ArticleEuropean radiology2023
Assessing breast density using the chemical-shift encoding-based proton density fat fraction in 3-T MRI.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Correlation of ultrasound attenuation with proton density fat fraction across multiple organs in healthy volunteers.Medical physics · 2026Article
- Infrapatellar fat pad stiffness is associated with knee symptoms in patients with knee osteoarthritis.Clinical rheumatology · 2025Article
- Linearity and bias of proton density fat fraction across the full dynamic range of 0-100%: a multiplatform, multivendor phantom study using 1.5T and 3T MRI at two sites.Magma (New York, N.Y.) · 2024Article
- Breast MRI in patients with implantable loop recorder: initial experience.European radiology · 2024Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesThere is a clinical need for a non-ionizing, quantitative assessment of breast density, as one of the strongest independent risk factors for breast cancer. This study aims to establish proton density fat fraction (PDFF) as a quantitative biomarker for fat tissue concentration in breast MRI and correlate mean breast PDFF to mammography.
methodsIn this retrospective study, 193 women were routinely subjected to 3-T MRI using a six-echo chemical shift encoding-based water-fat sequence. Water-fat separation was based on a signal model accounting for a single T
resultsThe PDFF negatively correlated with mammographic and MRI breast density measurements (Spearman rho: -0.74, p < .001) and revealed a significant distinction between all four ACR categories. Mean T
conclusionThe proposed breast PDFF as an automated tissue fat concentration measurement is comparable with mammographic breast density estimations. Therefore, it is a promising approach to an accurate, user-independent, and non-ionizing breast density assessment that could be easily incorporated into clinical routine breast MRI exams. KEY POINTS: • The proposed PDFF strongly negatively correlates with visually determined mammographic and MRI-based breast density estimations and therefore allows for an accurate, non-ionizing, and user-independent breast density measurement. • In combination with T2*, the PDFF can be used to track structural alterations in the composition of breast tissue for an individualized risk assessment for breast cancer.
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Registered trials
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