Combining images and anatomical knowledge to improve automated vein segmentation in MRI

Incorporating a-priori information in deep learning models for quantitative susceptibility mapping via adaptive convolution

Quantitative susceptibility mapping (QSM) has attracted considerable interest for tissue characterization (e.g., iron and calcium accumulation, myelination, venous vasculature) in the human brain and relies on extensive data processing of gradient-echo MRI phase images. While deep learning-based field-to-susceptibility inversion has shown great potential, the acquisition parameters applied in clinical settings such as image resolution or image orientation with respect to the magnetic field have not been fully accounted for. Furthermore, the lack of comprehensive training data covering a wide range of acquisition parameters further limits the current QSM deep learning approaches. Here, we propose the integration of a priori information of imaging parameters into convolutional neural networks with our approach, adaptive convolution, that learns the mapping between the additional presented information (acquisition parameters) and the changes in the phase images associated with these varying acquisition parameters. By associating a-priori information with the network parameters itself, the optimal set of convolution weights is selected based on data-specific attributes, leading to generalizability towards changes in acquisition parameters. Moreover, we demonstrate the feasibility of pre-training on synthetic data and transfer learning to clinical brain data to achieve substantial improvements in the computation of susceptibility maps. The adaptive convolution 3D U-Net demonstrated generalizability in acquisition parameters on synthetic and in-vivo data and outperformed models lacking adaptive convolution or transfer learning. Further experiments demonstrate the impact of the side information on the adaptive model and assessed susceptibility map computation on simulated pathologic data sets and measured phase data.

Modeling venous bias in resting state functional MRI metrics

Resting-state (rs) functional magnetic resonance imaging (fMRI) is used to detect low-frequency fluctuations in the blood oxygen-level dependent (BOLD) signal across brain regions. Correlations between temporal BOLD signal fluctuations are commonly used to infer functional connectivity. However, because BOLD is based on the dilution of deoxyhemoglobin, it is sensitive to veins of all sizes, and its amplitude is biased by draining veins. These biases affect local BOLD signal location and amplitude, and may also influence BOLD-derived connectivity measures, but the magnitude of this venous bias and its relation to vein size and proximity is unknown. Here, veins were identified using high-resolution quantitative susceptibility maps and utilized in a biophysical model to investigate systematic venous biases on common local rsfMRI-derived measures. Specifically, we studied the impact of vein diameter and distance to veins on the amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), Hurst exponent (HE), regional homogeneity (ReHo), and eigenvector centrality values in the grey matter. Values were higher across all distances in smaller veins, and decreased with increasing vein diameter. Additionally, rsfMRI values associated with larger veins decrease with increasing distance from the veins. ALFF and ReHo were the most biased by veins, while HE and fALFF exhibited the smallest bias. Across all metrics, the amplitude of the bias was limited in voxel-wise data, confirming that venous structure is not the dominant source of contrast in these rsfMRI metrics. Finally, the models presented can be used to correct this venous bias in rsfMRI metrics.

Cerebral oxygen metabolism from MRI susceptibility

This article provides an overview of MRI methods exploiting magnetic susceptibility properties of blood to assess cerebral oxygen metabolism, including the tissue oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2). The first section is devoted to describing blood magnetic susceptibility and its effect on the MRI signal. Blood circulating in the vasculature can have diamagnetic (oxyhemoglobin) or paramagnetic properties (deoxyhemoglobin). The overall balance between oxygenated and deoxygenated hemoglobin determines the induced magnetic field which, in turn, modulates the transverse relaxation decay of the MRI signal via additional phase accumulation. The following sections of this review then illustrate the principles underpinning susceptibility-based techniques for quantifying OEF and CMRO2. Here, it is detailed whether these techniques provide global (OxFlow) or local (Quantitative Susceptibility Mapping - QSM, calibrated BOLD - cBOLD, quantitative BOLD - qBOLD, QSM+qBOLD) measurements of OEF or CMRO2, and what signal components (magnitude or phase) and tissue pools they consider (intravascular or extravascular). Validations studies and potential limitations of each method are also described. The latter include (but are not limited to) challenges in the experimental setup, the accuracy of signal modeling, and assumptions on the measured signal. The last section outlines the clinical uses of these techniques in healthy aging and neurodegenerative diseases and contextualizes these reports relative to results from gold-standard PET.

