Aim: When planning SIRT using 90Y microspheres, the partition model is used to refine the activity calculated by the body surface area (BSA) method to potentially improve the safety and efficacy of treatment. For this partition model dosimetry, accurate determination of mean tumor-to-normal liver ratio (TNR) is critical since it directly impacts absorbed dose estimates. This work aimed at developing and assessing a reliable methodology for the calculation of 99mTc-MAA SPECT/CT-derived TNR ratios based on phantom studies.
Materials and methods: IQ NEMA (6 hot spheres) and Kyoto liver phantoms with different hot/background activity concentration ratios were imaged on a SPECT/CT (GE Infinia Hawkeye 4). For each reconstruction with the IQ phantom, TNR quantification was assessed in terms of relative recovery coefficients (RC) and image noise was evaluated in terms of coefficient of variation (COV) in the filled background. RCs were compared using OSEM with Hann, Butterworth and Gaussian filters, as well as FBP reconstruction algorithms. Regarding OSEM, RCs were assessed by varying different parameters independently, such as the number of iterations (i) and subsets (s) and the cut-off frequency of the filter (fc). The influence of the attenuation and diffusion corrections was also investigated. Furthermore, both 2D-ROIs and 3D-VOIs contouring were compared. For this purpose, dedicated Matlab© routines were developed in-house for automatic 2D-ROI/3D-VOI determination to reduce intra-user and intra-slice variability. Best reconstruction parameters and RCs obtained with the IQ phantom were used to recover corrected TNR in case of the Kyoto phantom for arbitrary hot-lesion size. In addition, we computed TNR volume histograms to better assess uptake heterogeneityResults: The highest RCs were obtained with OSEM (i=2, s=10) coupled with the Butterworth filter (fc=0.8). Indeed, we observed a global 20% RC improvement over other OSEM settings and a 50% increase as compared to the best FBP reconstruction. In any case, both attenuation and diffusion corrections must be applied, thus improving RC while preserving good image noise (COV<10%). Both 2D-ROI and 3D-VOI analysis lead to similar results. Nevertheless, we recommend using 3D-VOI since tumor uptake regions are intrinsically 3D. RC-corrected TNR values lie within 17% around the true value, substantially improving the evaluation of small volume (<15 mL) regions.
Conclusions: This study reports the multi-parameter optimization of 99mTc MAA SPECT/CT images reconstruction in planning 90Y dosimetry for SIRT. In phantoms, accurate quantification of TNR was obtained using OSEM coupled with Butterworth and RC correction.