Work

Optimisation of Q.Clear (BSREM) Reconstruction Parameters for 123I and 177Lu Imaging with a 360° CZT Detector

Year: 2026

Type: article

Abstract: Accurate quantitative SPECT depends strongly on the reconstruction protocol, particularly for penalised-likelihood reconstruction algorithms, such as Q.Clear (BSREM). This study aimed to optimise Q.Clear reconstruction parameters for 123I and 177Lu imaging. SPECT images of a NEMA IEC PET Body phantom filled with 123I and 177Lu were acquired on a ring-shaped CZT camera and on a conventional Anger camera. The images were reconstructed using Q.Clear and OSEM and evaluated using quantitative image-quality metrics. Q.Clear was optimised for each radionuclide. The 123I dataset was reconstructed using different combinations of the regularisation parameters β and γ. The 177Lu dataset was reconstructed using literature-reported parameters, and the best-performing reconstruction was fine-tuned. The best-performing Q.Clear reconstructions were compared with corresponding OSEM reconstructions. Overall, increasing β reduced the recovery coefficients, background variability, and contrast recovery coefficients while increasing the signal-to-noise ratio. γ had no appreciable influence on the metrics within the investigated range. The candidate optimised StarGuide/Q.Clear reconstructions outperformed the standard Symbia/OSEM reconstructions in terms of activity recovery, whereas Symbia/OSEM produced lower image noise for most of the analysed VOIs. This study identified settings associated with improved quantitative metrics within the evaluated parameter space, with potential implications for quantitative imaging requiring clinical validation. Nevertheless, multiple reconstruction parameter combinations remain unexplored.

Source: Bioengineering

DOI: 10.3390/bioengineering13091004

Authors: Rafaela Carvalhais, Joana Teixeira, Vera Antunes, João Santos

Institutions: Universidade do Porto, IPO Porto, Centro de Investigação do Instituto Português de Oncologia do Porto Francisco Gentil, Instituto de Ciências Biomédicas Albel Salazar

Language: English

Topic: Medical Imaging Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,258