Automated claustrum segmentation in human brain MRI using deep learning

In the last two decades, neuroscience has produced intriguing evidence for a central role of the claustrum in mammalian forebrain structure and function. However, relatively few in vivo studies of the claustrum exist in humans. A reason for this may be the delicate and sheet-like structure of the claustrum lying between the insular cortex and the putamen, which makes it not amenable to conventional segmentation methods. Recently, Deep Learning (DL) based approaches have been successfully introduced for automated segmentation of complex, subcortical brain structures. In the following, we present a multi-view DL-based approach to segment the claustrum in T1-weighted MRI scans. We trained and evaluated the proposed method in 181 individuals, using bilateral manual claustrum annotations by an expert neuroradiologist as reference standard. Cross-validation experiments yielded median volumetric similarity, robust Hausdorff distance, and Dice score of 93.3%, 1.41 mm, and 71.8%, respectively, representing equal or superior segmentation performance compared to human intra-rater reliability. The leave-one-scanner-out evaluation showed good transferability of the algorithm to images from unseen scanners at slightly inferior performance. Furthermore, we found that DL-based claustrum segmentation benefits from multi-view information and requires a sample size of around 75 MRI scans in the training set. We conclude that the developed algorithm allows for robust automated claustrum segmentation and thus yields considerable potential for facilitating MRI-based research of the human claustrum. The software and models of our method are made publicly available

Aberrant claustrum microstructure in humans after premature birth

Several observations suggest an impact of prematurity on the claustrum. First, the claustrum’s development appears to depend on transient subplate neurons of intra-uterine brain development, which are affected by prematurity. Second, the claustrum is the most densely connected region of the mammalian forebrain relative to its volume; due to its effect on pre-oligodendrocytes, prematurity impacts white matter connections and thereby the development of sources and targets of such connections, potentially including the claustrum. Third, due to its high connection degree, the claustrum contributes to general cognitive functioning (e.g., selective attention and task switching/maintaining); general cognitive functioning, however, is at risk in prematurity. Thus, we hypothesized altered claustrum structure after premature birth, with these alterations being associated with impaired general cognitive performance in premature born persons. Using T1-weighted and diffusion-weighted magnetic resonance imaging in 70 very preterm/very low-birth-weight (VP/VLBW) born adults and 87 term-born adults, we found specifically increased mean diffusivity in the claustrum of VP/VLBW adults, associated both with low birth weight and at-trend with reduced IQ. This result demonstrates altered claustrum microstructure after premature birth. Data suggest aberrant claustrum development, which is potentially related with aberrant subplate neuron and forebrain connection development of prematurity