χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain.

Obtaining a histological fingerprint from the in-vivo brain has been a long-standing target of magnetic resonance imaging (MRI). In particular, non-invasive imaging of iron and myelin, which are involved in normal brain functions and are histopathological hallmarks in neurodegenerative diseases, has practical utilities in neuroscience and medicine. Here, we propose a biophysical model that describes the individual contribution of paramagnetic (e.g., iron) and diamagnetic (e.g., myelin) susceptibility sources to the frequency shift and transverse relaxation of MRI signals. Using this model, we develop a method, χ-separation, that generates the voxel-wise distributions of the two sources. The method is validated using computer simulation and phantom experiments, and applied to ex-vivo and in-vivo brains. The results delineate the well-known histological features of iron and myelin in the specimen, healthy volunteers, and multiple sclerosis patients. This new technology may serve as a practical tool for exploring the microstructural information of the brain.

Multiple b-values improve discrimination of cortical gray matter regions using diffusion MRI: an experimental validation with a data-driven approach.

OBJECTIVE: To investigate whether varied or repeated b-values provide better diffusion MRI data for discriminating cortical areas with a data-driven approach. METHODS: Data were acquired from three volunteers at 1.5T with b-values of 800, 1400, 2000 s/mm2 along 64 diffusion-encoding directions. The diffusion signal was sampled from gray matter in seven regions of interest (ROIs). Rotational invariants of the local diffusion profile were extracted as features that characterize local tissue properties. Random forest classification experiments assessed whether classification accuracy improved when data with multiple b-values were used over repeated acquisition of the same (1400 s/mm2) b-value to compare all possible pairs of the seven ROIs. Three data sets from the Human Connectome Project were subjected to similar processing and analysis pipelines in eight ROIs. RESULTS: Three different b-values showed an average improvement in correct classification rates of 5.6% and 4.6%, respectively, in the local and HCP data over repeated measurements of the same b-value. The improvement in correct classification rate reached as high as 16% for individual binary classification experiments between two ROIs. Often using only two of the available three b-values were adequate to make such an improvement in classification rates. CONCLUSION: Acquisitions with varying b-values are more suitable for discriminating cortical areas.

Multiparameter mapping of relaxation (R1, R2*), proton density and magnetization transfer saturation at 3 T: A multicenter dual-vendor reproducibility and repeatability study.

Multicenter clinical and quantitative magnetic resonance imaging (qMRI) studies require a high degree of reproducibility across different sites and scanner manufacturers, as well as time points. We therefore implemented a multiparameter mapping (MPM) protocol based on vendor's product sequences and demonstrate its repeatability and reproducibility for whole-brain coverage. Within ~20 min, four MPM metrics (magnetization transfer saturation [MT], proton density [PD], longitudinal [R1], and effective transverse [R2*] relaxation rates) were measured using an optimized 1 mm isotropic resolution protocol on six 3 T MRI scanners from two different vendors. The same five healthy participants underwent two scanning sessions, on the same scanner, at each site. MPM metrics were calculated using the hMRI-toolbox. To account for different MT pulses used by each vendor, we linearly scaled the MT values to harmonize them across vendors. To determine longitudinal repeatability and inter-site comparability, the intra-site (i.e., scan-rescan experiment) coefficient of variation (CoV), inter-site CoV, and bias across sites were estimated. For MT, R1, and PD, the intra- and inter-site CoV was between 4 and 10% across sites and scan time points for intracranial gray and white matter. A higher intra-site CoV (16%) was observed in R2* maps. The inter-site bias was below 5% for all parameters. In conclusion, the MPM protocol yielded reliable quantitative maps at high resolution with a short acquisition time. The high reproducibility of MPM metrics across sites and scan time points combined with its tissue microstructure sensitivity facilitates longitudinal multicenter imaging studies targeting microstructural changes, for example, as a quantitative MRI biomarker for interventional clinical trials.

hMRI - A toolbox for quantitative MRI in neuroscience and clinical research.

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.

In-vivo magnetic resonance imaging (MRI) of laminae in the human cortex.

