Background: Renal ultrasound is the first-line imaging method for postnatal hydronephrosis, but its severity grading remains partly reader dependent. Although previous studies have applied artificial intelligence (AI) to pediatric hydronephrosis assessment, the clinical feasibility of a simplified two-still-image workflow in a homogeneous infant cohort remains insufficiently defined. Methods: This retrospective single-center proof-of-concept diagnostic accuracy study was conducted among 186 infants younger than 12 months with unilateral hydronephrosis who had one protocol-compatible transverse and one sagittal renal ultrasound image. The AI workflow classified hydronephrosis as mild, moderate, or severe using a two-branch convolutional neural network (CNN). Model performance was assessed using stratified patient-level five-fold internal validation. The reference standard was expert consensus based on the complete ultrasound examination. Study categories were aligned descriptively with accepted Society for Fetal Urology (SFU) and Urinary Tract Dilation (UTD) severity concepts but were not intended to replace these systems. Results: A total of 186 infants were included. Expert consensus classified 79 cases as mild, 62 as moderate, and 45 as severe. The AI-assisted workflow showed exact agreement with expert consensus in 159 of 186 infants, corresponding to 85.5%, with a linear weighted kappa of 0.83. For clinically significant hydronephrosis, defined as moderate or severe disease, the AI workflow showed a sensitivity of 92.5%, a specificity of 86.1%, an accuracy of 89.8%, a positive predictive value of 90.0%, and a negative predictive value of 89.5%. The ordinal-score area under the curve (AUC), which is based on class labels rather than calibrated probability outputs, was 0.92 for clinically significant hydronephrosis and 0.96 for severe hydronephrosis. Because patient-level probability outputs were unavailable, formal calibration, decision curve analysis, threshold adjustment, and individualized risk estimation could not be performed. Conclusions: This single-center proof-of-concept internal validation study suggests that a simplified two-plane AI-assisted workflow could closely match expert consensus grading in selected infants with unilateral hydronephrosis. The workflow should be considered a research-only ordinal class assignment tool. This study does not establish clinical readiness, external generalizability, calibrated risk prediction, or diagnostic superiority over routine reporting. Prospective multicenter validation with preserved probability outputs and formal calibration is needed before any clinical implementation.

Background/Objectives: Pediatric uroflowmetry is volume dependent, and low-volume voids can yield recordings that require repetition or cannot be interpreted confidently. To evaluate whether documented bladder volume-guided timing was associated with first-attempt pediatric uroflowmetry process adequacy in children undergoing evaluation for suspected non-neurogenic lower urinary tract dysfunction. Methods: This single-center retrospective workflow cohort included 110 toilet-trained children aged 5–12 years who underwent uroflowmetry for suspected non-neurogenic lower urinary tract dysfunction. The exposure was classified from contemporaneous pre-test documentation as bladder volume-guided timing (n = 55) or standard urge-based timing (n = 55). Expected bladder capacity (EBC) was calculated as (age + 1) × 30 mL. The primary process outcome was first-attempt voided volume ≥ 50% EBC. Repetition after an inadequate first attempt was treated as a deterministic workflow consequence rather than an independent endpoint. Analyses were observational and effect estimates were interpreted as associations. Results: Adequate first-attempt voided volume was documented in 50/55 children (90.9%) with bladder volume-guided timing and 39/55 (70.9%) with standard urge-based timing (unadjusted risk ratio 1.28, 95% confidence interval [CI] 1.06–1.55; Newcombe risk difference 20.0 percentage points, 95% CI 5.3–34.0). After adjustment for age, baseline urgency score, and time since last void, the association remained (adjusted risk ratio 1.27, 95% CI 1.06–1.53; p = 0.011), and the model converged without numerical warnings. Using the age-specific lowest acceptable voided volume, adequacy occurred in 53/55 children (96.4%) versus 46/55 (83.6%) (adjusted risk ratio 1.15, 95% CI 1.01–1.31; p = 0.040). Repetition after an inadequate first attempt occurred in 9.1% versus 29.1% and was treated as a direct consequence of primary-threshold failure; it was not tested independently. Workflow-time measures were exploratory. Conclusions: Documented bladder volume-guided timing was associated with greater first-attempt process adequacy. Adjustment for age, baseline urgency score, and time since last void did not materially change the estimate. The association was attenuated but remained directionally consistent when the age-specific lowest acceptable voided volume was used. Because the timing rule deliberately targeted the same volume construct as the primary outcome, this finding does not establish improved diagnostic accuracy, clinical decision making, or patient outcomes. Retrospective exposure classification and routine documentation further preclude causal interpretation. Documented bladder volume-guided timing was associated with higher first-attempt achievement of a prespecified voided-volume threshold than standard urge-based timing. Because the pathway targeted the same volume construct used to define the primary outcome and was non-randomized, these findings are interpreted as hypothesis-generating workflow data rather than evidence of improved diagnostic accuracy or downstream clinical benefit.