Publications by Year: 2015

One key pitfall in diffusion magnetic resonance imaging (dMRI) clinical neuroimaging research is the challenge of understanding and interpreting the results of a complex analysis pipeline. The sophisticated algorithms employed by the analysis software, combined with the relatively non-specific nature of many diffusion measurements, lead to challenges in interpretation of the results. This paper is aimed at an intended audience of clinical researchers who are learning about dMRI or trying to interpret dMRI results, and who may be wondering "Does dMRI tell us anything about the white matter?" We present a critical review of dMRI methods and measures used in clinical neuroimaging research, focusing on the most commonly used analysis methods and the most commonly reported measures. We describe important pitfalls in every section, and provide extensive references for the reader interested in more detail.

The anisotropy of water diffusion in brain tissue is affected by both disease and development. This change can be detected using diffusion MRI and is often quantified by the fractional anisotropy (FA) derived from diffusion tensor imaging (DTI). Although FA is sensitive to anisotropic cell structures, such as axons, it is also sensitive to their orientation dispersion. This is a major limitation to the use of FA as a biomarker for "tissue integrity", especially in regions of complex microarchitecture. In this work, we seek to circumvent this limitation by disentangling the effects of microscopic diffusion anisotropy from the orientation dispersion. The microscopic fractional anisotropy (μFA) and the order parameter (OP) were calculated from the contrast between signal prepared with directional and isotropic diffusion encoding, where the latter was achieved by magic angle spinning of the q-vector (qMAS). These parameters were quantified in healthy volunteers and in two patients; one patient with meningioma and one with glioblastoma. Finally, we used simulations to elucidate the relation between FA and μFA in various micro-architectures. Generally, μFA was high in the white matter and low in the gray matter. In the white matter, the largest differences between μFA and FA were found in crossing white matter and in interfaces between large white matter tracts, where μFA was high while FA was low. Both tumor types exhibited a low FA, in contrast to the μFA which was high in the meningioma and low in the glioblastoma, indicating that the meningioma contained disordered anisotropic structures, while the glioblastoma did not. This interpretation was confirmed by histological examination. We conclude that FA from DTI reflects both the amount of diffusion anisotropy and orientation dispersion. We suggest that the μFA and OP may complement FA by independently quantifying the microscopic anisotropy and the level of orientation coherence.

The past decade has seen impressive advances in the types of neuroimaging information that can be acquired in patients with traumatic brain injury. However, despite this increase in information, understanding of the contribution of this information to prognostic accuracy and treatment pathways for patients is limited. Available techniques often allow us to infer the presence of microscopic changes indicative of alterations in physiology and function in brain tissue. However, because histologic confirmation is typically lacking, conclusions reached by using these techniques remain solely inferential in almost all cases. Hence, a need exists for validation of these techniques by using data from large population samples that are obtained in a uniform manner, analyzed according to well-accepted procedures, and correlated with closely monitored clinical outcomes. At present, many of these approaches remain confined to population-based research rather than diagnosis at an individual level, particularly with regard to traumatic brain injury that is mild or moderate in degree. A need and a priority exist for patient-centered tools that will allow advanced neuroimaging tools to be brought into clinical settings. One barrier to developing these tools is a lack of an age-, sex-, and comorbidities-stratified, sequence-specific, reference imaging data base that could provide a clear understanding of normal variations across populations. Such a data base would provide researchers and clinicians with the information necessary to develop computational tools for the patient-based interpretation of advanced neuroimaging studies in the clinical setting. The recent "Joint ASNR-ACR HII-ASFNR TBI Workshop: Bringing Advanced Neuroimaging for Traumatic Brain Injury into the Clinic" on May 23, 2014, in Montreal, Quebec, Canada, brought together neuroradiologists, neurologists, psychiatrists, neuropsychologists, neuroimaging scientists, members of the National Institute of Neurologic Disorders and Stroke, industry representatives, and other traumatic brain injury stakeholders to attempt to reach consensus on issues related to and develop consensus recommendations in terms of creating both a well-characterized normative data base of comprehensive imaging and ancillary data to serve as a reference for tools that will allow interpretation of advanced neuroimaging tests at an individual level of a patient with traumatic brain injury. The workshop involved discussions concerning the following: 1) designation of the policies and infrastructure needed for a normative data base, 2) principles for characterizing normal control subjects, and 3) standardizing research neuroimaging protocols for traumatic brain injury. The present article summarizes these recommendations and examines practical steps to achieve them.

