Bayesian modelling of time series data (BayModTS)-a FAIR workflow to process sparse and highly variable data.

MOTIVATION: Systems biology aims to better understand living systems through mathematical modelling of experimental and clinical data. A pervasive challenge in quantitative dynamical modelling is the integration of time series measurements, which often have high variability and low sampling resolution. Approaches are required to utilize such information while consistently handling uncertainties. RESULTS: We present BayModTS (Bayesian modelling of time series data), a new FAIR (findable, accessible, interoperable, and reusable) workflow for processing and analysing sparse and highly variable time series data. BayModTS consistently transfers uncertainties from data to model predictions, including process knowledge via parameterized models. Further, credible differences in the dynamics of different conditions can be identified by filtering noise. To demonstrate the power and versatility of BayModTS, we applied it to three hepatic datasets gathered from three different species and with different measurement techniques: (i) blood perfusion measurements by magnetic resonance imaging in rat livers after portal vein ligation, (ii) pharmacokinetic time series of different drugs in normal and steatotic mice, and (iii) CT-based volumetric assessment of human liver remnants after clinical liver resection. AVAILABILITY AND IMPLEMENTATION: The BayModTS codebase is available on GitHub at https://github.com/Systems-Theory-in-Systems-Biology/BayModTS. The repository contains a Python script for the executable BayModTS workflow and a widely applicable SBML (systems biology markup language) model for retarded transient functions. In addition, all examples from the paper are included in the repository. Data and code of the application examples are stored on DaRUS: https://doi.org/10.18419/darus-3876. The raw MRI ROI voxel data were uploaded to DaRUS: https://doi.org/10.18419/darus-3878. The steatosis metabolite data are published on FairdomHub: 10.15490/fairdomhub.1.study.1070.1.

Propentdyopents as Heme Degradation Intermediates Constrict Mouse Cerebral Arterioles and Are Present in the Cerebrospinal Fluid of Patients With Subarachnoid Hemorrhage.

RATIONALE: Delayed ischemic neurological deficit is the most common cause of neurological impairment and unfavorable prognosis in patients with subarachnoid hemorrhage (SAH). Despite the existence of neuroimaging modalities that depict the onset of the accompanying cerebral vasospasm, preventive and therapeutic options are limited and fail to improve outcome owing to an insufficient pathomechanistic understanding of the delayed perfusion deficit. Previous studies have suggested that BOXes (bilirubin oxidation end products), originating from released heme surrounding ruptured blood vessels, are involved in arterial vasoconstriction. Recently, isolated intermediates of oxidative bilirubin degradation, known as PDPs (propentdyopents), have been considered as potential additional effectors in the development of arterial vasoconstriction. OBJECTIVE: To investigate whether PDPs and BOXes are present in hemorrhagic cerebrospinal fluid and involved in the vasoconstriction of cerebral arterioles. METHODS AND RESULTS: Via liquid chromatography/mass spectrometry, we measured increased PDP and BOX concentrations in cerebrospinal fluid of SAH patients compared with control subjects. Using differential interference contrast microscopy, we analyzed the vasoactivity of PDP isomers in vitro by monitoring the arteriolar diameter in mouse acute brain slices. We found an arteriolar constriction on application of PDPs in the concentration range that occurs in the cerebrospinal fluid of patients with SAH. By imaging arteriolar diameter changes using 2-photon microscopy in vivo, we demonstrated a short-onset vasoconstriction after intrathecal injection of either PDPs or BOXes. Using magnetic resonance imaging, we observed a long-term PDP-induced delay in cerebral perfusion. For all conditions, the arteriolar narrowing was dependent on functional big conductance potassium channels and was absent in big conductance potassium channels knockout mice. CONCLUSIONS: For the first time, we have quantified significantly higher concentrations of PDP and BOX isomers in the cerebrospinal fluid of patients with SAH compared to controls. The vasoconstrictive effect caused by PDPs in vitro and in vivo suggests a hitherto unrecognized pathway contributing to the pathogenesis of delayed ischemic deficit in patients with SAH.

A comprehensive numerical analysis of background phase correction with V-SHARP.

