Combination of compressed sensing-based iterative reconstruction and offset acquisition for I-123 FP-CIT SPECT: a...

Area of Science:

• Medical Imaging
• Nuclear Medicine
• Image Reconstruction

Background:

• Single-photon emission computed tomography (SPECT) imaging often requires long acquisition times.
• Undersampling projection data in SPECT can significantly reduce scan duration but may compromise image quality and quantification.
• Compressed sensing (CS) techniques offer potential for reconstructing images from undersampled data.

Purpose of the Study:

• To validate a novel SPECT imaging approach combining compressed sensing iterative reconstruction (CS-IR) with offset acquisition.
• To evaluate the efficacy of this combined method for improving image quality and quantification in undersampled SPECT data.

Main Methods:

• Numerical phantoms were used to assess image quality and quantification.
• SPECT images were reconstructed using filtered back-projection (FBP), maximum likelihood-expectation maximization (ML-EM), CS-IR, and CS-IR with offset acquisition.
• Key metrics evaluated included spatial resolution, aspect ratio, activity concentration linearity, contrast, percent coefficient of variation (%CV), and specific binding ratio (SBR).

Main Results:

• CS-IR with offset acquisition maintained spatial resolution even with decreased projections.
• This method demonstrated substantially lower %CV compared to ML-EM and CS-IR, comparable to FBP with full sampling.
• Specific binding ratios (SBRs) with CS-IR and offset acquisition were stable across varying projection numbers.

Conclusions:

• CS-IR with offset acquisition provides superior image quality and quantification for undersampled SPECT data compared to standard methods.
• This technique can significantly shorten SPECT acquisition times, benefiting patients and enabling dynamic SPECT studies.
• The validated method holds promise for more efficient and quantitative SPECT imaging.