Recommendations of Choice of Head Coil and Prescan Normalize Filter Depend on Region of Interest and Task

Overview

Journal Front Neurosci

Date 2021 Nov 15

PMID 34776844

Citations 4

Authors

Tina Schmitt

Jochem W Rieger

Affiliations

Soon will be listed here.

Abstract

The performance of MRI head coils together with the influence of the prescan normalize filter in different brain regions was evaluated. Functional and structural data were recorded from 26 participants performing motor, auditory, and visual tasks in different conditions: with the 20- and 64-channel Siemens head/neck coil and the prescan normalize filter turned ON or OFF. Data were analyzed with the MRIQC tool to evaluate data quality differences. The functional data were statistically evaluated by comparison of the β estimates and the time-course signal-to-noise ratio (tSNR) in four regions of interest, i.e., the auditory, visual, and motor cortices and the thalamus. The MRIQC tool indicated a better data quality for both functional and structural data with the prescan normalize filter, with an advantage for the 20-channel head coil in functional data and an advantage for the 64-channel head coil in structural measurements. Nevertheless, recommendations for the functional data regarding choice of head coils and prescan normalize filter depend on the brain regions of interest. Higher β estimates and tSNR values occurred in the auditory cortex and thalamus with the prescan normalize filter, whereas the contrary was true for the visual and motor cortices. Due to higher β estimates in the visual cortex in the 64-channel head coil, this head coil is recommended for studies investigating the visual cortex. For most of the research questions, the 20-channel head coil is better suited for functional experiments, with the prescan normalize filter, especially when investigating deep brain areas. For anatomical studies, the 64-channel head coil seemed to be the better choice.

Citing Articles

Evaluating the capabilities and challenges of layer-fMRI VASO at 3T.

Huber L, Kronbichler L, Stirnberg R, Ehses P, Stocker T, Fernandez-Cabello S Apert Neuro. 2025; 3.

PMID: 39991189 PMC: 11845223. DOI: 10.52294/001c.85117.

Customization of neonatal functional magnetic resonance imaging: A preclinical phantom-based study.

Quinones J, Schmitt T, Pavan T, Hildebrandt A, Heep A PLoS One. 2024; 19(11):e0313192.

PMID: 39485821 PMC: 11530025. DOI: 10.1371/journal.pone.0313192.

The role of magnetic resonance imaging in the diagnosis and prognosis of dementia.

Zivanovic M, Aracki Trenkic A, Milosevic V, Stojanov D, Misic M, Radovanovic M Biomol Biomed. 2022; 23(2):209-224.

PMID: 36453893 PMC: 10113939. DOI: 10.17305/bjbms.2022.8085.

Open and reproducible neuroimaging: From study inception to publication.

Niso G, Botvinik-Nezer R, Appelhoff S, de la Vega A, Esteban O, Etzel J Neuroimage. 2022; 263:119623.

PMID: 36100172 PMC: 10008521. DOI: 10.1016/j.neuroimage.2022.119623.

Relationship between Memory Load and Listening Demands in Age-Related Hearing Impairment.

Pauquet J, Thiel C, Mathys C, Rosemann S Neural Plast. 2021; 2021:8840452.

PMID: 34188676 PMC: 8195652. DOI: 10.1155/2021/8840452.

References

Reiss-Zimmermann M, Gutberlet M, Kostler H, Fritzsch D, Hoffmann K . Improvement of SNR and acquisition acceleration using a 32-channel head coil compared to a 12-channel head coil at 3T. Acta Radiol. 2013; 54(6):702-8. DOI: 10.1177/0284185113479051. View

Belaroussi B, Milles J, Carme S, Zhu Y, Benoit-Cattin H . Intensity non-uniformity correction in MRI: existing methods and their validation. Med Image Anal. 2005; 10(2):234-46. DOI: 10.1016/j.media.2005.09.004. View

Keil B, Blau J, Biber S, Hoecht P, Tountcheva V, Setsompop K . A 64-channel 3T array coil for accelerated brain MRI. Magn Reson Med. 2012; 70(1):248-58. PMC: 3538896. DOI: 10.1002/mrm.24427. View

Wiggins G, Triantafyllou C, Potthast A, Reykowski A, Nittka M, Wald L . 32-channel 3 Tesla receive-only phased-array head coil with soccer-ball element geometry. Magn Reson Med. 2006; 56(1):216-23. DOI: 10.1002/mrm.20925. View

