Stephanie Schindler

Structural studies of the hypothalamus and its nuclei in mood disorders

A large body of evidence indicates that the hypothalamus is involved in pathogenetic mechanisms of mood disorders. It has been suggested that functional abnormalities of the hypothalamus are associated with structural hypothalamic changes. Structural neuroimaging allows in vivo investigation of the hypothalamus that may shed light on the underlying pathogenetic mechanisms of unipolar and bipolar disorder. Clearly, the detection of subtle structural cerebral changes depends on the limitations of the neuroimaging technique used. Making a comprehensive database search, we reviewed the literature on hypothalamic macrostructure in affective disorders, addressing the specific question of what structural magnetic resonance imaging might be expected to show. Studies with convincing methodology, although rare, suggest a global volume decrease in the hypothalamus in affective disorders, a decrease which is not shown by the two specific nuclei investigated, the paraventricular and supraoptic nuclei. We discuss the implications of these findings and provide directions for future research.

Development and evaluation of an algorithm for the computer-assisted segmentation of the human hypothalamus on 7-Tesla magnetic resonance images.

Post mortem studies have shown volume changes of the hypothalamus in psychiatric patients. With 7T magnetic resonance imaging this effect can now be investigated in vivo in detail. To benefit from the sub-millimeter resolution requires an improved segmentation procedure. The traditional anatomical landmarks of the hypothalamus were refined using 7T T1-weighted magnetic resonance images. A detailed segmentation algorithm (unilateral hypothalamus) was developed for colour-coded, histogram-matched images, and evaluated in a sample of 10 subjects. Test-retest and inter-rater reliabilities were estimated in terms of intraclass-correlation coefficients (ICC) and Dices coefficient (DC). The computer-assisted segmentation algorithm ensured test-retest reliabilities of ICC≥.97 (DC≥96.8) and inter-rater reliabilities of ICC≥.94 (DC = 95.2). There were no significant volume differences between the segmentation runs, raters, and hemispheres. The estimated volumes of the hypothalamus lie within the range of previous histological and neuroimaging results. We present a computer-assisted algorithm for the manual segmentation of the human hypothalamus using T1-weighted 7T magnetic resonance imaging. Providing very high test-retest and inter-rater reliabilities, it outperforms former procedures established at 1.5T and 3T magnetic resonance images and thus can serve as a gold standard for future automated procedures.

Habenula volume increases with disease severity in unmedicated major depressive disorder as revealed by 7T MRI

The habenula is a paired epithalamic structure involved in the pathogenesis of major depressive disorder (MDD). Evidence comes from its impact on the regulation of serotonergic and dopaminergic neurons, the role in emotional processing and studies on animal models of depression. The present study investigated habenula volumes in 20 unmedicated and 20 medicated MDD patients and 20 healthy controls for the first time by applying a triplanar segmentation algorithm on 7 Tesla magnetic resonance (MR) whole-brain T1 maps. The hypothesis of a right-side decrease of habenula volumes in the MDD patients was tested, and the relationship between volumetric abnormalities and disease severity was exploratively investigated. Absolute and relative total and hemispheric habenula volumes did not differ significantly between the three groups. In the patients with short duration of disease for which medication effects could be ruled out, significant correlations were found between bilateral habenula volumes and HAMD-17- and BDI-II-related severities. In the medicated patients, this positive relationship disappeared. Our findings suggest an involvement of habenula pathology in the beginning of MDD, while general effects independent of severity or stage of disease did not occur. Our findings warrant future combined tractographic and functional investigation using ultra-high-resolution in vivo MR imaging.

Diffusion imaging-based subdivision of the human hypothalamus: A magnetic resonance study with clinical implications

The hypothalamus and its subdivisions are involved in many neuropsychiatric conditions such as affective disorders, schizophrenia, or narcolepsy, but parcellations of hypothalamic subnuclei have hitherto been feasible only with histological techniques in postmortem brains. In an attempt to map subdivisions of the hypothalamus in vivo, we analyzed the directionality information from high-resolution diffusion-weighted magnetic resonance images of healthy volunteers. We acquired T1-weighted and diffusion-weighted scans in ten healthy subjects at 3 T. In the T1-weighted images, we manually delineated an individual mask of the hypothalamus in each subject and computed in the co-registered diffusion-weighted images the similarity of the principal diffusion direction for each pair of mask voxels. By clustering the similarity matrix into three regions with a k-means algorithm, we obtained an anatomically coherent arrangement of subdivisions across hemispheres and subjects. In each hypothalamus mask, we found an anterior region with dorsoventral principal diffusion direction, a posteromedial region with rostro-caudal direction, and a lateral region with mediolateral direction. A comparative analysis with microstructural hypothalamus parcellations from the literature reveals that each of these regions corresponds to a specific group of hypothalamic subnuclei as defined in postmortem brains. This is to our best knowledge the first in vivo study that attempts a delineation of hypothalamic subdivisions by clustering diffusion-weighted magnetic resonance imaging data. When applied in a larger sample of neuropsychiatric patients, a structural analysis of hypothalamic subnuclei should contribute to a better understanding of the pathogenesis of neuropsychiatric conditions such as affective disorders.

