ranged from 10 to 38 weeks. Three experienced sonographers delineated the placental contour to define the region of interest (ROI). From these sonograms, 72 texture features were derived from the spatial gray-level dependence matrices and gray-level difference matrices. We used these as input variables in a multiple linear regression analysis. RESULTS: A significant positive correlation (P < 0.01) was found between the multiple linear regression results and the corresponding gestation ages by the three assessors (r (A) = 0.755, r (B) = 0.851, and r (C) = 0.832). We also found good agreement between multiple linear regression results for the three observers. Their κ statistic values were 0.685 between assessors A and B, 0.679 between A and C, and 0.804 between B and C. CONCLUSION: Quantitative sonography using texture analysis of the placenta was useful in practice to determine gestational age.
PURPOSE: Routine ultrasound screening to predict gestational age is important for risk assessment of pregnancy complications among pregnant women. We explored a quantitative method for sonographic analysis of placental texture, with the objective of reproducible measurement. METHODS: We studied 151 pregnant women; the gestational ages of their fetuses ranged from 10 to 38 weeks. Three experienced sonographers delineated the placental contour to define the region of interest (ROI). From these sonograms, 72 texture features were derived from the spatial gray-level dependence matrices and gray-level difference matrices. We used these as input variables in a multiple linear regression analysis. RESULTS: A significant positive correlation (P < 0.01) was found between the multiple linear regression results and the corresponding gestation ages by the three assessors (r (A) = 0.755, r (B) = 0.851, and r (C) = 0.832). We also found good agreement between multiple linear regression results for the three observers. Their κ statistic values were 0.685 between assessors A and B, 0.679 between A and C, and 0.804 between B and C. CONCLUSION: Quantitative sonography using texture analysis of the placenta was useful in practice to determine gestational age.
Authors: Christopher D Nguyen; Ana Correia-Branco; Nimish Adhikari; Ezgi Mercan; Srivalleesha Mallidi; Mary C Wallingford Journal: EMJ Radiol Date: 2020-09
Authors: Quyen N Do; Matthew A Lewis; Ananth J Madhuranthakam; Yin Xi; April A Bailey; Robert E Lenkinski; Diane M Twickler Journal: PLoS One Date: 2019-01-22 Impact factor: 3.240