Cortical formation abnormalities on foetal MR imaging: a proposed classification system trialled on 356 cases from Italian and UK centres.

ABSTRACT

OBJECTIVE: To formulate a classification system for foetal cortical formation abnormalities (CFAs) based on in utero magnetic resonance (iuMR) appearances and trial it in 356 cases. METHODS: This retrospective study included all cases of foetal CFA diagnosed between 2000 and 2017 from seven centres in Italy and UK. All of the studies were reviewed by a panel of paediatric neuroradiologists experienced in iuMR with the aid of an algorithm designed to categorise the abnormalities. RESULTS: Consensus expert review confirmed 356 foetuses with CFA and the first level of classification distinguished bilateral CFA (229/356-64%) from unilateral CFA (127/356-36%) cases with sub-classification of the bilateral cases into asymmetric (65/356-18%) and symmetric (164/356-46%) involvement. There was a statistically significant excess of foetuses with small head size, e.g. 17% of the cohort had a bi-parietal diameter < 3rd centile. There was a small but statistically significant excess of males in the cohort. Further categorisation was made on fine anatomical structure. CONCLUSIONS: It is often not possible to classify foetal CFA using the principles and nomenclature used in paediatric neuroradiology. We have created a classification system for foetal CFA based on the analysis of 356 cases and believe that this will assist future research designed to correlate ante-natal and post-natal imaging features and understand the clinical sequelae of CFA described in utero. KEY POINTS • We describe a morphological classification system of foetal brain cortical formation abnormalities that can be used in clinical practice. • This classification system can be used in future research studies to evaluate the long-term imaging and clinical outcomes of foetal brain cortical formation abnormalities in 17- to 38-week gestational age range. • The practical value of the work is in providing a framework and language to look for imaging clues that may differentiate between different CFA in further studies.