A quantitative analysis of the benefits of cardiac gating in practical diffusion tensor imaging of the brain

DTI-MR fingerprinting for rapid high-resolution whole-brain T1 , T2 , proton density, ADC, and fractional anisotropy mapping

PURPOSE

This study aims to develop a high-efficiency and high-resolution 3D imaging approach for simultaneous mapping of multiple key tissue parameters for routine brain imaging, including T1 , T2 , proton density (PD), ADC, and fractional anisotropy (FA). The proposed method is intended for pushing routine clinical brain imaging from weighted imaging to quantitative imaging and can also be particularly useful for diffusion-relaxometry studies, which typically suffer from lengthy acquisition time.

METHODS

To address challenges associated with diffusion weighting, such as shot-to-shot phase variation and low SNR, we integrated several innovative data acquisition and reconstruction techniques. Specifically, we used M1-compensated diffusion gradients, cardiac gating, and navigators to mitigate phase variations caused by cardiac motion. We also introduced a data-driven pre-pulse gradient to cancel out eddy currents induced by diffusion gradients. Additionally, to enhance image quality within a limited acquisition time, we proposed a data-sharing joint reconstruction approach coupled with a corresponding sequence design.

RESULTS

The phantom and in vivo studies indicated that the T1 and T2 values measured by the proposed method are consistent with a conventional MR fingerprinting sequence and the diffusion results (including diffusivity, ADC, and FA) are consistent with the spin-echo EPI DWI sequence.

CONCLUSION

The proposed method can achieve whole-brain T1 , T2 , diffusivity, ADC, and FA maps at 1-mm isotropic resolution within 10 min, providing a powerful tool for investigating the microstructural properties of brain tissue, with potential applications in clinical and research settings.

Assessing pulsatile waveforms of paravascular cerebrospinal fluid dynamics using dynamic diffusion-weighted imaging (dDWI)

Cerebrospinal fluid (CSF) in the paravascular spaces of the surface arteries (sPVS) is a vital pathway in brain waste clearance. Arterial pulsations may be the driving force of the paravascular flow, but its pulsatile pattern remains poorly characterized, and no clinically practical method for measuring its dynamics in the human brain is available. In this work, we introduce an imaging and quantification framework for in-vivo non-invasive assessment of pulsatile fluid dynamics in the sPVS. It used dynamic Diffusion-Weighted Imaging (dDWI) at a lower b-values of 150s/mm² and retrospective gating to detect the slow flow of CSF while suppressing the fast flow of adjacent arterial blood. The waveform of CSF flow over a cardiac cycle was revealed by synchronizing the measurements with the heartbeat. A data-driven approach was developed to identify sPVS and allow automatic quantification of the whole-brain fluid waveforms. We applied dDWI to twenty-five participants aged 18–82 y/o. Results demonstrated that the fluid waveforms across the brain showed an explicit cardiac-cycle dependency, in good agreement with the vascular pumping hypothesis. Furthermore, the shape of the CSF waveforms closely resembled the pressure waveforms of the artery wall, suggesting that CSF dynamics is tightly related to artery wall mechanics. Finally, the CSF waveforms in aging participants revealed a strong age effect, with a significantly wider systolic peak observed in the older relative to younger participants. The peak widening may be associated with compromised vascular compliance and vessel wall stiffening in the older brain. Overall, the results demonstrate the feasibility, reproducibility, and sensitivity of dDWI for detecting sPVS fluid dynamics of the human brain. Our preliminary data suggest age-related alterations of the paravascular pumping. With an acquisition time of under six minutes, dDWI can be readily applied to study fluid dynamics in normal physiological conditions and cerebrovascular/neurodegenerative diseases.