De Wilde J, Lunt J, Straughan K . Information in magnetic resonance images: evaluation of signal, noise and contrast. Med Biol Eng Comput. 1997; 35(3):259-65. DOI: 10.1007/BF02530047. View

Eickhoff S, Stephan K, Mohlberg H, Grefkes C, Fink G, Amunts K . A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage. 2005; 25(4):1325-35. DOI: 10.1016/j.neuroimage.2004.12.034. View

Liu T . Noise contributions to the fMRI signal: An overview. Neuroimage. 2016; 143:141-151. DOI: 10.1016/j.neuroimage.2016.09.008. View

de Zwart J, Ledden P, van Gelderen P, Bodurka J, Chu R, Duyn J . Signal-to-noise ratio and parallel imaging performance of a 16-channel receive-only brain coil array at 3.0 Tesla. Magn Reson Med. 2004; 51(1):22-6. DOI: 10.1002/mrm.10678. View

Sijbers J, den Dekker A, Van Audekerke J, Verhoye M, Van Dyck D . Estimation of the noise in magnitude MR images. Magn Reson Imaging. 1998; 16(1):87-90. DOI: 10.1016/s0730-725x(97)00199-9. View

10.

Saad Z, Reynolds R, Jo H, Gotts S, Chen G, Martin A . Correcting brain-wide correlation differences in resting-state FMRI. Brain Connect. 2013; 3(4):339-52. PMC: 3749702. DOI: 10.1089/brain.2013.0156. View

11.

Lufkin R, Sharpless T, Flannigan B, HANAFEE W . Dynamic-range compression in surface-coil MRI. AJR Am J Roentgenol. 1986; 147(2):379-82. DOI: 10.2214/ajr.147.2.379. View

12.

Reeder S, Wintersperger B, Dietrich O, Lanz T, Greiser A, Reiser M . Practical approaches to the evaluation of signal-to-noise ratio performance with parallel imaging: application with cardiac imaging and a 32-channel cardiac coil. Magn Reson Med. 2005; 54(3):748-54. DOI: 10.1002/mrm.20636. View

13.

Bernstein M, Huston 3rd J, Ward H . Imaging artifacts at 3.0T. J Magn Reson Imaging. 2006; 24(4):735-46. DOI: 10.1002/jmri.20698. View

14.

Triantafyllou C, Hoge R, Krueger G, Wiggins C, Potthast A, Wiggins G . Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters. Neuroimage. 2005; 26(1):243-50. DOI: 10.1016/j.neuroimage.2005.01.007. View

15.

Vovk U, Pernus F, Likar B . A review of methods for correction of intensity inhomogeneity in MRI. IEEE Trans Med Imaging. 2007; 26(3):405-21. DOI: 10.1109/TMI.2006.891486. View

16.

Albrecht J, Burke M, Haegler K, Schopf V, Kleemann A, Paolini M . Potential impact of a 32-channel receiving head coil technology on the results of a functional MRI paradigm. Clin Neuroradiol. 2010; 20(4):223-9. DOI: 10.1007/s00062-010-0029-2. View

17.

Robson P, Grant A, Madhuranthakam A, Lattanzi R, Sodickson D, McKenzie C . Comprehensive quantification of signal-to-noise ratio and g-factor for image-based and k-space-based parallel imaging reconstructions. Magn Reson Med. 2008; 60(4):895-907. PMC: 2838249. DOI: 10.1002/mrm.21728. View

18.

Walsh D, Gmitro A, Marcellin M . Adaptive reconstruction of phased array MR imagery. Magn Reson Med. 2000; 43(5):682-90. DOI: 10.1002/(sici)1522-2594(200005)43:5<682::aid-mrm10>3.0.co;2-g. View

19.

Triantafyllou C, Polimeni J, Wald L . Physiological noise and signal-to-noise ratio in fMRI with multi-channel array coils. Neuroimage. 2010; 55(2):597-606. PMC: 3039683. DOI: 10.1016/j.neuroimage.2010.11.084. View

20.

Seidel P, Levine S, Tahedl M, Schwarzbach J . Temporal Signal-to-Noise Changes in Combined Multislice- and In-Plane-Accelerated Echo-Planar Imaging with a 20- and 64-Channel Coil. Sci Rep. 2020; 10(1):5536. PMC: 7099092. DOI: 10.1038/s41598-020-62590-y. View