Vascular Cognitive Impairment After Mild Stroke: Connectomic Insights, Neuroimaging, and Knowledge Translation

We don't need to simply detect vascular cognitive impairment. WHAT THE FUCK ARE YOU DOING TO PREVENT THAT?  OH, NOTHING? You're fired!

Vascular Cognitive Impairment After Mild Stroke: Connectomic Insights, Neuroimaging, and Knowledge Translation

Jess A. Holguin^1*, John L. Margetis¹, Anisha Narayan², Grant M. Yoneoka³ and Andrei Irimia^4,5*

• ¹T.H. Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
• ²Tulane University School of Medicine, Tulane University, New Orleans, LA, United States
• ³John A. Burns School of Medicine, University of Hawai‘i at Mānoa, Honolulu, HI, United States
• ⁴Leonard Davis School of Gerontology, Ethel Percy Andrus Gerontology Center, University of Southern California, Los Angeles, CA, United States
• ⁵Corwin D. Denney Research Center, Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States

Contemporary stroke assessment protocols have a limited ability to detect vascular cognitive impairment (VCI), especially among those with subtle deficits. This lesser-involved categorization, termed mild stroke (MiS), can manifest compromised processing speed that negatively impacts cognition. From a neurorehabilitation perspective, research spanning neuroimaging, neuroinformatics, and cognitive neuroscience supports that processing speed is a valuable proxy for complex neurocognitive operations, insofar as inefficient neural network computation significantly affects daily task performance. This impact is particularly evident when high cognitive loads compromise network efficiency by challenging task speed, complexity, and duration. Screening for VCI using processing speed metrics can be more sensitive and specific. Further, they can inform rehabilitation approaches that enhance patient recovery, clarify the construct of MiS, support clinician-researcher symbiosis, and further clarify the occupational therapy role in targeting functional cognition. To this end, we review relationships between insult-derived connectome alterations and VCI, and discuss novel clinical approaches for identifying disruptions of neural networks and white matter connectivity. Furthermore, we will frame knowledge translation efforts to leverage insights from cutting-edge structural and functional connectomics research. Lastly, we highlight how occupational therapists can provide expertise as knowledge brokers acting within their established scope of practice to drive substantive clinical innovation.

Introduction

Stroke is the most frequent cause of disability in the United States (Ovbiagele and Nguyen-Huynh, 2011), a fact that spurs investigation into the nature and variability of infarct-related deficits along a continuum of impairment. The literature is replete with widely accepted functional characterizations of moderate through severe stroke (Murphy et al., 2001; Hodics et al., 2012; Rost et al., 2016), with less clarity available on mild clinical presentations (Brott et al., 1989; Roberts et al., 2020). This uncertainty stems from the absence of a precise taxonomy for characterizing the mild stroke (MiS) population (Roberts et al., 2020). In clinical practice, the lack of a consensus definition precludes consistency in evaluation and treatment approaches and obscures understanding of this population’s needs.

Ongoing work to develop an accord on MiS codification can benefit both research and clinical practice. In their systematic review on downstream effects of inconsistent MiS classification, Roberts et al. (2020) discuss 10 distinct definitions present in the literature. This lack of diagnostic and taxonomic uniformity potentiates knowledge translation efforts targeting the depth and breadth of understanding within this important stroke practice and research area. However, even a robust consensus definition cannot explain mechanisms that drive variation in post-stroke disability, especially regarding shared and distinct underpinnings among each NIH Stroke Scale (NIHSS) severity level (National Institute of Neurological Disorders and Stroke, 2011).

Within this review, we address MiS-relevant associations between vascular cognitive impairment (VCI), processing speed (PS), and neural network efficiency, as informed by insights from neuroimaging and connectomics research. We present evidence suggesting that established norms for key neurocognitive assessments can be used as proxies for detecting potentially overlooked VCI. Infusing emerging theoretical perspectives from multiple academic disciplines, we review approaches that can fuel substantial clinical innovation. In particular, we focus on using proxy-defined, threshold-specific instances of dysfunction that are scalable according to premorbid capacities and inherent daily routine demands. Drawing from neuroimaging-informed models employed to predict and monitor stroke recovery, we argue that performance capacity can be quantified by the degree of dissociation between available and necessary performance skills. Such quantification could empower clinicians and MiS survivors to more strategically consider interrelationships between current abilities and requisite progress along an ecologically valid, individualized recovery timeline.

We also examine three intersecting themes that provide a framework for early MiS care innovation and highlight paths to advance clinical investigation targeting health and wellbeing. After providing background on essential considerations of stroke and associated cognitive sequelae, we first review the problem of MiS-associated-VCI (MiS-VCI) underdetection and clarify the consequences of imprecisely characterizing stroke-derived neurocognitive dysfunction. Secondly, we examine the promise of knowledge translation efforts to improve stroke care and address priorities articulated by healthcare systems and research funding agencies. Thirdly, we overview and delineate knowledge relevant to MiS-VCI rehabilitation that derives from cutting-edge neuroanatomic, structural, and functional connectomics research. These studies employ advanced neuroimaging technologies plus conventional computed tomography (CT) and magnetic resonance imaging (MRI). Importantly, we focus on PS as a proxy for the integrity of neural networks and neurocognitive capacities. Lastly, we highlight clinical implications and future directions by providing evidence and arguments supporting more comprehensive MiS-VCI screening in early stroke care and emphasize the pivotal role of occupational therapy (OT) in addressing functional cognition.

While calling attention to the valuable confluence of contemporary research findings and clinical stroke rehabilitation practices, we will discuss literature ranging from the acute to more chronic phases of recovery. Beyond temporal considerations, foundational links between network theory and neurological insults are influenced by a broad range of factors such as demographic characteristics, lesion laterality, and even mechanisms of injury (e.g., ischemic vs. hemorrhagic stroke vs. traumatic brain injury). Herein, we do not focus on such differentiating factors, as it would far exceed the scope of this endeavor and is the likely purview of future prospective data-analytic studies. We do, however, discuss in detail the findings from conceptual and applied perspectives on an overarching construct poised to drive innovation in clinical practice. Please see Table 1. for a summary of constructs and interrelationships.

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