STIR

STIR reconstructs tomographic imaging data from positron emission tomography (PET) and integrated PET-MR systems to produce quantitatively accurate images for metabolic and anatomical analysis.

Key Features:

• Integration with GE SIGNA PET/MR (TOF ~390 ps): Supports time-of-flight PET data from the GE SIGNA PET/MR scanner with approximately 390 picoseconds timing resolution.
• Advanced reconstruction algorithms (OSEM, KEM): Implements Ordered Subset Expectation Maximisation (OSEM) and Kernelised Expectation Maximisation (KEM), with KEM integrating anatomical information from MR images into PET reconstruction.
• Random coincidence simulation: Simulates random coincidences using singles rates per crystal.
• Detector efficiency and geometric modelling: Calculates detector efficiencies and models geometric effects of the acquisition system.
• Attenuation correction models: Implements attenuation correction to account for tissue absorption variations.
• Validation with real datasets: Validated using both phantom and clinical datasets.

Scientific Applications:

• Metabolic uptake quantification: Enables detailed metabolic uptake analysis through accurate PET reconstruction.
• Oncology: Supports precise tumor localization and characterization in PET studies.
• Neurology: Facilitates study of brain metabolism and function using PET and PET-MR data.
• Cardiology: Assists assessment of myocardial perfusion and viability in cardiac PET studies.

Methodology:

Data acquisition: PET data collected using scanners such as the GE SIGNA PET/MR. Algorithmic processing: data processed with algorithms that model physical, mathematical, and anatomical aspects of the imaging process. Image reconstruction: a system matrix incorporating the modelled effects is used to reconstruct images reflecting metabolic activity.