Publicaciones: marzo 2025

Ledged Beam Walking Test Automatic Tracker: Artificial intelligence-based functional evaluation in a stroke model

Ruiz-Vitte A, Gutiérrez-Fernández M, Laso-García F et al. Comput Biol Med. 2025 Mar;186:109689. doi: 10.1016/j.compbiomed.2025.109689. Epub 2025 Jan 24. PMID: 39862465.

https://pubmed.ncbi.nlm.nih.gov/39862465/

Abstract: The quantitative evaluation of motor function in experimental stroke models is essential for the preclinical assessment of new therapeutic strategies that can be transferred to clinical research; however, conventional assessment tests are hampered by the evaluator’s subjectivity. We present an artificial intelligence-based system for the automatic, accurate, and objective analysis of target parameters evaluated by the ledged beam walking test, which offers higher sensitivity than the current methodology based on manual and visual counting. This system employs a residual deep network model, trained with DeepLabCut (DLC) to extract target paretic hindlimb coordinates, which are categorized to provide a ratio measurement of the animal’s neurological deficit. The results correlate with the measurements performed by a professional observer and have greater reproducibility, easing the analysis of motor deficits and providing a reliable and useful tool applicable to other diseases causing motor deficits.

Funding: This study was supported by the Instituto de Salud Carlos III (ISCIII) PI20/00243, co-funded by the European Union; RICORS network RD21/ 0006/0012 and the Next Generation EU funding that finances the actions of the Recovery and Resilience Mechanism; Miguel Servet CPII20/ 00002 to MG-F; FI18/00026 to FL-G. and FI17/00188 to MCG-F and by the Spanish Ministry of University, Recovery, Transformation and Resilience Plan and the Universidad Aut´ onoma de Madrid under grant CA1/RSUE/2021-00753 to DP-A.

Early automated cerebral edema assessment following endovascular therapy: impact on stroke outcome

Guasch-Jiménez M, Dhar R, Kumar A et al.  J Neurointerv Surg. 2025 Mar 17;17(4):354-359. doi: 10.1136/jnis-2024-021641. PMID: 38637151.

https://pubmed.ncbi.nlm.nih.gov/38637151/

Abstract:

Background Cerebral edema (CED) is associated with poorer outcome in patients with acute ischemic stroke (AIS). The aim of the study was to investigate the factors contributing to greater early CED formation in patients with AIS who underwent endovascular therapy (EVT) and its association with functional outcome.

Methods We conducted a multicenter cohort study of patients with an anterior circulation AIS undergoing EVT. The volume of cerebrospinal fluid (CSF) was extracted from baseline and 24-hour follow-up CT using an automated algorithm. The severity of CED was quantified by the percentage reduction in CSF volume between CT scans (∆CSF). The primary endpoint was a shift towards an unfavorable outcome, assessed by modified Rankin Scale (mRS) score at 3 months. Multivariable ordinal logistic regression analyses were performed. The ∆CSF threshold that predicted unfavorable outcome was selected using receiver operating characteristic curve analysis.

Results We analyzed 201 patients (mean age 72.7 years, 47.8% women) in whom CED was assessable for 85.6%. Higher systolic blood pressure during EVT and failure to achieve modified Thrombolysis In Cerebral Infarction (mTICI) 3 were found to be independent predictors of greater CED. ∆CSF was independently associated with the probability of a one-point worsening in the mRS score (common odds ratio (cOR) 1.05, 95% CI 1.03 to 1.08) after adjusting for age, baseline mRS, National Institutes of Health Stroke Scale (NIHSS), and number of passes. Displacement of more than 25% of CSF was associated with an unfavorable outcome (OR 6.09, 95% CI 3.01 to 12.33) and mortality (OR 6.72, 95% CI 2.94 to 15.32).

Conclusions Early CED formation in patients undergoing EVT was affected by higher blood pressure and incomplete reperfusion. The extent of early CED, measured by automated ∆CSF, was associated with worse outcomes.

Funding: Redes de Investigación Con Objetivos de Resultados en Salud (RICORS) RD21/0006/0006, FEDER (Fondo Europeo de Desarrollo Regional) and PI19/00859 grant, Instituto de Salud Carlos III, Ministry of Science and Innovation (Government of Spain).