TY  - JOUR
AU  - Akdeniz, Aslı
AU  - Ríos, Ana Sofía
AU  - Temuulen, Uchralt
AU  - Fiebach, Jochen B
AU  - Villringer, Kersten
AU  - Ali, Huma Fatima
AU  - Khalil, Ahmed
AU  - Grittner, Ulrike
AU  - Liman, Thomas G.
AU  - Endres, Matthias
AU  - Kufner, Anna
TI  - Lesion Network Mapping of Acute Neurological Deficits and Its Prognostic Value After Ischemic Stroke.
JO  - NeuroImage: Clinical
VL  - 48
SN  - 2213-1582
CY  - [Amsterdam u.a.]
PB  - Elsevier
M1  - DZNE-2025-01369
SP  - 103895
PY  - 2025
AB  - Predicting functional recovery after ischemic stroke is vital for guiding clinical care. This study investigated whether lesion network mapping (LNM), a technique for modeling symptom-specific brain networks, can improve outcome prediction of functional recovery up to one-year post-stroke.We pooled data from two prospective stroke cohorts (1000Plus and PROSCIS-B; N = 565). Seven NIHSS-derived symptom networks were generated using LNM based on NIHSS sub-scores on admission (i.e., consciousness, language, motor, sensory, vision, neglect and ataxia). Lesion masks derived from MRI (within 7 days) were intersected with each symptom network to calculate individual network damage scores. Functional outcome was defined by the modified Rankin Scale (mRS) at 3 months (1000Plus) or 12 months (PROSCIS-B). Ordinal logistic regression models were performed to evaluate additional predictive value of LNM: Model 1 included age, lesion volume, and presence of selected neurological deficits; Model 2 included age, lesion volume, and NIHSS-derived network damage scores. Models were compared using pseudo-R2 and AIC.Patients had a mean age of 68 years and a median NIHSS of 3 (IQR 1-5). LNM revealed distinct, symptom-specific networks, with corresponding damage scores that were higher in patients exhibiting the respective deficits compared to those without. However, inclusion of these scores did not enhance the predictive accuracy of functional outcomes beyond that achieved with clinical variables alone (Model 1 vs. Model 2: pseudo-R2: 0.0468 vs. 0.0159; AIC:1730.598 vs. 1769.222).LNM-derived scores reflected symptom topography but did not enhance prediction of functional recovery. While promising as a mechanistic tool, the clinical utility of LNM-based damage metrics for prognostication remains limited and requires further validation.
KW  - Humans
KW  - Male
KW  - Female
KW  - Ischemic Stroke: diagnostic imaging
KW  - Ischemic Stroke: physiopathology
KW  - Ischemic Stroke: complications
KW  - Ischemic Stroke: pathology
KW  - Aged
KW  - Middle Aged
KW  - Prognosis
KW  - Magnetic Resonance Imaging: methods
KW  - Recovery of Function: physiology
KW  - Nerve Net: diagnostic imaging
KW  - Nerve Net: pathology
KW  - Nerve Net: physiopathology
KW  - Prospective Studies
KW  - Aged, 80 and over
KW  - Brain: diagnostic imaging
KW  - Brain: pathology
KW  - Connectome (Other)
KW  - Functional outcome (Other)
KW  - Ischemic stroke (Other)
KW  - Lesion-network mapping (Other)
KW  - Stroke severity (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:41176879
C2  - pmc:PMC12621467
DO  - DOI:10.1016/j.nicl.2025.103895
UR  - https://pub.dzne.de/record/282908
ER  -