Quantitative susceptibility mapping using plug-and-play alternating direction method of multipliers

Quantitative susceptibility mapping employs regularization to reduce artifacts, yet many recent denoisers are unavailable for reconstruction. We developed a plug-and-play approach to QSM reconstruction (PnP QSM) and show its flexibility using several patch-based denoisers. We developed PnP QSM using alternating direction method of multiplier framework and applied collaborative filtering denoisers. We apply the technique to the 2016 QSM Challenge and in 10 glioblastoma multiforme datasets. We compared its performance with four published QSM techniques and a multi-orientation QSM method. We analyzed magnetic susceptibility accuracy using brain region-of-interest measurements, and image quality using global error metrics. Reconstructions on glioblastoma data were analyzed using ranked and semiquantitative image grading by three neuroradiologist observers to assess image quality (IQ) and sharpness (IS). PnP-BM4D QSM showed good correlation (β = 0.84, R² = 0.98, p < 0.05) with COSMOS and no significant bias (bias = 0.007 ± 0.012). PnP-BM4D QSM achieved excellent quality when assessed using structural similarity index metric (SSIM = 0.860), high frequency error norm (HFEN = 58.5), cross correlation (CC = 0.804), and mutual information (MI = 0.475) and also maintained good conspicuity of fine features. In glioblastoma datasets, PnP-BM4D QSM showed higher performance (IQ_Grade = 2.4 ± 0.4, IS_Grade = 2.7 ± 0.3, IQ_Rank = 3.7 ± 0.3, IS_Rank = 3.9 ± 0.3) compared to MEDI (IQ_Grade = 2.1 ± 0.5, IS_Grade = 2.1 ± 0.6, IQ_Rank = 2.4 ± 0.6, IS_Rank = 2.9 ± 0.2) and FANSI-TGV (IQ_Grade = 2.2 ± 0.6, IS_Grade = 2.1 ± 0.6, IQ_Rank = 2.7 ± 0.3, IS_Rank = 2.2 ± 0.2). We illustrated the modularity of PnP QSM by interchanging two additional patch-based denoisers. PnP QSM reconstruction was feasible, and its flexibility was shown using several patch-based denoisers. This technique may allow rapid prototyping and validation of new denoisers for QSM reconstruction for an array of useful clinical applications.

Venous cerebral blood flow quantification and cognition in patients with sickle cell anemia

Prior studies have described high venous signal qualitatively using arterial spin labelling (ASL) in patients with sickle cell anemia (SCA), consistent with arteriovenous shunting. We aimed to quantify the effect and explored cross-sectional associations with arterial oxygen content (CaO2), disease-modifying treatments, silent cerebral infarction (SCI), and cognitive performance. 94 patients with SCA and 42 controls underwent cognitive assessment and MRI with single- and multi- inflow time (TI) ASL sequences. Cerebral blood flow (CBF) and bolus arrival time (BAT) were examined across gray and white matter and high-signal regions of the sagittal sinus. Across gray and white matter, increases in CBF and reductions in BAT were observed in association with reduced CaO2 in patients, irrespective of sequence. Across high-signal sagittal sinus regions, CBF was also increased in association with reduced CaO2 using both sequences. However, BAT was increased rather than reduced in patients across these regions, with no association with CaO2. Using the multiTI sequence in patients, increases in CBF across white matter and high-signal sagittal sinus regions were associated with poorer cognitive performance. These novel findings highlight the utility of multiTI ASL in illuminating, and identifying objectively quantifiable and functionally significant markers of, regional hemodynamic stress in patients with SCA.

