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CLINICAL AND TRANSLATIONAL NEUROSCIENCE

COMMENTARY Advance MR imaging in sports-related concussion and mild traumatic brain injury – ready for clinical use? (Commentary on Tremblay et al. 2017)

Sven Haller1,2,3,4 1Affidea CDRC Centre Diagnostique Radiologique de Carouge Clos de la Fonderie 1, 1227 Carouge, Switzerland 2Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden 3Department of Neuroradiology, University Hospital Freiburg, Freiburg, Germany 4Faculty of Medicine, University of Geneva, Geneva, Switzerland

Sports-related concussion – including chronic traumatic encephalopathy in adult professional American football players – has recently attracted considerable interest, even in the general media. The Hollywood movie entitled ‘Concussion’ is one recent example. Furthermore, discussion about brain abnormalities as a consequence of sports injuries should also include younger players (Bahrami et al., 2016). It remains to be explored how traumatic brain injury in the youth may alter the normal trajectory of brain development. In Europe, more attention is paid to sports-related concussion in the commonly played game of soccer (Koerte et al., 2012; Lipton et al., 2013). Likewise, there is growing interest in brain abnormalities related to mild traumatic brain injury (MTBI) resulting from minor accidents (e.g. whip-lash injury), particularly with respect to medico-legal and insurance-related issues. In both sports-related concussion and MTBI, conventional CT and MR imaging results generally do not reveal clear abnormalities. However, advanced imaging techniques, including diffusion tensor imaging (DTI) (Bahrami et al., 2016), MR spectroscopy (MRS) (Maugans et al., 2012; Vagnozzi et al., 2013), MR perfusion (Maugans et al., 2012), functional MRI (Zhou et al., 2012), as well as nuclear medicine techniques such as tau positron emission tomography (Small et al., 2013), may reveal subtle trauma-related brain abnormalities not evident to the naked eye or through standard imaging. In ‘Defining a multimodal signature of remote sports concussions’, Tremblay et al. (2017) used DTI and MRS to characterize white matter

changes in aging, retired athletes with a history of sports-related MTBI. Using machine learning approaches, the authors achieved up to 90% accuracy in identifying former athletes on the basis of their white matter profiles. While this research is certainly promising, there are several concerns that require strict and careful consideration before such automated classification techniques can be used clinically.

Regional specific pattern of brain abnormalities?

Advanced imaging techniques have been used in the domain of neurodegeneration, particularly in Alzheimer’s dementia and its prodromal stages, with the same basic aim – to detect subtle brain abnormalities not evident using standard imaging techniques. There is, however, a fundamental difference between trauma-related and neurodegenerative abnormalities. Neurodegenerative diseases typically share common, dis- ease-specific patterns of brain changes. For example, Alzheimer’s dementia is characterized by atrophy particularly within the hippocampal and parietal regions, while behavioral variant fronto-temporal dementia is typically associated with a predominantly fronto-temporal atrophy (Haller et al., 2013). For post-traumatic changes, we may assume that some traumatic mechanisms are more common than others, and that trauma-related changes are more or less widespread in the brain. Therefore, trauma-related changes will overlap to a certain degree. However, the individual trauma-related changes are variable depending on the site, direction and velocity of the impact, and consequently trauma-related variability is larger than the more stereotypical neurodegeneration-related brain alterations. This implies that several patterns of trauma-related brain abnormalities should be defined, and the best-suited reference dataset for comparison will depend on the specific trauma of each individual case.

Progressive or regressive brain abnormalities?

Making the comparison with neurodegenerative diseases again, it is important to highlight that neurodegenerative brain abnormalities are, in general, progressive. The time point of imaging is consequently of lesser importance, as brain changes will only accumulate during the disease progress. This situation is different in trauma-related changes. For example, it was believed that trauma-related microbleeds (also known as hemorrhagic diffuse axonal injuries or shearing injuries) remain more or less constant over years. However, recent evidence suggests that such lesions may decrease overtime (Liu et al., 2016), grow (Toth et al., 2016) or (temporarily) disappear (Watanabe et al., 2016). Moreover, we can assume that some regions might show white matter Wallerian-type degeneration after brain trauma, while other areas might develop com- pensatory increasing connectivity. This suggests that the timing of the imaging, relative to the trauma, might influence the results and should therefore be carefully considered.

European Journal of Neuroscience, Vol. 46, pp. 1954–1955, 2017 doi:10.1111/ejn.13643

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Group-level vs. single participant analyses

The majority of previous imaging studies have used group-level statistics, that is, comparing a group of patients vs. a group of controls (Messe et al., 2011; Toth et al., 2012). Such group-level analyses are interesting from a scientific perspective and may reveal brain areas involved in a given disease or condition. However, such group-level analyses cannot be used for diagnosis of individual patients. The current investigation ‘Defining a multimodal signature of remote sports concussions’ (2017) elaborated on traditional group-level analyses using machine learning approaches to differentiate aging athletes with a history of TBI from healthy controls. However, as in most related studies, the training and testing datasets were derived from the same sample, which can lead to optimistic results (Haller et al., 2014). Ideally, training and test datasets should be separate, preferably even acquired on different scanners (see below).

Single-center vs. multicenter studies

Most advanced neuroimaging studies in the domain of MTBI and sports-related concussions are single-center studies, typically using only one scanner with an identical imaging protocol for all participants. Trauma-related changes may be very subtle, and easily within the range of the normal variability among different MR scanners or sequences. Consequently, to have a clinically useful tool, platform-independent strict imaging protocols must be established that should ideally be validated using phantom scans – equivalent to the ongoing scanner harmoniza- tion in the Alzheimer’s disease neuroimaging initiative (ADNI).

Software dependence

Advanced image analysis methods often substantially influence the results, for example, in DTI tractography (Christidi et al., 2016). Moreover, even within a given software package, there are multiple parameters that can be modified. Similar to the data acquisition discussed above, it is fun- damental to strictly harmonize and standardize data analysis techniques to obtain reproducible and, as a consequence, clinically applicable results.

Conclusions

In conclusion, advanced imaging and data analysis techniques have the potential to detect subtle alterations in the brain related to MTBI and sports-related concussion, which are not evident to the naked eye and standard CT or MR imaging. However, to obtain reproducible and clin- ically applicable results at the individual level, strictly standardized data acquisition including standardized timing and data analyses protocols is fundamental. These need to be accompanied by large-scale reference datasets controlling for, at least age, gender and education, and ideally additional information regarding site, direction, and velocity of head impact.

Conflict of interest

No conflicts of interest.

References

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