Diffusion Kurtosis Imaging Fiber Tractography of Major White Matter Tracts in Neurosurgery

Diffusion tensor imaging (DTI)-based fiber tractography is routinely used in clinical applications to visualize major white matter tracts, such as the corticospinal tract (CST), optic radiation (OR), and arcuate fascicle (AF). Nevertheless, DTI is limited due to its capability of resolving intra-voxel multi-fiber populations. Sophisticated models often require long acquisition times not applicable in clinical practice. Diffusion kurtosis imaging (DKI), as an extension of DTI, combines sophisticated modeling of the diffusion process with short acquisition times but has rarely been investigated in fiber tractography. In this study, DTI- and DKI-based fiber tractography of the CST, OR, and AF was investigated in healthy volunteers and glioma patients. For the CST, significantly larger tract volumes were seen in DKI-based fiber tractography. Similar results were obtained for the OR, except for the right OR in patients. In the case of the AF, results of both models were comparable with DTI-based fiber tractography showing even significantly larger tract volumes in patients. In the case of the CST and OR, DKI-based fiber tractography contributes to advanced visualization under clinical time constraints, whereas for the AF, other models should be considered.

Gradient waveform design for tensor-valued encoding in diffusion MRI

Diffusion encoding along multiple spatial directions per signal acquisition can be described in terms of a b-tensor. The benefit of tensor-valued diffusion encoding is that it unlocks the 'shape of the b-tensor' as a new encoding dimension. By modulating the b-tensor shape, we can control the sensitivity to microscopic diffusion anisotropy which can be used as a contrast mechanism; a feature that is inaccessible by conventional diffusion encoding. Since imaging methods based on tensor-valued diffusion encoding are finding an increasing number of applications we are prompted to highlight the challenge of designing the optimal gradient waveforms for any given application. In this review, we first establish the basic design objectives in creating field gradient waveforms for tensor-valued diffusion MRI. We also survey additional design considerations related to limitations imposed by hardware and physiology, potential confounding effects that cannot be captured by the b-tensor, and artifacts related to the diffusion encoding waveform. Throughout, we discuss the expected compromises and tradeoffs with an aim to establish a more complete understanding of gradient waveform design and its impact on accurate measurements and interpretations of data.

Motion-compensated gradient waveforms for tensor-valued diffusion encoding by constrained numerical optimization

PURPOSE

Diffusion-weighted MRI is sensitive to incoherent tissue motion, which may confound the measured signal and subsequent analysis. We propose a "motion-compensated" gradient waveform design for tensor-valued diffusion encoding that negates the effects bulk motion and incoherent motion in the ballistic regime.

METHODS

Motion compensation was achieved by constraining the magnitude of gradient waveform moment vectors. The constraint was incorporated into a numerical optimization framework, along with existing constraints that account for b-tensor shape, hardware restrictions, and concomitant field gradients. We evaluated the efficacy of encoding and motion compensation in simulations, and we demonstrated the approach by linear and planar b-tensor encoding in a healthy heart in vivo.

RESULTS

The optimization framework produced asymmetric motion-compensated waveforms that yielded b-tensors of arbitrary shape with improved efficiency compared with previous designs for tensor-valued encoding, and equivalent efficiency to previous designs for linear (conventional) encoding. Technical feasibility was demonstrated in the heart in vivo, showing vastly improved data quality when using motion compensation. The optimization framework is available online in open source.

CONCLUSION

Our gradient waveform design is both more flexible and efficient than previous methods, facilitating tensor-valued diffusion encoding in tissues in which motion would otherwise confound the signal. The proposed design exploits asymmetric encoding times, a single refocusing pulse or multiple refocusing pulses, and integrates compensation for concomitant gradient effects throughout the imaging volume.

Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models

Purpose

Diffusion-weighted imaging (DWI) plays an important role in the preoperative assessment of gliomas; however, the diagnostic performance of histogram-derived parameters from mono-, bi-, and stretched-exponential DWI models in the grading of gliomas has not been fully investigated. Therefore, we compared these models’ ability to differentiate between high-grade and low-grade gliomas.

Methods

This retrospective study included 22 patients with diffuse gliomas (age, 23–74 years; 12 males; 11 high-grade and 11 low-grade gliomas) who underwent preoperative 3 T-magnetic resonance imaging from October 2014 to August 2019. The apparent diffusion coefficient was calculated from the mono-exponential model. Using 13 b-values, the true-diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction were obtained from the bi-exponential model, and the distributed-diffusion coefficient and heterogeneity index were obtained from the stretched-exponential model. Region-of-interests were drawn on each imaging parameter map for subsequent histogram analyses.

