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Weingärtner, Sebastian

https://orcid.org/0000-0002-0739-6306

Mayo Clinic

Delft University of Technology

Citations 2

Cross‐Vendor Validation of Proton Density Fat Fraction and T 1 Mapping Using a Combined Proton Density Fat Fraction—
Starekova, Jitka , Weingärtner, Sebastian , Rutkowski, David , Fullerton, Garrett , Bae, Won C. , Do, Hung P. , Madhuranthakam, Ananth J. , Lin, S. , Serai, Suraj D., Brittain, Jean H. , Hernando, D, Rutkowski, David R , Fullerton, Garrett C , Lin, Sheng Qing , Serai, Suraj D , Yokoo, Takeshi , Reeder, Scott B. , Brittain, Jean H , Hernando, Diego , Do, Hung Phi , Malis, Vadim , Serai, Suraj D. , Yokoo, Takeshi

Journal of Magnetic Resonance Imaging | May 20, 2026 | Volume: 64 | Issue: 2 | Pages: 482-492

10.1002/jmri.70344 Get It

ABSTRACT Background In chronic liver disease, fat and fibroinflammatory changes often coexist. However, their biomarkers, proton density fat fraction (PDFF) and T 1 , are typically assessed separately. Their reproducibility under mutual confounding remains unclear. Purpose To assess multicenter, multi‐vendor reproducibility of confounder‐corrected chemical shift‐encoded (CSE)‐MRI‐based PDFF mapping and MOLLI‐based T 1 mapping using a combined PDFF‐T 1 phantom. Study Type Prospective phantom study. Phantom Commercial PDFF‐T 1 Phantom (Model 725) with varying PDFF (0%–30%) and T 1 (200–1400 ms) values. Field Strength/Sequence 1.5 T and 3 T multi‐echo, three‐dimensional spoiled‐gradient‐echo (SGRE) sequence for PDFF mapping, and MOLLI sequence (5(3)3 acquisition scheme) using two‐dimensional SGRE readouts for T 1 mapping across four centers and vendors. Assessment PDFF and T 1 maps were acquired using standardized protocols. PDFF maps were reconstructed locally, while T 1 maps were generated using a centralized algorithm. All maps were quantitatively analyzed by a single radiologist using standardized region‐of‐interest placement. Phantom temporal stability was assessed at one center across five sessions over 9 months (baseline, retest, 1 week, 6 and 9 months). Statistical Tests Intraclass correlation coefficients (ICC), reproducibility coefficients (RDC), and linear regression analysis were used. A p value < 0.05 was considered statistically significant. Results PDFF showed overall excellent reproducibility (ICC = 0.987, RDC = 3.7%), with increased variability at higher T 1 values (RDC up to 7.9% at T 1 = 1400 ms). T 1 mapping showed good reproducibility in the absence of fat (RDC 16–161 ms at PDFF = 0%), but moderate to poor reproducibility in the presence of fat, with RDC increasing up to 1553 ms at PDFF 30%. Temporal stability was excellent ICC ≥ 0.998 for both PDFF and T 1 , and RDC of 1.1%–1.3% for PDFF and 52–57 ms for T 1 . Data Conclusion This phantom study demonstrated high reproducibility of PDFF, whereas T 1 reproducibility deteriorated at higher fat and T 1 levels, underscoring the need for fat‐corrected T 1 mapping for reliable assessment of fibroinflammatory changes. Evidence Level N/A. Technical Efficacy Stage 1.
Development, validation, qualification, and dissemination of quantitative MR methods: Overview and recommendations by the ISMRM quantitative MR study group
Weingärtner, Sebastian , Desmond, Kimberly L. , Obuchowski, Nancy A. , Zhang, Yuxin , Biondetti, Emma , Ma, Dan , Golay, Xavier , Boss, Michael A. , Gunter, Jeffrey L. , Group, the ISMRM Quantitative MR Study, Zhang, Yuxin , Biondetti, Emma , Ma, Dan , Golay, Xavier , Boss, Michael A , Gunter, Jeffrey L , Keenan, Kathryn E , Hernando, Diego , Baeßler, Bettina , Keenan, Kathryn E. , Group, the ISMRM Quantitative MR Study

Magnetic Resonance in Medicine | November 26, 2021 | Volume: 87 | Issue: 3 | Pages: 1184-1206

10.1002/mrm.29084 Get It

On behalf of the International Society for Magnetic Resonance in Medicine (ISMRM) Quantitative MR Study Group, this article provides an overview of considerations for the development, validation, qualification, and dissemination of quantitative MR (qMR) methods. This process is framed in terms of two central technical performance properties, i.e., bias and precision. Although qMR is confounded by undesired effects, methods with low bias and high precision can be iteratively developed and validated. For illustration, two distinct qMR methods are discussed throughout the manuscript: quantification of liver proton‐density fat fraction, and cardiacT1. These examples demonstrate the expansion of qMR methods from research centers toward widespread clinical dissemination. The overall goal of this article is to provide trainees, researchers, and clinicians with essential guidelines for the development and validation of qMR methods, as well as an understanding of necessary steps and potential pitfalls for the dissemination of quantitative MR in research and in the clinic.