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The BasGan algorithm quantifies [123I]FP-CIT SPECT scans, showing linearity but varying with system setup. Tomographic spatial resolution can normalize BasGan output across devices for multicenter studies.

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Area of Science:

  • Nuclear medicine
  • Medical imaging analysis
  • Quantitative SPECT imaging

Background:

  • Semi-automatic quantification of [123I]FP-CIT SPECT studies is crucial for assessing neurodegenerative diseases.
  • The BasGan algorithm offers a user-friendly approach to this quantification.

Purpose of the Study:

  • To evaluate the linearity of the BasGan algorithm.
  • To assess the algorithm's dependence on key SPECT acquisition parameters.
  • To determine if tomographic spatial resolution can be used for normalization.

Main Methods:

  • Utilized an anthropomorphic Striatal Phantom with varying activity ratios to test linearity.
  • Investigated software response across different acquisition parameters (rotation radius, pixel size, projections, collimator types).
  • Determined tomographic spatial resolution using a Triple Line Source Phantom for each configuration.

Main Results:

  • BasGan output strongly correlates with Specific Binding Ratio under fixed conditions.
  • Quantification accuracy is influenced by system configuration and partial volume effects.
  • Software response shows a high correlation with tomographic spatial resolution.

Conclusions:

  • BasGan is a reliable, free tool for [123I]FP-CIT SPECT quantification.
  • Tomographic spatial resolution is a key factor affecting BasGan output.
  • Measuring tomographic spatial resolution allows for normalization, enabling multicenter studies and use of reference values.