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Study Design

Methods
A stochastic microsphere deposition algorithm sampled histologically-derived cumulative distribution functions (CDFs) governing microsphere cluster diameter, distance between clusters, and cluster population. Six unique models were generated to examine the impact of algorithm complexity on absorbed dose distribution.
Funding
Unclear
The microsphere spatial distribution following Yttrium-90 radioembolization (90Y-RE) is inherently nonuniform, resulting in substantial microscopic dose heterogeneity not captured by conventional macroscopic dosimetry models. The motivation for this study was to build a robust framework to further understand the relationship between microdosimetry and macrodosimetry-based clinical outcomes. In this study, a stochastic microsphere deposition algorithm sampled histologically-derived cumulative distribution functions (CDFs) governing microsphere cluster diameter (Cdia), distance between clusters (Cdist), and cluster population (Cpop). Six unique models were generated to examine the impact of algorithm complexity on the corresponding absorbed dose distribution, ranging from a completely uniform to fully stochastic reference model. A two-sample statistical Kolmogorov-Smirnov test comparedCdia,Cdist, andCpopderived separately from discrete and continuous CDFs. Microdosimetry calculations were performed by convolving a high-resolution dose-voxel kernel with each model. The mean absorbed doseDmeanand various dose-volume metrics (Dx,x=1,5,10,50,90,95,99) were calculated and compared to the reference model to assess the impact of algorithm complexity on dose metric error (Ex). Published median values ofCdia,Cdist, andCpopagreed well with simulated counterparts. There were no statistically significant differences in sampling between discrete and continuous CDFs forCdia(p=0.083),Cdist(p=0.104), andCpop(p=0.094). Convolution with the90Y dose-voxel kernel resulted a -0.3% deviation compared to a single compartment dose estimate. Model comparisons suggest that samplingCdist​ is critical for accurately modeling low-dose regions (E99=16%), while samplingCpopis critical for resolving absorbed dose hot spots (E1=-12%). In contrast, sampling fromCdia​ had minimal impact on model accuracy. The results of this study provide the necessary framework to develop an improved understanding of the relationship between microdosimetry and macrodosimetry-based clinical outcomes following90Y-RE.

Research Insights

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