Determination of contrast medium dose for hepatic CT enhancement with improved body size dependency using a non-linear analysis based on pharmacokinetic principles

[A New Method for Calculating Iodine Dose in Abdominal Dynamic Contrast-enhanced Computed Tomography: Calculation Based on Patients' Body Size Parameters and Estimated Volume of Distribution of Non-ionic Contrast Medium]

PURPOSE

This study aimed at analyzing the relationship between the estimated volume of distribution on computed tomography (eVd_CT) of non-ionic contrast medium and four different patients' body size parameters (BSPs) (total body weight, body mass index, body surface area, and lean body weight) in abdominal dynamic contrast-enhanced computed tomography (ADCE-CT) . Moreover, this study intended to derive a method for calculating the iodine dose to target contrast enhancement.

METHODS

We measured enhanced CT values of the equilibrium phase of the abdominal aorta in 527 patients who underwent ADCE-CT. The eVd_CT of the ADCE-CT equilibrium phase was calculated from enhanced CT values based on the pharmacokinetic model. The optimal iodine dose (OID) was calculated from the regression analysis of eVd_CT and BSP.

RESULTS

The eVd_CT was 7741.1±1799.5 ml. The eVd_CT showed a strong positive correlation with BSP and could be calculated using a linear regression equation. The correlation coefficients for total body weight, body surface area, and lean body weight were 0.83, 0.84, and 0.81, respectively. The OID per unit BSP required for target iodine concentration of the abdominal aorta on ADCE-CT (TIC) could be calculated as "OID [mgI/BSP]=[(a･BSP+b)×TIC]/BSP".

CONCLUSION

The OID calculation method based on the patients' body size parameters and estimated volume of distribution can normalize contrast enhancement in abdominal dynamic contrast-enhanced CT.

An investigation into the variability of radiographers assessing body composition prior to CT contrast media administration

INTRODUCTION

To evaluate and report the variability of radiographers in determining a patient's body type and using this to determine contrast media (CM) volumes for chest computed tomography (CT).

METHODS

This prospective study recruited 50 patients undergoing chest CT examinations. Three radiographers independently used two methods to determine patient body type and consequently CM volume. In Method 1, subjective evaluation of body type together with patient weight determined CM volume. In Method 2, patient weight along with additional criteria applied by the radiographer determined CM volume. Both the determination of body type and CM volumes were compared in terms of agreement and variability between radiographers, and between methods.

RESULTS

Fleiss' kappa was lower (0.583) for Method 1 when compared to Method 2 (0.926) indicating stronger agreement in the radiographer determination of body type for Method 2. Median (IQR) CM volume was 95.0 mL (85.0-110.0) for Method 1, compared to 92.5 mL (85.0-100.0) for method 2 (P < 0.001).

CONCLUSION

Method 2 provided greater agreement in determination of body type, and reduction of CM volumes compared to Method 1.

IMPLICATIONS FOR PRACTICE

Determining body type as part of a CT CM strategy can be subjective and enhanced methods are required to ensure that the most appropriate CM volumes are reliably used.