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Record W4388034525 · doi:10.1002/mp.16810

A feasibility study of three‐dimensional ultrasound imaging of the vagina under distension

2023· article· en· W4388034525 on OpenAlexaff
Shufei Zhang, Alexandra M. Blokker, Ali Borazjani, Christopher X. Hong, Michael Chaikof, Maria Giroux, Humara Edell, Ahmed Eltahawi, Golafsoun Ameri, Colleen D. McDermott

Bibliographic record

VenueMedical Physics · 2023
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of TorontoMount Sinai HospitalOntario Medical Association
Fundersnot available
KeywordsVaginaUltrasoundMedicineMedical imagingDistensionRadiologyUltrasound imagingMedical physicsAnatomy

Abstract

fetched live from OpenAlex

BACKGROUND: The distension properties of the vagina are critical to its function including support of surrounding organs, childbirth, and intercourse. It could be altered by many pathophysiological processes like pregnancy, radiotherapy, and reconstruction surgery. However, there are no clinically available diagnostic tools capable of quantifying the distension properties of the vagina. PURPOSE: A proof-of-concept study was designed to assess the feasibility of a novel three-dimensional (3D) ultrasound imaging technique that allows quantitative evaluation of the vagina under distension. METHODS: Patients with symptomatic pelvic organ prolapse (POP) were recruited for the study. An ultrathin, oversized bag was inserted into the vagina and filled with water using a modified urodynamics system. The instilled water volume and intravaginal pressure were continuously recorded. At maximum vaginal capacity, 3D transintroital ultrasound of the distended vagina and surrounding pelvic structures was performed. Exams were performed in duplicate for each patient, two hours apart (round A and round B). Following the development of a 3D surface model of the distended vagina from each scan, several measurements were obtained, including cross-sectional area, anteroposterior (AP) length and lateral width in the plane of minimum hiatal dimensions (PMHD), AP and lateral diameter at the pubic symphysis (PS) level, maximum and minimum diameter, and maximum vertical length. To assess repeatability between measurements in two rounds, the coefficient of variation (CV) and the intraclass correlation coefficient (ICC) were calculated for each measurement. Correlations between physical measurements including the pelvic organ prolapse quantification (POP-Q) system and vaginal diameter measurements, and obtained metrics were also assessed. RESULTS: Sixteen patients with POP (average age 69 years) completed both rounds of imaging. There was sufficient echogenicity on 3D transintroital ultrasound of the distended vaginal wall to establish boundaries for 3D surface models of the vagina. Overall, all metrics had good or excellent reliability (ICC = 0.77-0.93, p < 0.05; CV = 3%-18%) except maximum diameter, which demonstrated only moderate reliability (ICC = 0.67, p = 0.092). Strong correlations were found between physical exam measurements including D point of POP-Q, introitus diameter and lateral diameter at apex, and maximum vaginal capacity, maximum vertical length, lateral diameter at PS, minimum diameter, and distended PMHD measurements. The results demonstrated that this system could generate 3D models of the shape of the distended vagina and provide multiple metrics that could be reliably calculated from automated analyses of the models. CONCLUSIONS: A novel system for evaluation of the distension properties of the vagina was developed and preliminary evaluation was performed. This system may represent a technique for evaluation of the biomechanical and structural properties of the vagina.

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)0.003
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.309
Teacher spread0.275 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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