Nonuniform Fourier-decomposition MRI for ventilation- and perfusion-weighted imaging of the lung

Abstract

Purpose: To improve the robustness of pulmonary ventilation- and perfusion-weighted imaging with Fourier decomposition (FD) MRI in the presence of respiratory and cardiac frequency variations by replacing the standard fast Fourier transform with the more general nonuniform Fourier transform.

Theory and methods: Dynamic coronal single-slice MRI of the thorax was performed in 11 patients and 5 healthy volunteers on a 1.5T whole-body scanner using a 2D ultra-fast balanced steady-state free-precession sequence with temporal resolutions of 4-9 images/s. For the proposed nonuniform Fourier-decomposition (NUFD) approach, the original signal with variable physiological frequencies that was acquired with constant sampling rate was retrospectively transformed into a signal with (ventilation or perfusion) frequency-adapted sampling rate. For that purpose, frequency tracking was performed with the synchro-squeezed wavelet transform. Ventilation- and perfusion-weighted NUFD amplitude and signal delay maps were generated and quantitatively compared with regularly sampled FD maps based on their signal-to-noise ratio (SNR).

Results: Volunteers and patients showed statistically significant increases of SNR in frequency-adapted NUFD results compared to regularly sampled FD results. For ventilation data, the mean SNR increased by $43.4\%\pm 25.3\%$ and $24.4\%\pm 31.9\%$ in volunteers and patients, respectively; for perfusion data, SNR increased by $93.0\%\pm 36.1\%$ and $75.6\%\pm 62.8\%$ . Two patients showed perfusion signal in pulmonary areas with NUFD that could not be imaged with FD.

Conclusion: This study demonstrates that using nonuniform Fourier transform in combination with frequency tracking can significantly increase SNR and reduce frequency overlaps by collecting the signal intensity onto single frequency bins.

Keywords: Fourier decomposition; lung; nonuniform Fourier transform; pulmonary MRI.