BACKGROUND: The Anterior Commissure (AC) is an important interhemispheric pathway that connects contralateral temporal lobes and orbitofrontal areas. The role of the AC is not yet well understood, although abnormalities in this white matter tract have been reported in patients diagnosed with chronic schizophrenia. However, it is not known whether changes in the AC are present at earlier stages of the disease. METHODS: Diffusion Magnetic Resonance Images (dMRI) were acquired from 17 First Episode Schizophrenia Patients (FESZ) and 20 healthy controls. The AC was reconstructed using a streamline tractography approach. DMRI measures, including Fractional Anisotropy (FA), Trace, Axial Diffusivity (AD) and Radial Diffusivity (RD) were computed in order to assess microstructural changes in the AC. RESULTS: FA was reduced, while trace and RD showed increases in FESZ. AD did not show differences between groups. CONCLUSION: The observed changes in these dMRI measures, namely reductions in FA and increases in trace and RD, without changes in AD, likely point to myelin abnormalities of this white matter tract, and provide evidence of white matter pathology extant in the early phases of schizophrenia.

We examined intelligence and memory in 25 healthy participants who had both prior magnetic resonance imaging (MRI) of gray matter volumes of medial orbital frontal cortex (mOFC) and rostral anterior cingulate cortex (rACC), along with diffusion tensor imaging (DTI) of posterior and anterior mOFC-rACC white matter microstructure, as assessed by fractional anisotropy (FA). Results showed distinct relationships between these basic structural brain parameters and higher cognition, highlighted by a highly significant correlation of left rACC gray matter volume with memory, and to a lesser extent, though still statistically significant, correlation of left posterior mOFC-rACC FA with intelligence. Regression analyses showed that left posterior mOFC-rACC connections and left rACC gray matter volume each contributed to intelligence, with left posterior mOFC-rACC FA uniquely accounting for between 20.43 and 24.99% of the variance in intelligence, in comparison to 13.54 to 17.98% uniquely explained by left rACC gray matter volume. For memory, only left rACC gray matter volume explained neuropsychological performance, uniquely accounting for a remarkably high portion of individual variation, ranging from 73.61 to 79.21%. These results pointed to differential contributions of white mater microstructure connections and gray matter volumes to individual differences in intelligence and memory, respectively.

This study examined whether intracranial neuroimaging abnormalities in those with mild traumatic brain injury (MTBI) (i.e., "complicated" MTBIs) are associated with worse subacute outcomes as measured by cognitive testing, symptom ratings, and/or diffusion tensor imaging (DTI). We hypothesized that (i) as a group, participants with complicated MTBIs would report greater symptoms and have worse neurocognitive outcomes than those with uncomplicated MTBI, and (ii) as a group, participants with complicated MTBIs would show more Diffusion Tensor Imaging (DTI) abnormalities. Participants were 62 adults with MTBIs (31 complicated and 31 uncomplicated) who completed neurocognitive testing, symptom ratings, and DTI on a 3T MRI scanner approximately 6-8 weeks post injury. There were no statistically significant differences between groups on symptom ratings or on a broad range of neuropsychological tests. When comparing the groups using tract-based spatial statistics for DTI, no significant difference was found for axial diffusivity or mean diffusivity. However, several brain regions demonstrated increased radial diffusivity (purported to measure myelin integrity), and decreased fractional anisotropy in the complicated group compared with the uncomplicated group. Finally, when we extended the DTI analysis, using a multivariate atlas based approach, to 32 orthopedic trauma controls (TC), the findings did not reveal significantly more areas of abnormal DTI signal in the complicated vs. uncomplicated groups, although both MTBI groups had a greater number of areas with increased radial diffusivity compared with the trauma controls. This study illustrates that macrostructural neuroimaging changes following MTBI are associated with measurable changes in DTI signal. Of note, however, the division of MTBI into complicated and uncomplicated subtypes did not predict worse clinical outcome at 6-8 weeks post injury.

