New MRI Technology Enables Non-Invasive Assessment of Interstitial Fluid Flow

However, there are very few non-invasive measurement methods available for measuring low-velocity biological fluid flow. The interstitial fluid velocity is four orders of magnitude lower than blood flow. The phase-contrast MRI (PC-MRI) technology is widely used to measure the velocity of rapid flow in biological tissues, such as blood. PC-MRI requires significant gradient intensity and duration when used for slow flow measurements, although high gradient intensity is especially sensitive to motion and creates motion artifacts during imaging. Additionally, when measuring slow flow velocity, the encoding gradient is large, and the echo time is relatively long. The SNR is significantly lost as the gradient echo is based on T2 relaxation decay. As a result, PC-MRI application is very limited.

Now, a team of researchers from the National Center for Nanoscience and Technology (NCNST, Beijing, China) has proposed a new, non-invasive MRI technology designed specifically for measuring interstitial fluid flow. The researchers combined PC-MRI with an improved stimulation echo sequence (ISTE). Conventional PC-MRI usually uses gradient echo, spin echo (SE), and stimulated echo (STE). Compared to the gradient echo, SE uses a 180° focusing pulse to focus the signal in the transverse plane, and its signal is affected by T2 relaxation, which decays more slowly and has a slightly higher image SNR. STE excites a part of the signal to the longitudinal plane and mitigates part of the T2 relaxation decay.

However, STE is not superior to SE under any TE condition. Hence, the research team proposed ISTE which refocuses the magnetic moment vectors in the longitudinal plane and yields better SNRs than STE or SE. Their effort led to an increase in the velocity encoding gradient interval, which can minimize the diffusion sensitivity factor under the same flow velocity measurement sensitivity, thereby reducing the signal loss caused by diffusion and improving the detection accuracy of slow-flow imaging. The researchers are hopeful that their novel method can further improve understanding of interstitial fluid flow.

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