Results

The skewness of the apparent diffusion, true-diffusion, and distributed-diffusion coefficients was significantly higher in high-grade than in low-grade gliomas (0.67 ± 0.67 vs. − 0.18 ± 0.63, 0.68 ± 0.74 vs. − 0.08 ± 0.66, 0.63 ± 0.72 vs. − 0.15 ± 0.73; P = 0.0066, 0.0192, and 0.0128, respectively). The 10th percentile of the heterogeneity index was significantly lower (0.77 ± 0.08 vs. 0.88 ± 0.04; P = 0.0004), and the 90th percentile of the perfusion fraction was significantly higher (12.64 ± 3.44 vs. 7.14 ± 1.70%: P < 0.0001), in high-grade than in low-grade gliomas. The combination of the 10th percentile of the true-diffusion coefficient and 90th percentile of the perfusion fraction showed the best area under the receiver operating characteristic curve (0.96).

Conclusion

The bi-exponential model exhibited the best diagnostic performance for differentiating high-grade from low-grade gliomas.

Electronic supplementary material

The online version of this article (10.1007/s00234-020-02456-2) contains supplementary material, which is available to authorized users.

Intravoxel Incoherent Motion MR Imaging of Pediatric Intracranial Tumors: Correlation with Histology and Diagnostic Utility

BACKGROUND AND PURPOSE

Intravoxel incoherent motion imaging, which simultaneously measures diffusion and perfusion parameters, is promising for brain tumor grading. However, intravoxel incoherent motion imaging has not been tested in children. The purpose of this study was to evaluate the correlation between intravoxel incoherent motion parameters and histology to assess the accuracy of intravoxel incoherent motion imaging for pediatric intracranial tumor grading.

MATERIALS AND METHODS

Between April 2013 and September 2015, 17 children (11 boys, 6 girls; 2 months to 15 years of age) with intracranial tumors were included in this retrospective study. Intravoxel incoherent motion parameters were fitted using 13 b-values for a biexponential model. The perfusion-free diffusion coefficient, pseudodiffusion coefficient, and perfusion fraction were measured in high- and low-grade tumors. These intravoxel incoherent motion parameters and the ADC were compared using the unpaired t test. The correlations between the intravoxel incoherent motion parameters and microvessel density or the MIB-1 index were analyzed using the Spearman correlation test. Receiver operating characteristic analysis was used to evaluate diagnostic performance.

RESULTS

The perfusion-free diffusion coefficient and ADC were lower in high-grade than in low-grade tumors (perfusion-free diffusion coefficient, 0.85 ± 0.40 versus 1.53 ± 0.21 × 10^-3 mm²/s, P < .001; ADC, 1.04 ± 0.33 versus 1.60 ± 0.21 × 10^-3 mm²/s, P < .001). The pseudodiffusion coefficient showed no difference between the groups. The perfusion fraction was higher in high-grade than in low-grade tumors (21.7 ± 8.2% versus 7.6 ± 4.3%, P < .001). Receiver operating characteristic analysis found that the combined perfusion-free diffusion coefficient and perfusion fraction had the best diagnostic performance for tumor differentiation (area under the curve = 0.986).

CONCLUSIONS

Intravoxel incoherent motion imaging reflects tumor histology and may be a helpful, noninvasive method for pediatric intracranial tumor grading.

Fiber tractography of the optic radiations: impact of diffusion model, voxel shape and orientation

BACKGROUND

Reliable visualization of the optic radiations (OR) is of major importance in tumor surgery close to the OR to prevent permanent visual field deficits. Diffusion tensor imaging (DTI) based fiber tractography (FT) has become a standard tool to visualize major white matter tracts and to support the prevention of postoperative deficits. Nevertheless, FT of the OR is notoriously challenging due to its high neuroanatomical complexity.

