Background The aim of this study was to optimise the acquisition and reconstruction parameters for <InlineEquation ID="IEq3"><EquationSource Format="TEX">\(^{90}Y\)</EquationSource></InlineEquation> imaging on a digital PET scanner (Discovery MI 4-ring) under high (3 GBq), intermediate (1 GBq), and low (200 MBq) activity conditions. First, quantitative linearity was evaluated. Then, NEMA IEC body phantom acquisitions were reconstructed using various scan durations and Q.Clear reconstruction parameters. Next, optimal protocols were identified by minimising the discrepancies between absorbed dose maps derived from images (using the Local Deposition Model (LDM)) and those obtained from Monte Carlo (MC) simulations. The images reconstructed with these optimal protocols were then used to evaluate effective spatial resolution and to compare the accuracy of LDM with that of the Dose Voxel Kernel (DVK) approach. Results Quantitative linearity analysis revealed an underestimation of phantom activity at high activity (up to − 15.7% at 3.6 GBq) and an overestimation at lower levels (up to 52.1% at 208 MBq). At high activity, the most accurate results were produced by 15- and 20-minute acquisitions with intermediate beta values (2000–5000). In contrast, intermediate and low activity levels required longer acquisition times and higher beta values (> 6000). Effective spatial resolution ranged from 7 mm at high activity to 24.9 mm at low activity. In terms of absorbed dose accuracy, the mean absorbed dose was underestimated in all spheres of the phantom. However, the error in the mean absorbed dose could be kept within 10% in the background by applying non-linearity corrections. Using MC as reference, LDM achieved greater accuracy in terms of mean absorbed dose and Dose Volume Histogram (DVH) agreement in the spheres, while DVK performed better in the background. Conclusions This study enabled the optimisation of scan duration and beta parameter values for Q.Clear reconstructions for dosimetric purposes. Although accurate dosimetry remains challenging in <InlineEquation ID="IEq4"><EquationSource Format="TEX">\(^{90}Y\)</EquationSource></InlineEquation> PET imaging due to quantitative nonlinearity and limited spatial resolution, an error of less than 10% on the mean absorbed dose can be achieved in large structures if model-specific nonlinearities are corrected for.

Optimising \(^{90}Y\) PET imaging for dosimetry in SIRT: insights from phantom and simulation studies on the Discovery MI scanner

期刊论文
出版模式：

开放获取
发表日期：

2026年6月25日

查看全文

Farzam Sayah,
Benoît Presles,
Hussein Harb,
Tien-Phong Pham,
Jean-Louis Alberini,
Romain Popoff,
Jean-Marc Vrigneaud

摘要

Background

The aim of this study was to optimise the acquisition and reconstruction parameters for \(^{90}Y\) imaging on a digital PET scanner (Discovery MI 4-ring) under high (3 GBq), intermediate (1 GBq), and low (200 MBq) activity conditions. First, quantitative linearity was evaluated. Then, NEMA IEC body phantom acquisitions were reconstructed using various scan durations and Q.Clear reconstruction parameters. Next, optimal protocols were identified by minimising the discrepancies between absorbed dose maps derived from images (using the Local Deposition Model (LDM)) and those obtained from Monte Carlo (MC) simulations. The images reconstructed with these optimal protocols were then used to evaluate effective spatial resolution and to compare the accuracy of LDM with that of the Dose Voxel Kernel (DVK) approach.

Results

Quantitative linearity analysis revealed an underestimation of phantom activity at high activity (up to − 15.7% at 3.6 GBq) and an overestimation at lower levels (up to 52.1% at 208 MBq). At high activity, the most accurate results were produced by 15- and 20-minute acquisitions with intermediate beta values (2000–5000). In contrast, intermediate and low activity levels required longer acquisition times and higher beta values (> 6000). Effective spatial resolution ranged from 7 mm at high activity to 24.9 mm at low activity. In terms of absorbed dose accuracy, the mean absorbed dose was underestimated in all spheres of the phantom. However, the error in the mean absorbed dose could be kept within 10% in the background by applying non-linearity corrections. Using MC as reference, LDM achieved greater accuracy in terms of mean absorbed dose and Dose Volume Histogram (DVH) agreement in the spheres, while DVK performed better in the background.

Conclusions

This study enabled the optimisation of scan duration and beta parameter values for Q.Clear reconstructions for dosimetric purposes. Although accurate dosimetry remains challenging in \(^{90}Y\) PET imaging due to quantitative nonlinearity and limited spatial resolution, an error of less than 10% on the mean absorbed dose can be achieved in large structures if model-specific nonlinearities are corrected for.