What type of study is this?

This is a Quantitative Study study (also classified as: Experimental Study).

September 17, 2025

Automatic velocity encoding (VENC) calibration for accurate quantitative flow measurement

Key Points

The calibration module improved flow measurement accuracy in the ascending aorta, achieving 97% optimal VENC.
Sixteen healthy volunteers were imaged to validate the automatic velocity encoding calibration process.
Inline calibration significantly reduced the time required for setting velocity encoding parameters during MRI.
This approach may enhance workflow efficiency in clinical settings by simplifying acquisition processes.

Abstract

Motivation: The optimal velocity encoding limit (VENC) in phase contrast MRI is subject-specific and is currently manually set by the technologist in a time-consuming process. Goal(s): We propose an inline automatic velocity encoding calibration for 2D phase-contrast flow MRI, which automatically computes and sets the optimal VENC. Approach: We designed a calibration module to automatically estimate the optimal VENC inline and set it in the subsequent flow measurement. Sixteen healthy volunteers were imaged at 0.55T. Results: Deployed inline, the calibration module calculated correctly the optimal VENC, mean of 97% of the maximum velocity in the ascending aorta, and automatically applied for subsequent flow sequence. Impact: Inline automatic velocity encoding calibration ensures the optimal precision in flow measurements and simplifies the acquisition workflow.

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