BackgroundZika virus infection during pregnancy is linked to birth defects, most notably, microcephaly, which in its turn, is associated with neurodevelopmental delays.
ObjectiveThe goal of the study is to propose a method for severity classification of congenital microcephaly based on neuroradiological findings of MRI scans, and to investigate the association of severity with neuropsychomotor developmental scores. We also propose a semi-automated method for MRI-based severity classification of microcephaly.
MethodsCross-sectional investigation of 42 infants born with congenital Zika infection. Bayley-III developmental evaluations and MRI scans were carried out at ages 13-39 months (mean: 24.8, SD: 5.8). The severity score was generated based on neuroradiologist evaluations of brain malformations. Next, we established a distribution of Zika virus-microcephaly severity score into mild, moderate, and severe and investigated the association of severity with neuropsychomotor developmental scores. Finally, we propose a simplified semi-automated procedure for estimating the severity score, based only on volumetric measures.
ResultsResults showed a correlation of r = 0.89 (p < 0.001) between the Zika virus-microcephaly severity score and the semi-automated method. The trimester of infection did not correlate with the semi-automated method. Neuropsychomotor development correlated with the severity classification based on radiological readings and with the semi-automated method; the more severe the imaging scores, the lower neuropsychomotor developmental scores.
ConclusionThe severity classification methods may be used to evaluate severity of microcephaly and possible association with developmental consequences. The semi-automated methods thus may be an alternative for prediction of severity of microcephaly using only one MRI sequence.