Imaging of the pial arterial vasculature of the human brain in vivo using high-resolution 7T time-of-flight angiography

The pial arterial vasculature of the human brain is the only blood supply to the neocortex, but quantitative data on the morphology and topology of these mesoscopic arteries (diameter 50–300 µm) remains scarce. Because it is commonly assumed that blood flow velocities in these vessels are prohibitively slow, non-invasive time-of-flight magnetic resonance angiography (TOF-MRA)—which is well suited to high 3D imaging resolutions—has not been applied to imaging the pial arteries. Here, we provide a theoretical framework that outlines how TOF-MRA can visualize small pial arteries in vivo, by employing extremely small voxels at the size of individual vessels. We then provide evidence for this theory by imaging the pial arteries at 140 µm isotropic resolution using a 7 Tesla (T) magnetic resonance imaging (MRI) scanner and prospective motion correction, and show that pial arteries one voxel width in diameter can be detected. We conclude that imaging pial arteries is not limited by slow blood flow, but instead by achievable image resolution. This study represents the first targeted, comprehensive account of imaging pial arteries in vivo in the human brain. This ultra-high-resolution angiography will enable the characterization of pial vascular anatomy across the brain to investigate patterns of blood supply and relationships between vascular and functional architecture.

Individual differences in haemoglobin concentration influence bold fMRI functional connectivity and its correlation with cognition

Resting-state connectivity measures the temporal coherence of the spontaneous neural activity of spatially distinct regions, and is commonly measured using BOLD-fMRI. The BOLD response follows neuronal activity, when changes in the relative concentration of oxygenated and deoxygenated haemoglobin cause fluctuations in the MRI T2* signal. Since the BOLD signal detects changes in relative concentrations of oxy/deoxy-haemoglobin, individual differences in haemoglobin levels may influence the BOLD signal-to-noise ratio in a manner independent of the degree of neural activity. In this study, we examined whether group differences in haemoglobin may confound measures of functional connectivity. We investigated whether relationships between measures of functional connectivity and cognitive performance could be influenced by individual variability in haemoglobin. Finally, we mapped the neuroanatomical distribution of the influence of haemoglobin on functional connectivity to determine where group differences in functional connectivity are manifest. In a cohort of 518 healthy elderly subjects (259 men), each sex group was median-split into two groups with high and low haemoglobin concentration. Significant differences were obtained in functional connectivity between the high and low haemoglobin groups for both men and women (Cohen's d 0.17 and 0.03 for men and women respectively). The haemoglobin connectome in males showed a widespread systematic increase in functional connectivity correlation values, whilst the female connectome showed predominantly parietal and subcortical increases and temporo-parietal decreases. Despite the haemoglobin groups having no differences in cognitive measures, significant differences in the linear relationships between cognitive performance and functional connectivity were obtained for all 5 cognitive tests in males, and 4 out of 5 tests in females. Our findings confirm that individual variability in haemoglobin levels that give rise to group differences are an important confounding variable in BOLD-fMRI-based studies of functional connectivity. Controlling for haemoglobin variability as a potentially confounding variable is crucial to ensure the reproducibility of human brain connectome studies, especially in studies that compare groups of individuals, compare sexes, or examine connectivity-cognition relationships.

