ArticleBMC medical imaging2025
Enhancing radiomics robustness using bayesian penalized likelihood PET reconstruction: application to Phantom and non-small cell lung cancer patient studies.
Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeThis study aims to enhance the diagnostic and prognostic capabilities of PET imaging through improved robustness of radiomics features, utilizing the Bayesian penalized likelihood (BPL) reconstruction algorithm. Specifically, we focus on
methodWe studied a NEMA image quality (IQ) phantom and 15 patient PET lesions (14 NSCLC patients selected from 30 patients originally considered). The study assessed the stability of radiomics features against various imaging parameters, emphasizing the impact of the BPL reconstruction algorithm with varying β-values (50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 600, and 700) and three phantom lesion to background ratios (LBRs) of 2:1, 4:1, and 8:1. Manual segmentation was performed, and subsequently, 130 radiomic features were extracted from the reconstructed images. The stability of radiomics features was assessed by calculating the coefficient of variation (COV) for each feature across variations in reconstruction parameters. A COV of ≤ 5% indicated high stability.
resultsOur results indicate that morphological and intensity-based features exhibit excellent stability, with a COV of less than 5%. Texture-based features, despite their complexity, also demonstrated robustness. Specifically, 32.3%, 39.2%, 42.3%, and 37.6% of features exhibited high stability in phantom LBR 2:1, phantom LBR 4:1, phantom LBR 8:1, and patient studies, respectively. Overall, 13 morphological, 8 intensity, 6 intensity-histogram, and 5 texture-based features were found to be highly stable against different LBRs and reconstruction parameters.
conclusionsThe BPL reconstruction algorithm may enhance the robustness of PET radiomics features, supporting their use in clinical settings for non-invasive diagnosis and staging. The adoption of BPL towards improved PET radiomics robustness has the potential to transform NSCLC evaluation and management, but still needs standardization.
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