Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 Jan 28;9(1):e86005.
doi: 10.1371/journal.pone.0086005. eCollection 2014.

Landmarking the brain for geometric morphometric analysis: an error study

Affiliations

Landmarking the brain for geometric morphometric analysis: an error study

Madeleine B Chollet et al. PLoS One. .

Abstract

Neuroanatomic phenotypes are often assessed using volumetric analysis. Although powerful and versatile, this approach is limited in that it is unable to quantify changes in shape, to describe how regions are interrelated, or to determine whether changes in size are global or local. Statistical shape analysis using coordinate data from biologically relevant landmarks is the preferred method for testing these aspects of phenotype. To date, approximately fifty landmarks have been used to study brain shape. Of the studies that have used landmark-based statistical shape analysis of the brain, most have not published protocols for landmark identification or the results of reliability studies on these landmarks. The primary aims of this study were two-fold: (1) to collaboratively develop detailed data collection protocols for a set of brain landmarks, and (2) to complete an intra- and inter-observer validation study of the set of landmarks. Detailed protocols were developed for 29 cortical and subcortical landmarks using a sample of 10 boys aged 12 years old. Average intra-observer error for the final set of landmarks was 1.9 mm with a range of 0.72 mm-5.6 mm. Average inter-observer error was 1.1 mm with a range of 0.40 mm-3.4 mm. This study successfully establishes landmark protocols with a minimal level of error that can be used by other researchers in the assessment of neuroanatomic phenotypes.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Landmarks and the associated error analyzed in this study.
Left lateral view of a 3D reconstruction of the brain (anterior is to the left). Projected positions of landmarks are shown with numbers corresponding to Table 2. Cortical surface landmarks are white with white wireframe; subcortical landmarks are purple with purple wireframe. The size of the pink ellipses around each landmark indicate the magnitude of average precision (error) at anatomic scale. Landmarks for which no ellipse is visible had average error less than the 1.5 mm radius of the landmark marker. Note that the greatest magnitudes of error were associated with cortical surface landmarks.
Figure 2
Figure 2. Histogram of the intra-observer precision of each landmark.
This histogram indicates the level of intra-observer precision associated with each landmark using the original (P1) and modified (P2) protocols. The error bar is equal to one standard deviation above and below the mean. Landmark numbers correspond with the landmark numbers in Table 2.
Figure 3
Figure 3. Histogram of the inter-observer precision of each landmark.
This histogram indicates the level of inter-observer precision associated with each landmark using the original (P1) and modified (P2) protocols. Landmark numbers correspond with the landmark numbers in Table 2.

Similar articles

Cited by

References

    1. Casey BJ, Tottenham N, Liston C, Durston S (2005) Imaging the developing brain: what have we learned about cognitive development? Trends Cogn Sci 9: 104–110. - PubMed
    1. Giedd JN, Rapoport JL (2010) Structural MRI of pediatric brain development: what have we learned and where are we going? Neuron 67: 728–734. - PMC - PubMed
    1. Raz N, Rodrigue KM (2006) Differential aging of the brain: patterns of cognitive correlates and modifiers. Neurosci Biobehav Rev 30: 730–748. - PMC - PubMed
    1. Gold SM, Dziobek I, Sweat V, Tirsi A, Rogers K, et al. (2007) Hippocampal damage and memory impairments as possible early brain complications of type 2 diabetes. Diabetologia 50: 711–719. - PubMed
    1. Lorenzetti V, Allen NB, Fornito A, Yucel M (2009) Structural brain abnormalities in major depressive disorder: a selective review of recent MRI studies. J Affect Disord 117: 1–17. - PubMed

Publication types

LinkOut - more resources