Intensity standardisation of 7T MR images for intensity-based segmentation of the human hypothalamus

The high spatial resolution of 7T MRI enables us to identify subtle volume changes in brain structures, providing potential biomarkers of mental disorders. Most volumetric approaches require that similar intensity values represent similar tissue types across different persons. By applying colour-coding to T1-weighted MP2RAGE images, we found that the high measurement accuracy achieved by high-resolution imaging may be compromised by inter-individual variations in the image intensity. To address this issue, we analysed the performance of five intensity standardisation techniques in high-resolution T1-weighted MP2RAGE images. Twenty images with extreme intensities in the GM and WM were standardised to a representative reference image. We performed a multi-level evaluation with a focus on the hypothalamic region—analysing the intensity histograms as well as the actual MR images, and requiring that the correlation between the whole-brain tissue volumes and subject age be preserved during standardisation. The results were compared with T1 maps. Linear standardisation using subcortical ROIs of GM and WM provided good results for all evaluation criteria: it improved the histogram alignment within the ROIs and the average image intensity within the ROIs and the whole-brain GM and WM areas. This method reduced the inter-individual intensity variation of the hypothalamic boundary by more than half, outperforming all other methods, and kept the original correlation between the GM volume and subject age intact. Mixed results were obtained for the other four methods, which sometimes came at the expense of unwarranted changes in the age-related pattern of the GM volume. The mapping of the T1 relaxation time with the MP2RAGE sequence is advertised as being especially robust to bias field inhomogeneity. We found little evidence that substantiated the T1 map’s theoretical superiority over the T1-weighted images regarding the inter-individual image intensity homogeneity.

A semi-automated algorithm for hypothalamus volumetry in 3 Tesla magnetic resonance images

The hypothalamus, a small diencephalic gray matter structure, is part of the limbic system. Volumetric changes of this structure occur in psychiatric diseases, therefore there is increasing interest in precise volumetry. Based on our detailed volumetry algorithm for 7 Tesla magnetic resonance imaging (MRI), we developed a method for 3 Tesla MRI, adopting anatomical landmarks and work in triplanar view. We overlaid T1-weighted MR images with gray matter-tissue probability maps to combine anatomical information with tissue class segmentation. Then, we outlined regions of interest (ROIs) that covered potential hypothalamus voxels. Within these ROIs, seed growing technique helped define the hypothalamic volume using gray matter probabilities from the tissue probability maps. This yielded a semi-automated method with short processing times of 20-40 min per hypothalamus. In the MRIs of ten subjects, reliabilities were determined as intraclass correlations (ICC) and volume overlaps in percent. Three raters achieved very good intra-rater reliabilities (ICC 0.82-0.97) and good inter-rater reliabilities (ICC 0.78 and 0.82). Overlaps of intra- and inter-rater runs were very good (≥ 89.7%). We present a fast, semi-automated method for in vivo hypothalamus volumetry in 3 Tesla MRI.

Hypothalamus enlargement in mood disorders

The purpose of this study was to determine, in vivo, whether the hypothalamus volume is reduced in patients with mood disorders.

PB 15 Hypothalamic enlargement in mood disorders – high-resolution in-vivo evidence

This article has been removed: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been removed at the request of the Publisher, as the authors did not give permission for the abstract to be published.This article has been removed: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been removed at the request of the Publisher, as the authors did not give permission for the abstract to be published.

PB 14 Color up your MRI! – performance of intensity standardisation techniques with 7T high-resolution MRIs

This article has been removed: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been removed at the request of the Publisher, as the authors did not give permission for the abstract to be published.This article has been removed: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been removed at the request of the Publisher, as the authors did not give permission for the abstract to be published.