Reduction in Constitutively Activated Auditory Brainstem Microglia in Aging and Alzheimer's Disease

Background

Alzheimer's disease (AD) pathology is considered to begin in the brainstem, and cerebral microglia are known to play a critical role in AD pathogenesis, yet little is known about brainstem microglia in AD. Translocator protein (TSPO) PET, sensitive to activated microglia, shows high signal in dorsal brainstem in humans, but the precise location and clinical correlates of this signal are unknown.

Objective

To define age and AD associations of brainstem TSPO PET signal in humans.

Methods

We applied new probabilistic maps of brainstem nuclei to quantify PET-measured TSPO expression over the whole brain including brainstem in 71 subjects (43 controls scanned using 11C-PK11195; 20 controls and 8 AD subjects scanned using 11C-PBR28). We focused on inferior colliculi (IC) because of visually-obvious high signal in this region, and potential relevance to auditory dysfunction in AD. We also assessed bilateral cortex.

Results

TSPO expression was normally high in IC and other brainstem regions. IC TSPO was decreased with aging (p = 0.001) and in AD subjects versus controls (p = 0.004). In cortex, TSPO expression was increased with aging (p = 0.030) and AD (p = 0.033).

Conclusions

Decreased IC TSPO expression with aging and AD-an opposite pattern than in cortex-highlights underappreciated regional heterogeneity in microglia phenotype, and implicates IC in a biological explanation for strong links between hearing loss and AD. Unlike in cerebrum, where TSPO expression is considered pathological, activated microglia in IC and other brainstem nuclei may play a beneficial, homeostatic role. Additional study of brainstem microglia in aging and AD is needed.

Critical Appraisal of Artificial Intelligence-Enabled Imaging Tools Using the Levels of Evidence System

Clinical adoption of an artificial intelligence-enabled imaging tool requires critical appraisal of its life cycle from development to implementation by using a systematic, standardized, and objective approach that can verify both its technical and clinical efficacy. Toward this concerted effort, the ASFNR/ASNR Artificial Intelligence Workshop Technology Working Group is proposing a hierarchal evaluation system based on the quality, type, and amount of scientific evidence that the artificial intelligence-enabled tool can demonstrate for each component of its life cycle. The current proposal is modeled after the levels of evidence in medicine, with the uppermost level of the hierarchy showing the strongest evidence for potential impact on patient care and health care outcomes. The intended goal of establishing an evidence-based evaluation system is to encourage transparency, foster an understanding of the creation of artificial intelligence tools and the artificial intelligence decision-making process, and to report the relevant data on the efficacy of artificial intelligence tools that are developed. The proposed system is an essential step in working toward a more formalized, clinically validated, and regulated framework for the safe and effective deployment of artificial intelligence imaging applications that will be used in clinical practice.

Resting State Functional Connectivity is Directly Related to Clinical Presentation of Mild Traumatic Brain Injury

Objective

To determine the utility of fractional amplitude of low frequency fluctuations (fALFF) during resting state fMRI (rs-fMRI) as an advanced neuroimaging biomarker for Mild Traumatic Brain Injury (mTBI).

Background

mTBI is defined by a constellation of functional rather than structural deficits. As a measure of functional connectivity, fALFF has been implicated in long-term outcomes post-mTBI. It is unclear however, how longitudinal changes in fALFF may relate to the clinical presentation of mTBI.

Design/Methods

111 patients and 32 controls (15–50 years old) were enrolled acutely after mTBI and followed with up to 4 standardized serial assessments. Patients were enrolled at either Encounter 1 (E1), within 72 hours, or Encounter 2 (E2), 5–10 days post-injury, and returned for Encounter 3 (E3) at 15–29 days and Encounter 4 (E4) at 83–97 days. Each encounter included a clinical exam, neuropsychological assessment, as well as rs-fMRI imaging. fALFF was analyzed independently in 14 functional networks and, in grey and white matter as a function of symptom severity. Symptom severity scores (SSS) ranged from 0–132 as defined by the SCAT2 symptom evaluation.