METHODS

To improve FT of the OR we analyzed the effect of a more complex diffusion model and the effect of different voxel shapes and orientations. MRI data of 21 healthy subjects was acquired using isometric and anisometric voxel sizes and standard and adapted slice angulation. FT was performed using the DTI based approach and an orientation distribution function (ODF) based approach. Results were visually inspected, and fiber tract volumes were compared.

RESULTS

DTI based FT led to poor results, failing to reconstruct plausible tracts at all in up to 26.11 % of all cases. The ODF based approach resulted in more compound and solid tracts showing also significantly larger tract volumes. Voxel shape or orientation did not influence DTI but ODF based FT. Isometric or anisometric voxels with standard slice orientation revealed highest tract volumes. Adapted orientation in combination with anisometric voxels led to significantly smaller tract volumes.

CONCLUSIONS

Plausible tractography of the OR can be achieved using ODF based fiber tracking within a clinically feasible timeframe. Voxel shape and orientation seem to be of minor importance and might be kept to isometric voxel for flexible application of FT.

Tractography-based classification in distinguishing patients with first-episode schizophrenia from healthy individuals

BACKGROUND

Schizophrenia has been characterized as a neurodevelopmental disorder of brain disconnectivity. However, whether disrupted integrity of white matter tracts in schizophrenia can potentially serve as individual discriminative biomarkers remains unclear.

METHODS

A random forest algorithm was applied to tractography-based diffusion properties obtained from a cohort of 65 patients with first-episode schizophrenia (FES) and 60 healthy individuals to investigate the machine-learning discriminative power of white matter disconnectivity. Recursive feature elimination was used to select the ultimate white matter features in the classification. Relationships between algorithm-predicted probabilities and clinical characteristics were also examined in the FES group.

RESULTS

The classifier was trained by 80% of the sample. Patients were distinguished from healthy individuals with an overall accuracy of 71.0% (95% confident interval: 61.1%, 79.6%), a sensitivity of 67.3%, a specificity of 75.0%, and the area under receiver operating characteristic curve (AUC) was 79.3% (χ2 p < 0.001). In validation using the held-up 20% of the sample, patients were distinguished from healthy individuals with an overall accuracy of 76.0% (95% confident interval: 54.9%, 90.6%), a sensitivity of 76.9%, a specificity of 75.0%, and an AUC of 73.1% (χ2 p = 0.012). Diffusion properties of inter-hemispheric fibres, the cerebello-thalamo-cortical circuits and the long association fibres were identified to be the most discriminative in the classification. Higher predicted probability scores were found in younger patients.

CONCLUSIONS

Our findings suggest that the widespread connectivity disruption observed in FES patients, especially in younger patients, might be considered potential individual discriminating biomarkers.

Increased posterior default mode network activity and structural connectivity in young adult APOE-ε4 carriers: a multimodal imaging investigation

Young adult APOE-ε4 carriers show increased activity in posterior regions of the default mode network (pDMN), but how this is related to structural connectivity is unknown. Thirty young adults (one half of whom were APOE-ε4 carriers; mean age 20 years) were scanned using both diffusion and functional magnetic resonance imaging. The parahippocampal cingulum bundle (PHCB)-which links the pDMN and the medial temporal lobe-was manually delineated in individual participants using deterministic tractography. Measures of tract microstructure (mean diffusivity and fractional anisotropy) were then extracted from these tract delineations. APOE-ε4 carriers had lower mean diffusivity and higher fractional anisotropy relative to noncarriers in PHCB, but not in a control tract (the inferior longitudinal fasciculus). Furthermore, PHCB microstructure was selectively associated with pDMN (and medial temporal lobe) activity during a scene discrimination task known to be sensitive to Alzheimer's disease. These findings are consistent with a lifespan view of Alzheimer's disease risk, where early-life, connectivity-related changes in specific, vulnerable "hubs" (e.g., pDMN) lead to increased neural activity. Critically, such changes may reflect reduced network efficiency/flexibility in APOE-ε4 carriers, which in itself may portend a faster decline in connectivity over the lifespan and ultimately trigger early amyloid-β deposition in later life.

