AJNR. American journal of neuroradiology · 2026
18F-FDG PET/MR-Based Individual Metabolic Network Analysis for Prognosis Assessment in Temporal and Extratemporal Lobe Refractory Epilepsy.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Zhang Siqi, Lu Weizhao, Yao Chenyang, Wang Jingjuan, Cui Bixiao, Lu Jie
Аннотация
BACKGROUND AND PURPOSE: This study aimed to employ the individual-specific metabolic network (ISMN) for prognosis assessment in refractory temporal lobe epilepsy (TLE) and extratemporal lobe epilepsy (ETLE), analyzing homogeneity and heterogeneity among patients based on glucose metabolism patterns from 18F-FDG PET/MR and exploring their association with surgical outcomes.
MATERIALS AND METHODS: Clinical and 18F-FDG PET/MR data were retrospectively reviewed from patients with refractory epilepsy who underwent surgical resection. Healthy controls served as references for network construction. Patients were categorized into TLE and ETLE based on the epileptogenic zone determined by surgery and pathology. ISMN nodal and edge characteristics were compared between patients and controls, as well as between TLE and ETLE. Associations between network properties and clinical variables were examined. A linear classifier using nodal and edge features predicted surgical outcomes.
RESULTS: 18F-FDG PET/MR images were collected from patients with TLE (n=39), ETLE (n=33), and healthy controls (n=68), subdivided into reference (n=46) and control (n=22) groups. TLE and ETLE showed increased node degrees in the right angular and inferior temporal gyri but reduced edge connectivity between the right anterior ventral temporal region and temporal pole. ETLE exhibited broader, more fluctuating ISMN alterations with stronger clinical correlations. ISMN features strongly predicted postoperative outcomes, with edge features influencing TLE, while node features were key in ETLE.
CONCLUSIONS: ISMN analysis highlights metabolic network contributions to refractory epilepsy prognosis, uncovering distinct and shared pathophysiological mechanisms in TLE and ETLE to guide personalized therapy.
MATERIALS AND METHODS: Clinical and 18F-FDG PET/MR data were retrospectively reviewed from patients with refractory epilepsy who underwent surgical resection. Healthy controls served as references for network construction. Patients were categorized into TLE and ETLE based on the epileptogenic zone determined by surgery and pathology. ISMN nodal and edge characteristics were compared between patients and controls, as well as between TLE and ETLE. Associations between network properties and clinical variables were examined. A linear classifier using nodal and edge features predicted surgical outcomes.
RESULTS: 18F-FDG PET/MR images were collected from patients with TLE (n=39), ETLE (n=33), and healthy controls (n=68), subdivided into reference (n=46) and control (n=22) groups. TLE and ETLE showed increased node degrees in the right angular and inferior temporal gyri but reduced edge connectivity between the right anterior ventral temporal region and temporal pole. ETLE exhibited broader, more fluctuating ISMN alterations with stronger clinical correlations. ISMN features strongly predicted postoperative outcomes, with edge features influencing TLE, while node features were key in ETLE.
CONCLUSIONS: ISMN analysis highlights metabolic network contributions to refractory epilepsy prognosis, uncovering distinct and shared pathophysiological mechanisms in TLE and ETLE to guide personalized therapy.