Quantitative assessment of changes in diffusion tensor imaging (DTI) metrics along the courses of the cortico-ponto-cerebellar tracts secondary to supratentorial human brain glial tumors.

BACKGROUND: The cortico-ponto-cerebellar tract (CPCT) is the largest projection pathway, which synapses at the pons. Remote effects of supratentorial brain tumors have not been evaluated along the infratentorial course of the CPCT. AIM: The purpose of this study is to evaluate the possible lateralization of the diffusion tensor metrics of the affected CPCT in patients with supratentorial brain tumor. METHODS AND RESULTS: We included 39 patients with 29 left-sided tumors (LST) and 10 right-sided tumors, retrospectively. We measured the magnitude of changes of the fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of the CPCT prior to the brain surgery at the level of crus cerebri and middle cerebellar peduncle. Regions of interest (ROIs) were placed on the lateral side of crus cerebri, and ROI-1 (anterior 1/3), ROI-2 (middle 1/3), ROI-3 (posterior 1/3), and ROI-4 were placed at the level of middle cerebellar peduncle. We hypothesized that there would be decreased FA and increased ADC values of the ipsilesional CPCT compared with contralesional CPCT. Ipsilesional FA values were decreased with simultaneous increased ADC value along the CPCT compared with contralesional CPCT in following ROIs, ROI-1 (LST FA: P = .005, ADC: P = .037) and ROI-3 (LST FA: P = .049, ADC: P = .049), respectively. Affected ROI-4 in LST cases also showed lower FA values, although not statistically significant. CONCLUSION: We observed a statistically significant FA value decrease and ADC increase along the left ROI-1 and ROI-3 as well as the nonstatistically significant FA decrease of the left ROI-4 at the second neuron level when there was a related supratentorial tumor. These findings are suggestive of presynaptic and postsynaptic microstructural changes of these tracts following the presynaptic involvement by a primary supratentorial brain tumor.

Quantitative MRI of the spinal cord and brain in adrenomyeloneuropathy: in vivo assessment of structural changes.

Adrenomyeloneuropathy is the late-onset form of X-linked adrenoleukodystrophy, and is considered the most frequent metabolic hereditary spastic paraplegia. In adrenomyeloneuropathy the spinal cord is the main site of pathology. Differently from quantitative magnetic resonance imaging of the brain, little is known about the feasibility and utility of advanced neuroimaging in quantifying the spinal cord abnormalities in hereditary diseases. Moreover, little is known about the subtle pathological changes that can characterize the brain of adrenomyeloneuropathy subjects in the early stages of the disease. We performed a cross-sectional study on 13 patients with adrenomyeloneuropathy and 12 age-matched healthy control subjects who underwent quantitative magnetic resonance imaging to assess the structural changes of the upper spinal cord and brain. Total cord areas from C2-3 to T2-3 level were measured, and diffusion tensor imaging metrics, i.e. fractional anisotropy, mean, axial and radial diffusivity values were calculated in both grey and white matter of spinal cord. In the brain, grey matter regions were parcellated with Freesurfer and average volume and thickness, and mean diffusivity and fractional anisotropy from co-registered diffusion maps were calculated in each region. Brain white matter diffusion tensor imaging metrics were assessed using whole-brain tract-based spatial statistics, and tractography-based analysis on corticospinal tracts. Correlations among clinical, structural and diffusion tensor imaging measures were calculated. In patients total cord area was reduced by 26.3% to 40.2% at all tested levels (P < 0.0001). A mean 16% reduction of spinal cord white matter fractional anisotropy (P ≤ 0.0003) with a concomitant 9.7% axial diffusivity reduction (P < 0.009) and 34.5% radial diffusivity increase (P < 0.009) was observed, suggesting co-presence of axonal degeneration and demyelination. Brain tract-based spatial statistics showed a marked reduction of fractional anisotropy, increase of radial diffusivity (P < 0.001) and no axial diffusivity changes in several white matter tracts, including corticospinal tracts and optic radiations, indicating predominant demyelination. Tractography-based analysis confirmed the results within corticospinal tracts. No significant cortical volume and thickness reduction or grey matter diffusion tensor imaging values alterations were observed in patients. A correlation between radial diffusivity and disease duration along the corticospinal tracts (r = 0.806, P < 0.01) was found. In conclusion, in adrenomyeloneuropathy patients quantitative magnetic resonance imaging-derived measures identify and quantify structural changes in the upper spinal cord and brain which agree with the expected histopathology, and suggest that the disease could be primarily caused by a demyelination rather than a primitive axonal damage. The results of this study may also encourage the employment of quantitative magnetic resonance imaging in other hereditary diseases with spinal cord involvement.