The effect of pulsatile motion and cardiac-gating on reconstruction and diffusion tensor properties of the corticospinal tract

Pulsatile motion occurs in the cardiac systolic period and leads to significantly larger displacement of water molecules as it is observed during diffusion weighted image acquisition. Obvious pulsatile motion arises in the brain stem and basal ganglia and might affect the corticospinal tract. So far there is no consensus on the real effect of pulsatile motion on diffusion properties, diffusion tensor parameters and fiber tractography and on the role of cardiac-gating to overcome these effects. The present study aimed at detecting effects of pulsatile motion on imaging properties and reconstruction of the corticospinal tract. Non-gated and cardiac-gated data of 22 healthy subjects was acquired using clinical standard protocols and analysed with regard to effects on signal intensities, diffusion tensor properties and tractography results concerning the corticospinal tract. Analyses resulted in obvious effects of pulsatile motion on signal intensities, especially alterations in diffusion tensor properties, compensated by the application of cardiac-gating, whereas no effect on fiber tract volume was seen. Therefore, pulsatile motion and cardiac-gating should be kept in mind as critical aspects when analysing and interpreting diffusion tensor properties within the human brain, but are of minor interest when considering fiber tractography of the corticospinal tract.

Connectivity-based segmentation of the brainstem by probabilistic tractography

Diffusion magnetic resonance imaging is a non-invasive tool increasingly used for the investigation of brain connectivity in vivo. In this paper we propose a method that allows segmentation of the brainstem to four subregions (frontopontine, motor, sensory and reticular) based on connections to supratentorial structures, thereby eliminating the need for using anatomical landmarks within the brainstem for the identification of these subregions. The feasibility of connectivity-based brainstem segmentation was investigated in a group of healthy subjects (n = 20). Multifiber probabilistic tractography was performed using the FMRIB Software Library, and connections between a pontomesencephalic seed mask and four supratentorial target regions (anterior and posterior limbs of the internal capsule, sensory and medial thalamus) were used to determine connectivity maps of the brainstem. Results were compared with a neuroanatomy atlas and histological sections, confirming good anatomic correspondence. The four subregions detected by the connectivity-based segmentation showed good intersubject reproducibility. The presented method may be a potential tool to investigate brainstem connectivity in diseases that distort normal anatomy, and quantitative analyses of the diffusion-related parameters may provide additional information on the involvement of brainstem pathways in certain disease states (e.g., traumatic brain injury, demyelinating disorders, brainstem tumors). The potential clinical applicability of the method is demonstrated in two cases of severe traumatic brain injury.

Fornix Under Water? Ventricular Enlargement Biases Forniceal Diffusion Magnetic Resonance Imaging Indices in Anorexia Nervosa

BACKGROUND

Acute anorexia nervosa (AN) is characterized by reduced brain mass and corresponding increased sulcal and ventricular cerebrospinal fluid. Recent studies of white matter using diffusion tensor imaging consistently identified alterations in the fornix, such as reduced fractional anisotropy (FA). However, because the fornix penetrates the ventricles, it is prone to cerebrospinal fluid-induced partial volume effects that interfere with a valid assessment of FA. We investigated the hypothesis that in the acute stage of AN, FA of the fornix is markedly affected by ventricular volumes.

METHODS

First, using diffusion tensor imaging data we established the inverse associations between forniceal FA and volumes of the third and lateral ventricles in a prestudy with 32 healthy subjects to demonstrate the strength of ventricular influence on forniceal FA independent of AN. Second, we investigated a sample of 25 acute AN patients and 25 healthy control subjects.

RESULTS

Using ventricular volumes as covariates markedly reduced the group effect of forniceal FA, even with tract-based spatial statistics focusing only on the center of the fornix. In addition, after correcting for free water on voxel level, the group differences in forniceal FA between AN patients and controls disappeared completely.

CONCLUSIONS

It is unlikely that microstructural changes affecting FA occurred in the fornix of AN patients. Previously identified alterations in acute AN may have been biased by partial volume effects and the proposed central role of this structure in the pathophysiology may need to be reconsidered. Future studies on white matter alterations in AN should carefully deal with partial volume effects.

