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Record W4405122482 · doi:10.1080/10255842.2024.2431653

The effect of uterine fibroid region and depth on endometrial stress and strain: a finite element approach

2024· article· en· W4405122482 on OpenAlexaff
Blake S. Miller, Sukhbir S. Singh, Teresa E. Flaxman

Bibliographic record

VenueComputer Methods in Biomechanics & Biomedical Engineering · 2024
Typearticle
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsEndometriumUterusUterine fibroidsInfertilityMedicineGynecologyObstetricsInternal medicineBiologyPregnancy

Abstract

fetched live from OpenAlex

Uterine fibroids are common benign gynecological tumors that are observed in up to 80% of premenopausal women. It is understood that as the fibroid size increases, the surrounding tissues will be subject to greater loads. However, the effect of fibroid region on the uterine structure is not as clear. To better understand the mechanical loading of the endometrium due to the presence of a uterine fibroid, we developed a finite element model of the uterus to examine the effect of both fibroid depth and region in relation to the endometrium. The finite element model of the uterus, endometrium, and a uterine fibroid were created from a 3D segmentation of a patient's magnetic resonance images. This model was then loaded into ANSYS Mechanical 2023 R1, and then deformation, stress, and strain of the endometrium was measured for 24 fibroid positions (8 regions × 3 depths). The highest endometrial loads (deformation, stress, strain) were observed when the fibroid region was superior to the uterus and the depth was deep. Superior regions generated 10-20% higher loads on the endometrium in comparison to other regions, while deep locations had 5-10% higher endometrium loads when compared to superficial depths across almost all regions. A simple uterus model was used to show the effect of fibroid position on loads acting on the endometrium. This can provide insight into mechanisms of abnormal uterine bleeding and infertility and better inform clinical decision making.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.022
GPT teacher head0.334
Teacher spread0.313 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreMethods

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

Citations0
Published2024
Admission routes1
Has abstractyes

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