A Comprehensive Framework to Capture the Arcana of Neuroimaging Analysis

Mastering the "arcana of neuroimaging analysis", the obscure knowledge required to apply an appropriate combination of software tools and parameters to analyse a given neuroimaging dataset, is a time consuming process. Therefore, it is not typically feasible to invest the additional effort required generalise workflow implementations to accommodate for the various acquisition parameters, data storage conventions and computing environments in use at different research sites, limiting the reusability of published workflows. We present a novel software framework, Abstraction of Repository-Centric ANAlysis (Arcana), which enables the development of complex, "end-to-end" workflows that are adaptable to new analyses and portable to a wide range of computing infrastructures. Analysis templates for specific image types (e.g. MRI contrast) are implemented as Python classes, which define a range of potential derivatives and analysis methods. Arcana retrieves data from imaging repositories, which can be BIDS datasets, XNAT instances or plain directories, and stores selected derivatives and associated provenance back into a repository for reuse by subsequent analyses. Workflows are constructed using Nipype and can be executed on local workstations or in high performance computing environments. Generic analysis methods can be consolidated within common base classes to facilitate code-reuse and collaborative development, which can be specialised for study-specific requirements via class inheritance. Arcana provides a framework in which to develop unified neuroimaging workflows that can be reused across a wide range of research studies and sites.

Serial assessment of iron in the motor cortex in limb-onset amyotrophic lateral sclerosis using quantitative susceptibility mapping

BACKGROUND

Dysregulation of iron in the cerebral motor areas has been hypothesized to occur in individuals with amyotrophic lateral sclerosis (ALS). There is still limited knowledge regarding iron dysregulation in the progression of ALS pathology. Our objectives were to use magnetic resonance based quantitative susceptibility mapping (QSM) to investigate the association between iron dysregulation in the motor cortex and clinical manifestations in patients with limb-onset ALS, and to examine changes in the iron concentration in the motor cortex in these patients over a 6-month period.

METHODS

Iron concentration was investigated using magnetic resonance based QSM in the primary motor cortex and the pre-motor area in 13 limb-onset ALS patients (including five lumbar onset, six cervical onset and two flail arm patients), and 11 age- and sex-matched control subjects. Nine ALS patients underwent follow-up scans at 6 months.

RESULTS

Significantly increased QSM values were observed in the left posterior primary motor area (P=0.02, Cohen's d =0.9) and right anterior primary motor area (P=0.02, Cohen's d =0.92) in the group of limb-onset ALS patients compared to that of control subjects. Increased QSM was observed in the primary motor and pre-motor area at baseline in patients with lumbar onset ALS patients, but not cervical limb-onset ALS patients, compared to control subjects. No significant change in QSM was observed at the 6-month follow-up scans in the ALS patients.

CONCLUSIONS

The findings suggest that iron dysregulation can be detected in the motor cortex in limb-onset ALS, which does not appreciably change over a further 6 months. Individuals with lumbar onset ALS appear to be more susceptible to motor cortex iron dysregulation compared to the individuals with cervical onset ALS. Importantly, this study highlights the potential use of QSM as a quantitative radiological indicator in early disease diagnosis in limb-onset ALS and its subtypes. Our serial scans results suggest a longer period than 6 months is needed to detect significant quantitative changes in the motor cortex.

Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging

Introduction

Susceptibility weighted imaging (SWI) is a very sensitive technique that often depicts prominent focal veins (PFV) in patients with acute migraine with aura (MwA). Interpretation of visual venous asymmetry (VVA) between brain hemispheres on SWI may help support the clinical diagnosis of MwA. Our goal was to develop an automated algorithm for segmentation and quantification of cerebral veins using SWI.

Materials and methods

Expert readers visually evaluated SWI of patients with acute MwA for VVA. Subsequently a fully automated algorithm based on 3D normalization and 2D imaging processing using SPM and MATLAB image processing software including top-hat transform was used to quantify cerebral veins and to calculate volumetric differences between hemispheres.

Results

Fifty patients with MwA were examined with SWI. VVA was present in 20 of 50 patients (40%). In 95% of patients with VVA, the fully automated calculation agreed with the side that visually harboured more PFV. Our algorithm showed a sensitivity of 95%, specificity of 90% and accuracy of 92% for detecting VVA. Patients with VVA had significantly larger vein volume on the hemisphere with more PFV compared to patients without (15.90 ± 5.38 ml vs 11.93 ± 5.31 ml; p = 0.013). The mean difference in venous volume between hemispheres in patients with VVA was larger compared to patients without VVA (16.34 ± 7.76% vs 4.31 ± 3.26% p < 1E-10). The average time between aura onset and SWI correlated negatively with venous volume of the dominant brain hemisphere (r = -0.348; p = 0.038).

