Symptoms
after stroke are not only determined by location and extent of a lesion, but
also by alterations of connectivity. Such changes have been assessed with functional
connectivity MRI (fcMRI) based on resting-state recordings. Here, different fcMRI
approaches are reviewed ranging from interhemispheric connectivity in one
network, simultaneous assessment of many networks to methods based on graph theory.
A recent approach overcomes the notion of “fixed separate connectivity networks”
but assumes a multidimensional connectivity space (Margulies et al. PNAS 2016).
As a perspective, fcMRI will allow to tailor brain stimulation therapies to the
pathophysiological state of the individual patient.
Target audience
Researchers and/or clinicians doing and interpreting MRI in patients with acute and chronic stroke, for example (neuro-)radiologists, neurologists, neurosurgeons, neuroscientists, MR physicists, and MR-technicians.
Outcome / objectives
After this course learners should better understand
- stroke symptoms as network-related,
- different methods for the assessment of functional connectivity MRI, particularly graph metrics,
- imaging biomarkers for stroke recovery.
Background and purpose
In neurological practice, clinical symptoms after stroke are classically thought to be determined by the location and extent of a focal lesion. Indeed, this lesion-symptom approach – since it has been put forward by Broca and others in the 19th century - has had considerable value for clinical diagnosis and clinical decision making. However, this approach overlooks the fact that very similar focal lesions can be associated with highly divergent neurological symptoms and – on the other hand - that very different focal lesions can produce strikingly similar symptoms. While interindividual anatomical variability may explain some of these findings, a major component underlying this variability is likely better explained by a connectivity/network- based approach, i.e., a conceptual framework in which complex functions (which typically underlie clinical symptoms) are thought to be achieved by a “concert” of connected brain areas. A related concept in clinical neurology is known as Diaschisis, which is based on the observation that a focal lesion can induce impaired function, reduced blood flow and metabolism and even atrophy in distant – but presumably functionally connected - brain areas.
While these considerations are important for our understanding of clinical symptoms in the acute stage of a stroke, they are even more relevant for understanding neurological recovery in the chronic phase of stroke, given that in this phase, the focal lesion remains stable, nevertheless, the disturbed function can still improve – most likely due to functional (connectivity) changes within the network.
Thus, methods which can identify connectivity maps and/or networks in human subjects are particularly interesting for the assessment of patients in their recovery period after stroke. The most promising of these approaches is functional connectivity MRI (fc-MRI). In principal, an assessment of functional connectivity can be performed based on task-based or on resting-state fMRI recordings. While some very interesting fcMRI studies have been performed based on task-based fMRI (e.g., Grefkes et al. 2008), the main advantage of fcMRI based on resting-state fMRI recordings is the universal applicability in patients even with severe deficits (not requiring any task) and the fact that findings are not confounded by quality or strategy of task performance. Therefore, in this lecture, the focus will be on fcMRI based on resting-state recordings as initiated by Biswal et al. (Biswal et al. 1995).
Overview on methods and results
The first pioneering studies of resting-state based fcMRI in patients after stroke tested functional connectivity, especially interhemispheric connectivity in one or few individual networks, e.g., the attentional network or the motor network (He et al. 2007, Carter et al. 2010). Subsequent studies assessed differential effects of focal brain lesions on several functional brain networks and related these changes to behavioral assessments (Ovadia-Caro et al. 2013, Siegel et al. 2016). These studies showed that functional connectivity was preferentially altered in networks within which a focal lesion was located, however, they also indicated that network alterations could spread beyond the predefined networks. A recent approach in resting-state based fcMRI research tried to overcome the assumption of “fixed separate connectivity networks” but rather assumed a “connectivity space” the dimensions of which are termed gradients of connectivity features (Margulies et al. 2017). Bayrak et al. observed that in patients after stroke connectivity changes during the first week after symptom onset were specific for certain gradients of this connectivity space, i.e., depended on the distance from the lesion along those gradients rather than the anatomical distance (Bayrak et al. 2018).
In several reports other measures based on graph theory were used to assess changes in functional brain organization after stroke: For example, Zhu et al. described so called “small worldness” features in stroke patients versus controls and found that stroke patients had “a lower shortest path length and higher global efficiency” (Zhu et al. 2017). Termenon et al. defined a “hub disruption index” and showed a reduction of this index in the contralesional hemisphere of stroke patients compared to healthy controls (Termenon et al. 2016).
Conclusion and Outlook
In summary, several studies employing different approaches of fcMRI based on resting-state fMRI recordings have demonstrated pronounced changes in network connectivity in patients after stroke and some of them indicated a correlation to clinical and behavioral findings. While these findings are extremely promising, most studies so far are to be categorized as pilot studies. As a next step, large scale prospective multi-center studies sharing MRI data and associated clinical data should be performed in order to establish a valid neuroimaging biomarker for functional recovery after stroke.
An exciting therapeutic perspective lies in the combination of fcMRI with brain stimulation therapies such as transcranial magnetic stimulation (TMS), transcranial direct current stimulation (TDCS) and brain computer interface (BCI). Findings of fcMRI will be useful in tailoring these stimulation approaches to the patients regarding the site of stimulation and the type of stimulation (inhibitory, excitatory) and as a biomarker for therapeutic success.
Bayrak Ş, Khalil AA, Villringer K, Fiebach JB, Villringer A, Margulies DS, Ovadia-Caro S (2018). The impact of ischemic stroke on connectivity gradients bioRxiv link:https://www.biorxiv.org/content/10.1101/481689v1
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