Predictors for drug effects with brain disease: Shed new light from EEG parameters to brain connectomics

Tian, Yin; Yang, Li; Xu, Wei; Zhang, Huiling; Wang, Zhongyan; Zhang, Haiyong; Zheng, Shuxing; Shi, Yupan; Xu, Peng

doi:10.1016/j.ejps.2017.04.019

Cited by 6 publications

(6 citation statements)

References 125 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…17 These measures may be useful in characterizing FC patterns of epileptogenic networks and monitoring drug effects. 18,19 FC metrics have been increasingly studied in epilepsy and other neurologic disorders and their relationships to clinically relevant measures must be better understood.…”

Section: Discussionmentioning

confidence: 99%

SEEG Functional Connectivity Measures to Identify Epileptogenic Zones

et al. 2022

View full text Add to dashboard Cite

Background and Objective:Functional connectivity (FC) measures can be used to differentiate epileptogenic zones (EZs) from non-EZs in patients with medically refractory epilepsy. However, little work has been done to evaluate stability of stereoelectroencephalography (SEEG) FC measures over time and their relationship with anti-seizure medication (ASM) use – a critical confounder in epilepsy FC studies to date. In this study, we aim to answer the following questions: 1) are SEEG FC measures stable over time, 2) are they influenced by ASMs, and 3) are they impacted by patient data collection state?Methods:In 32 patients with medically-refractory focal epilepsy, we collected a single two-minute prospective SEEG resting-state (awake, eyes closed) data set, and consecutive two-minute retrospective pseudo-rest (awake, eyes open) data sets for days 1-7 post-implantation. ASM dosages were recorded for days 1-7 post-implantation and drug load score (DLS) per day was calculated to standardize and compare across patients. FC was evaluated using directed and nondirected measures. Standard clinical interpretation of ictal SEEG was used to classify brain regions as EZs and non-EZs.Results:Over seven days, presumed EZs consistently had higher FC than non-EZs when using Between Imaginary Coherence (ImCoh) and Partial Directed Coherence (PDC) Inward strength, without accounting for DLS. These measures were demonstrated to be stable over a short-term period of three consecutive days with the same DLS. Between ImCoh FC differences between EZs and non-EZs were reduced with DLS decreases, whereas other measures were not affected by DLS. FC differences between EZs and non-EZs were seen during both resting-state and pseudo-rest conditions; ImCoh values were strongly correlated between the two conditions, whereas PDC values were not.Discussion:Inward and non-directed SEEG FC is higher in presumed EZs versus non-EZs, and measures are stable over time. However, certain measures may be impacted by ASM dose, as Between ImCoh differences between EZs and non-EZs are less pronounced with lower doses, and other measures such as PDC are poorly correlated across recording conditions. These findings allow novel insight into how SEEG FC measures may aid surgical localization, and how they are influenced by ASMs and other factors.

show abstract

Section: Discussionmentioning

confidence: 99%

SEEG Functional Connectivity Measures to Identify Epileptogenic Zones

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Some researchers revealed that the parahippocampal cortex and hippocampus were involved in memory [10][11][12][13]. The parahippocampal cortex played a role for spatial configuration of object in memory [14].…”

Section: Resultsmentioning

confidence: 99%

Identify the radiotherapy-induced abnormal changes in the patients with nasopharyngeal carcinoma

Wang

Zhao

Zhang³

et al. 2017

ADMET DMPK

Self Cite

View full text Add to dashboard Cite

<p class="ADMETabstracttext">Radiotherapy (RT) is the standard treatment for nasopharyngeal carcinoma, which often causes inevitable brain injury in the process of treatment. The majority of patients has no abnormal signal or density change of the conventional magnetic resonance imaging (MRI) and computed tomography (CT) examination in the long-term follow-up after radiation therapy. However, when there is a visible CT and conventional MR imaging changes, the damage often has been severe and lack of effective treatments, seriously influencing the prognosis of patients. Therefore, the present study aimed to investigate the abnormal changes in nasopharyngeal carcinoma (NPC) patients after RT. In the present study, we exploited the machine learning framework which contained two parts: feature extraction and classification to automatically detect the brain injury. Our results showed that the method could effectively identify the abnormal regions reduced by radiotherapy. The highest classification accuracy was 82.5 % in the abnormal brain regions. The parahippocampal gyrus was the highest accuracy region, which suggested that the parahippocampal gyrus could be most sensitive to radiotherapy and involved in the pathogenesis of radiotherapy-induced brain injury in NPC patients.</p>

show abstract

“…EEG and MEG give good temporal resolution as compared to fMRI. [15] Quantitative techniques based on EEG measures can be used as biomarkers. EEG biomarkers are comparable to Alzheimer's disease (AD) severity.…”

Section: Connectomics In Pharmacologymentioning

confidence: 99%

“…Levetiracetam shows the cognitive effect in epilepsy patients which is evaluated by EEG frequency and observe the depth of anesthesia. [15]…”

Section: Connectomics In Pharmacologymentioning

confidence: 99%