Sophisticated harmonic artifact reduction for phase data (SHARP) is a method to remove background field contributions in MRI phase images, which is an essential processing step for quantitative susceptibility mapping (QSM). To perform SHARP, a spherical kernel radius and a regularization parameter need to be defined. In this study, we carried out an extensive analysis of the effect of these two parameters on the corrected phase images and on the reconstructed susceptibility maps. As a result of the dependence of the parameters on acquisition and processing characteristics, we propose a new SHARP scheme with generalized parameters. The new SHARP scheme uses a high-pass filtering approach to define the regularization parameter. We employed the variable-kernel SHARP (V-SHARP) approach, using different maximum radii (Rm ) between 1 and 15 mm and varying regularization parameters (f) in a numerical brain model. The local root-mean-square error (RMSE) between the ground-truth, background-corrected field map and the results from SHARP decreased towards the center of the brain. RMSE of susceptibility maps calculated with a spatial domain algorithm was smallest for Rm between 6 and 10 mm and f between 0 and 0.01 mm-1 , and for maps calculated with a Fourier domain algorithm for Rm between 10 and 15 mm and f between 0 and 0.0091 mm-1 . We demonstrated and confirmed the new parameter scheme in vivo. The novel regularization scheme allows the use of the same regularization parameter irrespective of other imaging parameters, such as image resolution. Copyright © 2016 John Wiley & Sons, Ltd.

Quantitative Susceptibility Mapping in Parkinson's Disease.

BACKGROUND: Quantitative susceptibility mapping (QSM) and R2* relaxation rate mapping have demonstrated increased iron deposition in the substantia nigra of patients with idiopathic Parkinson's disease (PD). However, the findings in other subcortical deep gray matter nuclei are converse and the sensitivity of QSM and R2* for morphological changes and their relation to clinical measures of disease severity has so far been investigated only sparsely. METHODS: The local ethics committee approved this study and all subjects gave written informed consent. 66 patients with idiopathic Parkinson's disease and 58 control subjects underwent quantitative MRI at 3T. Susceptibility and R2* maps were reconstructed from a spoiled multi-echo 3D gradient echo sequence. Mean susceptibilities and R2* rates were measured in subcortical deep gray matter nuclei and compared between patients with PD and controls as well as related to clinical variables. RESULTS: Compared to control subjects, patients with PD had increased R2* values in the substantia nigra. QSM also showed higher susceptibilities in patients with PD in substantia nigra, in the nucleus ruber, thalamus, and globus pallidus. Magnetic susceptibility of several of these structures was correlated with the levodopa-equivalent daily dose (LEDD) and clinical markers of motor and non-motor disease severity (total MDS-UPDRS, MDS-UPDRS-I and II). Disease severity as assessed by the Hoehn & Yahr scale was correlated with magnetic susceptibility in the substantia nigra. CONCLUSION: The established finding of higher R2* rates in the substantia nigra was extended by QSM showing superior sensitivity for PD-related tissue changes in nigrostriatal dopaminergic pathways. QSM additionally reflected the levodopa-dosage and disease severity. These results suggest a more widespread pathologic involvement and QSM as a novel means for its investigation, more sensitive than current MRI techniques.

Quantitative susceptibility mapping differentiates between blood depositions and calcifications in patients with glioblastoma.

OBJECTIVES: The application of susceptibility weighted imaging (SWI) in brain tumor imaging is mainly used to assess tumor-related "susceptibility based signals" (SBS). The origin of SBS in glioblastoma is still unknown, potentially representing calcifications or blood depositions. Reliable differentiation between both entities may be important to evaluate treatment response and to identify glioblastoma with oligodendroglial components that are supposed to present calcifications. Since calcifications and blood deposits are difficult to differentiate using conventional MRI, we investigated whether a new post-processing approach, quantitative susceptibility mapping (QSM), is able to distinguish between both entities reliably. MATERIALS AND METHODS: SWI, FLAIR, and T1-w images were acquired from 46 patients with glioblastoma (14 newly diagnosed, 24 treated with radiochemotherapy, 8 treated with radiochemotherapy and additional anti-angiogenic medication). Susceptibility maps were calculated from SWI data. All glioblastoma were evaluated for the appearance of hypointense or hyperintense correlates of SBS on the susceptibility maps. RESULTS: 43 of 46 glioblastoma presented only hyperintense intratumoral SBS on susceptibility maps, indicating blood deposits. Additional hypointense correlates of tumor-related SBS on susceptibility maps, indicating calcification, were identified in 2 patients being treated with radiochemotherapy and in one patient being treated with additional anti-angiogenic medication. Histopathologic reports revealed an oligodendroglial component in one patient that presented calcifications on susceptibility maps. CONCLUSIONS: QSM provides a quantitative, local MRI contrast, which reliably differentiates between blood deposits and calcifications. Thus, quantitative susceptibility mapping appears promising to identify rare variants of glioblastoma with oligodendroglial components non-invasively and may allow monitoring the role of calcification in the context of different therapy regimes.