The human neocortex is organized radially into six layers which differ in their myelination and the density and arrangement of neuronal cells. This cortical cyto- and myeloarchitecture plays a central role in the anatomical and functional neuroanatomy but is primarily accessible through invasive histology only. To overcome this limitation, several non-invasive MRI approaches have been, and are being, developed to resolve the anatomical cortical layers. As a result, recent studies on large populations and structure-function relationships at the laminar level became possible. Early proof-of-concept studies targeted conspicuous laminar structures such as the stria of Gennari in the primary visual cortex. Recent work characterized the laminar structure outside the visual cortex, investigated the relationship between laminar structure and function, and demonstrated layer-specific maturation effects. This paper reviews the methods and in-vivo MRI studies on the anatomical layers in the human cortex based on conventional and quantitative MRI (excluding diffusion imaging). A focus is on the related challenges, promises and potential future developments. The rapid development of MRI scanners, motion correction techniques, analysis methods and biophysical modeling promise to overcome the challenges of spatial resolution, precision and specificity of systematic imaging of cortical laminae.

Confocal endomicroscopy in diagnosis of intestinal chronic graft-versus-host disease.

Graft-versus-host disease (GvHD) is a major complication of allogeneic stem cell transplantation. High-resolution in vivo histology of the intestine by confocal endomicroscopy (CEM) detects acute GvHD (aGvHD) with high sensitivity. This pilot study aims to evaluate the diagnostic value of CEM for intestinal chronic GvHD (cGvHD). The study included 20 patients with gastrointestinal symptoms and confirmed cGvHD in other organs as well as 20 patients with clinically suspected acute GvHD for control. Confocal endomicroscopy was performed as gastroscopy followed by sigmoidoscopy after intravenous injection of fluorescein (10%) and topical application of acriflavine (0.05%). Histopathology from H&E-stained biopsy samples throughout the intestinal tract complemented the survey. All histological features of intestinal cGvHD were predominantly mild to moderate. Stroma fibrosis detected by standard histology (16/20 patients) was not seen by CEM. Apoptosis assessed by histology in 12/20 patients was concordant with CEM (8/12 patients). Confocal endomicroscopy revealed esophageal manifestation of cGvHD in 3 patients. For each biopsy site, CEM correlated with intestinal histology (r = 0.64). Classical histology from intestinal biopsy samples taken under CEM monitoring confirmed the final diagnosis of cGvHD. The sensitivity of CEM with 40% in cGvHD was significantly lower compared to 70% in patients with aGvHD. Confocal endomicroscopy detected acute features of cGvHD and contributed to the diagnosis of esophageal cGvHD but failed to display stroma fibrosis in vivo. Although CEM represents a useful noninvasive tool in routine diagnostic of intestinal aGvHD, the method is not sufficient to fully establish the diagnosis of cGvHD within the intestinal tract. Confocal endomicroscopy allowed acquisition of targeted biopsies in patients suspected of having cGvHD.

[Computational neuroanatomy and microstructure imaging using magnetic resonance imaging]. / Computationale Neuroanatomie und Mikrostrukturbildgebung mit der Magnetresonanztomographie.

BACKGROUND: Current computational neuroanatomy focuses on morphological measurements of the brain using standard magnetic resonance imaging (MRI) techniques. In comparison quantitative MRI (qMRI) typically provides a better tissue contrast and also greatly improves the sensitivity and specificity with respect to the microstructural characteristics of tissue. OBJECTIVE: Current methodological developments in qMRI are presented, which go beyond morphology because this provides standardized measurements of the microstructure of the brain. The concept of in-vivo histology is introduced, based on biophysical modelling of qMRI data (hMRI) for determination of quantitative histology-like markers of the microstructure. RESULTS: The qMRI metrics can be used as direct biomarkers of the microstructural mechanisms driving observed morphological findings. The hMRI metrics utilize biophysical models of the MRI signal in order to determine 3­dimensional maps of histology-like measurements in the white matter. CONCLUSION: Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both scientific and clinical applications. Both approaches improve the comparability across sites and time points, facilitate multicenter and longitudinal studies as well as standardized diagnostics. The hMRI is expected to shed new light on the relationship between brain microstructure, function and behavior both in health and disease. In the future hMRI will play an indispensable role in the field of computational neuroanatomy.

