Predicting Motor Outcomes Using Atlas-Based Voxel Features of Post-Stroke Neuroimaging: A Scoping Review

You're predicting failure to recover! Useless! Get with the program and do the research that solves the recovery problem!  I'd have you all fired!

Predicting Motor Outcomes Using Atlas-Based Voxel Features of Post-Stroke Neuroimaging: A Scoping Review

Ji-Hun Yoo https://orcid.org/0000-0002-7140-936X, Benjamin Chong, PhD https://orcid.org/0000-0003-4410-5894, […], and Alan Wang, PhD alan.wang@auckland.ac.nz+2View all authors and affiliations

Volume 37, Issue 7

https://doi.org/10.1177/15459683231173668

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• • Abstract
  • Introduction
  • Objectives
  • Methods
  • Data Extraction
  • Results
  • Basic Methodological Summary of Studies
  • Image Modalities and Acquisition
  • Spatial Normalization and Preprocessing
  • Lesion Segmentation
  • Lesion Quantification Measures
  • Regions of Interest Determination
  • Discussion
  • Variability of Atlas Choice and Use
  • Study Limitations and Future Direction
  • Conclusion
  • Declaration of Conflicting Interests
  • Funding
  • ORCID iDs
  • References
• PDF / ePub
• • Cite article
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  • Metrics and citations
  • Figures and tables

Abstract

Background

Atlas-based voxel features have the potential to aid motor outcome prognostication after stroke, but are seldom used in clinically feasible prediction models. This could be because neuroimaging feature development is a non-standardized, complex, multistep process. This is a barrier to entry for researchers and poses issues for reproducibility and validation in a field of research where sample sizes are typically small.

Objectives

The primary aim of this review is to describe the methodologies currently used in motor outcome prediction studies using atlas-based voxel neuroimaging features. Another aim is to identify neuroanatomical regions commonly used for motor outcome prediction.

Methods

A Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol was constructed and OVID Medline and Scopus databases were searched for relevant studies. The studies were then screened and details about imaging modality, image acquisition, image normalization, lesion segmentation, region of interest determination, and imaging measures were extracted.

Results

Seventeen studies were included and examined. Common limitations were a lack of detailed reporting on image acquisition and the specific brain templates used for normalization and a lack of clear reasoning behind the atlas or imaging measure selection. A wide variety of sensorimotor regions relate to motor outcomes and there is no consensus use of one single sensorimotor atlas for motor outcome prediction.

Conclusion

There is an ongoing need to validate imaging predictors and further improve methodological techniques and reporting standards in neuroimaging feature development for motor outcome prediction post-stroke.