Juliane Dinse

Anatomically motivated modeling of cortical laminae.

Improvements in the spatial resolution of structural and functional MRI are beginning to enable analysis of intracortical structures such as heavily myelinated layers in 3D, a prerequisite for in-vivo parcellation of individual human brains. This parcellation can only be performed precisely if the profiles used in cortical analysis are anatomically meaningful. Profiles are often constructed as traverses that are perpendicular to computed laminae. In this case they are fully determined by these laminae. The aim of this study is to evaluate models for cortical laminae used so far and to establish a new model. Methods to model the laminae used so far include constructing laminae that keep a constant distance to the cortical boundaries, so-called equidistant laminae. Another way is to compute equipotentials between the cortical boundary surfaces with the Laplace equation. The Laplace profiles resulting from the gradients to the equipotentials were often-used because of their nice mathematical properties. However, the equipotentials these Laplacian profiles are constructed from and the equidistant laminae do not follow the anatomical layers observed using high resolution MRI of cadaver brain. To remedy this problem, we introduce a novel equi-volume model that derives from work by Bok (1929). He argued that cortical segments preserve their volume, while layer thickness changes to compensate cortical folding. We incorporate this preservation of volume in our new equi-volume model to generate a three-dimensional well-adapted undistorted coordinate system of the cortex. When defined by this well-adapted coordinate system, cortical depth is anatomically meaningful. We compare isocontours from these cortical depth values to locations of myelinated bands on high-resolution ex-vivo and in-vivo three-dimensional MR images. A similar comparison was performed with equipotentials computed with the Laplace equation and with equidistant isocontours. A quantitative evaluation of the equi-volume model using measured image intensities confirms that it provides a much better fit to observed cortical layering.

A computational framework for ultra-high resolution cortical segmentation at 7 Tesla

This paper presents a computational framework for whole brain segmentation of 7Tesla magnetic resonance images able to handle ultra-high resolution data. The approach combines multi-object topology-preserving deformable models with shape and intensity atlases to encode prior anatomical knowledge in a computationally efficient algorithm. Experimental validation on simulated and real brain images shows accuracy and robustness of the method and demonstrates the benefits of an increased processing resolution.

A cytoarchitecture-driven myelin model reveals area-specific signatures in human primary and secondary areas using ultra-high resolution in-vivo brain MRI

This work presents a novel approach for modelling laminar myelin patterns in the human cortex in brain MR images on the basis of known cytoarchitecture. For the first time, it is possible to estimate intracortical contrast visible in quantitative ultra-high resolution MR images in specific primary and secondary cytoarchitectonic areas. The presented technique reveals different area-specific signatures which may help to study the spatial distribution of cortical T1 values and the distribution of cortical myelin in general. It may lead to a new discussion on the concordance of cyto- and myeloarchitectonic boundaries, given the absence of such concordance atlases. The modelled myelin patterns are quantitatively compared with data from human ultra-high resolution in-vivo 7T brain MR images (9 subjects). In the validation, the results are compared to one post-mortem brain sample and its ex-vivo MRI and histological data. Details of the analysis pipeline are provided. In the context of the increasing interest in advanced methods in brain segmentation and cortical architectural studies, the presented model helps to bridge the gap between the microanatomy revealed by classical histology and the macroanatomy visible in MRI.

A subject-specific framework for in vivo myeloarchitectonic analysis using high resolution quantitative MRI