Assessment of the Characteristics of Orientation Distribution Functions in HARDI Using Morphological Metrics.

Orientation distribution functions (ODFs) are widely used to resolve fiber crossing problems in high angular resolution diffusion imaging (HARDI). The characteristics of the ODFs are often assessed using a visual criterion, although the use of objective criteria is also reported, which are directly borrowed from classic signal and image processing theory because they are intuitive and simple to compute. However, they are not always pertinent for the characterization of ODFs. We propose a more general paradigm for assessing the characteristics of ODFs. The idea consists in regarding an ODF as a three-dimensional (3D) point cloud, projecting the 3D point cloud onto an angle-distance map, constructing an angle-distance matrix, and calculating metrics such as length ratio, separability, and uncertainty. The results from both simulated and real data show that the proposed metrics allow for the assessment of the characteristics of ODFs in a quantitative and relatively complete manner.

Quantitative assessment of diffusional kurtosis anisotropy.

Diffusional kurtosis imaging (DKI) measures the diffusion and kurtosis tensors to quantify restricted, non-Gaussian diffusion that occurs in biological tissue. By estimating the kurtosis tensor, DKI accounts for higher order diffusion dynamics, when compared with diffusion tensor imaging (DTI), and consequently can describe more complex diffusion profiles. Here, we compare several measures of diffusional anisotropy which incorporate information from the kurtosis tensor, including kurtosis fractional anisotropy (KFA) and generalized fractional anisotropy (GFA), with the diffusion tensor-derived fractional anisotropy (FA). KFA and GFA demonstrate a net enhancement relative to FA when multiple white matter fiber bundle orientations are present in both simulated and human data. In addition, KFA shows net enhancement in deep brain structures, such as the thalamus and the lenticular nucleus, where FA indicates low anisotropy. Thus, KFA and GFA provide additional information relative to FA with regard to diffusional anisotropy, and may be particularly advantageous for the assessment of diffusion in complex tissue environments.

A comprehensive reliability assessment of quantitative diffusion tensor tractography.

Diffusion tensor tractography is increasingly used to examine structural connectivity in the brain in various conditions, but its test-retest reliability is understudied. The main purposes of this study were to evaluate 1) the reliability of quantitative measurements of diffusion tensor tractography and 2) the effect on reliability of the number of gradient sampling directions and scan repetition. Images were acquired from ten healthy participants. Ten fiber regions of nine major fiber tracts were reconstructed and quantified using six fiber variables. Intra- and inter-session reliabilities were estimated using intraclass correlation coefficient (ICC) and coefficient of variation (CV), and were compared to pinpoint major error sources. Additional pairwise comparisons were made between the reliability of images with 30 directions and NEX 2 (DTI30-2), 30 directions and NEX 1 (DTI30-1), and 15 directions and NEX 2 (DTI15-2) to determine whether increasing gradient directions and scan repetition improved reliability. Of the 60 tractography measurements, 43 showed intersession CV ≤ 10%, ICC ≥ .70, or both for DTI30-2, 40 measurements for DTI30-1, and 37 for DTI15-2. Most of the reliable measurements were associated with the tracts corpus callosum, cingulum, cerebral peduncular fibers, uncinate fasciculus, and arcuate fasciculus. These reliable measurements included factional anisotropy (FA) and mean diffusivity of all 10 fiber regions. Intersession reliability was significantly worse than intra-session reliability for FA, mean length, and tract volume measurements from DTI15-2, indicating that the combination of MRI signal variation and physiological noise/change over time was the major error source for this sequence. Increasing the number of gradient directions from 15 to 30 while controlling the scan time, significantly affected values for all six variables and reduced intersession variability for mean length and tract volume measurements. Additionally, while increasing scan repetition from 1 to 2 had no significant effect on the reliability for DTI with 30 directions, this significantly reduced the upward bias in FA values from all 10 fiber regions and fiber count, mean length, and tract volume measurements from 5 to 7 fiber regions. In conclusion, diffusion tensor tractography provided many measurements with high test-retest reliability across different fiber variables and various fiber tracts even for images with 15 directions (NEX 2). Increasing the number of gradient directions from 15 to 30 with equivalent scan time reduced variability whereas increasing repetition from 1 to 2 for 30-direction DTI improved the accuracy of tractography measurements.