Conclusion

A fully automated algorithm can accurately identify and quantify cerebral venous distribution on SWI. Absolute quantification may be useful for the future assessment of patients with suspected diseases, which may be associated with a unilateral abnormal degree of venous oxygenation.

Data-Driven Quantitative Susceptibility Mapping Using Loss Adaptive Dipole Inversion (LADI)

BACKGROUND

Quantitative susceptibility mapping (QSM) uses prior information to reconstruct maps, but prior information may not show pathology and introduce inconsistencies with susceptibility maps, degrade image quality and inadvertently smoothing image features.

PURPOSE

To develop a local field data-driven QSM reconstruction that does not depend on spatial edge prior information.

STUDY TYPE

Retrospective.

SUBJECTS, ANIMAL MODELS

A dataset from 2016 ISMRM QSM Challenge, 11 patients with glioblastoma, a patient with microbleeds and porcine heart.

SEQUENCE/FIELD STRENGTH

3D gradient echo sequence on 3T and 7T scanners.

ASSESSMENT

Accuracy was compared to Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS), and several published techniques using region of interest (ROI) measurements, root-mean-squared error (RMSE), structural similarity index metric (SSIM), and high-frequency error norm (HFEN). Numerical ranking and semiquantitative image grading was performed by three expert observers to assess overall image quality (IQ) and image sharpness (IS).

STATISTICAL TESTS

Bland-Altman, Friedman test, and Conover multiple comparisons.

RESULTS

Loss adaptive dipole inversion (LADI) (β = 0.82, R² = 0.96), morphology-enabled dipole inversion (MEDI) (β = 0.91, R² = 0.97), and fast nonlinear susceptibility inversion (FANSI) (β = 0.81, R² = 0.98) had excellent correlation with COSMOS and no bias was detected (bias = 0.006 ± 0.014, P < 0.05). In glioblastoma patients, LADI showed consistently better performance (IQ_Grade = 2.6 ± 0.4, IS_Grade = 2.6 ± 0.3, IQ_Rank = 3.5 ± 0.4, IS_Rank = 3.9 ± 0.2) compared with MEDI (IQ_Grade = 2.1 ± 0.3, IS_Grade = 2 ± 0.5, IQ_Rank = 2.4 ± 0.5, IS_Rank = 2.8 ± 0.2) and FANSI (IQ_Grade = 2.2 ± 0.5, IS_Grade = 2 ± 0.4, IQ_Rank = 2.8 ± 0.3, IS_Rank = 2.1 ± 0.2). Dark artifact visible near the infarcted region in MEDI (Inf_MEDI = -0.27 ± 0.06 ppm) was better mitigated by FANSI (Inf_FANSI-TGV = -0.17 ± 0.05 ppm) and LADI (Inf_LADI = -0.18 ± 0.05 ppm).

CONCLUSION

For neuroimaging applications, LADI preserved image sharpness and fine features in glioblastoma and microbleed patients. LADI performed better at mitigating artifacts in cardiac QSM.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;52:823-835.

Elevated brain oxygen extraction fraction measured by MRI susceptibility relates to perfusion status in acute ischemic stroke