Structural magnetic resonance imaging can now resolve laminar features within the cerebral cortex in vivo. A variety of intracortical contrasts have been used to study the cortical myeloarchitecture with the purpose of mapping cortical areas in individual subjects. In this article, we first briefly review recent advances in MRI analysis of cortical microstructure to portray the potential and limitations of the current state-of-the-art. We then present an integrated framework for the analysis of intracortical structure, composed of novel image processing tools designed for high resolution cortical images. The main features of our framework are the segmentation of quantitative T1 maps to delineate the cortical boundaries (Bazin et al., 2014), and the use of an equivolume layering model to define an intracortical coordinate system that follows the anatomical layers of the cortex (Waehnert et al., 2014). We evaluate the framework with 150μm isotropic post mortem T2(∗)-weighted images and 0.5mm isotropic in vivo T1 maps, a quantitative index of myelin content. We study the laminar structure of the primary visual cortex (Brodmann area 17) in the post mortem and in vivo data, as well as the central sulcus region in vivo, in particular Brodmann areas 1, 3b and 4. We also investigate the impact of the layering models on the relationship between T1 and cortical curvature. Our experiments demonstrate that the equivolume intracortical surfaces and transcortical profiles best reflect the laminar structure of the cortex in areas of curvature in comparison to the state-of-the-art equidistant and Laplace implementations. This framework generates a subject specific intracortical coordinate system, the basis for subsequent architectonic analyses of the cortex. Any structural or functional contrast co-registered to the T1 maps, used to segment the cortex, can be sampled on the curved grid for analysis. This work represents an important step towards in vivo structural brain mapping of individual subjects.

Multi-contrast multi-scale surface registration for improved alignment of cortical areas

The position of cortical areas can be approximately predicted from cortical surface folding patterns. However, there is extensive inter-subject variability in cortical folding patterns, prohibiting a one-to-one mapping of cortical folds in certain areas. In addition, the relationship between cortical area boundaries and the shape of the cortex is variable, and weaker for higher-order cortical areas. Current surface registration techniques align cortical folding patterns using sulcal landmarks or cortical curvature, for instance. The alignment of cortical areas by these techniques is thus inherently limited by the sole use of geometric similarity metrics. Magnetic resonance imaging T1 maps show intra-cortical contrast that reflects myelin content, and thus can be used to improve the alignment of cortical areas. In this article, we present a new symmetric diffeomorphic multi-contrast multi-scale surface registration (MMSR) technique that works with partially inflated surfaces in the level-set framework. MMSR generates a more precise alignment of cortical surface curvature in comparison to two widely recognized surface registration algorithms. The resulting overlap in gyrus labels is comparable to FreeSurfer. Most importantly, MMSR improves the alignment of cortical areas further by including T1 maps. As a first application, we present a group average T1 map at a uniquely high-resolution and multiple cortical depths, which reflects the myeloarchitecture of the cortex. MMSR can also be applied to other MR contrasts, such as functional and connectivity data.

Body Topography Parcellates Human Sensory and Motor Cortex

Abstract The cytoarchitectonic map as proposed by Brodmann currently dominates models of human sensorimotor cortical structure, function, and plasticity. According to this model, primary motor cortex, area 4, and primary somatosensory cortex, area 3b, are homogenous areas, with the major division lying between the two. Accumulating empirical and theoretical evidence, however, has begun to question the validity of the Brodmann map for various cortical areas. Here, we combined in vivo cortical myelin mapping with functional connectivity analyses and topographic mapping techniques to reassess the validity of the Brodmann map in human primary sensorimotor cortex. We provide empirical evidence that area 4 and area 3b are not homogenous, but are subdivided into distinct cortical fields, each representing a major body part (the hand and the face). Myelin reductions at the hand–face borders are cortical layer-specific, and coincide with intrinsic functional connectivity borders as defined using large-scale resting state analyses. Our data extend the Brodmann model in human sensorimotor cortex and suggest that body parts are an important organizing principle, similar to the distinction between sensory and motor processing.

A Histology-Based Model of Quantitative T1 Contrast for In-vivo Cortical Parcellation of High-Resolution 7 Tesla Brain MR Images

A conclusive mapping of myeloarchitecture (myelin patterns) onto the cortical sheet and, thus, a corresponding mapping to cytoarchitecture (cell configuration) does not exist today. In this paper we present a generative model which can predict, on the basis of known cytoarchitecture, myeloarchitecture in different primary and non-primary cortical areas, resulting in simulated in-vivo quantitative T1 maps. The predicted patterns can be used in brain parcellation. Our model is validated using a similarity distance metric which enables quantitative comparison of the results with empirical data measured using MRI. The work presented may provide new perspectives for this line of research, both in imaging and in modelling the relationship with myelo- and cytoarchitecture, thus leading the way towards in-vivo histology using MRI.

