Altered temporal variability-based functional reorganization of brain networks predicts motor outcome after stroke

 Predicting recovery rather than delivering recovery IS COMPLETE INCOMPETENCE!

I take no prisoners in trying to get stroke solved and that means a lot of dead wood needs to be removed. 

Altered temporal variability-based functional reorganization of brain networks predicts motor outcome after stroke

• Guojun Xu,
• Ling Li,
• Qinyang Li,
• Hewei Wang,
• Mingxia Fan,
• Limin Sun,
• Zhiyong Zhao &
• Hongxing Wang 

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

Background

Dynamic functional connectivity (FC) studies have shown that motor recovery after stroke was associated with functional reorganization of brain networks. However, most previous studies have focused on interregional variability rather than the temporal variability (TV) of specific regions or networks. TV quantifies the dynamic reconfiguration of a region’s or network’s functional connectivity profile over time and reflects neural flexibility.

Purpose

This study investigated functional reorganization in chronic subcortical stroke using TV of brain networks derived from resting-state fMRI.

Methods

Thirty-three patients with left subcortical stroke (LSS), thirty with right subcortical stroke (RSS), and fifty-six age- and sex-matched healthy controls (HCs) were enrolled. Stroke patients underwent resting-state fMRI and Upper Extremity Fugl-Meyer Assessment (UE-FMA) at two time points. TV was computed to characterize dynamic functional connectivity at regional, intra-network, and inter-network levels. Group differences were assessed using one-way ANCOVA with post hoc tests. Linear regression was used to examine associations between TV and motor outcomes. The false discovery rate was used to multiple comparisons correction.

Results

Compared with HCs, both LSS and RSS showed significantly reduced TV in the right frontal-cingulate regions, the somatomotor hand network (SSH), and the connections between SSH and higher-order cognitive networks (all p < 0.05, |Cohen’s d| > 0.49). Increased TV was observed in the left postcentral gyrus, inferior frontal gyrus, cerebellar network (CEN), and somatomotor mouth network (all p < 0.05, |Cohen’s d| > 0.48). Relative to LSS, RSS exhibited additional TV reductions in the right middle occipital gyrus, orbital middle frontal gyrus, default mode network (DMN), and interactions among higher-order cognitive networks (all p < 0.05, |Cohen’s d| > 0.65). Notably, TV in the right opercular inferior frontal gyrus (IFGoperc) (β = 102.69, adjusted p = 6.4 × 10^− 5) and CEN (β = 27.87, adjusted p = 0.011) at the first observation positively correlated with UE-FMA scores at follow-up, with effects modulated by lesion laterality.

Conclusion

TV captures multiscale functional reorganization in chronic subcortical stroke involving motor, cognitive, and sensory networks. TV of the right IFGoperc showed potential as a neuroimaging biomarker for predicting post-stroke motor recovery.

Could the Early Disinhibition of the Unaffected Motor Cortex Predict Motor Recovery After Stroke?

 Why the fuck are you blithering idiots predicting recovery rather than delivering recovery?  You don't have two neurons to rub together for a spark of intelligence?

Could the Early Disinhibition of the Unaffected Motor Cortex Predict Motor Recovery After Stroke?

Rosso, MD, PhD https://orcid.org/0000-0001-7236-1508  charlotte.rosso@gmail.com, Lina Daghsen, PhD https://orcid.org/0000-0002-6617-4666, Justine Bouvier,BSc, Thomas Checkouri, MD, Sarah Millot MD, Flore MD, PhD, Damien Galanaud, MD, PhD https://orcid.org/0000-0002-9285-8121, Romain Valabregue PhD, Pierre Pouget, PhD, Jean-Charles Lamy,PhD https://orcid.org/0000-0002-9078-3429, and Emmanuel Roze, MD, PhD https://orcid.org/0000-0001-9727-3459 Author Info & AffiliationsStroke New online

https://doi.org/10.1161/STROKEAHA.125.051614

Abstract

BACKGROUND:

Whether intracortical inhibition in the unaffected hemisphere is related to motor recovery after stroke may depend on the status of corticospinal excitability in the affected hemisphere. The aims are (1) to identify the presence of short-latency intracortical inhibition (SICI) in the acute phase according to the motor-evoked potential (MEP) status of the patients and (2) to investigate whether unaffected hemisphere SICI is associated with motor recovery at 3 months in subgroups of patients (with or without an MEP).

