Discriminating Mild Traumatic Brain Injury and Posttraumatic Stress Disorder Using Latent Neuroimaging and Neuropsychological Profiles in Active-Duty Military Service Members

OBJECTIVE

Mild traumatic brain injury (mTBI) and posttraumatic stress disorder (PTSD) commonly occur among military Service Members and Veterans and have heterogenous, but also overlapping symptom presentations, which often complicate the diagnoses of underlying impairments and development of effective treatment plans. Thus, we sought to examine whether the combination of whole brain gray matter (GM) and white matter (WM) structural measures with neuropsychological performance can aid in the classification of military personnel with mTBI and PTSD.

METHODS

Active-Duty US Service Members ( n = 156; 87.8% male) with a history of mTBI, PTSD, combined mTBI+PTSD, or orthopedic injury completed a neuropsychological battery and T1- and diffusion-weighted structural neuroimaging. Cortical, subcortical, ventricular, and WM volumes and whole brain fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were calculated. Latent profile analyses were performed to determine how the GM and WM indicators, together with neuropsychological indicators, classified individuals.

RESULTS

For both GM and WM, respectively, a 4-profile model was the best fit. The GM model identified greater ventricular volumes in Service Members with cognitive symptoms, including those with a diagnosis of mTBI, either alone or with PTSD. The WM model identified reduced FA and elevated RD in those with psychological symptoms, including those with PTSD or mTBI and comorbid PTSD. However, contrary to expectation, a global neural signature unique to those with comorbid mTBI and PTSD was not identified.

CONCLUSIONS

The findings demonstrate that neuropsychological performance alone is more robust in differentiating Active-Duty Service Members with mTBI and PTSD, whereas global neuroimaging measures do not reliably differentiate between these groups.

medna-metadata: an open-source data management system for tracking environmental DNA samples and metadata

MOTIVATION

Environmental DNA (eDNA), as a rapidly expanding research field, stands to benefit from shared resources including sampling protocols, study designs, discovered sequences, and taxonomic assignments to sequences. High-quality community shareable eDNA resources rely heavily on comprehensive metadata documentation that captures the complex workflows covering field sampling, molecular biology lab work, and bioinformatic analyses. There are limited sources that provide documentation of database development on comprehensive metadata for eDNA and these workflows and no open-source software.

RESULTS

We present medna-metadata, an open-source, modular system that aligns with Findable, Accessible, Interoperable, and Reusable guiding principles that support scholarly data reuse and the database and application development of a standardized metadata collection structure that encapsulates critical aspects of field data collection, wet lab processing, and bioinformatic analysis. Medna-metadata is showcased with metabarcoding data from the Gulf of Maine (Polinski et al., 2019).

AVAILABILITY AND IMPLEMENTATION

The source code of the medna-metadata web application is hosted on GitHub (https://github.com/Maine-eDNA/medna-metadata). Medna-metadata is a docker-compose installable package. Documentation can be found at https://medna-metadata.readthedocs.io/en/latest/?badge=latest. The application is implemented in Python, PostgreSQL and PostGIS, RabbitMQ, and NGINX, with all major browsers supported. A demo can be found at https://demo.metadata.maine-edna.org/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Traumatic brain injury imaging research roadmap

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.

Ultrasound processing and computing: review and future directions

Since the introduction of medical ultrasound in the 1950s, modern diagnostic ultrasound has progressed to see many major diagnostic tools come into widespread clinical use, such as B-mode imaging, color-flow imaging, and spectral Doppler. New applications, such as panoramic imaging, three-dimensional imaging, and quantitative imaging, are now beginning to be offered on some commercial ultrasound machines and are expected to grow in popularity. In this review, we focus on the various algorithms, their processing requirements, and the challenges of these ultrasound modes. Whereas the older, mature B and color-flow modes could be systolically implemented using hardwired components and boards, new applications, such as three-dimensional imaging and image feature extraction, are being implemented more by using programmable processors. This trend toward programmable ultrasound machines will continue, because the programmable approach offers the advantages of quick implementation of new applications without any additional hardware and the flexibility to adapt to the changing requirements of these dynamic new applications.

Enterprise-class Digital Imaging and Communications in Medicine (DICOM) image infrastructure

Most current picture archiving and communication systems (PACS) are designed for a single department or a single modality. Few PACS installations have been deployed that support the needs of the hospital or the entire Integrated Delivery Network (IDN). The authors propose a new image management architecture that can support a large, distributed enterprise.

NMR studies of succinoglycan repeating-unit octasaccharides from Rhizobium meliloti and Agrobacterium radiobacter

Complete 1H and 13C-nuclear magnetic resonance assignments have been obtained for the octasaccharide repeating units of the bacterial polysaccharide succinoglycan from Rhizobium meliloti Rm1021 and Agrobacterium radiobacter NCIB 11883. The assignments were used to determine the locations of the O-succinyl and O-acetyl substituents. The O-acetyl substituent in Rm1021 was attached to the 3rd residue from the reducing end, and the O-succinyl group was attached to the 7th residue in both octasaccharides. The structure of the Rm1021 octasaccharide is as shown below: [formula: see text] A small amount of succinate was also attached to C6 of the 6th residue in both octasaccharides.