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease confirmed at postmortem. Those at highest risk are professional athletes who participate in contact sports and military personnel who are exposed to repetitive blast events. All neuropathologically confirmed CTE cases, to date, have had a history of repetitive head impacts. This suggests that repetitive head impacts may be necessary for the initiation of the pathogenetic cascade that, in some cases, leads to CTE. Importantly, while all CTE appears to result from repetitive brain trauma, not all repetitive brain trauma results in CTE. Magnetic resonance imaging has great potential for understanding better the underlying mechanisms of repetitive brain trauma. In this review, we provide an overview of advanced imaging techniques currently used to investigate brain anomalies. We also provide an overview of neuroimaging findings in those exposed to repetitive head impacts in the acute/subacute and chronic phase of injury and in more neurodegenerative phases of injury, as well as in military personnel exposed to repetitive head impacts. Finally, we discuss future directions for research that will likely lead to a better understanding of the underlying mechanisms separating those who recover from repetitive brain trauma vs. those who go on to develop CTE.

In a previous study we have demonstrated, using a novel diffusion MRI analysis called free-water imaging, that the early stages of schizophrenia are more likely associated with a neuroinflammatory response and less so with a white matter deterioration or a demyelination process. What is not known is how neuroinflammation and white matter deterioration change along the progression of the disorder. In this study we apply the free-water measures on a population of 29 chronic schizophrenia subjects and compare them with 25 matching controls. Our aim was to compare the extent of free-water imaging abnormalities in chronic subjects with the ones previously obtained for subjects at their first psychotic episode. We find that chronic subjects showed a limited extent of abnormal increase in the volume of the extracellular space, suggesting a less extensive neuroinflammatory response relative to patients at the onset of schizophrenia. At the same time, the chronic schizophrenia subjects had greater extent of reduced fractional anisotropy compared to the previous study, suggesting increased white matter deterioration along the progression of the disease. Our findings substantiate the role of neuroinflammation in the earlier stages of the disorder, and the effect of neurodegeneration that is worsening in the chronic phase.

Subcaudate tractotomy (SCT) is a neurosurgical lesioning procedure that can reduce symptoms in medically intractable obsessive compulsive disorder (OCD). Due to the putative importance of the orbitofrontal cortex (OFC) in symptomatology, fibers that connect the OFC, SCT lesion, and either the thalamus or brainstem were investigated with two-tensor tractography using an unscented Kalman filter approach. From this dataset, fibers were warped to Montreal Neurological Institute space, and probability maps with center-of-mass analysis were subsequently generated. In comparing fibers from the same OFC region, including medial OFC (mOFC), central OFC (cOFC), and lateral OFC (lOFC), the area of divergence for fibers connected with the thalamus versus the brainstem is posterior to the anterior commissure. At the anterior commissure, fibers connected with the thalamus run dorsal to those connected with the brainstem. As OFC fibers travel through the ventral aspect of the internal capsule, lOFC fibers are dorsal to cOFC and mOFC fibers. Using neuroanatomical comparison, tracts coursing between the OFC and thalamus are likely part of the anterior thalamic radiations, while those between the OFC and brainstem likely belong to the medial forebrain bundle. These data support the involvement of the OFC in OCD and may be relevant to creating differential lesional procedures of specific tracts or to developing deep brain stimulation programming paradigms.

Measures from diffusion magnetic resonance imaging reflect changes in the substantia nigra of Parkinson’s disease. It is the case, however, that partial volume effects from free water can bias diffusion measurements. The bi-tensor diffusion model was introduced to quantify the contribution of free water and eliminates its bias on estimations of tissue microstructure. Here, we test the hypothesis that free water is elevated in the substantia nigra for Parkinson’s disease compared with control subjects. This hypothesis was tested between large cohorts of Parkinson’s disease and control participants in a single-site study and validated against a multisite study using multiple scanners. The fractional volume of free water was increased in the posterior region of the substantia nigra in Parkinson’s disease compared with control subjects in both the single-site and multi-site studies. We did not observe changes in either cohort for free-water-corrected fractional anisotropy or free-water-corrected mean diffusivity. Our findings provide new evidence that the free-water index reflects alteration of the substantia nigra in Parkinson’s disease, and this was evidenced across both single-site and multi-site cohorts.