Assessment of the Impact of Turbo Factor on Image Quality and Tissue Volumetrics in Brain Magnetic Resonance Imaging Using the Three-Dimensional T1-Weighted (3D T1W) Sequence
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
International Journal of Biomedical Imaging
Abstract
Background. The 3D T1W turbo field echo sequence is a standard imaging method for acquiring high-contrast images of the
brain. However, the contrast-to-noise ratio (CNR) can be affected by the turbo factor, which could affect the delineation and
segmentation of various structures in the brain and may consequently lead to misdiagnosis. This study is aimed at evaluating
the effect of the turbo factor on image quality and volumetric measurement reproducibility in brain magnetic resonance
imaging (MRI). Methods. Brain images of five healthy volunteers with no history of neurological diseases were acquired on a
1.5 T MRI scanner with varying turbo factors of 50, 100, 150, 200, and 225. The images were processed and analyzed with
FreeSurfer. The influence of the TFE factor on image quality and reproducibility of brain volume measurements was
investigated. Image quality metrics assessed included the signal-to-noise ratio (SNR) of white matter (WM), CNR between gray
matter/white matter (GM/WM) and gray matter/cerebrospinal fluid (GM/CSF), and Euler number (EN). Moreover, structural
brain volume measurements of WM, GM, and CSF were conducted. Results. Turbo factor 200 produced the best SNR
(median = 17 01) and GM/WM CNR (median = 2 29), but turbo factor 100 offered the most reproducible SNR (IQR = 2 72)
and GM/WM CNR (IQR = 0 14). Turbo factor 50 had the worst and the least reproducible SNR, whereas turbo factor 225 had
the worst and the least reproducible GM/WM CNR. Turbo factor 200 again had the best GM/CSF CNR but offered the least
reproducible GM/CSF CNR. Turbo factor 225 had the best performance on EN (-21), while turbo factor 200 was next to the
most reproducible turbo factor on EN (11). The results showed that turbo factor 200 had the least data acquisition time, in
addition to superior performance on SNR, GM/WM CNR, GM/CSF CNR, and good reproducibility characteristics on EN.
Both image quality metrics and volumetric measurements did not vary significantly (p > 0 05) with the range of turbo factors
used in the study by one-way ANOVA analysis. Conclusion. Since no significant differences were observed in the performance
of the turbo factors in terms of image quality and volume of brain structure, turbo factor 200 with a 74% acquisition time
reduction was found to be optimal for brain MR imaging at 1.5 T.
Description
Research Article
Keywords
Turbo Factor, Image Quality, 3D T1W