Neurobiological origin of spurious brain morphological changes: A quantitative MRI study.

The high gray-white matter contrast and spatial resolution provided by T1-weighted magnetic resonance imaging (MRI) has made it a widely used imaging protocol for computational anatomy studies of the brain. While the image intensity in T1-weighted images is predominantly driven by T1, other MRI parameters affect the image contrast, and hence brain morphological measures derived from the data. Because MRI parameters are correlates of different histological properties of brain tissue, this mixed contribution hampers the neurobiological interpretation of morphometry findings, an issue which remains largely ignored in the community. We acquired quantitative maps of the MRI parameters that determine signal intensities in T1-weighted images (R1 (=1/T1), R2 *, and PD) in a large cohort of healthy subjects (n = 120, aged 18-87 years). Synthetic T1-weighted images were calculated from these quantitative maps and used to extract morphometry features-gray matter volume and cortical thickness. We observed significant variations in morphometry measures obtained from synthetic images derived from different subsets of MRI parameters. We also detected a modulation of these variations by age. Our findings highlight the impact of microstructural properties of brain tissue-myelination, iron, and water content-on automated measures of brain morphology and show that microstructural tissue changes might lead to the detection of spurious morphological changes in computational anatomy studies. They motivate a review of previous morphological results obtained from standard anatomical MRI images and highlight the value of quantitative MRI data for the inference of microscopic tissue changes in the healthy and diseased brain. Hum Brain Mapp 37:1801-1815, 2016. © 2016 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data.

Purpose: We present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity. Theory: The proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [P(r)] and (2) the g-ratio of the individual axons that compose this tract [g(r)]. P(r) is assumed to follow a Gamma distribution with mode and scale parameters, M and θ, and g(r) is described by a power law with parameters α and ß. Methods: MRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI-measured g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract. Results: The estimated interhemispheric transfer time was 11.72 ± 2.87 ms, leading to an average conduction velocity across subjects of 13.22 ± 1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated θ - the width of the right tail of the axonal radius distribution - and ß - the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter θ was 0.40 ± 0.07 µm and the parameter ß was 0.67 ± 0.02 µm-α. Conclusion: The estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in vivo histological studies of the human brain.

Towards in vivo g-ratio mapping using MRI: Unifying myelin and diffusion imaging.

BACKGROUND: The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease. NEW METHOD: This is the second review on the topic of g-ratio mapping using MRI. RESULTS: This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches. COMPARISON WITH EXISTING METHODS: Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology. CONCLUSIONS: We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.

Improved decision making for prioritizing tumor targeting antibodies in human xenografts: Utility of fluorescence imaging to verify tumor target expression, antibody binding and optimization of dosage and application schedule.

Preclinical efficacy studies of antibodies targeting a tumor-associated antigen are only justified when the expression of the relevant antigen has been demonstrated. Conventionally, antigen expression level is examined by immunohistochemistry of formalin-fixed paraffin-embedded tumor tissue section. This method represents the diagnostic "gold standard" for tumor target evaluation, but is affected by a number of factors, such as epitope masking and insufficient antigen retrieval. As a consequence, variances and discrepancies in histological staining results can occur, which may influence decision-making and therapeutic outcome. To overcome these problems, we have used different fluorescence-labeled therapeutic antibodies targeting human epidermal growth factor receptor (HER) family members and insulin-like growth factor-1 receptor (IGF1R) in combination with fluorescence imaging modalities to determine tumor antigen expression, drug-target interaction, and biodistribution and tumor saturation kinetics in non-small cell lung cancer xenografts. For this, whole-body fluorescence intensities of labeled antibodies, applied as a single compound or antibody mixture, were measured in Calu-1 and Calu-3 tumor-bearing mice, then ex vivo multispectral tumor tissue analysis at microscopic resolution was performed. With the aid of this simple and fast imaging method, we were able to analyze the tumor cell receptor status of HER1-3 and IGF1R, monitor the antibody-target interaction and evaluate the receptor binding sites of anti-HER2-targeting antibodies. Based on this, the most suitable tumor model, best therapeutic antibody, and optimal treatment dosage and application schedule was selected. Predictions drawn from obtained imaging data were in excellent concordance with outcome of conducted preclinical efficacy studies. Our results clearly demonstrate the great potential of combined in vivo and ex vivo fluorescence imaging for the preclinical development and characterization of monoclonal antibodies.

