Predicting hepatic enhancement in contrast-enhanced CT abdomen: A systematic review and meta-analysis of patient-specific factors.

INTRODUCTION

Achieving optimal hepatic enhancement in contrast-enhanced computed tomography (CECT) is crucial for accurate diagnosis but is influenced by patient-specific factors. Fixed-dose contrast protocols often result in variability, particularly in individuals with extreme body sizes (e.g., obese patients with BMI >30 kg/m2 or very low body weight). Body size parameters: total body weight (TBW), lean body weight (LBW), body surface area (BSA), and body mass index (BMI) have been proposed to optimize dosing, yet no consensus exists.

METHODS

A systematic review and meta-analysis were conducted following PRISMA guidelines. PubMed, Web of Science, Scopus, and Embase were searched (2000-2025) for studies evaluating the correlation between body parameters and hepatic enhancement during the portal venous phase in adults undergoing abdominal CECT. Correlation coefficients were extracted and pooled using a random-effects model, with heterogeneity assessed via I2 statistics.

RESULTS

Seven studies were included in the meta-analysis. Pooled correlations revealed significant negative associations for TBW (r = -0.604, p < 0.001), BSA (r = -0.647, p < 0.001), and BMI (r = -0.466, p < 0.001). LBW showed a non-significant association (r = -0.379, p = 0.269). Heterogeneity was high for all parameters (I2 = 72.7-99 %). BSA and TBW consistently demonstrated the strongest correlations, while LBW results varied due to methodological differences.

CONCLUSION

Both TBW and BSA are strong predictors of hepatic enhancement, with BSA offering greater physiological relevance. LBW, while theoretically optimal, requires standardized measurement methods.

IMPLICATIONS FOR PRACTICE: Weight- or BSA-based dosing should be considered over fixed-dose protocols to achieve consistent hepatic enhancement. Incorporating standardized LBW estimation may further improve image quality and patient safety. Future research should focus on methodological consistency and diverse population validation.