Optimizing LM-DRAMA parameters and non-local means filtering to improve small-lesion detectability in SiPM-based TOF breast PET.

Publication date: Jul 22, 2025

This study aimed to optimize image reconstruction parameters for a dedicated time-of-flight (TOF) breast positron emission tomography (PET) system equipped with silicon photomultipliers (SiPMs) that maximize lesion detectability while minimizing image noise. A cylindrical phantom containing four hot spheres (3-10 mm diameter) was scanned at sphere-to-background ratios of 4:1, 6:1, and 8:1. All data were reconstructed using a 3D list-mode dynamic row-action maximum likelihood algorithm with β values of 10-200, followed by non-local means (NLM) filtering at intensities of 0. 5-2. 0 or no filtering. Image quality was evaluated using background coefficient of variation (COV), contrast recovery coefficient (CRC), and detectability index (DI) for the 3 mm sphere. As β increased, CRC and DI improved, particularly for smaller spheres and higher SBRs; however, background noise also rose. Applying the NLM filter reduced COV, especially when increasing the filter intensity from 0. 5 to 1. 0, although noise reduction gains plateaued at intensities above 1. 0. Optimal trade-offs in lesion detectability and noise were observed at moderate β (50-100) with NLM intensities of 1. 0-1. 5, yielding higher CRC and DI without excessive background noise or blurring effects. A balanced approach to β and NLM filtering substantially enhances small-lesion visibility in SiPM-based TOF-dedicated breast PET imaging. These findings offer a practical framework for parameter selection, supporting better lesion detectability and advancing breast cancer diagnostics through more sensitive PET protocols.

Semantics

Original Article