CBF changes in drug naive juvenile myoclonic epilepsy patients

Tae, Woo Suk; Joo, Eun Yeon; Han, Seok Joo; Lee, Kyung-Han; Hong, Seung Bong

doi:10.1007/s00415-006-0491-6

Cited by 27 publications

(24 citation statements)

References 36 publications

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“…This finding is consistent with the negative correlation found between right frontal lobe volume and JME disease duration in our previous study [25]. In an interictal SPECT study on drug naïve JME patients, we also reported a negative correlation between regional cerebral blood flow (rCBF) and the disease duration in frontal cortices [26]. These findings suggest that frontal lobe dysfunction in JME may change over time.…”

Section: Discussionsupporting

confidence: 84%

“…Recently, a serotonin 1A receptor PET study reported the reductions of serotonin 1A receptor binding potential in the raphe nucleus of pons, hippocampus, and anterior dorsolateral frontal cortex of JME patients suggesting an affected serotonin system [19]. Moreover, an interictal SPECT analysis of drug naïve JME patients revealed decreased rCBF in areas of the left hippocampus, subcallosal gyrus, thalamus, pons, and also showed negative correlations between rCBF and disease duration in the bilateral frontal cortices, caudate nuclei, left putamen, right anterobasal temporal lobe, bilateral brainstem [26]. The caudal raphe nuclei project to the cerebellar cortex and spinal cord, whereas rostal raphe nuclei project to the thalamus, nucleus accumbens, hypothalamus, amygdala, hippocampus, and the cortex [13].…”

Section: Discussionmentioning

confidence: 92%

“…In a [ 11 C]flumazenil (FMZ) PET study, a significantly higher mean [ 11 C]FMZ volume of distribution (FMZVD) in the cerebral cortex was reported, and it was suggested that increased FMZVD could reflect microdysgenesis or a state of cortical hyperexcitability [22]. In addition, another study reported mildly increased rCBF in the superior frontal area of JME patients [26].…”

Section: Discussionmentioning

confidence: 97%

“…Various functional abnormalities of JMEs have been reported by magnetic resonance spectroscopy (MRS) [23], positron emission tomography (PET) [15,19], single photon emission computed tomography (SPECT) [26], and neuropsychological studies [5].…”

Section: Introductionmentioning

confidence: 99%

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Cortical thickness abnormality in juvenile myoclonic epilepsy

et al. 2008

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Section: Discussionsupporting

confidence: 84%

Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

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Cortical thickness abnormality in juvenile myoclonic epilepsy

et al. 2008

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“…This is in accordance with the few previous reports point to the role of the cerebellum in the development of JME. Tae et al (2007) assessed the regional cerebral blood flow abnormality in JME patients. They showed a significant regional cerebral blood reduction in bilateral thalami, red nucleus, midbrain, pons, left hippocampus, and in the cerebella, and an increase in the left superior frontal gyrus.…”

Section: Discussionmentioning

confidence: 99%

Magnetoencephalographic Findings in Two Cases of Juvenile Myoclonus Epilepsy

et al. 2009

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The aim of this study is to investigate the electromagnetic sources of epileptic activity in two patients with juvenile myoclonus epilepsy (JME). The first patient was a 22-year old female with JME diagnosis by the age of 17 years old. Her initial EEG recording showed characteristic paroxysmal generalized activity with polyspike-wave complexes. She was on remission for 9 months. The second patient was a 29-year old male with JME diagnosis by the age 18 of years old. He showed an EEG recording with generalized spike-wave complexes of 3.5-4 Hz and presented a great improvement after therapeutic treatment. The MRI examinations for both patients did not disclose any focal lesions or areas of abnormal signal intensity or enhancement by contrast media. Magnetoencephalography (MEG) was recorded with a 122-channel whole-head system, 5 years after the disease onset for the first patient and 11 years for the second patient. For the first patient dipolar sources of MEG paroxysmal activity were localised at the vermis with extension up to the occipital region, whereas, for the second patient dipolar sources of MEG paroxysmal activity were localised at the cerebellar area (vermis and hemisphere). Implication of the cerebellum in JME, as suggested by MEG data in this study, is in accordance with previous reports employing functional MRI or cerebral blood flow evaluation in JME.

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MRI‐Based Radiomics Approach for Differentiating Juvenile Myoclonic Epilepsy from Epilepsy with Generalized Tonic–Clonic Seizures Alone

Sim,

Lee,

Chu

et al. 2023

Magnetic Resonance Imaging

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BackgroundThe clinical presentation of juvenile myoclonic epilepsy (JME) and epilepsy with generalized tonic–clonic seizures alone (GTCA) is similar, and MRI scans are often perceptually normal in both conditions making them challenging to differentiate.PurposeTo develop and validate an MRI‐based radiomics model to accurately diagnose JME and GTCA, as well as to classify prognostic groups.Study TypeRetrospective.Population164 patients (127 with JME and 37 with GTCA) patients (age 24.0 ± 9.6; 50% male), divided into training (n = 114) and test (n = 50) sets in a 7:3 ratio with the same proportion of JME and GTCA patients kept in both sets.Field Strength/Sequence3T; 3D T1‐weighted spoiled gradient‐echo.AssessmentA total of 17 region‐of‐interest in the brain were identified as having clinical evidence of association with JME and GTCA, from where 1581 radiomics features were extracted for each subject. Forty‐eight machine‐learning combinations of oversampling, feature selection, and classification algorithms were explored to develop an optimal radiomics model. The performance of the best radiomics models for diagnosis and for classification of the favorable outcome group were evaluated in the test set.Statistical TestsModel performance measured using area under the curve (AUC) of receiver operating characteristic (ROC) curve. Shapley additive explanations (SHAP) analysis to estimate the contribution of each radiomics feature.ResultsThe AUC (95% confidence interval) of the best radiomics models for diagnosis and for classification of favorable outcome group were 0.767 (0.591–0.943) and 0.717 (0.563–0.871), respectively. SHAP analysis revealed that the first‐order and textural features of the caudate, cerebral white matter, thalamus proper, and putamen had the highest importance in the best radiomics model.ConclusionThe proposed MRI‐based radiomics model demonstrated the potential to diagnose JME and GTCA, as well as to classify prognostic groups. MRI regions associated with JME, such as the basal ganglia, thalamus, and cerebral white matter, appeared to be important for constructing radiomics models.Level of Evidence3Technical EfficacyStage 3

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CBF changes in drug naive juvenile myoclonic epilepsy patients

Abstract: Our results suggest that abnormal neural networks in the thalamus, hippocampus, brainstem and cerebellum are associated with JME.

Cited by 27 publications

References 36 publications

Cortical thickness abnormality in juvenile myoclonic epilepsy

Cortical thickness abnormality in juvenile myoclonic epilepsy

Magnetoencephalographic Findings in Two Cases of Juvenile Myoclonus Epilepsy

MRI‐Based Radiomics Approach for Differentiating Juvenile Myoclonic Epilepsy from Epilepsy with Generalized Tonic–Clonic Seizures Alone

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