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Abstract #5012

Evaluation of AI Based Reconstruction to Improve image Quality of T2w Images of the Breast

Christopher M Walker1, Megha Madhukar Kapoor 2, Ray Cody Mayo III2, Jia Sun3, R Jason Stafford1, and Huong T Le-Petross2
1Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States, 2Breast Imaging, MD Anderson Cancer Center, Houston, TX, United States, 3Biostatistics, MD Anderson Cancer Center, Houston, TX, United States

Synopsis

Keywords: Breast, Breast

Motivation: Breast MRI has exceptional sensitivity but is limited by image quality and several artifacts. Advancements in AI-based reconstruction hold promise for improved image quality and efficiency.

Goal(s): This study assesses the impact of applying a vendor AI-based reconstruction on breast MRI at 3T.

Approach: This study retroactively reconstructed 45 series using a commercially available AI-based reconstruction. Three board-certified radiologists scored traditional and reconstructed sequences for quality and improvement.

Results: AI reconstruction showed more conspicuous margins as well as an enhanced noise texture. 54 cases showed improvement, 63 showed no change, and 15 exhibited degraded quality. Higher-quality exams were associated with the greatest improvement.

Impact: A retrospective analysis of a recent FDA approved AI based reconstruction method to improve MRI image quality for breast studies.

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