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. 2022 May;52(5):941-950.
doi: 10.1007/s00247-022-05284-z. Epub 2022 Mar 1.

Zika virus congenital microcephaly severity classification and the association of severity with neuropsychomotor development

Nathalia Bianchini Esper  1   2 , Alexandre Rosa Franco  3   4   5 , Ricardo Bernardi Soder  1   2 , Rodrigo Cerqueira Bomfim  6 , Magda Lahorgue Nunes  1   2 , Graciane Radaelli  1 , Katherine Bianchini Esper  7 , Aline Kotoski  2 , Willian Pripp  7 , Felipe Kalil Neto  1 , Luciana Schermann Azambuja  1   8 , Nathália Alves Mathias  8 , Danielle Irigoyen da Costa  1   9 , Mirna Wetters Portuguez  1   2 , Jaderson Costa da Costa  10   11 , Augusto Buchweitz  1   9
Affiliations

Zika virus congenital microcephaly severity classification and the association of severity with neuropsychomotor development

Nathalia Bianchini Esper et al. Pediatr Radiol. 2022 May.

Abstract

Background: Zika virus infection during pregnancy is linked to birth defects, most notably microcephaly, which is associated with neurodevelopmental delays.

Objective: The goals of the study were to propose a method for severity classification of congenital microcephaly based on neuroradiologic 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.

Materials and methods: We conducted a cross-sectional investigation of 42 infants born with congenital Zika infection. Bayley Scales of Infant and Toddler Development III (Bayley-III) developmental evaluations and MRI scans were carried out at ages 13-39 months (mean: 24.8 months; standard deviation [SD]: 5.8 months). The severity score was generated based on neuroradiologist evaluations of brain malformations. Next, we established a distribution of Zika virus-microcephaly severity score including 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.

Results: The results 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 the radiologic readings and semi-automated method; the more severe the imaging scores, the lower the neuropsychomotor developmental scores.

Conclusion: These severity classification methods can be used to evaluate severity of microcephaly and possible association with developmental consequences. The semi-automated methods thus provide an alternative for predicting severity of microcephaly based on only one MRI sequence.

Keywords: Brain; Congenital microcephaly; Development; Infants; Magnetic resonance imaging; Zika virus.

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