FADTTS: functional analysis of diffusion tensor tract statistics.

The aim of this paper is to present a functional analysis of a diffusion tensor tract statistics (FADTTS) pipeline for delineating the association between multiple diffusion properties along major white matter fiber bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these white matter tract properties in various diffusion tensor imaging studies. The FADTTS integrates five statistical tools: (i) a multivariate varying coefficient model for allowing the varying coefficient functions in terms of arc length to characterize the varying associations between fiber bundle diffusion properties and a set of covariates, (ii) a weighted least squares estimation of the varying coefficient functions, (iii) a functional principal component analysis to delineate the structure of the variability in fiber bundle diffusion properties, (iv) a global test statistic to test hypotheses of interest, and (v) a simultaneous confidence band to quantify the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FADTTS. We apply FADTTS to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment. FADTTS can be used to facilitate the understanding of normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. The advantages of FADTTS compared with the other existing approaches are that they are capable of modeling the structured inter-subject variability, testing the joint effects, and constructing their simultaneous confidence bands. However, FADTTS is not crucial for estimation and reduces to the functional analysis method for the single measure.

Magnetic resonance neurography and diffusion tensor imaging: origins, history, and clinical impact of the first 50,000 cases with an assessment of efficacy and utility in a prospective 5000-patient study group.

OBJECTIVE: Methods were invented that made it possible to image peripheral nerves in the body and to image neural tracts in the brain. The history, physical basis, and dyadic tensor concept underlying the methods are reviewed. Over a 15-year period, these techniques-magnetic resonance neurography (MRN) and diffusion tensor imaging-were deployed in the clinical and research community in more than 2500 published research reports and applied to approximately 50,000 patients. Within this group, approximately 5000 patients having MRN were carefully tracked on a prospective basis. METHODS: A uniform Neurography imaging methodology was applied in the study group, and all images were reviewed and registered by referral source, clinical indication, efficacy of imaging, and quality. Various classes of image findings were identified and subjected to a variety of small targeted prospective outcome studies. Those findings demonstrated to be clinically significant were then tracked in the larger clinical volume data set. RESULTS: MRN demonstrates mechanical distortion of nerves, hyperintensity consistent with nerve irritation, nerve swelling, discontinuity, relations of nerves to masses, and image features revealing distortion of nerves at entrapment points. These findings are often clinically relevant and warrant full consideration in the diagnostic process. They result in specific pathological diagnoses that are comparable to electrodiagnostic testing in clinical efficacy. A review of clinical outcome studies with diffusion tensor imaging also shows convincing utility. CONCLUSION: MRN and diffusion tensor imaging neural tract imaging have been validated as indispensable clinical diagnostic methods that provide reliable anatomic pathological information. There is no alternative diagnostic method in many situations. With the elapsing of 15 years, tens of thousands of imaging studies, and thousands of publications, these methods should no longer be considered experimental.