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Record W7116089056 · doi:10.82417/nbef-m409

Development of a bladder flow simulator for visualizing ureteral jet dynamics

2025· other· en· W7116089056 on OpenAlexaff

Bibliographic record

VenueEspace ÉTS (ETS) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsJet (fluid)Particle image velocimetryFlow (mathematics)EllipsoidUltrasoundInstrumentation (computer programming)

Abstract

fetched live from OpenAlex

Ultrasound imaging of ureteral jets provides valuable insights into urogenital health, but its diagnostic capabilities remain limited. The unilateral absence of a ureteral jet often indicates ureteral obstruction, however recent studies also suggest correlations between jet characteristics and conditions such as non-obstructive renal stones, urinary tract infections and other pathologies. Nevertheless, significant variability among patients limits diagnostic reliability. To address these challenges, we developed a physiologically-accurate in vitro simulator of the bladder flow environment, offering a controlled platform for studying ureteral jet dynamics under various pathological conditions.The design of the simulator draws inspiration from existing cardiovascular flow simulators and is divided into three critical components. The first is the development of a bladder model that closely approximates human anatomy. The second is the activation system, which provides precise control over ureteral jet characteristics using high-precision linear motors. The third is the instrumentation system, enabling data collection through ultrasound imaging, particle image velocimetry (PIV) and pressure sensors for real-time analysis.The bladder is modelled as an ellipsoid with average human bladder dimensions and anatomically-accurate placements of the ureterovesical junctions and the urethra. A transparent silicone rubber mold, with elastic modulus similar to that of a human bladder, is created from a soluble 3D-printed polyvinyl alcohol (PVA) model. Two high-precision linear motors reproduce the ureteral jets with independently controlled pulses. These motors provide a positional accuracy of 50 ?m and, when paired with selected syringes, achieve a ureteral jet volume accuracy of ~5 ?L and physiological jet velocities of 50-100 cm/s. Precise motor control allows modulation of jet characteristics, duration, frequency and waveform (monophasic and polyphasic). A hemostasis valve integrated into the urethra provides access for a pressure probe to monitor bladder pressure. The entire system is housed in a transparent plexiglass enclosure, enabling real-time visualization of fluid dynamics through ultrasound modalities and PIV.The in vitro bladder flow simulator is the first to replicate the bladder flow environment with high physiological detail including realistic ureteral jet patterns. Moreover, comprehensive visualization and systematic analysis of bladder flow dynamics is made possible beyond basic ultrasound observations of the ureteral jets. This simulator offers an interesting platform to gain new insights into how various urogenital conditions disrupt normal bladder flow patterns. Its ability to model a wide array of characteristics is expected to enhance our understanding of the coupling between bladder flow and urogenital conditions, and may lead to new diagnostic strategies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.300
Teacher spread0.285 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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