ArticleEJNMMI physics2026
Clinical value of artificial intelligence in reducing PET image acquisition time: routine clinical validation using qualitative, quantitative, and radiomic analysis on a cohort of 282 patients undergoing [
Article in EJNMMI physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Artificial Intelligence Across the Cancer Theranostics Workflow: Critical Appraisal of Current Evidence and Future Clinical Translation.Molecular imaging and biology · 2026Review
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9 authors.
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Abstract
backgroundReducing acquisition time in PET/CT imaging can degrade image quality and may compromise both diagnostic reliability and the robustness of radiomic features. This study investigates, in a large clinical cohort, whether AI-based denoising can preserve image quality and maintain the accuracy of quantitative and radiomic parameters in [
methodsWe reconstructed three sets of images: 100% acquisition time (R100), 75% (R75), and 50% (R50), with their respective denoised versions using SubtlePET® (S75 and S50). On a NEMA phantom, we analysed six contrasts (12:1-2:1) using [
resultsThe phantom study showed no difference in sphere contrast, a reduction in background noise variability, and excellent preservation of radiomic features. In the clinical population, S75 images showed improvements across all criteria evaluated, except for diagnostic confidence, which remained higher with R75 (p = 0.555 when compared to R100) for [
conclusionsSubtlePET® improves the image quality of PET acquisitions performed with reduced acquisition times using [
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