SISCOS in focal cortical dysplasia: localization and comparative analysis with MRI.

Abstract

Purpose: This study evaluates the efficacy of SISCOS (Subtraction ictal-interictal SPECT coregistered to SPECT) in localizing the epileptogenic zone (EZ) in focal cortical dysplasia (FCD), comparing its predictive performance with MRI and post-surgical outcomes based on ILAE classification.

Methods: 84 patients with drug refractory epilepsy (DRE) who were operated and had histopathology consistent with FCD, were included in the study. All patients had undergone a complete work-up including SISCOS and MRI for EZ localization, followed by discussion in the multidisciplinary epilepsy surgery meeting prior to surgery. Ictal & interictal perfusion SPECT studies were performed with Tc-99 m Ethylene Cysteinate Dimer (Tc-99 m ECD) followed by SISCOS analysis using SPM2 and Bioimage Suite 2.6. Concordance for localization was determined by comparing with the surgical resection site and post-surgical outcomes were assessed using the ILAE classification.

Results: The concordance for EZ localization demonstrated by SISCOS was 73.8% and MRI was 82.1%. 52 patients (61.9%) had good surgical outcome and 31(59%) of these were FCD type 2. In patients with discordant MRI findings, SISCOS was able to provide localisation in 86% (13/15), with 69.2% showing good surgical outcomes. Sensitivity of SISCOS and MRI was 73% (95% CI = 59-84.8%) and 78% (95% CI = 67.5-90.3%) respectively with no significant difference between the two. In FCD type I, both SISCOS and MRI revealed a similar a sensitivity of 76.4% (95%CI = 50.1-93.2%). Concordant cases exhibited higher seizure-free odds ratios for both modalities.

Conclusion: SISCOS is effective in localizing the EZ in FCD patients, comparable to MRI. Integrating SISCOS and MRI enhances lesion detection, especially in MRI discordant cases. A comprehensive diagnostic approach utilizing SISCOS and MRI can optimize the non-invasive pre-surgical assessment in DRE thereby guiding surgical decision-making in a resource-limited setting.