Effect of respiratory and cardiac gating on the major diffusion-imaging metrics

The effect of respiratory gating on the major diffusion-imaging metrics and that of cardiac gating on mean kurtosis (MK) are not known. For evaluation of whether the major diffusion-imaging metrics-MK, fractional anisotropy (FA), and mean diffusivity (MD) of the brain-varied between gated and non-gated acquisitions, respiratory-gated, cardiac-gated, and non-gated diffusion-imaging of the brain were performed in 10 healthy volunteers. MK, FA, and MD maps were constructed for all acquisitions, and the histograms were constructed. The normalized peak height and location of the histograms were compared among the acquisitions by use of Friedman and post hoc Wilcoxon tests. The effect of the repetition time (TR) on the diffusion-imaging metrics was also tested, and we corrected for its variation among acquisitions, if necessary. The results showed a shift in the peak location of the MK and MD histograms to the right with an increase in TR (p ≤ 0.01). The corrected peak location of the MK histograms, the normalized peak height of the FA histograms, the normalized peak height and the corrected peak location of the MD histograms varied significantly between the gated and non-gated acquisitions (p < 0.05). These results imply an influence of respiration and cardiac pulsation on the major diffusion-imaging metrics. The gating conditions must be kept identical if reproducible results are to be achieved.

Diurnal microstructural variations in healthy adult brain revealed by diffusion tensor imaging

Biorhythm is a fundamental property of human physiology. Changes in the extracellular space induced by cell swelling in response to the neural activity enable the in vivo characterization of cerebral microstructure by measuring the water diffusivity using diffusion tensor imaging (DTI). To study the diurnal microstructural alterations of human brain, fifteen right-handed healthy adult subjects were recruited for DTI studies in two repeated sessions (8∶30 AM and 8∶30 PM) within a 24-hour interval. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial (λ_//) and radial diffusivity (λ_⊥) were compared pixel by pixel between the sessions for each subject. Significant increased morning measurements in FA, ADC, λ_// and λ_⊥ were seen in a wide range of brain areas involving frontal, parietal, temporal and occipital lobes. Prominent evening dominant λ_⊥ (18.58%) was detected in the right inferior temporal and ventral fusiform gyri. AM-PM variation of λ_⊥ was substantially left side hemisphere dominant (p<0.05), while no hemispheric preference was observed for the same analysis for ADC (p = 0.77), λ_// (p = 0.08) or FA (p = 0.25). The percentage change of ADC, λ_//, λ_⊥, and FA were 1.59%, 2.15%, 1.20% and 2.84%, respectively, for brain areas without diurnal diffusivity contrast. Microstructural variations may function as the substrates of the phasic neural activities in correspondence to the environment adaptation in a light-dark cycle. This research provided a baseline for researches in neuroscience, sleep medicine, psychological and psychiatric disorders, and necessitates that diurnal effect should be taken into account in following up studies using diffusion tensor quantities.

Image corruption detection in diffusion tensor imaging for post-processing and real-time monitoring

Due to the high sensitivity of diffusion tensor imaging (DTI) to physiological motion, clinical DTI scans often suffer a significant amount of artifacts. Tensor-fitting-based, post-processing outlier rejection is often used to reduce the influence of motion artifacts. Although it is an effective approach, when there are multiple corrupted data, this method may no longer correctly identify and reject the corrupted data. In this paper, we introduce a new criterion called "corrected Inter-Slice Intensity Discontinuity" (cISID) to detect motion-induced artifacts. We compared the performance of algorithms using cISID and other existing methods with regard to artifact detection. The experimental results show that the integration of cISID into fitting-based methods significantly improves the retrospective detection performance at post-processing analysis. The performance of the cISID criterion, if used alone, was inferior to the fitting-based methods, but cISID could effectively identify severely corrupted images with a rapid calculation time. In the second part of this paper, an outlier rejection scheme was implemented on a scanner for real-time monitoring of image quality and reacquisition of the corrupted data. The real-time monitoring, based on cISID and followed by post-processing, fitting-based outlier rejection, could provide a robust environment for routine DTI studies.

