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. 2014 May;35(5):2424-34.
doi: 10.1002/hbm.22338. Epub 2013 Aug 24.

Reliability of neuroanatomical measurements in a multisite longitudinal study of youth at risk for psychosis

Tyrone D Cannon  1 , Frank Sun, Sarah Jacobson McEwen, Xenophon Papademetris, George He, Theo G M van Erp, Aron Jacobson, Carrie E Bearden, Elaine Walker, Xiaoping Hu, Lei Zhou, Larry J Seidman, Heidi W Thermenos, Barbara Cornblatt, Doreen M Olvet, Diana Perkins, Aysenil Belger, Kristin Cadenhead, Ming Tsuang, Heline Mirzakhanian, Jean Addington, Richard Frayne, Scott W Woods, Thomas H McGlashan, R Todd Constable, Maolin Qiu, Daniel H Mathalon, Paul Thompson, Arthur W Toga
Affiliations

Reliability of neuroanatomical measurements in a multisite longitudinal study of youth at risk for psychosis

Tyrone D Cannon et al. Hum Brain Mapp. 2014 May.

Abstract

Multisite longitudinal neuroimaging designs are used to identify differential brain structural change associated with onset or progression of disease. The reliability of neuroanatomical measurements over time and across sites is a crucial aspect of power in such studies. Prior work has found that while within-site reliabilities of neuroanatomical measurements are excellent, between-site reliability is generally more modest. Factors that may increase between-site reliability include standardization of scanner platform and sequence parameters and correction for between-scanner variations in gradient nonlinearities. Factors that may improve both between- and within-site reliability include use of registration algorithms that account for individual differences in cortical patterning and shape. In this study 8 healthy volunteers were scanned twice on successive days at 8 sites participating in the North American Prodrome Longitudinal Study (NAPLS). All sites employed 3 Tesla scanners and standardized acquisition parameters. Site accounted for 2 to 30% of the total variance in neuroanatomical measurements. However, site-related variations were trivial (<1%) among sites using the same scanner model and 12-channel coil or when correcting for between-scanner differences in gradient nonlinearity and scaling. Adjusting for individual differences in sulcal-gyral geometries yielded measurements with greater reliabilities than those obtained using an automated approach. Neuroimaging can be performed across multiple sites at the same level of reliability as at a single site, achieving within- and between-site reliabilities of 0.95 or greater for gray matter density in the majority of voxels in the prefrontal and temporal cortical surfaces as well as for the volumes of most subcortical structures.

Keywords: amygdala; cerebral cortex; computer-assisted image processing; hippocampus; magnetic resonance imaging; neuroanatomy; reproducibility of results; thalamus.

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Figures

Figure 1
Figure 1
Between‐site (A) and within‐site (B) intraclass correlations for the cortical pattern matching method.
Figure 2
Figure 2
Between‐site (A) and within‐site (B) intraclass correlations for the voxel‐based morphometry method.
Figure 3
Figure 3
Frequency distributions of between‐site (A) and within‐site (B) intraclass correlations by analysis method.
Figure 4
Figure 4
Between‐site intraclass correlations before and after correction for across‐scanner variations in gradient non‐linearities.
See this image and copyright information in PMC

References

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