The Role of FDG‐PET in Patients with Epilepsy Related to Periventricular Nodular Heterotopias: Diagnostic Features and Long‐Term Outcome. Issue 4 (22nd April 2019)

• Record Type: Journal Article
• Authors: Popescu, Cristina Elena; Mai, Roberto; Sara, Roberto; Lizio, Domenico; Zanni, Daniela; Rossetti, Claudio; Caobelli, Federico
• Is Part Of: Journal of neuroimaging. Volume 29:Issue 4(2019)
• Page Start: 512
• Page End: 520
• Publication Date: 2019-04-22
• Subjects: Periventricular nodular heterotopias -- FDG PET/CT -- magnetic resonance imaging -- postsurgical long‐term outcome -- prognostic value; Diagnostic imaging -- Periodicals; Nervous system -- Diseases -- Diagnosis -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Système nerveux -- Maladies -- Diagnostic -- Périodiques; Imagerie médicale; Neuroimagerie; Neurologie; Système nerveux; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.804754
• DOI: 10.1111/jon.12620
• Languages: English
• ISSNs: 1051-2284

Abstract

ABSTRACT: BACKGROUND AND PURPOSE: Periventricular nodular heterotopias (PNHs) are frequently associated with drug‐resistant epilepsy (DRE). Although magnetic resonance imaging (MRI) can define the morphological features of PNHs, still there is a need to assess their metabolic activity in order to provide useful information on epileptogenicity and long‐term outcome. To that end, we investigated the ability of 18 F‐FDG PET to identify seizure onset zone in order to assess the metabolic activity of the ectopic neurons and to provide prognostic information on the postsurgical outcome. METHODS: Sixteen patients (6 men and 10 women; ranging between 24 and 53 years of age) with PNHs‐related DRE were evaluated. All patients underwent clinical evaluation, Stereo‐electroencephalogram (SEEG), brain MRI, and 18 F‐FDG brain PET/CT. PET images were superimposed on the patient‐specific 3‐dimensional‐brain MRI. The metabolic activity of each nodule and of their cortex was visually and semiquantitatively assessed. The outcome after intervention was assessed in all patients using Engel classification. RESULTS: Thirty‐one heterotopic sites were identified. Twenty‐one of 23 nodules with detectable electric activity on SEEG were identified by PET (91.3%), while 5 of 8 of nodules without electric activity showed no metabolism on PET (62.5%). Overall, the concordance between SEEG and FDG‐PET was 26/31 (83.9%). Furthermore, cortical metabolic alterations were depicted, correlating with epileptogenic areas. A favorable postsurgical outcome was reported in 13 patients (81.3%). The presence of a hypometabolic nodule significantly correlated with a worse outcome after surgical therapy ( P = .036). CONCLUSIONS: In PNHs‐related epilepsy, FDG‐PET more accurately identifies epileptogenic foci, which aids surgical planning and in postoperative seizure control.