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Record W4413330994 · doi:10.1002/uog.29312

Offline ultrasound– <scp>MRI</scp> fusion imaging for assessment of normal fetal brain development

2025· article· en· W4413330994 on OpenAlexaff
C. Codaccioni, Chloé Arthuis, B. Deloison, J.‐P. Bault, Claude R. Henry, Houman Mahallati, J Staś, L. Bussières, Y. Ville, D. Grévent, Laurent Salomon

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2025
Typearticle
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsUltrasoundUltrasound imagingFetusMedicineNeuroscienceRadiologyPsychologyBiologyPregnancy

Abstract

fetched live from OpenAlex

OBJECTIVES: Offline fusion imaging refers to a posteriori merging of two datasets, from the same or from different imaging modalities. The objectives were to assess the feasibility of a standardized manual method for the offline fusion of three-dimensional (3D) ultrasound (US) and magnetic resonance imaging (MRI) data in demonstrating normal fetal brain development and to evaluate its potential clinical use throughout pregnancy. METHODS: This was a prospective study conducted at the Necker-Enfants Malades Hospital, Paris, France, from January to September 2021. We included normal singleton pregnancies between 16 + 0 and 36 + 0 weeks' gestation. Each patient underwent a 3D-US scan, with and without Micro-Vascularization Imaging Doppler, immediately followed by a T2-weighted MRI examination (1.5 Tesla) of the fetal brain. 3D-US and MRI images were merged using at least three registration landmarks, using modified 4D View Fusion software. The primary outcome was the success of US-MRI fusion imaging in obtaining three usable orthogonal planes. Secondary outcomes were the rate of entire neurosonogram visualization (on 3D-US acquisitions, MRI stacks and US-MRI fusion imaging) and the rate of visualization of each International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) neurosonogram anatomical landmark. RESULTS: In total, 113 pregnant women were included in the analysis. We obtained usable datasets in the three orthogonal planes for 3D-US and MRI in 87.6% (99/113) and 97.3% (110/113) of cases respectively. Usable US-MRI fusion imaging in the three planes was achieved in 85.8% (85/99) of cases. The entire neurosonogram was obtained in 9.4% (8/85), 74.1% (63/85) and 87.1% (74/85) respectively of 3D-US acquisitions, MRI stacks and US-MRI fusion imaging volumes (P < 0.01). CONCLUSION: We present a promising offline 3D-US-MRI fusion imaging tool that permits navigation within two merged volumes acquired on the same day. This technique seems easily achievable and may be of value for educational purposes and longitudinal follow up of fetal brain development in cases with increased risk of brain abnormalities. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.035
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.279
Teacher spread0.267 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractyes

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