Optimising chest computed tomography (CT) scan ranges in paediatric patients to reduce radiation exposure.

AIM: The aim of this study was to accurately position the scan range of unenhanced chest computed tomography (CT) scans for paediatric patients by clarifying the upper and lower scan boundary ranges to meet clinical needs while minimising radiation risks. MATERIALS AND METHODS: This two-cohort study included 3174 children (aged 3-14 years) undergoing unenhanced chest CT scans. Cohort 1 (n=1894) was used to retrospectively analyse lung boundary variability to determine optimal scan ranges, while cohort 2 (n=1,280) was used to validate the accuracy in delineating lung boundaries and reducing radiation dose compared with traditional protocols. Traditional protocol: upper lung border at the first rib's upper edge; lower border below the diaphragm (technician dependent), covering apex to base. Precise protocol: upper border aligns with the first rib (0 mm offset); lower border 35 mm (3-6 years) or 40 mm (7-14 years) below costophrenic angle. Radiation dose calculation: effective dose (ED) derived from dose-length product (DLP) using age-specific conversion coefficients (k = 0.018 mSv·mGy-1·cm-1). RESULTS: Scan range optimisation reduced z-axis coverage by 4.7% (3-6 years) and 6.1% (7-14 years). The probability of missed lung parenchyma was <5% for both upper and lower boundaries using the optimised protocol. Radiation dose reductions were as follows: 3-6 year: ED decreased by 19.2% (0.09 mSv) and DLP by 17.7% (4.5 mGy-1cm1); 7-14 years: ED decreased by 17.0% (0.21 mSv) and DLP by 17.0% (11.7 mGy-1cm1). CONCLUSION: The proposed protocol achieves precise lung coverage while reducing radiation exposure by 17-19%. This strategy balances diagnostic quality and patient safety, offering a scalable solution for paediatric unenhanced chest CT imaging. Future multicentre validation and artificial intelligence (AI)-driven automation could further enhance clinical adoption.