Results

In mTBI patients, fALFF scores across 5 functional brain networks (language, sensorimotor, visuospatial, higher-order visual, and posterior salience) differed between mTBI patients with low versus high SSS (SSS <5 and >30, respectively). Overall, greater SSS were indexed by reduced connectivity (p < 0.03, Bonferroni corrected). Further analysis also identified corresponding network pairs which were most predictive of increased SSS. White matter fALFF was not correlated with symptom severity, however, decreased grey matter fALFF was significantly correlated with greater SSS (r = −0.25, p = 0.002).

Conclusions

Grey matter fALFF was correlated with mTBI symptom burden suggesting that patterns of neural connectivity relate directly to the clinical presentation of mTBI. Furthermore, differences in functional network connectivity as a function of SSS may reflect which networks are implicated in recovery of mTBI.

Recovery time, risk factors, and volumetric analysis in acute mTBI

Objective

This study investigated the influence of demographic factors, the course of recovery, and the utility of investigational MR sequences (specifically volumetry) in mild traumatic brain injury (mTBI) patients.

Background

Most literature suggests that the majority of mTBI patients achieve recovery within 1 month of injury, or sooner. This may be affected by younger age, female sex, concussion history, learning disability, psychiatric history, or migraines. The role of volumetric analysis in mTBI requires further investigation.

Methods

One hundred eleven patients (15–50 years old) enrolled in the study within 10 days of head injury. Patients completed a maximum of 4 encounters over 3 months, undergoing volumetric structural imaging at each visit. Patients were contacted to determine recovery date.

Results

Recovery date was obtained in 73 patients at HSS. The median days to recovery was 44 days (IQR: 23–88 days). 33% of this population was recovered in 30 days, 63% in 60 days, and >75% in 90 days. Of the subjects who were not recovered by 90 days, the right thalamus volume trended towards a negative correlation with SSS at that time point. Initial symptom severity score (SSS) was significantly correlated with increased days to recovery (p = 0.382, p = 0.001). Average days to recover was longer in patients with diagnosed depression, anxiety, or other psychiatric disorder (121 vs 70 days, p = 0.037). No significant differences in days to recovery were found between age groups, sex, learning disorder, previous concussions, or history of migraines.

Conclusion

Average time to recover from mTBI may be longer than previously reported. Acute SSS may be a useful indicator in determining recovery time. Of previously reported risk factors, personal psychiatric history may have the greatest effect on recovery time. Despite being interesting, the volumetric correlations did not survive multiple comparison corrections and may not be the most sensitive variable for mTBI imaging.

Concussion in sports

Context:

Recently, concussion has become a topic of much discussion within sports. The goal of this review is to provide an overview of the literature concerning the definition of concussion, management of initial injury, return to play, and future health risks.

Evidence Acquisition:

This article reviews the most recent findings on recognizing and managing sports-related concussion, which has become a significant health risk. We reviewed articles from the literature discussing concussion and its effects.

Results:

Though concussion patients typically have negative head imaging, imaging is warranted in those with severe mechanism, significant loss of consciousness, focal neurologic deficit, or worsening symptoms. The existence of “second-impact syndrome,” whereby a first minor head injury predisposes an athlete to later catastrophic injury, remains controversial; however, it is clear that concussion has significant effects on a patient and should be considered carefully in return-to-play decisions.

Conclusions:

A comprehensive understanding of concussion and its related risks is important in making return-to-play decisions as well as health care and league policy.

Individual Differences in Distinct Components of Attention are Linked to Anatomical Variations in Distinct White Matter Tracts

Inter-subject variations in white matter tract properties are known to correlate with individual differences in performance in cognitive domains such as attention. The specificity of such linkages, however, is largely unexplored at the level of specific component operations of attention associated with distinct anatomical networks. This study examines individual performance variation within three functional components of attention - alerting, orienting, and conflict processing - identified by the Attention Network Task (ANT), and relates each to inter-subject variation in a distinct set of white matter tract regions. Diffusion tensor imaging data collected at 3T was used to calculate average fractional anisotropy within a set of individualized a priori defined regions of interest using the Reproducible Objective Quantification Scheme (ROQS) (Niogi and McCandliss, 2006; Niogi et al., 2007). Results demonstrate three functionally distinct components of attention that each correlate distinctly with three white matter tract regions. Structure-function correlations were found between alerting and the anterior limb of the internal capsule, orienting and the splenium of the corpus callosum, and conflict and the anterior corona radiata. A multiple regression/dissociation analysis demonstrated a triple dissociation between these three structure-function relationships that provided evidence of three anatomically and functionally separable networks. These results extend previous findings from functional imaging and lesion studies that suggest these three components of attention are subserved by dissociable networks, and suggest that variations in white matter tract microstructure may modulate the efficiency of these cognitive processes in highly specific ways.