Whole-Brain In-vivo Measurements of the Axonal G-Ratio in a Group of 37 Healthy Volunteers.

The g-ratio, quantifying the ratio between the inner and outer diameters of a fiber, is an important microstructural characteristic of fiber pathways and is functionally related to conduction velocity. We introduce a novel method for estimating the MR g-ratio non-invasively across the whole brain using high-fidelity magnetization transfer (MT) imaging and single-shell diffusion MRI. These methods enabled us to map the MR g-ratio in vivo across the brain's prominent fiber pathways in a group of 37 healthy volunteers and to estimate the inter-subject variability. Effective correction of susceptibility-related distortion artifacts was essential before combining the MT and diffusion data, in order to reduce partial volume and edge artifacts. The MR g-ratio is in good qualitative agreement with histological findings despite the different resolution and spatial coverage of MRI and histology. The MR g-ratio holds promise as an important non-invasive biomarker due to its microstructural and functional relevance in neurodegeneration.

VPAC1 receptors for imaging breast cancer: a feasibility study.

UNLABELLED: VPAC1 encodes G-protein-coupled receptors expressed on all breast cancer (BC) cells at the onset of the disease, but not on benign lesions. Our extensive preclinical studies have shown that (64)Cu-TP3805 has a high affinity for VPAC1, is stable in vivo, and has the ability to distinguish spontaneously grown malignant BC masses from benign lesions. Our long-term goal is to develop (64)Cu-TP3805 as an agent to perform in vivo histology, to distinguish malignant lesions from benign masses noninvasively and thereby avoid patient morbidity and the excess economic costs of benign biopsies. METHODS: (18)F-FDG obtained commercially served as a control. (64)Cu-TP3805 was prepared using a sterile kit containing 20 µg of TP3805. Radiochemical purity and sterility were examined. Nineteen consenting women with histologically proven BC were given 370 MBq of (18)F-FDG. One hour later, 6 of these patients were imaged with PET/CT and 13 with positron emission mammography (PEM). Two to 7 d later, 6 PET/CT patients received 111 MBq (± 10%) (n = 2), 127 MBq (± 10%) (n = 2), or 148 MBq (± 10%) (n = 2) of (64)Cu-TP3805 and were imaged 2 and 4 h later. Thirteen PEM patients received 148 MBq (± 10%) of (64)Cu-TP3805 and were imaged 15 min, 1 h, 2 h, and 4 h later. Standardized uptake value (SUV) was calculated for PET/CT patients, and PUV/BGV (PEM uptake value/background value) was calculated for PEM patients. Tumor volume was also calculated. RESULTS: The radiochemical purity of (64)Cu-TP3805 was 97% ± 2%, and specific activity was 44.4 GBq (1.2 Ci)/µmol. In 19 patients, a total of 24 lesions were imaged (15 invasive ductal carcinoma, 1 high-grade mammary carcinoma, 3 lobular carcinoma, 1 invasive papilloma, and 4 sentinel lymph nodes). All lesions were unequivocally detected by (64)Cu-TP3805 and by (18)F-FDG. The average tumor volume as determined by PET/CT with (64)Cu-TP3805 was 90.6% ± 16.1% of that with (18)F-FDG PET/CT, and the average SUV was 92% ± 26.4% of that with (18)F-FDG. For PEM, the tumor volume with (64)Cu-TP3805 was 113% ± 37% of that with (18)F-FDG and the PUV/BGV ratio was 97.7% ± 24.5% of that with (18)F-FDG. CONCLUSION: (64)Cu-TP3805 is worthy of further investigation in patients requiring biopsy of suggestive imaging findings, to further evaluate its ability to distinguish malignant lesions from benign masses noninvasively.