Distribution of cerebral age-related white matter changes in relation to risk factors in stroke patients

INTRODUCTION

The distribution of cerebral age-related white matter changes (ARWMC) may be indicative of the underlying etiology and could suggest optimal interventions. We aimed to determine if left ventricular hypertrophy (LVH), a marker of uncontrolled hypertension, along with additional risk factors are associated with the distribution of cerebral ARWMC.

METHODS

We analyzed data of 172 patients from a hospital stroke registry who had acute stroke and brain MRI. We classified lesion location as superficial (frontal, parieto-occipital, or temporal) or deep (basal nuclei) using the ARWMC scale. We defined a superficial ARWMC index as the superficial minus the deep score. We excluded infratentorial lesions and patients with bilateral strokes. Regression analysis analyzed LVH and other relevant clinical factors for independent association with the superficial ARWMC index.

RESULTS

The superficial ARWMC scores ranged from 0 to 6, the deep scores from 0 to 3, and the superficial ARWMC index from -2 to 6. We categorized the superficial ARWMC index as -2 to 1 (n = 65), 2 (n = 50), and 3 - 6 (n = 57). In bivariate analysis, ARWMC distribution was significantly associated with older age, lower household income (HI), and lower serum triglyceride (TG) levels. In multiple logistic regression analysis, higher superficial ARWMC index was significantly associated with lower HI (OR 10.72, 95 % CI 2.30-49.85), lower serum low density cholesterol (LDL) (OR 0.86, 95 % CI 0.75-0.98, per 10 mg/dL), and lower serum TG levels (OR 0.91, 95 % CI 0.85-0.99, per 10 mg/dL). The area under the curve in receiver operating characteristic analysis (95 % CI) for HI was 0.63 (0.49-0.76), LDL level 0.64 (0.51-0.77), and TG level 0.77 (0.65-0.88).

CONCLUSION

In this study, LVH was not associated with the distribution of cerebral ARWMC. Using an alternate classification of ARWMC distribution and analyzing additional risk factors in larger studies may yield further discoveries.

Tolerability of transcranial magnetic stimulation language mapping in children

OBJECTIVE

Transcranial Magnetic Stimulation (TMS) has emerged as a viable non-invasive method for mapping language networks. Little is known about the tolerability of transcranial magnetic stimulation language mapping in children.

METHODS

Children aged 5-18 years underwent bilateral language mapping using repetitive transcranial magnetic stimulation (rTMS) to target 33 sites/hemisphere. Stimulation was delivered at 5 Hz, in 1-2 second bursts, during visual naming and auditory verb generation. Pain unpleasantness and pain intensity were assessed using an unpleasantness visual analog scale (VAS).

RESULTS

49 participants tolerated motor mapping and had repetitive transcranial magnetic stimulation. 35/49 (71%) completed visual naming and 26/49 (53%) completed both visual naming and verb generation. Mean electrical field per participant was 115 V/m. Young age and lower language ability were associated with lower completion. Visual analogue scale scores were significantly higher (6.1 vs. 2.8) in participants who withdrew early compared to those who completed at least visual naming.

CONCLUSIONS

Pain measured by VAS was a major contributor to early withdrawal. However, a complete bilateral map was obtained with one paradigm in 71% of participants. Future studies designed to reduce pain during repetitive transcranial magnetic stimulation over language cortex will boost viability.

SIGNIFICANCE

This study represents the first attempt to characterize tolerability of bilateral repetitive transcranial magnetic stimulation language mapping in healthy children.

Comparing electrical stimulation functional mapping with subdural electrodes and stereoelectroencephalography

OBJECTIVE

Electrical stimulation mapping (ESM) is the clinical standard for functional localization with subdural electrodes (SDE). As stereoelectroencephalography (SEEG) has emerged as an alternative option, we compared functional responses, afterdischarges (ADs), and unwanted ESM-induced seizures (EISs) between the two electrode types.

METHODS

Incidence and current thresholds for functional responses (sensory, motor, speech/language), ADs, and EISs were compared between SDE and SEEG using mixed models incorporating relevant covariates.

