科研速览 · Science Skim继续刷下去 · Keep skimming →
◆ Journal of magnetic resonance imaging : JMRI2026-08-07

Autonomous Velocity Encoding (VENC) Selection Improves Precision of Quantitative Flow Measurement.

Pierre Daudé, Rajiv Ramasawmy, Christine Mancini, Dominique Franson, Sunggun Lee, Anastasia Tsakirellis, W Patricia Bandettini, Ahsan Javed, Kelvin Chow, Adrienne E Campbell-Washburn

一句话结论 · In one sentence

Retrospective analysis demonstrated sub-optimal VENC setting in 96.5% of examinations with a VENC:Vmax ratio [2.03, 2.13] (two-sided bootstrap 90% confidence interval). In the prospective cohort, autonomous inline VENC selection yielded a mean VENC:Vmax ratio of 1.19 ± 0.10, significantly lower than subject-invariant VENC settings (VENC150:Vmax = 1.49 ± 0.31, VENC200:Vmax = 1.99 ± 0.41). Optimized VENC improved measurement precision, reducing velocity standard deviation by 41.9% ± 8.0%, and enabling shorter scan time to approximately 1/3 compared with default VENC 200 cm/s while maintaining equivalent velocity-to-noise performance.

原始摘要(英文原文)· Original abstract
BACKGROUND: The optimal velocity encoding limit (VENC) in phase contrast MRI is subject-specific because it depends on peak flow rate and the presence of flow jets. Currently, VENC is set manually with limited prior knowledge of the peak velocity. Setting the correct VENC might improve measurement precision or shorten scan times. PURPOSE: To evaluate a workflow for autonomous selection of the optimal VENC without technologist interaction. STUDY TYPE: Prospective and retrospective. POPULATION: The retrospective cohort included 254 scans from 113 patients (47 ± 14 years, 58 female) and 18 healthy volunteers (34 ± 15 years, 10 female). The prospective cohort included 5 patients with abnormal flow (47 ± 19 years, 2 female) and 10 healthy volunteers (28 ± 7 years, 6 female). FIELD STRENGTH/SEQUENCE: 1.5 T, 0.55 T; Cartesian gradient echo phase-contrast sequence. ASSESSMENT: A workflow has been designed to autonomously estimate and prescribe the optimal VENC. A 30s free-breathing calibration scan was followed by automatic estimation of the maximum velocity (Vmax) in < 6 s. The calculated optimal VENC was then automatically applied in the subsequent flow measurement without operator intervention. The target VENC:Vmax ratio was 1.1-1.25 according to consensus statements. STATISTICAL TESTS: Shapiro-Wilk test, nonparametric two-sided bootstrap with 90% confidence intervals, Wilcoxon signed-rank test, paired t-test. Holm correction was applied to prespecified pairwise comparisons. p < 0.05 was considered significant. RESULTS: Retrospective analysis demonstrated sub-optimal VENC setting in 96.5% of examinations with a VENC:Vmax ratio [2.03, 2.13] (two-sided bootstrap 90% confidence interval). In the prospective cohort, autonomous inline VENC selection yielded a mean VENC:Vmax ratio of 1.19 ± 0.10, significantly lower than subject-invariant VENC settings (VENC150:Vmax = 1.49 ± 0.31, VENC200:Vmax = 1.99 ± 0.41). Optimized VENC improved measurement precision, reducing velocity standard deviation by 41.9% ± 8.0%, and enabling shorter scan time to approximately 1/3 compared with default VENC 200 cm/s while maintaining equivalent velocity-to-noise performance. DATA CONCLUSION: Inline autonomous VENC selection improved flow-measurement precision, simplified the acquisition workflow, and reduced scan time at 0.55 T. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: 1.
读原文 · Read the paper ↗

AI 追问PRO

登录后使用 AI 追问

讨论区

登录后参与讨论

相关论文 · Related

Autonomous Velocity Encoding (VENC) Selection Improves Precision of Quantitative Flow Measurement. — 科研速览 Science Skim