White matter alterations in antipsychotic- and mood stabilizer-naïve individuals with bipolar II/NOS disorder

Structural magnetic resonance imaging (MRI) studies using voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) have been inconsistent in demonstrating impairments in gray matter (GM) and white matter (WM) structures in bipolar disorder (BD). This may be a consequence of significant confounding effects of medication, illness history and selection of controls in existing studies. Study of bipolar II or not-otherwise-specified (BD II/NOS) disorder provides a solution to these confounds and a bridge to unipolar cases across the affective spectrum. Thirty-eight euthymic, antipsychotic- and mood stabilizer-naïve young adults (mean age = 20.9 years) with BD II/NOS and 37 age-, cognitive ability- and gender-matched healthy controls (HCs) underwent MRI. Voxel-wise and regional gray matter volume comparisons were conducted using voxel-based morphometry (VBM). Tract-based spatial statistics (TBSS) were used to assess whole-brain WM, as indexed using fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusion values. No between-group differences were observed for whole-brain VBM comparisons. By contrast, in comparison to HCs, participants with BD II/NOS had significant widespread reductions in FA and increased MD and perpendicular diffusion values in virtually all the major cortical white matter tracts. These data suggest pathophysiological involvement of WM microstructures - but not GM macrostructures - in high functioning BD II/NOS patients at an early age and before significant clinical adversity has been recorded. We propose that white matter development is a valid candidate target for understanding genetic and environmental antecedents to bipolar disorder and mood disorder more generally.

Retrospective correction of physiological noise in DTI using an extended tensor model and peripheral measurements

Diffusion tensor imaging is widely used in research and clinical applications, but this modality is highly sensitive to artefacts. We developed an easy-to-implement extension of the original diffusion tensor model to account for physiological noise in diffusion tensor imaging using measures of peripheral physiology (pulse and respiration), the so-called extended tensor model. Within the framework of the extended tensor model two types of regressors, which respectively modeled small (linear) and strong (nonlinear) variations in the diffusion signal, were derived from peripheral measures. We tested the performance of four extended tensor models with different physiological noise regressors on nongated and gated diffusion tensor imaging data, and compared it to an established data-driven robust fitting method. In the brainstem and cerebellum the extended tensor models reduced the noise in the tensor-fit by up to 23% in accordance with previous studies on physiological noise. The extended tensor model addresses both large-amplitude outliers and small-amplitude signal-changes. The framework of the extended tensor model also facilitates further investigation into physiological noise in diffusion tensor imaging. The proposed extended tensor model can be readily combined with other artefact correction methods such as robust fitting and eddy current correction.

Pulse-triggered DTI sequence with reduced FOV and coronal acquisition at 3T for the assessment of the cervical spinal cord in patients with myelitis

BACKGROUND AND PURPOSE

DTI is a promising technique for imaging of the spinal cord, but the technique has susceptibility-induced artifacts. We evaluated a pulse-triggered DTI sequence with an rFOV technique and coronal acquisition for the assessment of the cervical spinal cord in patients with myelitis at 3T.

MATERIALS AND METHODS

A rFOV acquisition was established by a noncoplanar application of the excitation and the refocusing pulse in conjunction with outer volume suppression. The DTI sequence was performed in the coronal plane in 12 healthy volunteers and 40 consecutive patients with myelitis. Probabilistic tractography of the posterior and lateral funiculi was performed from the C1 to C7 levels. FA, MD, aD, rD, and ratios of aD and rD were measured.

RESULTS

In healthy volunteers, mean DTI indices within the whole-fiber pathways were the following: FA = 0.61, MD = 1.17 × 10(-3) mm(2)/s, aD = 1.96 × 10(-3) mm(2)/s, rD = 0.77 × 10(-3) mm(2)/s, and ratios of aD and rD = 2.5. Comparison of healthy controls and patients with myelitis identified statistically significant differences for all DTI parameters. Different patterns of myelitis, including spinal cord atrophy and active inflammatory lesions, were recognized. There was a significant correlation between clinical severity and DTI parameters.

CONCLUSIONS

The present work introduces a new approach for DTI of the cervical spinal cord at 3T, enabling a quantitative follow-up of patients with myelitis.