RESULTS

We identified 67 SEEG ESM and 106 SDE ESM patients (7207 and 4980 stimulated contacts, respectively). We found similar incidence of language and motor responses between electrode types; however, more SEEG patients reported sensory responses. ADs and EISs occurred less commonly with SEEG than SDE. Current thresholds for language, face motor, and upper extremity (UE) motor responses and EIS significantly decreased with age. However, they were not affected by electrode type, premedication, or dominant hemispheric stimulation. AD thresholds were higher with SEEG than with SDE. For SEEG ESM, language thresholds remained below AD thresholds up to 26 years of age, whereas this relationship was inverse for SDE. Also, face and UE motor thresholds fell below AD thresholds at earlier ages for SEEG than SDE. AD and EIS thresholds were not affected by premedication.

SIGNIFICANCE

SEEG and SDE have clinically relevant differences for functional brain mapping with electrical stimulation. Although evaluation of language and motor regions is comparable between SEEG and SDE, SEEG offers a higher likelihood of identifying sensory areas. A lower incidence of ADs and EISs, and a favorable relationship between functional and AD thresholds suggest superior safety and neurophysiologic validity for SEEG ESM than SDE ESM.

Validating the TeleStroke Mimic Score: A Prediction Rule for Identifying Stroke Mimics Evaluated Over Telestroke Networks

BACKGROUND AND PURPOSE

Up to 30% of acute stroke evaluations are deemed stroke mimics, and these are common in telestroke as well. We recently published a risk prediction score for use during telestroke encounters to differentiate stroke mimics from ischemic cerebrovascular disease derived and validated in the Partners TeleStroke Network. Using data from 3 distinct US and European telestroke networks, we sought to externally validate the TeleStroke Mimic (TM) score in a broader population.

METHODS

We evaluated the TM score in 1930 telestroke consults from the University of Utah, Georgia Regents University, and the German TeleMedical Project for Integrative Stroke Care Network. We report the area under the curve in receiver-operating characteristic curve analysis with 95% confidence interval for our previously derived TM score in which lower TM scores correspond with a higher likelihood of being a stroke mimic.

RESULTS

Based on final diagnosis at the end of the telestroke consultation, there were 630 of 1930 (32.6%) stroke mimics in the external validation cohort. All 6 variables included in the score were significantly different between patients with ischemic cerebrovascular disease versus stroke mimics. The TM score performed well (area under curve, 0.72; 95% confidence interval, 0.70-0.73; P<0.001), similar to our prior external validation in the Partners National Telestroke Network.

CONCLUSIONS

The TM score's ability to predict the presence of a stroke mimic during telestroke consultation in these diverse cohorts was similar to its performance in our original cohort. Predictive decision-support tools like the TM score may help highlight key clinical differences between mimics and patients with stroke during complex, time-critical telestroke evaluations.

Abstract 118: External Validation of the TeleStroke Mimic (TM) Score for Predicting Stroke Mimics Evaluated During Telestroke

Introduction: Up to 30% of acute stroke evaluations are deemed stroke mimics, and these are common in telestroke as well. We recently published a risk prediction score, derived from the Partners TeleStroke Network, for use during telestroke encounters to differentiate stroke mimics (SM) from ischemic cerebrovascular disease (iCVD). Using data from 3 distinct US and European telestroke networks, we sought to externally validate the TM score in a broader population.

Methods: We evaluated the TM score in 1,985 telestroke consults from the University of Utah Telestroke Program (n=190), Georgia Regents University Telestroke Network (n=719) and the Bavarian TeleMedical Project for integrative Stroke Care (TEMPiS) in Germany (n=1076). We report the AUC in ROC curve analysis with 95% CI. The TM score = 0.2*(Age in years) + 6*(Hx of atrial fib) + 3*(Hx of HTN) + 9*(facial weakness) + 5*(NIHSS > 14) - 6*(Hx of seizure). Lower TM scores correspond with a higher likelihood of being a stroke mimic.

Results: Based on final diagnosis at the end of the telestroke consultation, there were 691/1985 (34.8%) SM in the external validation cohort. We tested the association between the TM score and the diagnosis of stroke mimic (Table). The TM score performed well at the external centers on ROC curve analysis with an AUC of 0.70 (0.67 - 0.73; p<0.001), similar to what we observed during the development of the score at our center.

Conclusion: As telestroke consultation expands, increasing numbers of SM patients are being evaluated. The TM score correctly predicted the presence of a SM in these diverse cohorts just as well as in our original cohort. Decision-support tools based on predictive models, like the TM score, may help highlight key clinical differences during complex, time-critical telestroke evaluations.