Related Experiment Video
Updated: Dec 27, 2025

A Whole Body Dosimetry Protocol for Peptide-Receptor Radionuclide Therapy PRRT: 2D Planar Image and Hybrid 2D+3D SPECT/CT Image Methods
Published on: April 24, 2020
Systematic and random errors of PET-based 90 Y 3D dose quantification
W Siman1, O R Mawlawi2,3, F Mourtada4
1Department of Radiology, The University of Colorado School of Medicine, Denver, CO, USA.
Purpose:
The objective was to characterize both systematic and random errors in Positron Emission Tomography (PET)-based 90 Y three-dimensional (3D) dose quantification.
Methods:
A modified NEMA-IEC phantom was used to emulate 90 Y-microsphere PET imaging conditions: sphere activity concentrations of 1.6 and 4.8 MBq/cc, sphere-to-background ratios of 4 and 13, and sphere diameters of 13, 17, and 37 mm. PET data were acquired using a GE D690 PET/CT scanner for 300 min on days 0-11. The data were downsampled to 60-5 min for multiple realizations to evaluate the count starvation effect. The image reconstruction algorithm was 3D-OSEM with PSF + TOF modeling; the parameters were optimized for dose-volume histogram (DVH), as a 90 Y 3D dose quantification. 90 Y-PET images were converted to dose maps using the local deposition method, then the sphere DVHs were calculated. The ground truth for the DVH was calculated using convolution method. Dose linearity was evaluated in decaying 90 Y activity (reduced count rate and total count) and decreasing acquisition durations (reduced total count only). Finally, the impacts of the low 32-ppm positron yield on PET-based 3D 90 Y-dose quantification were evaluated; the bias and variability of resulting DVHs were characterized.
Results:
We observed nonlinear errors that depended on the 90 Y activity (count rate) and not on the total true prompt counts. These nonlinear errors in mean dose underestimated the measured mean dose by> 20% for a measured dose range of 40-230 Gy; although the shapes of the DVH were not altered. Compensation based on empirical models reduced the nonlinearity errors to be within 5% for measured dose range of 40-230 Gy. In contrast, the errors due to nonuniformity introduced by image noise dominated the systematic errors in the DVH and stretched the DVH on both tails. For the 37-mm sphere, the magnitude of errors in D80 increased from -25% to -36% when acquisition duration was decreased from 300 to 10 min. The effect of image noise on DVH was more extensive in smaller spheres; for the 17-mm sphere, the magnitude of errors in D80 increased from -29% to -45% acquisition duration was decreased from 300 to 10 min. For the 37-mm sphere, the errors in D20 increased from +3.5% to only +10.5% when the acquisition duration was decreased from 300 to 10 min; in the 17-mm sphere, the errors in D20 were 6.5% for both 300- and 10-min sphere images.
Conclusions:
Count-starved 90 Y-PET data introduce both systematic and random errors. The systematic error increases the apparent nonuniformity of the DVH, while the random error increases the uncertainty in the DVH. The systematic errors were larger than the random errors. Lower count rate of 90 Y-PET also introduces systematic bias, which is scanner specific. The errors of bias-compensated mean tumor dose were <10% when 90 Y-PET scan time was >15 min/bed for tumors >37 mm. Dmedian and Dmean were the most stable dose metrics. An acquisition duration of 30 min is recommended to keep the random errors < 10% for a typical tumor with sphere equivalent diameter >17 mm and average tumor dose >40 Gy.
More Related Videos
07:57Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
Published on: March 24, 2022
10:33Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation
Published on: September 4, 2017
Related Concept Videos
Random and Systematic Errors
Systematic Error: Methodological and Sampling Errors
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Uncertainty in Measurement: Accuracy and Precision
Propagation of Uncertainty from Systematic Error