Recent clinical trials of new revascularization therapies in acute ischemic stroke have highlighted the importance of physiological imaging to identify optimal treatments for patients. Oxygen extraction fraction (OEF) is a hallmark of at-risk tissue in stroke, and can be quantified from the susceptibility effect of deoxyhemoglobin molecules in venous blood on MRI phase scans. We measured OEF within cerebral veins using advanced quantitative susceptibility mapping (QSM) MRI reconstructions in 20 acute stroke patients. Absolute OEF was elevated in the affected (29.3 ± 3.4%) versus the contralateral hemisphere (25.5 ± 3.1%) of patients with large diffusion-perfusion lesion mismatch (P = 0.032). In these patients, OEF negatively correlated with relative CBF measured by dynamic susceptibility contrast MRI (P = 0.004), suggesting compensation for reduced flow. Patients with perfusion-diffusion match or no hypo-perfusion showed less OEF difference between hemispheres. Nine patients received longitudinal assessment and showed OEF ratio (affected to contralateral) of 1.2 ± 0.1 at baseline that normalized (decreased) to 1.0 ± 0.1 at follow-up three days later (P = 0.03). Our feasibility study demonstrates that QSM MRI can non-invasively quantify OEF in stroke patients, relates to perfusion status, and is sensitive to OEF changes over time. Clinical trial registration: Longitudinal MRI examinations of patients with brain ischemia and blood brain barrier permeability; clinicaltrials.org :NCT02077582.

Seven-tesla susceptibility-weighted analysis of hippocampal venous structures: Application to magnetic-resonance-normal focal epilepsy

OBJECTIVE

Vascular structures may play a significant role in epileptic pathology. Although previous attempts to characterize vasculature relative to epileptogenic zones and hippocampal sclerosis have been inconsistent, an in vivo method of analysis would assist in resolving these inconsistencies and facilitate a comparison against healthy controls in a human model. Magnetic resonance imaging is a noninvasive technique that provides excellent soft tissue contrast, and the relatively recent development of susceptibility-weighted imaging has dramatically improved the visibility of small veins.

METHODS

We built and tested a Hessian-based segmentation technique, which takes advantage of the increased signal and contrast available at 7 T to detect venous structures in vivo. We investigate the ability of this technique to quantify vessels in the brain and apply it to an asymmetry analysis of vessel density in the hippocampus in patients with mesial temporal lobe epilepsy (MTLE) and neocortical epilepsy.

RESULTS

Vessel density was highly symmetric in the hippocampus in controls (mean asymmetry = 0.080 ± 0.076, median = 0.05027), whereas average vessel density asymmetry was greater in neocortical (mean asymmetry = 0.23 ± 0.17, median = 0.14) and MTLE (mean asymmetry = 0.37 ± 0.46, median = 0.26) patients, with the decrease in vessel density ipsilateral to the suspected seizure onset zone. Post hoc testing with one-way analysis of variance and Tukey post hoc test indicated significant differences in the group means (P < .02) between MTLE and the control group only.

SIGNIFICANCE

Asymmetry in vessel density in the hippocampus is visible in patients with MTLE, even when qualitative and quantitative measures of hippocampal asymmetry show little volumetric difference between epilepsy patients and healthy controls.

High resolution atlas of the venous brain vasculature from 7 T quantitative susceptibility maps

The vascular organization of the human brain can determine neurological and neurophysiological functions, yet thus far it has not been comprehensively mapped. Aging and diseases such as dementia are known to be associated with changes to the vasculature and normative data could help detect these vascular changes in neuroimaging studies. Furthermore, given the well-known impact of venous vessels on the blood oxygen level dependent (BOLD) signal, information about the common location of veins could help detect biases in existing datasets. In this work, a quantitative atlas of the venous vasculature using quantitative susceptibility maps (QSM) acquired with a 0.6-mm isotropic resolution is presented. The Venous Neuroanatomy (VENAT) atlas was created from 5 repeated 7 Tesla MRI measurements in young and healthy volunteers (n = 20, 10 females, mean age = 25.1 ± 2.5 years) using a two-step registration method on 3D segmentations of the venous vasculature. This cerebral vein atlas includes the average vessel location, diameter (mean: 0.84 ± 0.33 mm) and curvature (0.11 ± 0.05 mm^-1) from all participants and provides an in vivo measure of the angio-architectonic organization of the human brain and its variability. This atlas can be used as a basis to understand changes in the vasculature during aging and neurodegeneration, as well as vascular and physiological effects in neuroimaging.

