Selective internal radiation therapy with 90Y glass microspheres: biases and uncertainties in absorbed dose calculations between clinical dosimetry models

Publication date: Available online 27 July 2016
Source:International Journal of Radiation Oncology*Biology*Physics
Author(s): Justin K. Mikell, Armeen Mahvash, Wendy Siman, Veera Baladandayuthapani, Firas Mourtada, S. Cheenu Kappadath
PurposeQuantify differences that exist between dosimetry models used for ⁹⁰Y selective internal radiation therapy (SIRT).Methods and MaterialsRetrospectively, 37 tumors were delineated on 19 post-therapy quantitative ⁹⁰Y SPECT/CT. Using matched volumes of interest (VOI), absorbed doses (AD) were reported using three dosimetry models: glass microsphere package insert standard model (SM), partition model (PM), and Monte Carlo (MC). Univariate linear regressions were performed to predict mean MC from SM and PM. Analysis was performed for two subsets: cases with a single tumor delineated (best case for PM); and cases with multiple tumors delineated (typical clinical scenario). Variability in PM from the ad hoc placement of a single spherical VOI to estimate the entire normal liver activity concentration for tumor (T) to non-tumoral liver (NL) ratios (TNR) was investigated. We interpreted the slope of the resulting regression as bias and the 95% prediction interval (95%PI) as uncertainty. MCNLsingle represents MC absorbed doses to the NL for the single tumor patient subset; other combinations of calculations follow a similar naming convention.ResultsSM was unable to predict MCTsingle or MCTmultiple (p>0.12, 95%PI>±177 Gy). However, SMsingle was able to predict (p<0.012) MCNLsingle, albeit with large uncertainties; SMsingle and SMmultiple yielded biases of 0.62 and 0.71, and 95%PI of ±40 and ±32 Gy, respectively. PMTsingle and PMTmultiple predicted (p<2E-6) MCTsingle and MCTmultiple with biases of 0.52 and 0.54, and 95%PI of ±38 and ±111 Gy, respectively. TNR variability in PMTsingle increased the 95%PI for predicting MCTsingle (bias=0.46 and 95%PI=±103 Gy). TNR variability in PMTmultiple modified the bias when predicting MCTmultiple (bias=0.32 and 95%PI=±110 Gy).ConclusionsSM is unable to predict mean MC tumor absorbed dose. PM is statistically correlated with mean MC, but the resulting uncertainties in predicted MC are large. Large differences observed between dosimetry models for ⁹⁰Y SIRT warrant caution when interpreting published SIRT absorbed doses. To reduce uncertainty, we suggest the entire NL VOI be used for TNR estimates when using PM.

Teaser

Relative to external beam, currently used standard (SM) and partition (PM) dosimetry models for ⁹⁰Y SIRT are simplistic. We show that large differences exist in calculated mean absorbed doses when voxel-level Monte Carlo (MC) calculations are compared to SM and PM absorbed doses. SM is unable to predict individual mean MC tumor absorbed dose. PM is statistically correlated to mean MC absorbed dose, but with large uncertainties in predicted values.


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