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Acquired brain injury (ABI) is associated with a range of cognitive and motor deficits, and poses a significant personal, societal, and economic burden. Rehabilitation programs are available that target motor skills or cognitive functioning. In this review, we summarize the existing evidence that training may enhance structural neuroplasticity in patients with ABI, as assessed using structural magnetic resonance imaging (MRI)-based techniques that probe microstructure or morphology. Twenty-five research articles met key inclusion criteria. Most trials measured relevant outcomes and had treatment benefits that would justify the risk of potential harm. The rehabilitation program included a variety of task-oriented movement exercises (such as facilitation therapy, postural control training), neurorehabilitation techniques (such as constraint-induced movement therapy) or computer-assisted training programs (eg, Cogmed program). The reviewed studies describe regional alterations in white matter architecture and/or gray matter volume with training. Only weak-to-moderate correlations were observed between improved behavioral function and structural changes. While structural MRI is a powerful tool for detection of longitudinal structural changes, specific measures about the underlying biological mechanisms are lacking. Continued work in this field may potentially see structural MRI metrics used as biomarkers to help guide treatment at the individual patient level.

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Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organisation. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "fixel-based analysis" (FBA) framework that implements bespoke solutions to this end, and has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to fixel-based analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of current fixel-based analysis studies (until August 2020), categorised across a broad range of neuroscientific domains, listing key design choices and summarising their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the fixel-based analysis framework, and outline some directions and future opportunities.

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IntroductionCannabis is the most widely used regulated substance by youth and adults. Cannabis use has been associated with psychosocial problems, which have been partly ascribed to neurobiological changes. Emerging evidence to date from diffusion-MRI studies shows that cannabis users compared to controls show poorer integrity of white matter fibre tracts, which structurally connect distinct brain regions to facilitate neural communication. However, the most recent evidence from diffusion-MRI studies thus far has yet to be integrated. Therefore, it is unclear if white matter differences in cannabis users are evident consistently in selected locations, in specific diffusion-MRI metrics, and whether these differences in metrics are associated with cannabis exposure levels.MethodsWe systematically reviewed the results from diffusion-MRI imaging studies that compared white matter differences between cannabis users and controls. We also examined the associations between cannabis exposure and other behavioral variables due to changes in white matter. Our review was pre-registered in PROSPERO (ID: 258250; https://www.crd.york.ac.uk/prospero/).ResultsWe identified 30 diffusion-MRI studies including 1,457 cannabis users and 1,441 controls aged 16-to-45 years. All but 6 studies reported group differences in white matter integrity. The most consistent differences between cannabis users and controls were lower fractional anisotropy within the arcuate/superior longitudinal fasciculus (7 studies), and lower fractional anisotropy of the corpus callosum (6 studies) as well as higher mean diffusivity and trace (4 studies). Differences in fractional anisotropy were associated with cannabis use onset (4 studies), especially in the corpus callosum (3 studies).DiscussionThe mechanisms underscoring white matter differences are unclear, and they may include effects of cannabis use onset during youth, neurotoxic effects or neuro adaptations from regular exposure to tetrahydrocannabinol (THC), which exerts its effects by binding to brain receptors, or a neurobiological vulnerability predating the onset of cannabis use. Future multimodal neuroimaging studies, including recently developed advanced diffusion-MRI metrics, can be used to track cannabis users over time and to define with precision when and which region of the brain the white matter changes commence in youth cannabis users, and whether cessation of use recovers white matter differences.Systematic review registrationwww.crd.york.ac.uk/prospero/, identifier: 258250.