METHODS:

We enrolled 95 patients with stroke (median age, 68 years; interquartile range, 61–78 years, sex: 61% males, n=58) with upper extremity weakness persistent on day 3 and analyzed 83 patients (median age, 67 years; interquartile range, 59–77 years, sex: 65% males, n=54) in this single-center study (from August 2022 to May 2024). Transcranial magnetic stimulation was performed before day 7 to determine the presence of MEP and to record SICI in both hemispheres. The motor evaluation was performed on day 7 using the Fugl-Meyer Assessment of the Upper Extremity and at 3 months by the Fugl-Meyer Assessment of the Upper Extremity and the Action Research Arm Test.

RESULTS:SICI was present in the unaffected hemisphere in 58% of MEP− patients (patients with no evocable MEP in the first dorsal interosseous; n=14/24) and 57% of MEP+ patients (patients with evocable MEP in the first dorsal interosseous; n=33/57, 2 missing data). The presence of SICI in the unaffected hemisphere in MEP− patients (but not in MEP+) was associated with better motor recovery (Spearman rank coefficient, −0.514 [95% CI, −0.774 to −0.106]; P=0.017) and was an independent predictor of motor recovery on a stepwise multiple linear regression, along with the Fugl-Meyer Assessment of the Upper Extremity at day 7 (R²=54%, P=0.002).

CONCLUSIONS:Implementing intracortical inhibition could improve prediction models in future studies for severe patients without an MEP whose recovery trajectories are hard to predict and for whom clinical rehabilitation decisions are difficult to make.Graphical Abstract

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Advancing Post-Stroke Outcome Prediction with Movement-Specific Structural and Functional Brain Atlases

 Predictions of recovery ARE USELESS FOR SURVIVORS! Deliver EXACT 100% RECOVERY PROTOCOLS! That's what is needed; NOT this useless crapola!

Advancing Post-Stroke Outcome Prediction with Movement-Specific Structural and Functional Brain Atlases

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https://doi.org/10.1016/j.neuroimage.2025.121376Get rights and content

Under a Creative Commons license

Open access

Highlights

• •
  Developed a functional brain atlas from ALE meta-analysis of upper limb motor tasks
• •
  Quantified lesion load using structural and functional brain atlases in stroke patients
• •
  ROI-based lesion load explained 6% additional variance beyond baseline FMUE
• •
  Total lesion load added minimal predictive value over baseline FMUE alone
• •
  SSCA and SMAA offered compact, movement-specific lesion quantification tools

Abstract

Stroke is a leading cause of death and disability, with motor deficits contributing significantly to post-stroke disability. Brain atlases hold promise for predicting motor outcomes post-stroke, but existing tools often lack comprehensive coverage of motor-related brain regions and do not integrate both structural and functional measures. This retrospective longitudinal study aimed to develop and evaluate neuroimaging biomarkers for predicting post-stroke motor outcomes by constructing comprehensive sensorimotor brain atlases. We developed two novel atlases: a sensorimotor structural connectivity atlas (SSCA), integrating three existing tractography-based atlases, and a probabilistic sensorimotor activation-based atlas (SMAA), derived from an ALE meta-analysis of 3,252 activation foci related to motor execution and learning. We assessed their predictive value by analysing the relationship between baseline lesion load and Action Research Arm Test scores at 12 weeks post-ischemic stroke in 142 patients, using multivariable linear regression models. Lesion loads from five published atlases were also quantified for comparison. While the SSCA demonstrated moderate predictive performance, it was outperformed by the Sensorimotor Area Tract Template, indicating that broader tract coverage did not improve prediction. Despite comprising only 12.8% of the Brainnetome atlas volume, the SMAA achieved comparable performance with reduced model complexity. Overall, these atlas-based lesion load metrics correlated with upper limb motor outcomes but provided only limited additional predictive value beyond baseline Fugl-Meyer Assessment for Upper Extremity scores, highlighting the need for refinement and future multimodal approaches.

Graphical Abstract

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Proximal Fugl-Meyer Assessment Scores Predict Clinically Important Upper Limb Improvement After Three Stroke Rehabilitative Interventions

 Predictions like this are useless! WHAT ARE THE EXACT PROTOCOLS THAT DELIVER RECOVERY! Since you failed at stroke research, you're all fired!

Proximal Fugl-Meyer Assessment Scores Predict Clinically Important Upper Limb Improvement After Three Stroke Rehabilitative Interventions

Ya-yun Lee PhD, PT a,∗ ∙ Yu-wei PhD, OT Wu, ScD, OTRb ∙ Keh-chung ScD, OTRc kehchunglin@ntu.edu.tw

Abstract

To identify the baseline motor characteristics of the patients who responded to 3 prominent intervention programs. Observational cohort study. Outpatient rehabilitation clinics. Participants Individuals with chronic stroke (N=174).>

Interventions

Participants received 30 hours of constraint-induced movement therapy (CIMT), robot-assisted therapy, or mirror therapy (MT).The primary outcome measure was the change score of the Upper Extremity Fugl-Meyer Assessment (UE-FMA). The potential predicting variables were baseline proximal, distal, and total UE-FMA and Action Research Arm Test scores. We combined polynomial regression analyses and the minimal clinically important difference to stratify the patients as responders and nonresponders for each intervention approach.

