Ex‐SPECTing Success: predictors of successful SPECT radiotracer injection during pre‐surgical video‐EEG admissions

Abstract

AbstractObjectivesTo determine predictors of successful ictal Single Photon Emission Computed Tomography (SPECT) injections during Epilepsy Monitoring Unit (EMU) admissions for patients undergoing presurgical evaluation for drug resistant focal epilepsy.MethodsIn this retrospective study, consecutive EMU admissions were analysed at a single centre between 2019‐2021. All seizures that occurred during the admission were reviewed. ‘Injectable seizures’ occurred during hours when the radiotracer was available. EMU‐level data were analysed to identify factors predictive of an EMU admission with a successful SPECT injection (successful admission). Seizure‐level data were analysed to identify factors predictive of an ‘injectable seizure’ receiving a SPECT injection during the ictal phase (successful injection). A multivariate generalised linear model was used to identify predictive variables.Results125 EMU admissions involving 103 patients (median 37 years, IQR27.0‐45.5) were analysed. 38.8% of seizures that were eligible for SPECT (n=134) were successfully injected; this represented 17.4% of all seizures (n=298) that occurred during admission. Unsuccessful admissions were most commonly due to a lack of seizures during EMU‐SPECT (19.3%) or no 'injectable seizures’ (62.3%). Successful EMU‐SPECT was associated with baseline seizure frequency >1 per week (95%CI 2.1‐3.0, p <0.001) and focal PET hypometabolism (95%CI 2.0‐3.7, p <0.001). On multivariate analysis, the only factor associated with successful injection was patients being able to indicate they were having a seizure to staff (95%CI 1.0‐4.4, p=0.038).SignificanceCompleting a successful ictal SPECT study remains challenging. Baseline seizure frequency of >1 per‐week, a PET hypometabolic focus and a patient's ability to indicate seizure onset were identified as predictors of success. These findings may assist EMUs in optimising their SPECT protocols, patient selection, and resource allocation.