A critical assessment of data quality and venous effects in sub-millimeter fMRI

Advances in hardware, pulse sequences, and reconstruction techniques have made it possible to perform functional magnetic resonance imaging (fMRI) at sub-millimeter resolution while maintaining high spatial coverage and acceptable signal-to-noise ratio. Here, we examine whether sub-millimeter fMRI can be used as a routine method for obtaining accurate measurements of fine-scale local neural activity. We conducted fMRI in human visual cortex during a simple event-related visual experiment (7 T, gradient-echo EPI, 0.8-mm isotropic voxels, 2.2-s sampling rate, 84 slices), and developed analysis and visualization tools to assess the quality of the data. Our results fall along three lines of inquiry. First, we find that the acquired fMRI images, combined with appropriate surface-based processing, provide reliable and accurate measurements of fine-scale blood oxygenation level dependent (BOLD) activity patterns. Second, we show that the highly folded structure of cortex causes substantial biases on spatial resolution and data visualization. Third, we examine the well-recognized issue of venous contributions to fMRI signals. In a systematic assessment of large sections of cortex measured at a fine scale, we show that time-averaged T2*-weighted EPI intensity is a simple, robust marker of venous effects. These venous effects are unevenly distributed across cortex, are more pronounced in gyri and outer cortical depths, and are, to a certain degree, in consistent locations across subjects relative to cortical folding. Furthermore, we show that these venous effects are strongly correlated with BOLD responses evoked by the experiment. We conclude that sub-millimeter fMRI can provide robust information about fine-scale BOLD activity patterns, but special care must be exercised in visualizing and interpreting these patterns, especially with regards to the confounding influence of the brain's vasculature. To help translate these methodological findings to neuroscience research, we provide practical suggestions for both high-resolution and standard-resolution fMRI studies.

Inference of Cerebrovascular Topology With Geodesic Minimum Spanning Trees

A vectorial representation of the vascular network that embodies quantitative features-location, direction, scale, and bifurcations-has many potential cardio- and neuro-vascular applications. We present VTrails, an end-to-end approach to extract geodesic vascular minimum spanning trees from angiographic data by solving a connectivity-optimized anisotropic level-set over a voxel-wise tensor field representing the orientation of the underlying vasculature. Evaluating real and synthetic vascular images, we compare VTrails against the state-of-the-art ridge detectors for tubular structures by assessing the connectedness of the vesselness map and inspecting the synthesized tensor field. The inferred geodesic trees are then quantitatively evaluated within a topologically aware framework, by comparing the proposed method against popular vascular segmentation tool kits on clinical angiographies. VTrails potentials are discussed towards integrating groupwise vascular image analyses. The performance of VTrails demonstrates its versatility and usefulness also for patient-specific applications in interventional neuroradiology and vascular surgery.

The morphology of the human cerebrovascular system

While several methodologies exist for quantifying gray and white matter properties in humans, relatively little is known regarding the spatial organization and the intersubject variability of cerebral vessels. To resolve this, we developed a fast, open-source processing algorithm using advanced vessel segmentation schemes and iterative nonlinear registration to isolate, extract, and quantify cerebral vessels in susceptibility weighting imaging (SWI) and time-of-flight angiography (TOF-MRA) datasets acquired in a large cohort (n = 42) of healthy individuals. From this, whole-brain venous and arterial probabilistic maps were generated along with the computation of regional densities and diameters within regions based on popular anatomical and functional atlases. The results show that cerebral vasculature is highly heterogeneous, displaying disproportionally large vessel densities in brain areas such as the anterior and posterior cingulate, cuneus, precuneus, parahippocampus, insula, and temporal gyri. On average, venous densities were slightly higher and less variable across subjects than arterial. Moreover, regional variations in both venous and arterial density were significantly correlated to cortical thickness (R = 0.42). This publicly available new atlas of the human cerebrovascular system provides a first step toward quantifying morphological changes in the diseased brain and serving as a potential regression tool in fMRI analysis.