Ten problems and solutions when predicting individual outcome from lesion site after stroke

Abstract

In this paper, we consider solutions to ten of the challenges faced when trying to predict an individual's functional outcome after stroke on the basis of lesion site. A primary goal is to find lesion-outcome associations that are consistently observed in large populations of stroke patients because consistent associations maximise confidence in future individualised predictions. To understand and control multiple sources of inter-patient variability, we need to systematically investigate each contributing factor and how each factor depends on other factors. This requires very large cohorts of patients, who differ from one another in typical and measurable ways, including lesion site, lesion size, functional outcome and time post stroke (weeks to decades). These multivariate investigations are complex, particularly when the contributions of different variables interact with one another. Machine learning algorithms can help to identify the most influential variables and indicate dependencies between different factors. Multivariate lesion analyses are needed to understand how the effect of damage to one brain region depends on damage or preservation in other brain regions. Such data-led investigations can reveal predictive relationships between lesion site and outcome. However, to understand and improve the predictions we need explanatory models of the neural networks and degenerate pathways that support functions of interest. This will entail integrating the results of lesion analyses with those from functional imaging (fMRI, MEG), transcranial magnetic stimulation (TMS) and diffusor tensor imaging (DTI) studies of healthy participants and patients.

Enhanced estimations of post‐stroke aphasia severity using stacked multimodal predictions

“…The use of multiple layers of crossvalidation during variable selection excludes the possibility that this might be caused by analyses choices. The reason, instead, might be interindividual variability [Price et al, ]. In the healthy population, substantial individual differences have been shown in cytoarchitectonic maps [Amunts et al, ] and resting state networks [Finn et al, ].…”

“…In principle, no area of the brain acts in isolation without sending or receiving signals to or from other areas. This means that cognitive processes are likely to emerge from multivariate signal interactions that cannot be captured when considering each area in isolation [Medaglia et al, ; Price et al, ; Turken and Dronkers, ]. In voxel‐based lesion‐to‐symptom (VLSM) analyses, the mass‐univariate approach not only misses the interaction between lesioned brain areas but also produces displaced results along the vascular anatomy [Mah et al, ].…”

A multivariate lesion symptom mapping toolbox and examination of lesion‐volume biases and correction methods in lesion‐symptom mapping

“…Lesion volume is an important confounding variable in lesion-symptom mapping analyses because larger lesions tend to cause more severe deficits regardless of location (Price, Hope, & Seghier, 2017). Further, at any given voxel, the patients with a lesion occupying that voxel are likely to have larger strokes than those without a lesion at that voxel.…”

How to study spoken language understanding: a survey of neuroscientific methods

“…One limitation of the traditional lesion method is that it only permits a limited degree of spatial specificity -patients with damage to Broca's area might also have damage to many other, adjacent brain regions as well as underlying white-matter tracts. Despite dramatic improvements in structural imaging methods it can still be difficult to specify which of several co-occurring forms of damage is most responsible for differences in observed behaviour (Price, Hope, & Seghier, 2017). Nonetheless, by using MRI or CT imaging to characterise brain lesions and adopting voxel-based statistical methods, it is possible to link the specific location and extent of neural damage to functional outcomes (i.e.…”