Literature DB >> 33425950

FDG-PET Profiles of Extratemporal Metabolism as a Predictor of Surgical Failure in Temporal Lobe Epilepsy.

Yongxiang Tang1, Guang Liao1, Jian Li1, Tingting Long1, Yulai Li1, Li Feng2, Dengming Chen1, Beisha Tang2,3, Shuo Hu1,3,4.   

Abstract

Objective: Metabolic abnormality in the extratemporal area on fluorine-18-fluorodeoxyglucose positron emission tomography (FDG-PET) is not an uncommon finding in drug-resistant temporal lobe epilepsy (TLE), however the correlation between extratemporal metabolic abnormalities and surgical long-term prognosis has not been fully elucidated. We aim to investigate FDG-PET extratemporal metabolic profiles predictive of failure in surgery for TLE patients.
Methods: Eighty-two patients with unilateral TLE (48 female, 34 male; 25.6 ± 10.6 years old; 37 left TLE, 45 right TLE) and 30 healthy age-matched controls were enrolled. Patients were classified either as experiencing seizure-recurrence (SZR, Engel class II through IV) or seizure-free (SZF, Engel class I) at least 1 year after surgery. Regional cerebral metabolism was evaluated by FDG-PET with statistical parametric mapping (SPM12). Abnormal metabolic profiles and patterns on FDG-PET in SZR group were evaluated and compared with those of healthy control and SZF subjects on SPM12. Volume and intensity as well as special brain areas of abnormal metabolism in temporal and extratemporal regions were quantified and visualized.
Results: With a median follow-up of 1.5 years, 60% of patients achieved Engel class I (SZF). SZR was associated with left TLE and widespread hypometabolism in FDG-PET visual assessment (both p < 0.05). All patients had hypometabolism in the ipsilateral temporal lobe but SZR was not correlated with volume or intensity of temporal hypometabolism (median, 1,456 vs. 1,040 mm3; p > 0.05). SZR was correlated with extratemporal metabolic abnormalities that differed according to lateralization: in right TLE, SZR exhibited larger volume in extratemporal areas compared to SZF (median, 11,060 vs. 2,112 mm3; p < 0.05). Surgical failure was characterized by Cingulum_Ant_R/L, Frontal_Inf_Orb_R abnormal metabolism in extratemporal regions. In left TLE, SZR presented a larger involvement of extratemporal areas similar to right TLE but with no significant (median, 5,873 vs. 3,464 mm3; p > 0.05), Cingulum_Ant_ R/L, Parietal_Inf_L, Postcentral_L, and Precuneus_R involved metabolic abnormalities were correlated with SZR. Conclusions: Extratemporal metabolic profiles detected by FDG-PET may indicate a prominent cause of TLE surgery failure and should be considered in predictive models for epilepsy surgery. Seizure control after surgery might be improved by investigating extratemporal areas as candidates for resection or neuromodulation.
Copyright © 2020 Tang, Liao, Li, Long, Li, Feng, Chen, Tang and Hu.

Entities:  

Keywords:  PET; PET in epilepsy; epilepsy; image processing; prognosis

Year:  2020        PMID: 33425950      PMCID: PMC7793721          DOI: 10.3389/fmed.2020.605002

Source DB:  PubMed          Journal:  Front Med (Lausanne)        ISSN: 2296-858X


  3 in total

1.  Machine Learning-Derived Multimodal Neuroimaging of Presurgical Target Area to Predict Individual's Seizure Outcomes After Epilepsy Surgery.

Authors:  Yongxiang Tang; Weikai Li; Lue Tao; Jian Li; Tingting Long; Yulai Li; Dengming Chen; Shuo Hu
Journal:  Front Cell Dev Biol       Date:  2022-01-21

2.  Individual Brain Metabolic Connectome Indicator Based on Jensen-Shannon Divergence Similarity Estimation Predicts Seizure Outcomes of Temporal Lobe Epilepsy.

Authors:  Zehua Zhu; Zhimin Zhang; Xin Gao; Li Feng; Dengming Chen; Zhiquan Yang; Shuo Hu
Journal:  Front Cell Dev Biol       Date:  2022-01-11

3.  Cortical abnormalities of synaptic vesicle protein 2A in focal cortical dysplasia type II identified in vivo with 18F-SynVesT-1 positron emission tomography imaging.

Authors:  Yongxiang Tang; Jie Yu; Ming Zhou; Jian Li; Tingting Long; Yulai Li; Li Feng; Dengming Chen; Zhiquan Yang; Yiyun Huang; Shuo Hu
Journal:  Eur J Nucl Med Mol Imaging       Date:  2022-01-03       Impact factor: 10.057

  3 in total

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