Abstract / Summary
Background: Transabdominal ultrasonographic measurement of rectal diameter is increasingly used as a non-invasive adjunct for assessing rectal distension and fecal loading in children. However, interpretation is limited by the lack of age-stratified reference data in pediatric populations without bowel dysfunction. This study aimed to characterize the distribution of the laterolateral (LL) rectal diameter across childhood and adolescence and provide preliminary age-stratified empirical reference percentiles. Methods: This single-center cross-sectional study included pediatric participants aged ≤18 years who underwent clinically indicated abdominal ultrasonography for reasons unrelated to bowel or anorectal disorders and fulfilled predefined eligibility criteria. Maximal LL rectal diameter was measured transabdominally using a standardized protocol. Empirical percentiles were calculated for four age groups (6–36, 37–72, 73–144, and 145–216 months), with precision assessed using non-parametric bootstrap resampling with 10,000 repetitions. Results: The cohort comprised 188 participants: 46, 43, 62, and 37 in the four age groups, respectively; 107 (56.9%) were boys. Overall LL rectal diameter was 3.55 ± 1.46 cm (median, 3.20 cm; IQR, 2.50–4.30 cm), ranging from 1.01 to 8.00 cm. The LL diameter differed significantly across age groups (p = 0.002), with mean values increasing from 3.02 cm in the youngest group to 3.96 cm in the oldest group. No significant sex-related difference was observed (p = 0.843). P5–P95 ranges were 1.60–4.90, 1.51–5.89, 2.20–6.59, and 2.27–7.00 cm, respectively. Bootstrap confidence intervals were wider for extreme percentiles, particularly in smaller age strata. Conclusions: LL rectal diameter shows substantial interindividual variability and a modest age-related increase during childhood. These findings provide preliminary age-stratified empirical reference data rather than diagnostic thresholds or definitive normative limits. Larger multicenter studies are needed for external validation and more precise estimation of extreme percentiles.