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196: Quantification of the fetal cortical sulci along gestation. A novel algorithm for evaluating the fetal brain development

      Objective

      The pattern of the cortical sulci and its development provides an important information about the fetal brain maturation along the middle to late gestation. In this study, we present a novel simple algorithm which uses sonographic images of the fetal brain to automatically quantify the brain cortex' sulcation.

      Study Design

      This is a prospective cross-sectional study. Ultrasound images of mid-sagittal fetal brains were obtained during a routine second and third trimesters scan. A novel image processing algorithm was used in order to measure the total lengths of the fetal brain sulci, at different gestational weeks. The algorithm is a semi-automatic: the user is required to choose the image he wants to process, and grossly mark the region of interest (ROI) in the ultrasound image. Then, the algorithm automatically extracts the sulci by using image processing tools. The user may interactively modify the results, by removing curves that were detected as sulci but are not. (such misdetection of sulci is caused by the noise in the US images). Furthermore, the user may also interactively connect between detected sulci which were not identified as connected, due to low grey levels of the image. The algorithm uses the imaging system scale, superimposed on each image (e.g. 0.5 centimeter interval between scale lines) to calculate the number of pixels per meter, to provide the total length of the sulci in centimeters instead of pixels.

      Results

      Overall, 74 fetuses were scanned between 27 and 35 weeks of gestation. On the sagittal plane, the sulci were visualized, as a hyper-echogenic lines, below the subarachnoid space, and above the corpus callosum. A linear regression line of the sulci was observed across gestational age (GA), and a first-degree correlation was found between GA and total lengths of the sulci, (r2=0.928; p=0.000534<0.001).

      Conclusion

      In our current study, we have established a novel algorithm for the quantification of the fetal brain sulcation. This simple automated technic might improve the sonographic evaluation of the fetal brain.
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