Planning dosimetry for Y radioembolization with glass microspheres: Evaluating the fidelity of Tc-MAA and partition model predictions.

PURPOSE

Tc-MAA-SPECT/CT may be used in Y-glass microsphere radioembolization treatment planning to assess perfused liver volumes and absorbed dose distributions. The partition model (PM) offers a more detailed planning dosimetry option beyond the single-compartment model more traditionally used in Y radioembolization. As Y radioembolization treatments shift toward activities and doses that aim to achieve tumor control, accurate and reliable treatment planning dosimetry for both tumors and normal liver (NL) becomes more critical. In this work, we explore the accuracy and precision of Y dosimetry predictions from pretherapy Tc-MAA and PM.

METHODS

Both PM and voxel dosimetry models were used to calculate tumor and NL mean doses using both planning Tc-MAA and verification Y-SPECT/CT in this retrospective analysis of hepatocellular carcinoma cases treated with glass microspheres (NCT01900002, n = 32). Linear regression models were developed at first access, and then later correct, the estimates by (a) Tc-MAA for Y voxel dosimetry and (b) Tc-MAA PM for voxel dosimetry, separately for both tumors and NL. Bland-Altman analysis was then used to evaluate the accuracy and precision of the regression model predictions with the mean bias and 95% prediction intervals (PI, ±1.96σ). Two categories of cases were stratified (catheter matched vs catheter unmatched) by establishing the level of Tc-MAA and Y catheter position alignment. Only catheter-matched cases were included in the Tc-MAA vs Y voxel dosimetry comparison, while all cases were used to compare dosimetry models (PM vs voxel).

RESULTS

Half (16/32) of cases were deemed catheter matched. Tc-MAA could reliably predict NL doses in catheter-matched cases after application of the linear model, with mean bias (PI) of -1% (±31%). PM was equivalent to voxel dosimetry for NL doses with mean bias (PI) of 0% (±1%). Even among catheter-matched cases, Tc-MAA planning for Y tumor voxel doses was poor, overestimating dose by an average of nearly 40%. Upon application of the linear model, Tc-MAA predictions for Y tumor voxel dose were only minimally biased (-4%) but possessed very large PI (±104%). PM predictions for tumor voxel dose using the linear model also showed small bias (-6%) but maintained similarly high PI of ±90%. Cases with tumors representing a large majority (>80%) of the total tumor volume demonstrated the best scenarios for Tc-MAA and PM tumor dose predictions, with mean biases (PI) of -3% (±53%) and -4% (±21%), respectively.

CONCLUSION

The unconditional use of Tc-MAA to predict Y dosimetry across all cases is not recommended due to: (a) demonstrated the risk of unmatched catheter positions between procedures, and (b) large bias and uncertainty in Tc-MAA predictions in cases with matched catheter locations. However, NL voxel dose predictions with Tc-MAA are clinically viable and either PM or voxel dosimetry can be used to produce equivalent predictions. Both Tc-MAA and PM can provide tumor dose predictions with potential clinical utility, but only in catheter-matched cases and with tumors comprising a clear majority (>80%) of the total tumor volume. These findings stratify the predictive fidelity of Tc-MAA- and PM-based treatment planning for Y dosimetry in improving treatment outcomes.