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@ARTICLE{Knab:169345,
author = {Knab, Felix and Koch, Stefan Paul and Major, Sebastian and
Farr, Tracy D. and Mueller, Susanne and Euskirchen, Philipp
and Eggers, Moritz and Kuffner, Melanie T. C. and Walter,
Josefine and Dreier, Jens P. and Endres, Matthias and
Dirnagl, Ulrich and Wenger, Nikolaus and Hoffmann, Christian
J. and Boehm-Sturm, Philipp and Harms, Christoph},
title = {{P}rediction of {S}troke {O}utcome in {M}ice {B}ased on
{N}on-{I}nvasive {MRI} and {B}ehavioral {T}esting},
reportid = {DZNE-2023-00120},
year = {2022},
abstract = {Prediction of post-stroke outcome using the degree of
subacute deficit or magnetic resonance imaging metrics is
well studied in humans. While mice are the most commonly
used animals in pre-clinical stroke research, systematic
analysis of outcome predictors is lacking.Methods Data from
a total of 13 studies that included 45 minutes of middle
cerebral artery occlusion on 148 mice were pooled. Motor
function was measured using a modified protocol for the
staircase test of skilled reaching. Phases of subacute and
residual deficit were defined. Magnetic resonance images of
stroke lesions were co-registered on the Allen Mouse Brain
Atlas to characterize stroke topology. Different random
forest prediction models that either used motor-functional
deficit or imaging parameters were generated for the
subacute and residual deficits.Results We detected both a
subacute and residual motor-functional deficit after stroke
in mice. Different functional severity grades and recovery
trajectories could be observed. We found that lesion volume
is the best predictor of subacute deficit. The residual
deficit can be predicted most accurately by the degree of
the subacute deficit. When using imaging parameters for the
prediction of the residual deficit, including information
about the lesion topology increases prediction accuracy. A
subset of anatomical regions within the ischemic lesion have
an outstanding impact on the prediction of long-term
outcome. Prediction accuracy depends on the degree of
functional impairment.Conclusions For the first time, we
identified and characterized predictors of post-stroke
outcome in a large cohort of mice and found strong
concordance with clinical data. In the future, using outcome
prediction can improve the design of pre-clinical studies
and guide intervention decisions.},
cin = {AG Endres / AG Dirnagl},
cid = {I:(DE-2719)1811005 / I:(DE-2719)1810002},
pnm = {353 - Clinical and Health Care Research (POF4-353)},
pid = {G:(DE-HGF)POF4-353},
typ = {PUB:(DE-HGF)25},
doi = {10.1101/2022.05.13.491869},
url = {https://pub.dzne.de/record/169345},
}