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Record W3041543631 · doi:10.1111/aogs.13958

Role of prenatal magnetic resonance imaging in fetuses with isolated agenesis of corpus callosum in the era of fetal neurosonography: A systematic review and meta‐analysis

2020· review· en· W3041543631 on OpenAlexaff
Filomena Giulia Sileo, Daniele Di Mascio, Giuseppe Rizzo, Massimo Caulo, Lucia Manganaro, Emma Bertucci, Sophie Masmejan, Marco Liberati, Alice D’Amico, Luigi Nappi, Danilo Buca, Tim Van Mieghem, Asma Khalil, F. D’Antonio

Bibliographic record

VenueActa Obstetricia Et Gynecologica Scandinavica · 2020
Typereview
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineAgenesis of the corpus callosumFetusCorpus callosumMagnetic resonance imagingAgenesisUltrasoundPrenatal diagnosisGestational ageMeta-analysisPregnancyObstetricsRadiologyAnatomyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Corpus callosum agenesis (ACC) is frequently diagnosed during fetal life; its prognosis depends also on additional anomalies. The additional value of fetal magnetic resonance imaging (MRI) in fetuses with "isolated" complete (cACC) and partial (pACC) agenesis of the corpus callosum on ultrasound is still debated. MATERIAL AND METHODS: We performed a systematic literature review and meta-analysis including fetuses with a prenatal diagnosis of cACC and pACC without associated structural anomalies on ultrasound, undergoing fetal MRI. The primary outcome was the rate of additional anomalies detected at fetal MRI. Further analyses assessed the effect of type of ultrasound assessment (neurosonography vs standard axial assessment), gestational age at fetal MRI and rate of postnatally detected brain anomalies. Random-effect meta-analyses of proportions were used to analyze the data. RESULTS: Fourteen studies (798 fetuses) were included. In cases with isolated cACC, 10.9% (95% CI 4.1-20.6) and 4.3% (95% CI 1.4-8.8) additional anomalies were detected by fetal MRI and postnatally, respectively. Stratifying according to the type of ultrasound assessment, the rate of associated anomalies detected only on fetal MRI was 5.7% (95% CI 0.5-16.0) with dedicated neurosonography and 18.5% (95% CI 7.8-32.4) with a standard axial assessment. In fetuses with isolated pACC, 13.4% (95% CI 4.0-27.0) and 16.2% (95% CI 5.9-30.3) additional anomalies were detected by fetal MRI or postnatally, respectively. Stratifying according to the type of ultrasound assessment, the rate of associated anomalies detected only on fetal MRI was 11.4% (95% CI 2.7-25.0) when dedicated neurosonography was performed. Cortical and posterior fossa anomalies represented the most common anomalies missed at ultrasound with both cACC and pACC. Due to the very small number of included cases, stratification according to early (<24 weeks of gestation) and late (>24 weeks) fetal MRI could not be done for either cACC or pACC. CONCLUSIONS: The rate of associated anomalies detected exclusively at fetal MRI in isolated ACC undergoing neurosonography is lower than previously reported. Cortical and posterior fossa anomalies are among the most common anomalies detected exclusively at MRI, thus confirming the crucial role of fetal MRI in determining the prognosis of these fetuses. However, some anomalies still go undetected prenatally and this should be stressed during parental counseling.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.031
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.025
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.277
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations51
Published2020
Admission routes1
Has abstractyes

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