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- Title
Zika virus congenital microcephaly severity classification and the association of severity with neuropsychomotor development.
- Authors
Esper, Nathalia Bianchini; Franco, Alexandre Rosa; Soder, Ricardo Bernardi; Bomfim, Rodrigo Cerqueira; Nunes, Magda Lahorgue; Radaelli, Graciane; Esper, Katherine Bianchini; Kotoski, Aline; Pripp, Willian; Neto, Felipe Kalil; Azambuja, Luciana Schermann; Mathias, Nathália Alves; da Costa, Danielle Irigoyen; Portuguez, Mirna Wetters; da Costa, Jaderson Costa; Buchweitz, Augusto
- 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.
- Publication
Pediatric Radiology, 2022, Vol 52, Issue 5, p941
- ISSN
0301-0449
- Publication type
Article
- DOI
10.1007/s00247-022-05284-z