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Purpose <p>For accurate diagnosis and tracking of neurological diseases using I-123 brain SPECT, precise measurement is critical. This research assesses the quantitative performance of two commercial gamma camera systems by simulating the specific impact of their collimator designs.</p> Method <p>A voxelized Zubal brain phantom was employed in SIMIND Monte Carlo simulations. Projection data were produced for two gamma camera configurations, which were identical in their detector and crystal specifications but differed solely in their Low-Energy High-Resolution (LEHR) collimator design. Image reconstruction was conducted using the Ordered-Subsets Expectation-Maximization (OSEM) algorithm (16 iterations, 8 subsets), integrated with Monte Carlo-derived scatter correction, voxel-specific attenuation correction, and partial-volume compensation utilizing recovery-coefficient (RC) analysis. The quantification error (QE) was assessed by computing the discrepancy between the reconstructed and known true activity concentrations within the cerebellum, temporal lobe, and parietal lobe.</p> Results <p>Following the implementation of the optimized protocol (OSEM 16 × 8 with Monte-Carlo-based scatter correction), both imaging systems demonstrated QE within a clinically acceptable range, albeit with variations across anatomical regions. Camera A exhibited QE values of 1.45%, 3.1%, and 7.5% in the cerebellum, temporal lobe, and parietal lobe, respectively. In contrast, the corresponding QE values for Camera B were 3.5%, 7.5%, and 15%. The most substantial quantification inaccuracies were observed in the parietal lobe, a finding attributable to the pronounced partial-volume effects inherent to its thin cortical structure and the inherent resolution-sensitivity trade-off dictated by the respective collimator geometries.</p> Conclusion <p>Results demonstrate that, despite being classified under the same LEHR category, This can lead to nearly twofold differences in error in certain brain regions and with potential implications for clinical decision-making. The findings further indicate that, for neuro-quantitative SPECT applications collimators with longer hole lengths (≥ 4&#xa0;cm) should be favored over higher-sensitivity designs to reduce partial-volume-effect–related bias in thin cortical structures. Future investigations are required to evaluate whether advanced correction strategies and also reconstruction algorithms can further mitigate such limitations.</p>

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Monte Carlo Based Validation of Quantitative Accuracy in I-123 Brain SPECT Through Comparative Evaluation of Gamma Camera Systems

  • 期刊论文

  • 发表日期：

    2026年2月24日

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  • Sara shirazi,
  • Albert Güveniş

摘要

Purpose

For accurate diagnosis and tracking of neurological diseases using I-123 brain SPECT, precise measurement is critical. This research assesses the quantitative performance of two commercial gamma camera systems by simulating the specific impact of their collimator designs.

Method

A voxelized Zubal brain phantom was employed in SIMIND Monte Carlo simulations. Projection data were produced for two gamma camera configurations, which were identical in their detector and crystal specifications but differed solely in their Low-Energy High-Resolution (LEHR) collimator design. Image reconstruction was conducted using the Ordered-Subsets Expectation-Maximization (OSEM) algorithm (16 iterations, 8 subsets), integrated with Monte Carlo-derived scatter correction, voxel-specific attenuation correction, and partial-volume compensation utilizing recovery-coefficient (RC) analysis. The quantification error (QE) was assessed by computing the discrepancy between the reconstructed and known true activity concentrations within the cerebellum, temporal lobe, and parietal lobe.

Results

Following the implementation of the optimized protocol (OSEM 16 × 8 with Monte-Carlo-based scatter correction), both imaging systems demonstrated QE within a clinically acceptable range, albeit with variations across anatomical regions. Camera A exhibited QE values of 1.45%, 3.1%, and 7.5% in the cerebellum, temporal lobe, and parietal lobe, respectively. In contrast, the corresponding QE values for Camera B were 3.5%, 7.5%, and 15%. The most substantial quantification inaccuracies were observed in the parietal lobe, a finding attributable to the pronounced partial-volume effects inherent to its thin cortical structure and the inherent resolution-sensitivity trade-off dictated by the respective collimator geometries.

Conclusion

Results demonstrate that, despite being classified under the same LEHR category, This can lead to nearly twofold differences in error in certain brain regions and with potential implications for clinical decision-making. The findings further indicate that, for neuro-quantitative SPECT applications collimators with longer hole lengths (≥ 4 cm) should be favored over higher-sensitivity designs to reduce partial-volume-effect–related bias in thin cortical structures. Future investigations are required to evaluate whether advanced correction strategies and also reconstruction algorithms can further mitigate such limitations.