Abstract
The purpose of this study was to establish a non-invasive clinical PET/MR protocol using [18F]-labeled deoxyglucose (FDG) that provides physicians with regional metabolic rate of glucose (MRGlc) values and to clarify the contribution of absolute quantification to clinical management of patients with non-lesional extratemporal lobe epilepsy (ETLE). The study included a group of 15 patients with non-lesional ETLE who underwent a dynamic FDG PET study using a fully-integrated PET/MRI system (Siemens Biograph). FDG tracer uptake images were converted to MRGlc (μmol/100 g/min) maps using an image derived input function that was extracted based on the combined analysis of PET and MRI data. In addition, the same protocol was applied to a group of healthy controls, yielding a normative database. Abnormality maps for ETLE patients were created with respect to the normative database, defining significant hypo- or hyper-metabolic regions that exceeded ±2 SD of normal regional mean MRGlc values. Abnormality maps derived from MRGlc images of ETLE patients contributed to the localization of hypo-metabolic areas against visual readings in 53% and increased the confidence in the original clinical readings in 33% of all cases. Moreover, quantification allowed identification of hyper-metabolic areas that are associated with frequently spiking cortex, rarely acknowledged in clinical readings. Overall, besides providing some confirmatory information to visual readings, quantitative PET imaging demonstrated only a moderate impact on clinical management of patients with complex pathology that leads to epileptic seizures, failing to provide new decisive information that would have changed classification of patients from being rejected to being considered for surgical intervention.
Highlights
Surgical interventions in patients with intractable epilepsy are planned based on a variety of diagnostic measures, including electrophysiological testing and neuroimaging procedures [1,2,3]
Our work demonstrates moderately improved characterization of glucose metabolic abnormalities in patients with non-lesional extratemporal lobe epilepsies (ETLE) epilepsy based on absolute quantification of metabolic rate of glucose (MRGlc) in a clinical setting
We report here four main findings: quantitative assessment of MRGlc: [1] does not provide sufficient additional information that could justify re-classification of patients who have been rejected as surgical candidates based on established clinical work-up; [2] contributes to increased confidence in the original visual readings in ∼50% of cases; [3] identifies hypermetabolic areas that are rarely acknowledged in clinical readings but might reflect dynamic changes in brain networks that are directly associated with seizure generation and propagation; and [4] sets a limit to the sensitivity of absolute quantification to detect hypo- or hyper-metabolic areas in epilepsy patients that is caused by the relatively large physiological variation (10–20%) of MRGlc values in the normal population
Summary
Surgical interventions in patients with intractable epilepsy are planned based on a variety of diagnostic measures, including electrophysiological testing and neuroimaging procedures [1,2,3]. There is a need for further development of methodologies that could provide more localized information about tissue epileptogenicity It is well-accepted that cortical glucose hypo-metabolism depicted by 2-[18F]fluoro-2-deoxy-D-glucose (FDG) PET provides valuable imaging clues with respect to the location of electrophysiologically confirmed seizure onset zones [8, 9]. Hyper-metabolic brain areas are occasionally observed during the patients’ interictal states that are poorly understood and as a result are either ignored or viewed as being of questionable significance [11, 12] Such areas might provide additional clues with respect to the location of either frequently spiking cortex [13] or might denote the presence of a network of inhibitory circuits that is activated in order to prevent the propagation of the epileptic discharge [14]. This view is substantiated by the observation that ictal intracranial EEG and glucose metabolic abnormalities in the human cortex are known to match only partially [15]
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