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Updated: Feb 2, 2026

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
Published on: January 7, 2021
Accelerated, first-pass cardiac perfusion pulse sequence with radial k-space sampling, compressed sensing, and
Nivedita K Naresh1, Hassan Haji-Valizadeh1,2, Pascale J Aouad1
1Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Purpose:
To develop an accelerated cardiac perfusion pulse sequence and test whether it is capable of increasing spatial coverage, generating high-quality images, and enabling quantification of myocardial blood flow (MBF).
Methods:
We implemented an accelerated first-pass cardiac perfusion pulse sequence by combining radial k-space sampling, compressed sensing (CS), and k-space weighted image contrast (KWIC) filtering. The proposed and clinical standard pulse sequences were evaluated in a randomized order in 13 patients at rest. For visual analysis, 3 readers graded the conspicuity of wall enhancement, artifact, and noise level on a 5-point Likert scale (overall score index = sum of 3 individual scores). Resting MBF was calculated using a Fermi function model with and without KWIC filtering. Mean visual scores and MBF values were compared between sequences using appropriate statistical tests.
Results:
The proposed pulse sequence produced greater spatial coverage (6-8 slices) with higher spatial resolution (1.6 × 1.6 × 8 mm3 ) and shorter readout duration (78 ms) compared to clinical standard (3-4 slices, 3 × 3 × 8 mm3 , 128 ms, respectively). The overall image score index between accelerated (11.1 ± 1.3) and clinical standard (11.2 ± 1.3) was not significantly different (P = 0.64). Mean resting MBF values with KWIC filtering (0.9-1.2 mL/g/min across different slices) were significantly lower (P < 0.0001) than those without KWIC filtering (3.1-4.3 mL/g/min) and agreed better with values reported in literature.
Conclusion:
An accelerated, first-pass cardiac perfusion pulse sequence with radial k-space sampling, CS, and KWIC filtering is capable of increasing spatial coverage, generating high-quality images, and enabling quantification of MBF.
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