Neuroimaging Characterization of Acute Traumatic Brain Injury with Focus on Frontline Clinicians: Recommendations from the 2024 National Institute of Neurological Disorders and Stroke Traumatic Brain Injury Classification and Nomenclature Initiative Imaging Working Group.
Authors
Affiliations (21)
Affiliations (21)
- Department of Neurological Surgery, University of Washington School of Medicine, Seattle, Washington, USA.
- Department of Radiology, University of California, San Francisco, San Francisco, California, USA.
- Department of Radiology, Antwerp University Hospital, Antwerp, Belgium.
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.
- Centre for Health Care and Technology, Imperial College London, London, United Kingdom.
- The Mind Research Network, Albuquerque, New Mexico, USA.
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom.
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA.
- George E. Wahlen VA Salt Lake City Healthcare System, Salt Lake City, Utah, USA.
- Department of Child and Adolescent Psychiatry, Ludwig-Maximilians-Universität, Munich, Germany.
- Department of Psychiatry, Salt Lake City VA MIRECC, University of Utah, Salt Lake City, Utah, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
- Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA.
- Division of Neuroscience, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA.
- Department of Rehabilitation and Human Performance, Icahn School of Medicine, Mount Sinai, New York, New York, USA.
- Department of Neurology, Icahn School of Medicine, Mount Sinai, New York, New York, USA.
- Department of Neurosurgery, Antwerp University Hospital, Edegem, Belgium.
- Department of Translational Neuroscience, Faculty of Medicine and Health Science, University of Antwerp, Antwerp, Belgium.
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
- Department Neurological Surgery, University of California San Francisco, San Francisco, California, USA.
Abstract
Neuroimaging screening and surveillance is one of the first frontline diagnostic tools leveraged in the acute assessment (first 24 h postinjury) of patients suspected to have traumatic brain injury (TBI). While imaging, in particular computed tomography, is used almost universally in emergency departments worldwide to evaluate possible features of TBI, there is no currently agreed-upon reporting system, standard terminology, or framework to contextualize brain imaging findings with other available medical, psychosocial, and environmental data. In 2023, the NIH-National Institute of Neurological Disorders and Stroke convened six working groups of international experts in TBI to develop a new framework for nomenclature and classification. The goal of this effort was to propose a more granular system of injury classification that incorporates recent progress in imaging biomarkers, blood-based biomarkers, and injury and recovery modifiers to replace the commonly used Glasgow Coma Scale-based diagnosis groups of mild, moderate, and severe TBI, which have shown relatively poor diagnostic, prognostic, and therapeutic utility. Motivated by prior efforts to standardize the nomenclature for pathoanatomic imaging findings of TBI for research and clinical trials, along with more recent studies supporting the refinement of the originally proposed definitions, the Imaging Working Group sought to update and expand this application specifically for consideration of use in clinical practice. Here we report the recommendations of this working group to enable the translation of structured imaging common data elements to the standard of care. These leverage recent advances in imaging technology, electronic medical record (EMR) systems, and artificial intelligence (AI), along with input from key stakeholders, including patients with lived experience, caretakers, providers across medical disciplines, radiology industry partners, and policymakers. It was recommended that (1) there would be updates to the definitions of key imaging features used for this system of classification and that these should be further refined as new evidence of the underlying pathology driving the signal change is identified; (2) there would be an efficient, integrated tool embedded in the EMR imaging reporting system developed in collaboration with industry partners; (3) this would include AI-generated evidence-based feature clusters with diagnostic, prognostic, and therapeutic implications; and (4) a "patient translator" would be developed in parallel to assist patients and families in understanding these imaging features. In addition, important disclaimers would be provided regarding known limitations of current technology until such time as they are overcome, such as resolution and sequence parameter considerations. The end goal is a multifaceted TBI characterization model incorporating clinical, imaging, blood biomarker, and psychosocial and environmental modifiers to better serve patients not only acutely but also through the postinjury continuum in the days, months, and years that follow TBI.