TY - JOUR
T1 - Post-stroke deficit prediction from lesion and indirect structural and functional disconnection
AU - Salvalaggio, Alessandro
AU - de Filippo De Grazia, Michele
AU - Zorzi, Marco
AU - de Schotten, Michel Thiebaut
AU - Corbetta, Maurizio
N1 - Funding Information:
Drs Michael Ferguson and Michael Fox for providing us with data from Ferguson et al. (2019). Padova Neuroscience Center PhD doctorate program to A.S.; NIH grant R01 NS095741; FLAG-ERA JTC 2017; Dipartimento Eccellenza del MIUR Neuro-DiP; Progetto Strategico UniPD to M.C.; the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 818521) to M.TdS.; the Italian Ministry of Health under Grant Number RF-2013-02359306 to M.Z.
Publisher Copyright:
© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Behavioural deficits in stroke reflect both structural damage at the site of injury, and widespread network dysfunction caused by structural, functional, and metabolic disconnection. Two recent methods allow for the estimation of structural and functional disconnection from clinical structural imaging. This is achieved by embedding a patient's lesion into an atlas of functional and structural connections in healthy subjects, and deriving the ensemble of structural and functional connections that pass through the lesion, thus indirectly estimating its impact on the whole brain connectome. This indirect assessment of network dysfunction is more readily available than direct measures of functional and structural connectivity obtained with functional and diffusion MRI, respectively, and it is in theory applicable to a wide variety of disorders. To validate the clinical relevance of these methods, we quantified the prediction of behavioural deficits in a prospective cohort of 132 first-time stroke patients studied at 2 weeks post-injury (mean age 52.8 years, range 22-77; 63 females; 64 right hemispheres). Specifically, we used multivariate ridge regression to relate deficits in multiple functional domains (left and right visual, left and right motor, language, spatial attention, spatial and verbal memory) with the pattern of lesion and indirect structural or functional disconnection. In a subgroup of patients, we also measured direct alterations of functional connectivity with resting-state functional MRI. Both lesion and indirect structural disconnection maps were predictive of behavioural impairment in all domains (0.16 5 R2 5 0.58) except for verbal memory (0.05 5 R2 5 0.06). Prediction from indirect functional disconnection was scarce or negligible (0.01 5 R2 5 0.18) except for the right visual field deficits (R2 = 0.38), even though multivariate maps were anatomically plausible in all domains. Prediction from direct measures of functional MRI functional connectivity in a subset of patients was clearly superior to indirect functional disconnection. In conclusion, the indirect estimation of structural connectivity damage successfully predicted behavioural deficits post-stroke to a level comparable to lesion information. However, indirect estimation of functional disconnection did not predict behavioural deficits, nor was a substitute for direct functional connectivity measurements, especially for cognitive disorders.
AB - Behavioural deficits in stroke reflect both structural damage at the site of injury, and widespread network dysfunction caused by structural, functional, and metabolic disconnection. Two recent methods allow for the estimation of structural and functional disconnection from clinical structural imaging. This is achieved by embedding a patient's lesion into an atlas of functional and structural connections in healthy subjects, and deriving the ensemble of structural and functional connections that pass through the lesion, thus indirectly estimating its impact on the whole brain connectome. This indirect assessment of network dysfunction is more readily available than direct measures of functional and structural connectivity obtained with functional and diffusion MRI, respectively, and it is in theory applicable to a wide variety of disorders. To validate the clinical relevance of these methods, we quantified the prediction of behavioural deficits in a prospective cohort of 132 first-time stroke patients studied at 2 weeks post-injury (mean age 52.8 years, range 22-77; 63 females; 64 right hemispheres). Specifically, we used multivariate ridge regression to relate deficits in multiple functional domains (left and right visual, left and right motor, language, spatial attention, spatial and verbal memory) with the pattern of lesion and indirect structural or functional disconnection. In a subgroup of patients, we also measured direct alterations of functional connectivity with resting-state functional MRI. Both lesion and indirect structural disconnection maps were predictive of behavioural impairment in all domains (0.16 5 R2 5 0.58) except for verbal memory (0.05 5 R2 5 0.06). Prediction from indirect functional disconnection was scarce or negligible (0.01 5 R2 5 0.18) except for the right visual field deficits (R2 = 0.38), even though multivariate maps were anatomically plausible in all domains. Prediction from direct measures of functional MRI functional connectivity in a subset of patients was clearly superior to indirect functional disconnection. In conclusion, the indirect estimation of structural connectivity damage successfully predicted behavioural deficits post-stroke to a level comparable to lesion information. However, indirect estimation of functional disconnection did not predict behavioural deficits, nor was a substitute for direct functional connectivity measurements, especially for cognitive disorders.
KW - Connectivity
KW - Functional disconnection
KW - Lesion
KW - Stroke
KW - Structural disconnection
UR - http://www.scopus.com/inward/record.url?scp=85088267547&partnerID=8YFLogxK
U2 - 10.1093/brain/awaa156
DO - 10.1093/brain/awaa156
M3 - Article
C2 - 32572442
AN - SCOPUS:85088267547
VL - 143
SP - 2173
EP - 2188
JO - Brain
JF - Brain
SN - 0006-8950
IS - 7
ER -