Abstracts

Real World Quantification of Hand Waving Episodes in Sunflower Syndrome – Feasibility Study

Abstract number : 1.499
Submission category : 2. Translational Research / 2B. Devices, Technologies, Stem Cells
Year : 2023
Submission ID : 1301
Source : www.aesnet.org
Presentation date : 12/2/2023 12:00:00 AM
Published date :

Authors :
Presenting Author: Jo Sourbron, MD, PhD, MPharm – KU Leuven, UZ Ghent, Belgium

Renee Proost, MD, PhD – Section Pediatric Neurology, Department of Development and Regeneration, University Hospital KU Leuven, Leuven, Belgium; Jan Vandenneucker, PhD – UCB Biopharma SRL, Brussels, Belgium; Valentina Ticcinelli, PhD – UCB Biopharma SRL, Brussels, Belgium; Filip Roelens, MD – Child Neurology, AZ Delta, Roeselare, Belgium; An-Sofie Schoonjans, MD, PhD – Department of Pediatrics, Antwerp University Hospital, Edegem, Belgium and University of Antwerp, Antwerp, Belgium; Helene Verhelst, MD, PhD – Department of Pediatric Neurology, Ghent University Hospital, Ghent, Belgium; Katrien Jansen, MD, PhD – Section Pediatric Neurology, Department of Development and Regeneration, University Hospital KU Leuven, Leuven, Belgium; Lieven Lagae, MD, PhD – ection Pediatric Neurology, Department of Development and Regeneration, University Hospital KU Leuven, Leuven, Belgium

Rationale:
Appropriate seizure detection is crucial since seizures can go unnoticed and can impact therapeutic decision making.

Sunflower syndrome is a unique photosensitive epilepsy, characterized by stereotyped seizures associated with hand waving. These hand waving events (HWEs) can last for a briefly and are thought to be an ictal phenomenon (Sourbron J, et al. Epilepsy Behav.113:107470 (2020)). The EEG usually shows generalized ictal and interictal epileptiform activity (Geenen KR, et al. Dev Med Child Neurol. 63(3) (2021)).

For seizure documentation outside the clinic, most studies rely on seizure diaries, which are believed to be underreporting (Hoppe C, et al. Arch Neurol. 64(11):1595-9 (2007)). Therefore, home monitoring could lead to a more accurate documentation of seizure types and frequency. Nonetheless, data are lacking regarding the clinical utility/reliability (Brinkmann, et al. Front Neurol. 13;12 (2021)). As Sunflower syndrome is characterized by the stereotypical HWEs, a feasibility study was performed to assess the possibility to quantify these HWEs by a wrist-word wearable device (Axivity AX6), which has been validated in other neurological diseases (Williamson JR, et al. Sensors (Basel) 14;21 (2021))).

Methods:
Axivity AX6 is a wrist worn wearable device combining an accelerometer (speed in different directions) and a gyroscope (speed of rotation). We first performed a simulation in a healthy person (simulation study) mimicking the HWEs while also performing daily activities (e.g. writing, toothbrushing). Subsequently, we performed an analysis of three consecutive days and nights in two Sunflower syndrome patients (real life study) to quantify real world HWE and unravel potential confounders. Data were logged in a seizure diary. This study was approved by the local ethical committee (approval number: ONZ-2023-0241AM01, UZ Ghent, Belgium).

Results:
During the simulation study, the feasibility of seizure (HWE) detection became rapidly clear due to the homogeneity and narrow-band frequency content of the simulated HWE. The most obvious simulated confounder was toothbrushing (TB), however, TB showed a toothier aspect that was clearly different from the HWE.

During the real life study, our first Sunflower syndrome patient did not have any HWE. The HWE of the second Sunflower syndrome patient showed a straightforward harmonic signal (Figure 1). We demonstrate that the gyroscope was necessary to uniquely distinguish HWE from TB (Figure 2) and other movements.

Conclusions:
Sunflower syndrome is characterized by HWE that can go unnoticed and seizure diaries have their limitations. We show that by Axivity AX6 measurements, we can detect HWEs and distinguish them from several confounders.

Even though this is a proof-of-concept study in a small number of patients without an automated algorithm detection method, our data show that objective seizure registration is possible. Hence, we will perform additional real life studies to further characterize the HWEs. Moreover, we believe that Axivity AX6 could be a valid measurement device for HWE quantification in clinical trials for this -often drug-resistant epilepsy- syndrome.

Funding: None

Translational Research