Transrectal ultrasound vector projectile imaging for time‐resolved visualization of flow dynamics in the male urethra: A clinical pilot study
Bibliographic record
Abstract
BACKGROUND: Quantitative and comprehensive visualization of urinary flow dynamics in the urethra is crucial for investigating patient-specific mechanisms of lower urinary tract symptoms (LUTS). Although some methods can evaluate the global properties of the urethra, it is critical to assess the local information, such as the location of the responsible lesion and its interactions with urinary flow in relation to LUTS. This approach is vital for enhancing personalized and focal treatments. However, there is a lack of such diagnostic tools that can directly observe how the urethral shape and motion impact urinary flow in the urethra. PURPOSE: This study aimed to develop a novel transrectal ultrasound imaging modality based on the contrast-enhanced urodynamic vector projectile imaging (CE-UroVPI) framework and validate its clinical applicability for visualizing time-resolved flow dynamics in the urethra. METHODS: A new CE-UroVPI system was developed using a research-purpose ultrasound platform and a custom transrectal linear probe, and an imaging protocol for acquiring urodynamic echo data in male patients was designed. Thirty-four male patients with LUTS participated in this study. CE-UroVPI was performed to acquire ultrasound echo signals from the participant's urethra and urinary flow at various voiding phases (initiation, maintenance, and terminal). The ultrasound datasets were processed with custom software to visualize urinary flow dynamics and urethra tissue deformation. RESULTS: The transrectal CE-UroVPI system successfully visualized the time-resolved multidirectional urinary flow dynamics in the prostatic urethra during the initiation, maintenance, and terminal phases of voiding in 17 patients at a frame rate of 1250 fps. The maximum flow speed measured in this study was 2.5 m/s. In addition, when the urethra had an obstruction or an irregular partial deformation, the devised imaging modality visualized complex flow patterns, such as vortices and flow jets around the lesion. CONCLUSIONS: Our study findings demonstrate that the transrectal CE-UroVPI system developed in this study can effectively image fluid-structural interactions in the urethra. This new diagnostic technology has the potential to facilitate quantitative and precise assessments of urethral voiding functions and aid in the improvement of focal and effective treatments for patients with LUTS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".