[Neurological diseases and SPECT--analysis using easy Z-score imaging system (eZIS)]

Area of Science:

• Medical Imaging
• Nuclear Medicine
• Neuroscience

Background:

• Brain perfusion Single-Photon Emission Computed Tomography (SPECT) is crucial for diagnosing neurological and psychiatric disorders.
• Variations in imaging equipment and protocols across different centers limit the use of shared normal databases.
• Automated analysis methods are needed to improve the consistency and accuracy of SPECT interpretation.

Purpose of the Study:

• To develop an automated method for brain perfusion SPECT diagnosis, named easy Z-score imaging system (eZIS).
• To enable the sharing of normal SPECT databases across different institutions by addressing inter-center variations.
• To enhance the diagnostic value of brain SPECT imaging through standardized data analysis.

Main Methods:

• Developed eZIS software for voxel-by-voxel Z-score analysis, normalizing to global mean or cerebellar values.
• Utilized Statistical Parametric Mapping (SPM) for anatomical standardization of SPECT images into stereotactic space.
• Incorporated a novel program within eZIS to create a 3D conversion map for standardizing SPECT data from different scanners, validated using a brain phantom.

Main Results:

• eZIS performs automated Z-score analysis and displays results on standardized MRI templates.
• A 3D conversion map effectively harmonized SPECT data from different scanners, as shown in phantom experiments.
• The developed method allows for the combination of normal databases from multiple centers.

Conclusions:

• The eZIS software provides an automated and standardized approach for brain perfusion SPECT analysis.
• The ability to share normal databases significantly enhances the diagnostic power of SPECT imaging.
• This standardization method is crucial for improving the reliability and consistency of SPECT diagnoses globally.