A list-mode multi-energy window low-count SPECT reconstruction method for isotopes with multiple emission peaks

Area of Science:

• Medical Imaging
• Nuclear Medicine
• Radiopharmaceutical Therapy

Background:

• Quantitative SPECT imaging is crucial for α-particle radiopharmaceutical therapies (α-RPTs) but faces challenges like low photon counts and complex spectra.
• Existing methods struggle with accuracy and precision in low-count SPECT scenarios.

Purpose of the Study:

• To develop and evaluate a novel low-count quantitative SPECT reconstruction method for isotopes with multiple emission peaks.
• To enhance absorbed dose quantification for α-RPTs by maximizing information from detected photons.

Main Methods:

• Proposed a list-mode multi-energy window (LM-MEW) ordered-subsets expectation-maximization (OSEM) algorithm for SPECT reconstruction.
• Utilized list-mode data and multiple energy windows, incorporating photon energy information.
• Implemented a multi-GPU accelerated version for computational efficiency.

Main Results:

• The LM-MEW method demonstrated superior performance in estimating activity uptake compared to single-energy window or binned data approaches.
• Improvements in both accuracy and precision were observed across various region sizes.
• Evaluated using 2-D SPECT simulations for [224Ra]RaCl2, an α-RPT for prostate cancer.

Conclusions:

• The LM-MEW method significantly improves quantification performance in low-count SPECT for isotopes with multiple emission peaks.
• Leveraging multiple energy windows and list-mode data is key to enhanced accuracy.
• Further validation of LM-MEW is warranted for α-RPT SPECT applications.