Results

Baseline proximal UE-FMA scores significantly predicted clinically important improvement on the primary outcome measure after all 3 interventions. Participants with baseline proximal UE-FMA scores of approximately <30 benefited significantly from CIMT and robot-assisted therapy, whereas participants with scores between 21 and 35 demonstrated significant improvement after MT. Baseline distal and total UE-FMA and Action Research Arm Test scores could also predict upper limb improvement after CIMT and MT, but not after robot-assisted therapy.

Conclusions

This study could inform clinicians about the selection of suitable rehabilitation approaches to help patients achieve clinically meaningful improvement in upper extremity function.

Quantitative insights into stroke recovery utilizing delayed vessel ratio from color-coded multiphase computed tomography angiography

Predicting recovery is totally fucking useless. DELIVER EXACT RECOVERY PROTOCOLS! I'd fire anyone doing prediction research, it's useless!

 Quantitative insights into stroke recovery utilizing delayed vessel ratio from color-coded multiphase computed tomography angiography

Yu Lin^1,2,3†, Xiaoxiao Zhang^2†, Zhen Xing¹, Xiefeng Yang¹, Qingwen Tong⁴, Shaomao Lv², Jinan Wang^2,3 and Dairong Cao^1,5,6,7*

¹Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China

²Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, School of Clinical Medicine of Fujian Medical University, Xiamen, China

³Xiamen Radiology Quality Control Center, Zhongshan Hospital Affiliated to Xiamen University, School of Clinical Medicine of Fujian Medical University, Xiamen, China

⁴Department of Health Examination, Xiamen Humanity Hospital Fujian Medical University, Xiamen, China

⁵Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital of Fujian Medical University, Fuzhou, China

⁶Fujian Provincial Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China

⁷Key Laboratory of Radiation Biology of Fujian Higher Education Institutions, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China

Edited by
Alan Wang, The University of Auckland, New Zealand

Reviewed by
Rodrigo Assar, University of Chile, Chile
Jihoon Kang, Seoul National University Bundang Hospital, Republic of Korea

*Correspondence
Dairong Cao, dairongcao@163.com

^†These authors have contributed equally to this work and share first authorship

Received 30 January 2025
Accepted 03 June 2025
Published 18 June 2025

Citation
Lin Y, Zhang X, Xing Z, Yang X, Tong Q, Lv S, Wang J and Cao D (2025) Quantitative insights into stroke recovery utilizing delayed vessel ratio from color-coded multiphase computed tomography angiography. Front. Neurol. 16:1568717. doi: 10.3389/fneur.2025.1568717

Background and objective: 

The color-coded multiphase computed tomography angiography (cmCTA) is an accredited technique that employs color-coding to visually depict the temporal dynamics of collateral blood flow in patients with acute ischemic stroke (AIS). This research aimed to assess the quantification of cmCTA in AIS patients for characterizing arterial and venous collateral flow, and predicting functional outcomes.

Methods: 

A retrospective study was performed on a consecutive cohort of AIS patients with large vessel occlusion who underwent cmCTA scan and reconstruction. Collateral ratio and delayed vessel ratio (DVR) were determined through semi-automatic delineation and calculation on the anterior cerebral artery regions and Alberta Stroke Program Early CT (ASPECT) Score regions of cmCTA maps. Deep venous outflow (DVO) and superficial venous outflow (SVO) scores were assessed using a 6-point scale. Logistic regression and propensity score were applied to confounding factors adjustment and model construction. Receiver operating characteristic curve, calibration curve, and decision curve analysis were utilized to evaluate the prediction model of functional independence and excellent recovery.

Results: 

Well-developed arterial collaterals as depicted by low DVR and adequate venous collaterals as indicated by high DVO or SVO were correlated with better outcomes (All p < 0.001). Adjusted DVR showed areas under the curve of 0.81–0.90 for predicting functional independence and excellent recovery. Adjusted DVO showed areas under the curve of 0.88 for predicting functional independence and excellent recovery. Each prediction model demonstrated good precision and net benefit.

Conclusion: 

The application of DVR and other parameters in cmCTA offers a quantitative perspective on the conventional ASPECT scoring scheme utilizing grayscale CT images. DVR from cmCTA may enhance pre-treatment collateral assessment and post-treatment outcome prediction in AIS, facilitating informed treatment decisions.