Frontostriatal connectivity and its role in cognitive control in parent-child dyads with ADHD

OBJECTIVE

Many studies have linked the structure and function of frontostriatal circuitry to cognitive control deficits in attention deficit hyperactivity disorder (ADHD). Few studies have examined the role of white matter tracts between these structures or the extent to which white matter tract myelination and regularity correlate in family members with the disorder.

METHOD

Functional imaging maps from a go/nogo task were used to identify portions of the ventral prefrontal cortex and striatum involved in suppressing an inappropriate action (i.e., cognitive control) in 30 parent-child dyads (N=60), including 20 dyads (N=40) with ADHD and 10 dyads (N=20) without ADHD. An automated fiber-tracking algorithm was used to delineate white matter fibers adjacent to these functionally defined regions based on diffusion tensor images. Fractional anisotropy, an index of white matter tract myelination and regularity derived from diffusion tensor images, was calculated to characterize the associations between white matter tracts and function.

RESULTS

Fractional anisotropy in right prefrontal fiber tracts correlated with both functional activity in the inferior frontal gyrus and caudate nucleus and performance of a go/nogo task in parent-child dyads with ADHD, even after controlling for age. Prefrontal fiber tract measures were tightly associated between ADHD parents and their children.

CONCLUSIONS

Collectively, these findings support previous studies suggesting heritability of frontostriatal structures among individuals with ADHD and suggest disruption in frontostriatal white matter tracts as one possible pathway to the disorder.

Frontostriatal Microstructure Modulates Efficient Recruitment of Cognitive Control

Many studies have linked activity in a frontostriatal network with the capacity to suppress inappropriate thoughts and actions, but relatively few have examined the role of connectivity between these structures. Here, we use diffusion tensor imaging to assess frontostriatal connectivity in 21 subjects (ages 7-31 years). Fifteen subjects were tested on a go/no-go task, where they responded with a button press to a visual stimulus and inhibited a response to a second infrequent stimulus. An automated fiber tracking algorithm was used to delineate white matter fibers adjacent to ventral prefrontal cortex and the striatum, and the corticospinal tract, which was not expected to contribute to control per se. Diffusion in frontostriatal and corticospinal tracts became more restricted with age. This shift was paralleled by an increase in efficiency of task performance. Frontostriatal radial diffusivities predicted faster reaction times, independent of age and accuracy, and this correlation grew stronger for trials expected to require greater control. This was not observed in the corticospinal tract. On trials matched for speed of task performance, adults were significantly more accurate, and accuracies were correlated with frontostriatal, but not corticospinal, diffusivities. These findings suggest that frontostriatal connectivity may contribute to developmental and individual differences in the efficient recruitment of cognitive control.

Fiber tracking using magnetic resonance diffusion tensor imaging and its applications to human brain development

Diffusion tensor imaging is unique in its ability to noninvasively visualize white matter fiber tracts in the human brain in vivo. Diffusion is the incoherent motion of water molecules on a microscopic scale. This motion is itself dependent on the micro-structural environment that restricts the movement of the water molecules. In white matter fibers there is a pronounced directional dependence on diffusion. With white matter fiber tracking or tractography, projections among brain regions can be detected in the three-dimensional diffusion tensor dataset according to the directionality of the fibers. Examples of developmental changes in diffusion, tracking of major fiber tracts, and examples of how diffusion tensor tractography and functional magnetic resonance imaging can be combined are provided. These techniques are complimentary and allow both the identification of the eloquent areas of the brain involved in specific functional tasks, and the connections between them. The noninvasive nature of magnetic resonance imaging will allow these techniques to be used in both longitudinal developmental and diagnostic studies. An overview of the technique and preliminary applications are presented, along with its current limitations.