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Predicting Net 90Y Administered Activity in 90Y-Radioembolization From Post-Therapy 90Y-SPECT/CT Images

M. Allan Thomas1*, Benjamin P. Lopez1, Adam Neff3, Armeen Mahvash2, S. Cheenu Kappadath1, (1) Department of Imaging Physics, UT MD Anderson Cancer Center, Houston, TX, (2) Department of Interventional Radiology, UT MD Anderson Cancer Center, Houston, TX, (3) MIM Software, Inc., Cleveland, OH


(Wednesday, 7/15/2020) 2:00 PM - 3:00 PM [Eastern Time (GMT-4)]

Room: Track 1

Purpose: Accurate determination of ?°Y net administered activity (AA) in ?°Y-radioembolization therapy is critical for dosimetry and assessment of potential mis-administrations. The accuracy and uncertainty in determination of AA depends on dose calibrator configuration and measurement of activity residuals post-therapy. While glass-microspheres typically have high fraction of AA and well-defined procedures for residual assessments, resin-microspheres are more prone to stasis and have poorly defined procedures for residual calculation. Consequently, determination of AA for ?°Y-radioembolization with resin-microspheres is challenging. Here, we propose a model to compute AA from post-therapy ?°Y-SPECT/CT.

Methods: Ground-truth AA for 67 cases of ?°Y-radioembolization using glass-microspheres was determined at time of post-therapy ?°Y-SPECT/CT imaging with adjustments for measured residuals (median=1.0%, 25%-75% range=0.4-2.9%) and ?°Y decay between administration and imaging (152, 120-188 min). Univariate linear models were developed based on leave-one-out cross validation to predict AA using reconstructed SPECT counts from two different VOIs: 1) full-FOV and 2) liver-only. Liver VOIs were generated by an AI-based auto-segmentation algorithm (MIM Software). The mean bias for accuracy and 95% prediction intervals (PI) were assessed with Bland-Altman analysis for both VOIs.

Results: Both SPECT VOIs produced excellent AA predictions relative to ground truth with mean absolute errors of 7.0% (r²=0.98) and 6.4% (r²=0.99) for full-FOV and liver-only VOIs, respectively. With Gaussian distribution of residual errors, mean errors and PI were 0.30% ± 17.7% for full-FOV and -0.50% ± 15.7% for liver-only VOIs. AA predictions based on full-FOV VOIs with PI<18% enable straightforward assessment of potential mis-administrations. AA predictions based on liver-only VOIs additionally provide liver activity with mean absolute errors <6% for dosimetry calculations.

Conclusion: Prediction models based on reconstructed SPECT counts offer an accurate and direct method for determination of AA values following ?°Y-radioembolization. Characterization of AA following ?°Y-radioembolization with resin-microspheres based on these models is underway.


SPECT, Image Analysis


IM- SPECT : Quantitative imaging

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