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Development of a stereo-EEG based seizure matching system for clinical decision making in epilepsy surgery

31 Oct 2024

Development of a stereo-EEG based seizure matching system for clinical decision making in epilepsy surgery

Objective.The proportion of patients becoming seizure-free after epilepsy surgery has stagnated. Large multi-center stereo-electroencephalography (SEEG) datasets can allow comparing new patients to past similar cases and making clinical decisions with the knowledge of how cases were treated in the past. However, the complexity of these evaluations makes the manual search for similar patients impractical. We aim to develop an automated system that electrographically and anatomically matches seizures to those in a database. Additionally, since features that define seizure similarity are unknown, we evaluate the agreement and features among experts in classifying similarity.Approach.We utilized 320 SEEG seizures from 95 consecutive patients who underwent epilepsy surgery. Eight international experts evaluated seizure-pair similarity using a four-level similarity score. As our primary outcome, we developed and validated an automated seizure matching system by employing patient data marked by independent experts. Secondary outcomes included the inter-rater agreement (IRA) and features for classifying seizure similarity.Main results.The seizure matching system achieved a median area-under-the-curve of 0.76 (interquartile range, 0.1), indicating its feasibility. Six distinct seizure similarity features were identified and proved effective: onset region, onset pattern, propagation region, duration, extent of spread, and propagation speed. Among these features, the onset region showed the strongest correlation with expert scores (Spearman's rho = 0.75,p< 0.001).

A&#160;closed 3D printed microfluidic device for automated growth and differentiation of cerebral organoids from single-cell suspension

1 Oct 2024

A closed 3D printed microfluidic device for automated growth and differentiation of cerebral organoids from single-cell suspension

The development of 3D organoids has provided a valuable tool for studying human tissue and organ development in vitro. Cerebral organoids, in particular, offer a unique platform for investigating neural diseases. However, current methods for generating cerebral organoids suffer from limitations such as labor-intensive protocols and high heterogeneity among organoids. To address these challenges, we present a microfluidic device designed to automate and streamline the formation and differentiation of cerebral organoids. The device utilizes microwells with two different shapes to promote the formation of a single aggregate per well and incorporates continuous medium flow for optimal nutrient exchange. In silico simulations supported the effectiveness of the microfluidic chip in replicating cellular microenvironments. Our results demonstrate that the microfluidic chip enables uniform growth of cerebral organoids, significantly reducing the hands-on time required for maintenance. Importantly, the performance of the microfluidic system is comparable to the standard 96-well plate format even when using half the amount of culture medium, and the resulting organoids exhibit substantially developed neuroepithelial buds and cortical structures. This study highlights the potential of custom-designed microfluidic technology in improving the efficiency of cerebral organoid culture.

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