Influence of magnet strength on background parenchymal enhancement evaluation

Lindsay Douglas; Trisha Mondal; Alexandra Edwards; Maryellen Giger

doi:10.1117/12.2654284

3 April 2023 Influence of magnet strength on background parenchymal enhancement evaluation

Lindsay Douglas, Trisha Mondal, Alexandra Edwards, Maryellen Giger

Proceedings Volume 12467, Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment; 124670X (2023) https://doi.org/10.1117/12.2654284
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

Background parenchymal enhancement (BPE) is an independent risk factor for breast cancer that is subjectively defined by the relative volume and intensity of enhancement in normal fibroglandular breast tissue after contrast injection in dynamic contrast-enhanced (DCE) MRI. Given the relative increasing use of 3T instead of 1.5T MRI, this study evaluates the influence of magnet strength on radiologist BPE ratings and on performance of our previously-developed computer method for objective BPE scoring. The retrospectively-collected dataset consisted of 661 conventional breast DCE-MR exams (394 1.5T, 267 3T) from 350 patients with diagnosed lesions (2007-2015) and 311 high-risk screening patients (2009-2022). For the subset of 350 cases, receiver operating characteristic analysis was performed to determine the predictive value of the computed BPE scores relative to radiologists’ BPE ratings. Resulting computer BPE scores showed statistically significant correlations with radiologist ratings and performed statistically superior to guessing in the classification tasks. For the entire dataset, the prevalence of BPE ratings was explored for each magnet strength. We found that radiologists perceived higher BPE ratings on 3T than on 1.5T images, however we failed to show a statistical difference between 1.5T and 3T distributions of the computer BPE scores. We speculate that the transition from 1.5T to 3T MRI has influenced radiologist perception of BPE and can influence the performance of machine-learning methods for BPE quantification.

Conference Presentation

Citation Download Citation

Lindsay Douglas, Trisha Mondal, Alexandra Edwards, and Maryellen Giger "Influence of magnet strength on background parenchymal enhancement evaluation", Proc. SPIE 12467, Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment, 124670X (3 April 2023); https://doi.org/10.1117/12.2654284

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