Quantifying differences between primary cortical areas in humans based on laminar profiles in in vivo MRI data

This paper presents an approach for mapping the human cortical architecture in vivo based on quantitative MRI indices of myelin. We automatically construct laminar profiles in several primary cortical areas and investigate different sampling strategies. The results demonstrate that our method is able to distinguish these areas at specific cortical depths.

Depth-dependent intracortical myelin organization in the living human brain determined by in vivo ultra-high field magnetic resonance imaging

Background: Intracortical myelin is a key determinant of neuronal synchrony and plasticity that underpin optimal brain function. Magnetic resonance imaging (MRI) facilitates the examination of intracortical myelin but presents with methodological challenges. Here we describe a whole‐brain approach for the in vivo investigation of intracortical myelin in the human brain using ultra‐high field MRI. Methods: Twenty‐five healthy adults were imaged in a 7 Tesla MRI scanner using diffusion‐weighted imaging and a T1‐weighted sequence optimized for intracortical myelin contrast. Using an automated pipeline, T1 values were extracted at 20 depth‐levels from each of 148 cortical regions. In each cortical region, T1 values were used to infer myelin concentration and to construct a non‐linearity index as a measure the spatial distribution of myelin across the cortical ribbon. The relationship of myelin concentration and the non‐linearity index with other neuroanatomical properties were investigated. Five patients with multiple sclerosis were also assessed using the same protocol as positive controls. Results: Intracortical T1 values decreased between the outer brain surface and the gray‐white matter boundary following a slope that showed a slight leveling between 50% and 75% of cortical depth. Higher‐order regions in the prefrontal, cingulate and insular cortices, displayed higher non‐linearity indices than sensorimotor regions. Across all regions, there was a positive association between T1 values and non‐linearity indices (P < 10−5). Both T1 values (P < 10−5) and non‐linearity indices (P < 10−15) were associated with cortical thickness. Higher myelin concentration but only in the deepest cortical levels was associated with increased subcortical fractional anisotropy (P = 0.05). Conclusions: We demonstrate the usefulness of an automatic, whole‐brain method to perform depth‐dependent examination of intracortical myelin organization. The extracted metrics, T1 values and the non‐linearity index, have characteristic patterns across cortical regions, and are associated with thickness and underlying white matter microstructure. HighlightsIntracortical myelin is a key determinant of optimal brain function.We used a new approach to study intracortical myelin using ultra‐high field MRI.A new non‐linearity index was used as a measure of intracortical organization.Intracortical myelin concentration correlated with non‐linearity indices.Intracortical myelin concentration correlated with subcortical fractional anisotropy.

Extracting the Fine Structure of the Left Cardiac Ventricle in 4D CT Data

We propose a pipeline for the segmentation of the left cardiac ventricle (LV) in 4D CT data based on the random walker (RW) algorithm. A segmentation of the LV allows to extract clinical relevant parameters such as ejection fraction (EF) and volume over time (VoT), supporting diagnostic and therapy planning. The presented pipeline works aside approaches incorporating annotated databases, statistical shape modeling or atlas-based segmentation. We have tested our segmentation approach on six clinical 4D CT datasets including different pathologies and typical artifacts and compared the segmentation results to manually segmented slices. We achieve a minimum sensitivity of 86% and specificity of 96%. The resulting EF and VoT is comparable to known reference values and reflects the present pathologies correctly. Additionally, we tested three different routines for thresholding the RW probability maps. An interview with surgical and radiological experts together with high sensitivity scores indicates the superiority of the fixed threshold selection method – especially in the presence of pathologies. The segmentation is also correct near problematic fine structures such as cardiac valves, papillary muscles and the apex of the heart.