Robust estimation of sulcal morphology

Abstract

While it is well established that cortical morphology differs in relation to a variety of inter-individual factors, it is often characterized using estimates of volume, thickness, surface area, or gyrification. Here we developed a computational approach for estimating sulcal width and depth that relies on cortical surface reconstructions output by FreeSurfer. While other approaches for estimating sulcal morphology exist, studies often require the use of multiple brain morphology programs that have been shown to differ in their approaches to localize sulcal landmarks, yielding morphological estimates based on inconsistent boundaries. To demonstrate the approach, sulcal morphology was estimated in three large sample of adults across the lifespan, in relation to aging. A fourth sample is additionally used to estimate test-retest reliability of the approach. This toolbox is now made freely available as supplemental to this paper: https://cmadan.github.io/calcSulc/ .

Keywords: Age; Atrophy; Cerebral sulci; Cortical structure; Gyrification; Sulcal depth; Sulcal width.

Fig. 1

Representative coronal slices and cortical surfaces with sulcal identification for 20- and 80-year-old individuals

Fig. 2

Histogram of age distribution for the three aging datasets: OASIS, DLBS, and SALD, only for participants included in the sulcal morphology analyses. Each bar corresponds to a 2-year age-range bin

Fig. 3

Example cortical surface with estimated sulci identified and labeled

Fig. 4

Illustration of the sulcal morphology method. a Cortical surface estimation and sulcal identification, as output from FreeSurfer. b Sulcal width and depth estimation procedure. Note that the surface mesh and estimation algorithm use many more vertices than shown here

Fig. 5

Relationship between a sulcal depth and b width for each of the sulci examined, based on the OASIS dataset