ArticleQuantitative imaging in medicine and surgery2026
Artificial intelligence-amplified contrast enhancement in brain magnetic resonance imaging for improving image quality and lesion visualization: a prospective pilot study.
Article in Quantitative imaging in medicine and surgery, 2026. 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
Background: Artificial intelligence (AI) algorithms synthesizing virtual standard-dose images from low-dose contrast-enhanced images of brain magnetic resonance imaging (MRI) have been repurposed to boost contrast from standard-dose input. This study aimed to prospectively evaluate the impact of a Food and Drug Administration (FDA)-cleared, deep learning-based software on contrast enhancement, lesion visualization, and diagnostic confidence for standard-dose contrast-enhanced images. Methods: This prospective study enrolled patients undergoing contrast-enhanced brain MRI between August 2025 and September 2025. Precontrast and standard-dose postcontrast three-dimensional T1-weighted (T1w) images were acquired. AI-amplified contrast-enhanced images were generated via an FDA-cleared deep learning software based on precontrast and standard postcontrast images. Two radiologists independently performed quantitative analyses, examining contrast-to-noise ratio (CNR), lesion-to-brain ratio (LBR), and contrast enhancement percentage (CEP). Qualitative assessments of lesion border delineation, internal morphology, and contrast enhancement, and diagnostic confidence were performed with a 4-point Likert scale. Comparisons between AI-amplified and standard-dose images were conducted via the Wilcoxon signed-rank test. Results: Forty-one patients (mean age 51.1±12.6 years) with enhancing brain lesions were included. For both readers, AI-amplified images, as compared with standard contrast-enhanced images, exhibited a significantly higher CNR (82.56±41.15 Conclusions: AI-based contrast amplification significantly increases the quantitative contrast metrics, qualitative lesion visualization, and diagnostic confidence for standard-dose contrast-enhanced brain MRI without increasing the gadolinium dose. These findings support the use of AI-based contrast amplification as a complementary tool in routine clinical neuroimaging.
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