Abnormalities of the corpus callosum. Can prenatal imaging predict the genetic status? Correlations between imaging phenotype and genotype.

OBJECTIVE: Recent studies have evaluated prenatal exome sequencing (pES) for abnormalities of the corpus callosum (CC). The objective of this study was to compare imaging phenotype and genotype findings. METHOD: This multicenter retrospective study included fetuses with abnormalities of the CC between 2018 and 2020 by ultrasound and/or MRI and for which pES was performed. Abnormalities of the CC were classified as complete (cACC) or partial (pACC) agenesis of the CC, short CC (sCC), callosal dysgenesis (CD), interhemispheric cyst (IHC), or pericallosal lipoma (PL), isolated or not. Only pathogenic (class 5) or likely pathogenic (class 4) (P/LP) variants were considered. RESULTS: 113 fetuses were included. pES identified P/LP variants for 3/29 isolated cACC, 3/19 isolated pACC, 0/10 isolated sCC, 5/10 isolated CD, 5/13 non-isolated cACC, 3/6 non-isolated pACC, 8/11 non-isolated CD and 0/12 isolated IHC and PL. Associated cerebellar abnormalities were significantly associated with P/LP variants (OR = 7.312, p = 0.027). No correlation was found between phenotype and genotype, except for fetuses with a tubulinopathy and an MTOR pathogenic variant. CONCLUSIONS: P/LP variants were more frequent in CD and in non-isolated abnormalities of the CC. No such variants were detected for fetuses with isolated sCC, IHC and PL.

Prenatal diagnosis of vermian cyst: a new type of posterior fossa cyst.

BACKGROUND: Prenatal diagnoses of cystic malformations of the posterior fossa mainly encompass arachnoid cysts, Blake's pouch cysts and Dandy-Walker syndrome. To date, vermian cysts have not been reported prenatally. OBJECTIVES: To report a series of fetuses with a vermian cyst. MATERIALS AND METHODS: This was a single-center retrospective study conducted from 2012 to 2021. We included all fetuses presenting with a vermian cyst and excluded all other types of posterior fossa cyst. The cyst was visible at prenatal ultrasound (US) and/or magnetic resonance imaging (MRI). Postnatal imaging and/or clinical outcome data were available. RESULTS: Sixteen fetuses fulfilled the inclusion criteria with a strong female predominance (n=13). US and MRI were performed at a mean gestational age of 29+5 and 33+1 weeks, respectively. In all patients, the cyst was in the vermian horizontal fissure. The mean longest dimension was about 10 mm. The vermis and other posterior fossa structures were otherwise normal. At postnatal imaging, 13 children underwent brain imaging including 11 MRIs with complete regression (n=9), stability (n=1) and increase in size (n=3) of the cyst. Psychomotor development was normal in 14 children. One child (with an inner ear malformation) showed a slight delay in walking and language acquisition. Slight walking ataxia was present in another child. CONCLUSION: We report 16 fetuses with posterior fossa cysts located within the vermis at the level of the horizontal fissure, diagnosed at US and/or MRI and carrying an overall excellent neurological prognosis.

Radiomic analysis of HTR-DCE MR sequences improves diagnostic performance compared to BI-RADS analysis of breast MR lesions.

PURPOSE: To assess the diagnostic performance of radiomic analysis using high temporal resolution (HTR)-dynamic contrast enhancement (DCE) MR sequences compared to BI-RADS analysis to distinguish benign from malignant breast lesions. MATERIALS AND METHODS: We retrospectively analyzed data from consecutive women who underwent breast MRI including HTR-DCE MR sequencing for abnormal enhancing lesions and who had subsequent pathological analysis at our tertiary center. Semi-quantitative enhancement parameters and textural features were extracted. Temporal change across each phase of textural features in HTR-DCE MR sequences was calculated and called "kinetic textural parameters." Statistical analysis by LASSO logistic regression and cross validation was performed to build a model. The diagnostic performance of the radiomic model was compared to the results of BI-RADS MR score analysis. RESULTS: We included 117 women with a mean age of 54 years (28-88). Of the 174 lesions analyzed, 75 were benign and 99 malignant. Seven semi-quantitative enhancement parameters and 57 textural features were extracted. Regression analysis selected 15 significant variables in a radiomic model (called "malignant probability score") which displayed an AUC = 0.876 (sensitivity = 0.98, specificity = 0.52, accuracy = 0.78). The performance of the malignant probability score to distinguish benign from malignant breast lesions (AUC = 0.876, 95%CI 0.825-0.925) was significantly better than that of BI-RADS analysis (AUC = 0.831, 95%CI 0.769-0.892). The radiomic model significantly reduced false positives (42%) with the same number of missed cancers (n = 2). CONCLUSION: A radiomic model including kinetic textural features extracted from an HTR-DCE MR sequence improves diagnostic performance over BI-RADS analysis. KEY POINTS: • Radiomic analysis using HTR-DCE is of better diagnostic performance (AUC = 0.876) than conventional breast MRI reading with BI-RADS (AUC = 0.831) (p < 0.001). • A radiomic malignant probability score under 19.5% gives a negative predictive value of 100% while a malignant probability score over 81% gives a positive predictive value of 100%. • Kinetic textural features extracted from HTR-DCE-MRI have a major role to play in distinguishing benign from malignant breast lesions.