A mesoscale finite element modeling approach for understanding brain morphology and material heterogeneity effects in chronic traumatic encephalopathy

Chronic traumatic encephalopathy (CTE): criteria for neuropathological diagnosis and relationship to repetitive head impacts

Over the last 17 years, there has been a remarkable increase in scientific research concerning chronic traumatic encephalopathy (CTE). Since the publication of NINDS-NIBIB criteria for the neuropathological diagnosis of CTE in 2016, and diagnostic refinements in 2021, hundreds of contact sport athletes and others have been diagnosed at postmortem examination with CTE. CTE has been reported in amateur and professional athletes, including a bull rider, boxers, wrestlers, and American, Canadian, and Australian rules football, rugby union, rugby league, soccer, and ice hockey players. The pathology of CTE is unique, characterized by a pathognomonic lesion consisting of a perivascular accumulation of neuronal phosphorylated tau (p-tau) variably alongside astrocytic aggregates at the depths of the cortical sulci, and a distinctive molecular structural configuration of p-tau fibrils that is unlike the changes observed with aging, Alzheimer's disease, or any other tauopathy. Computational 3-D and finite element models predict the perivascular and sulcal location of p-tau pathology as these brain regions undergo the greatest mechanical deformation during head impact injury. Presently, CTE can be definitively diagnosed only by postmortem neuropathological examination; the corresponding clinical condition is known as traumatic encephalopathy syndrome (TES). Over 97% of CTE cases published have been reported in individuals with known exposure to repetitive head impacts (RHI), including concussions and nonconcussive impacts, most often experienced through participation in contact sports. While some suggest there is uncertainty whether a causal relationship exists between RHI and CTE, the preponderance of the evidence suggests a high likelihood of a causal relationship, a conclusion that is strengthened by the absence of any evidence for plausible alternative hypotheses. There is a robust dose-response relationship between CTE and years of American football play, a relationship that remains consistent even when rigorously accounting for selection bias. Furthermore, a recent study suggests that selection bias underestimates the observed risk. Here, we present the advances in the neuropathological diagnosis of CTE culminating with the development of the NINDS-NIBIB criteria, the multiple international studies that have used these criteria to report CTE in hundreds of contact sports players and others, and the evidence for a robust dose-response relationship between RHI and CTE.

Applying the Bradford Hill Criteria for Causation to Repetitive Head Impacts and Chronic Traumatic Encephalopathy

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with a history of repetitive head impacts (RHI). CTE was described in boxers as early as the 1920s and by the 1950s it was widely accepted that hits to the head caused some boxers to become "punch drunk." However, the recent discovery of CTE in American and Australian-rules football, soccer, rugby, ice hockey, and other sports has resulted in renewed debate on whether the relationship between RHI and CTE is causal. Identifying the strength of the evidential relationship between CTE and RHI has implications for public health and medico-legal issues. From a public health perspective, environmentally caused diseases can be mitigated or prevented. Medico-legally, millions of children are exposed to RHI through sports participation; this demographic is too young to legally consent to any potential long-term risks associated with this exposure. To better understand the strength of evidence underlying the possible causal relationship between RHI and CTE, we examined the medical literature through the Bradford Hill criteria for causation. The Bradford Hill criteria, first proposed in 1965 by Sir Austin Bradford Hill, provide a framework to determine if one can justifiably move from an observed association to a verdict of causation. The Bradford Hill criteria include nine viewpoints by which to evaluate human epidemiologic evidence to determine if causation can be deduced: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy. We explored the question of causation by evaluating studies on CTE as it relates to RHI exposure. Through this lens, we found convincing evidence of a causal relationship between RHI and CTE, as well as an absence of evidence-based alternative explanations. By organizing the CTE literature through this framework, we hope to advance the global conversation on CTE mitigation efforts.

Brain aging mechanisms with mechanical manifestations

Brain aging is a complex process that affects everything from the subcellular to the organ level, begins early in life, and accelerates with age. Morphologically, brain aging is primarily characterized by brain volume loss, cortical thinning, white matter degradation, loss of gyrification, and ventricular enlargement. Pathophysiologically, brain aging is associated with neuron cell shrinking, dendritic degeneration, demyelination, small vessel disease, metabolic slowing, microglial activation, and the formation of white matter lesions. In recent years, the mechanics community has demonstrated increasing interest in modeling the brain's (bio)mechanical behavior and uses constitutive modeling to predict shape changes of anatomically accurate finite element brain models in health and disease. Here, we pursue two objectives. First, we review existing imaging-based data on white and gray matter atrophy rates and organ-level aging patterns. This data is required to calibrate and validate constitutive brain models. Second, we review the most critical cell- and tissue-level aging mechanisms that drive white and gray matter changes. We focuse on aging mechanisms that ultimately manifest as organ-level shape changes based on the idea that the integration of imaging and mechanical modeling may help identify the tipping point when normal aging ends and pathological neurodegeneration begins.