Impact of body weight on arterial partition coefficient estimation in 123I-IMP SPECT: a comparison between ARG and no-arterial sampling methods.

OBJECTIVE

To evaluate the impact of body weight on the estimation of the arterial blood-to-whole-body partition coefficient in 123I-iodoamphetamine (IMP) SPECT using a no-arterial sampling method (validation method) and to compare it with the autoradiographic (ARG) method.

METHODS

A total of 172 123I-IMP SPECT scans from clinical patients were retrospectively analyzed. To investigate systematic differences between the partition coefficients obtained by the ARG method and those estimated by the validation method in the QSPECT/DTARG package, a Bland-Altman plot was used. The distribution of differences was further visualized across body weights. Observing a trend related to body weight, we then performed regression analysis using body weight as a predictor of the difference between the two methods. The improvement in fit achieved by incorporating body weight was evaluated using the residual sum of squares (RSS).

RESULTS

The validation method systematically underestimated the partition coefficient when the actual value by the ARG method is high, and overestimated it when the true value is low. On the Bland-Altman plot, samples with light body weight were more likely to fall into the region of lower partition coefficients, whereas samples with heavy body weight tended to fall into the region of higher partition coefficients. After correction of body weight, the distribution of partition coefficients more closely approximated an ideal pattern across all body weight groups. Regression analysis revealed that the weight-corrected model provided a significantly better fit than the assumption of a constant partition coefficient (F = 51.36, p < 0.001). The RSS was reduced by 25% following weight correction, supporting the utility of this adjustment.

CONCLUSIONS

The assumption of a constant arterial partition coefficient in the validation method may not be valid for individuals with light or heavy body weight. Incorporating body weight into the estimation process significantly improves even without arterial sampling. The validation method adding body weight correction may reduce variability in cerebral blood flow (CBF) estimates derived from these coefficients, which may improve the accuracy of CBF quantification even without arterial sampling.