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Abstract #3026

Introducing an Automated Low-Contrast Detectability Test for the ACR MRI Phantom based on a Statistical Approach

Ali Golestani1,2 and Julia Gee2,3
1University of Calgary, Calgary, AB, Canada, 2Alberta Health Services, Calgary, AB, Canada, 3College of Engineering and physical sciences, University of Guelph, Guelph, ON, Canada

Synopsis

Keywords: Phantoms, Software Tools, Quality assurance, ACR Phantom, Low contrast detectability

Motivation: The low-contrast object detectability test in the ACR phantom is conventionally performed manually, which results in low reproducibility of measurements due to intra- and inter-rater variability.

Goal(s): To automate the test in MRI systems and verify its reliability against the manual procedure.

Approach: The algorithm creates 1-dimensional image profiles and compares it with the known structure of the low-contrast objects using the general linear method test.

Results: Raters demonstrated substantial to almost perfect intra-rater agreement (0.786 and 0.841), and the algorithm showed perfect intra-rater agreement (1). Raters exhibited substantial inter-rater agreement (0.807), while raters and the algorithm averaged moderate inter-rater agreement (0.583).

Impact: We implemented an automated method for low-contrast object detectability of the ACR MRI phantom. The manual and automated methods showed strong intra- and inter-rater agreement, supporting its potential clinical use.

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