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Record W4308057399 · doi:10.2196/27421

Using Magnetic Resonance Imaging During Childbirth to Demonstrate Fetal Head Moldability and Brain Compression: Prospective Cohort Study

2022· article· en· W4308057399 on OpenAlexvenueno aff
O. Ami, Jean Christophe Maran, D. Musset, Claude Dubray, G. Mage, L. Boyer

Bibliographic record

VenueJMIR Formative Research · 2022
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsFetal headMagnetic resonance imagingMedicineChildbirth3D ultrasoundRadiologyPregnancyBiomedical engineeringFetusUltrasound

Abstract

fetched live from OpenAlex

BACKGROUND: Childbirth is a physiological process with significant medical risk, given that neurological impairment due to the birthing process can occur at any time. Improvements in risk assessment and anticipatory interventions are constantly needed; however, the birthing process is difficult to assess using simple imaging technology because the maternal bony pelvis and fetal skeleton interfere with visualizing the soft tissues. Magnetic resonance imaging (MRI) is a noninvasive technique with no ionizing radiation that can monitor the biomechanics of the birthing process. However, the effective use of this modality requires teamwork and the implementation of the appropriate safeguards to achieve appropriate safety levels. OBJECTIVE: This study describes a clinically effective and safe method to perform real-time MRI during the birthing process. We reported the experience of our team as part of the IMAGINAITRE study protocol (France), which aimed to better understand the biomechanics of childbirth. METHODS: A total of 27 pregnant women were examined with 3D MRI sequences before going into labor using a 1-Tesla open-field MRI. Of these 27 patients, 7 (26%) subsequently had another set of 3D MRI sequences during the second stage of labor. Volumes of 2D images were transformed into finite element 3D reconstructions. Polygonal meshes for each part of the fetal body were used to study fetal head moldability and brain compression. RESULTS: All 7 observed babies showed a sugarloaf skull deformity and brain compression at the middle strait. The fetus showing the greatest degree of molding and brain shape deformation weighed 4525 g and was born spontaneously but also presented with a low Apgar score. In this case, observable brain shape deformation demonstrated that brain compression had occurred, and it was not necessarily well tolerated by the fetus. Depending on fetal head moldability, these observations suggest that cephalopelvic disproportion can result in either obstructed labor or major fetal head molding with brain compression. CONCLUSIONS: This study suggests the presence of skull moldability as a confounding factor explaining why MRI, even with the best precision to measure radiological landmarks, fails to accurately predict the modality of childbirth. This introduces the fetal head compliance criterion as a way to better understand cephalopelvic disproportion mechanisms in obstetrics. MRI might be the best imaging technology by which to explore all combined aspects of cephalopelvic disproportion and achieve a better understanding of the underlying mechanisms of fetal head molding and moldability.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.454
Teacher spread0.392 · 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 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

Citations9
Published2022
Admission routes1
Has abstractyes

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