Relative contributions of lesion location and lesion size to predictions of varied language deficits in post-stroke aphasia.

Melissa Thye,Daniel Mirman

doi:10.1016/j.nicl.2018.10.017

Abstract

Despite the widespread use of lesion-symptom mapping (LSM) techniques to study associations between location of brain damage and language deficits, the prediction of language deficits from lesion location remains a substantial challenge. The present study examined several factors which may impact lesion-symptom prediction by (1) testing the relative predictive advantage of general language deficit scores compared to composite scores that capture specific deficit types, (2) isolating the relative contribution of lesion location compared to lesion size, and (3) comparing standard voxel-based lesion-symptom mapping (VLSM) with a multivariate method (sparse canonical correlation analysis, SCCAN). Analyses were conducted on data from 128 participants who completed a detailed battery of psycholinguistic tests and underwent structural neuroimaging (MRI or CT) to determine lesion location. For both VLSM and SCCAN, overall aphasia severity (Western Aphasia Battery Aphasia Quotient) and object naming deficits were primarily predicted by lesion size, whereas deficits in Speech Production and Speech Recognition were better predicted by a combination of lesion size and location. The implementation of both VLSM and SCCAN raises important considerations regarding controlling for lesion size in lesion-symptom mapping analyses. These findings suggest that lesion-symptom prediction is more accurate for deficits within neurally-localized cognitive systems when both lesion size and location are considered compared to broad functional deficits, which can be predicted by overall lesion size alone.

Highlights

Aphasia is an impairment of language that occurs in up to 46% of stroke survivors and is associated with substantial negative effects on health and quality of life, including reduced participation in activities across all domains of daily life and increased likelihood of death within 2 years of stroke (Boehme et al, 2016; Flowers et al, 2016; Hilari, 2011)
For the Speech Recognition deficit scores, sparse canonical correlation analysis (SCCAN) identified a very small region primarily in Heschl's gyrus. This is entirely consistent with prior lesion-symptom mapping (LSM) studies that have identified the left posterior superior temporal lobe as critical for speech recognition, but the identified region was far smaller than those reported in prior studies
The deficit scores were weakly to moderately associated with lesion size, with higher correlations observed for Western Aphasia Battery (WAB) AQ (r = −0.55, p < .01), Philadelphia Naming Task (PNT) (r = −0.45, p < .01), and Semantics (r = −0.32, p < .01) and weaker correlations observed for Speech Production (r = −0.28, p < .01) and Speech Recognition (r = −0.04, p = .66)

Summary

Introduction

Aphasia is an impairment of language that occurs in up to 46% of stroke survivors and is associated with substantial negative effects on health and quality of life, including reduced participation in activities across all domains of daily life and increased likelihood of death within 2 years of stroke (Boehme et al, 2016; Flowers et al, 2016; Hilari, 2011). A more recent study used random forests with a multimodal combination of structural lesion data and functional and structural connectivity data (Pustina et al, 2017b) to account for nearly 80% of the variance on the Philadelphia Naming Task (PNT) and composite measures from the Western Aphasia Battery (WAB). These studies are promising, though they vary in the kind of lesion data used and the type of deficits predicted. The latter issue may be important as one group highlighted the utility of using a composite score comprised of several measures assessing the same domain of language (speech production) compared to individual scores from single-item measures (Hope et al, 2013)

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