Iterative Denoising Accelerated 3D FLAIR Sequence for Hydrops MR Imaging at 3T

BACKGROUND AND PURPOSE:

3D FLAIR sequences have become the criterion standard for identifying endolymphatic hydrops, but scan time remains an important limitation to their widespread use. Our purpose was to evaluate the diagnostic performance and image quality of an accelerated 3D FLAIR sequence combined with an iterative denoising algorithm.

MATERIALS AND METHODS:

This was a retrospective study performed on 30 patients with clinical suspicion of endolymphatic hydrops who underwent 3T MR imaging 4 hours after gadolinium injection using two 3D FLAIR sequences. The first (conventional FLAIR) was accelerated with a conventional turbo factor of 187. The second was accelerated with an increased turbo factor of 263, resulting in a 33% scan time reduction (5 minutes 36 seconds versus 8 minutes 15 seconds, respectively). A sequence was reconstructed in-line immediately after the accelerated 3D FLAIR acquisition from the same raw data with iterative denoising (accelerated-FLAIR iterative denoising). The signal intensity ratio image quality score and endolymphatic hydrops diagnosis were evaluated.

RESULTS:

The mean signal intensity ratio for symptomatic and asymptomatic ears of accelerated-FLAIR iterative denoising was significantly higher than the mean SNR of conventional FLAIR (29.5 versus 19 and 25.9 versus 16.3, P < .001). Compared with the conventional FLAIR sequence, the image-quality score was higher with accelerated-FLAIR iterative denoising (mean image-quality score, 3.8 [SD, 0.4] versus 3.3 [SD, 0.6] for accelerated-FLAIR iterative denoising and conventional FLAIR, respectively, P = .003). There was no significant difference in the diagnosis of endolymphatic hydrops between the 2 sequences. Interreader agreement was good-to-excellent.

CONCLUSIONS:

The iterative denoising algorithm applied to an accelerated 3D FLAIR sequence for exploration of endolymphatic hydrops enabled significantly reducing the scan time without compromising image quality and diagnostic performance.