Toward online reconstruction of quantitative susceptibility maps: superfast dipole inversion.

Magnetic susceptibility is an intrinsic tissue property that recently became measureable in vivo by a magnetic-resonance based technique called quantitative susceptibility mapping (QSM). Although QSM may be performed without additional acquisition time, for example, in the course of the well-established susceptibility weighted imaging, the applicability of QSM is currently hampered by the numerical complexity and computational cost associated with the reconstruction procedure. This work introduces a novel QSM framework called superfast dipole inversion which allows rapid online reconstruction of susceptibility maps from wrapped raw gradient-echo phase data. The algorithm relies on the extension and combination of several recent algorithms involving the precalculation of convolution kernels and the correction of inversion artifacts. Reconstruction of three-dimensional high resolution susceptibility maps of the human brain was achieved with superfast dipole inversion in less than 20 s on a conventional workstation computer. Thus, superfast dipole inversion opens the door to an implementation of QSM on MR scanner hardware as well as to the routine reconstruction of large cohorts of datasets.

Atlas-guided cluster analysis of large tractography datasets.

Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment.

Quantitative susceptibility mapping for investigating subtle susceptibility variations in the human brain.

Quantitative susceptibility mapping (QSM) is a novel magnetic resonance-based technique that determines tissue magnetic susceptibility from measurements of the magnetic field perturbation. Due to the ill-posed nature of this problem, regularization strategies are generally required to reduce streaking artifacts on the computed maps. The present study introduces a new algorithm for calculating the susceptibility distribution utilizing a priori information on its regional homogeneity derived from gradient echo phase images and analyzes the impact of erroneous a priori information on susceptibility map fidelity. The algorithm, Homogeneity Enabled Incremental Dipole Inversion (HEIDI), was investigated with a special focus on the reconstruction of subtle susceptibility variations in a numerical model and in volunteer data and was compared with two recently published approaches, Thresholded K-space Division (TKD) and Morphology Enabled Dipole Inversion (MEDI). HEIDI resulted in susceptibility maps without streaking artifacts and excellent depiction of subtle susceptibility variations in most regions. By investigating HEIDI susceptibility maps acquired with the volunteers' heads in different orientations, it was demonstrated that the apparent magnetic susceptibility distribution of human brain tissue considerably depends on the direction of the main magnetic field.

Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: an approach to in vivo brain iron metabolism?

Quantitative susceptibility mapping (QSM) based on gradient echo (GRE) magnetic resonance phase data is a novel technique for non-invasive assessment of magnetic tissue susceptibility differences. The method is expected to be an important means to determine iron distributions in vivo and may, thus, be instrumental for elucidating the physiological role of iron and disease-related iron concentration changes associated with various neurological and psychiatric disorders. This study introduces a framework for QSM and demonstrates calculation of reproducible and orientation-independent susceptibility maps from GRE data acquired at 3T. The potential of these susceptibility maps to perform anatomical imaging is investigated, as well as the ability to measure the venous blood oxygen saturation level in large vessels, and to assess the local tissue iron concentration. In order to take into account diamagnetic susceptibility contributions induced by myelin, a correction scheme for susceptibility based iron estimation is demonstrated. The findings suggest that susceptibility contrast, and therewith also phase contrast, are not only linked to the storage iron concentration but are also significantly influenced by other sources such as myelin. After myelin correction the linear dependence between magnetic susceptibilities and previously published iron concentrations from post mortem studies was significantly improved. Finally, a comparison between susceptibility maps and processed phase images indicated that caution should be exercised when drawing conclusions about iron concentrations when directly assessing processed phase information.