Liver R2* threshold to predict the failure of MR elastography at 3T: SE-EPI versus GRE sequences
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Liver iron overload is the most common cause of magnetic resonance elastography (MRE) failure. Purpose To determine a threshold of R2*, a surrogate of liver iron concentration (LIC), which predicts the failure of liver MRE for either 2D gradient–recalled echo (GRE) or spin-echo echo-planar imaging (SE-EPI) MRE sequence at 3 T. Material and Methods This single–center retrospective study included 247 patients who underwent GRE MRE, SE-EPI MRE sequences for fibrosis evaluation and 2D multi-echo GRE sequence for R2* quantification using MRQuantif software. The ability of R2* to predict the failed MRE related to liver iron accumulation was estimated by the area under the receiver operating characteristic curve (AUC). Results After excluding 26 exams for technical failure, we evaluated 221 patients (52 women; mean age = 56 ± 13) with R2* values in the range of 37–1665 s −1 . The iron–related failure rates of GRE MRE and SE-EPI MRE were 62.9% (139/221) and 10.0% (22/221), respectively. The best cutoff of R2* to predict failure exam due to liver iron deposition with GRE MRE was 101 s −1 with a sensitivity of 79.1% and specificity of 97.6% (AUC = 0.97; 95% confidence interval [CI] = 0.95–0.99). This cutoff for SE-EPI MRE was 289 s −1 with a sensitivity of 82.8% and specificity of 99.5% (AUC = 0.89; 95% CI = 0.78–1). Conclusion Liver R2* is a good predictor of MRE examination failure related to iron deposition for MRE at 3 T.
Source: Acta Radiologica
Institutions: Inserm, Laboratoire Traitement du Signal et de l'Image, Centre Hospitalier Universitaire de Rennes, Nutrition, métabolismes et cancer, Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Institut de Recherche en Informatique et Systèmes Aléatoires, Empenn, Université de Rennes, CIC Rennes
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4411206133