Robot-assisted stereoelectroencephalography electrode placement in twenty-three pediatric patients: a high-resolution analysis of individual lead placement time and accuracy at a single institution

Bonda, David J.; Pruitt, Rachel; Theroux, Liana; Goldstein, Todd; Stefanov, Dimitre; Kothare, Sanjeev V.; Karkare, Shefali; Rodgers, Shaun

doi:10.1007/s00381-021-05107-w

Cited by 10 publications

(8 citation statements)

References 28 publications

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“…Her electrode placement accuracy was excellent, with a mean target point error in line with previous reports [2] , [7] , [24] , [25] . Importantly, the accurate electrode placement in this case demonstrates the feasibility of accurate, safe electrode placement for someone of this age, and with very thin bone and an open fontanelle.…”

Section: Discussionsupporting

confidence: 87%

Stereoelectroencephalography in the very young: Case report

Katz

Armstrong

Kvint

et al. 2022

Epilepsy & Behavior Reports

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Section: Discussionsupporting

confidence: 87%

Stereoelectroencephalography in the very young: Case report

Katz

Armstrong

Kvint

et al. 2022

Epilepsy & Behavior Reports

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“…Our error measurements in this very young cohort compare favorably with reports of error in older patients. 6,[39][40][41][42] The patients reported here had severe epilepsy with many seizures per day and developmental delay, and 3 had experienced regression because of their epilepsy. Three patients had genetic epilepsy, making this study group a particularly difficult-to-treat cohort.…”

Section: Discussionmentioning

confidence: 90%

Stereoelectroencephalography before 2 years of age

Rahman

Tomlinson

Katz

et al. 2022

Neurosurgical Focus

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OBJECTIVE Stereoelectroencephalography (SEEG) is a widely used technique for localizing seizure onset zones prior to resection. However, its use has traditionally been avoided in children under 2 years of age because of concerns regarding pin fixation in the immature skull, intraoperative and postoperative electrode bolt security, and stereotactic registration accuracy. In this retrospective study, the authors describe their experience using SEEG in patients younger than 2 years of age, with a focus on the procedure’s safety, feasibility, and accuracy as well as surgical outcomes. METHODS A retrospective review of children under 2 years of age who had undergone SEEG while at Children’s Hospital of Philadelphia between November 2017 and July 2021 was performed. Data on clinical characteristics, surgical procedure, imaging results, electrode accuracy measurements, and postoperative outcomes were examined. RESULTS Five patients younger than 2 years of age underwent SEEG during the study period (median age 20 months, range 17–23 months). The mean age at seizure onset was 9 months. Developmental delay was present in all patients, and epilepsy-associated genetic diagnoses included tuberous sclerosis (n = 1), KAT6B (n = 1), and NPRL3 (n = 1). Cortical lesions included tubers from tuberous sclerosis (n = 1), mesial temporal sclerosis (n = 1), and cortical dysplasia (n = 3). The mean number of placed electrodes was 11 (range 6–20 electrodes). Bilateral electrodes were placed in 1 patient. Seizure onset zones were identified in all cases. There were no SEEG-related complications, including skull fracture, electrode misplacement, hemorrhage, infection, cerebrospinal fluid leakage, electrode pullout, neurological deficit, or death. The mean target point error for all electrodes was 1.0 mm. All patients proceeded to resective surgery, with a mean follow-up of 21 months (range 8–53 months). All patients attained a favorable epilepsy outcome, including Engel class IA (n = 2), IC (n = 1), ID (n = 1), and IIA (n = 1). CONCLUSIONS SEEG can be safely, accurately, and effectively utilized in children under age 2 with good postoperative outcomes using standard SEEG equipment. With minimal modification, this procedure is feasible in those with immature skulls and guides the epilepsy team’s decision-making for early and optimal treatment of refractory epilepsy through effective localization of seizure onset zones.

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“…Neurosurgical robots are currently commonly used in clinical practice, including the robotic stereotactic assistance (ROSA) and the Sinovation robotic system (Sinovation) (Zhao et al, 2020 ; Bonda et al, 2021 ). They are widely used in SEEG, deep brain stimulation, and other functional neurosurgical operations.…”

Section: Discussionmentioning

confidence: 99%

“…The effectiveness of SEEG depends on the quality of the electrode-implantation plan. Robot-assisted SEEG electrode implantation is increasingly being performed worldwide; numerous reports on its safety and accuracy have been published in the literature (Abel et al, 2018 ; Spyrantis et al, 2019 ; Bonda et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

FreeSurfer and 3D Slicer-Assisted SEEG Implantation for Drug-Resistant Epilepsy

Liu

Wang

et al. 2022

Front. Neurorobot.

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ObjectiveOur study aimed to develop an approach to improve the speed and resolution of cerebral-hemisphere and lesion modeling and evaluate the advantages and disadvantages of robot-assisted surgical planning software.MethodsWe applied both conventional robot planning software (method 1) and open-source auxiliary software (FreeSurfer and 3D Slicer; method 2) to model the brain and lesions in 19 patients with drug-resistant epilepsy. The patients' mean age at implantation was 21.4 years (range, 6–52 years). Each patient received an average of 12 electrodes (range, 9–16) between May and November 2021. The electrode-implantation plan was designed based on the models established using the two methods. We statistically analyzed and compared the duration of designing the models and planning the implantation using these two methods and performed the surgeries with the implantation plan designed using the auxiliary software.ResultsA significantly longer time was needed to reconstruct a cerebral-hemisphere model using method 1 (mean, 206 s) than using method 2 (mean, 20 s) (p < 0.05). Both methods identified a mean of 1.4 lesions (range, 1–5) in each patient. Overall, using method 1 required longer (mean, 130 s; range, 48–436) than using method 2 (mean, 68.1 s; range, 50–104; p < 0.05). In addition, the clarity of the model based on method 1 was lower than that based on method 2. To devise an electrode-implantation plan, it took 9.1–25.5 min (mean, 16) and 6.6–14.8 min (mean, 10.2) based on methods 1 and 2, respectively (p < 0.05). The average target point error of 231 electrodes amounted to 1.90 mm ± 0.37 mm (range, 0.33–3.61 mm). The average entry point error was 0.89 ± 0.26 mm (range, 0.17–1.67 mm). None of the patients presented with intracranial hemorrhage or infection, and no other serious complications were observed.ConclusionsFreeSurfer and 3D Slicer-assisted SEEG implantation is an excellent approach to enhance modeling speed and resolution, shorten the electrode-implantation planning time, and boost the efficiency of clinical work. These well-known, trusted open-source programs do not have explicitly restricted licenses. These tools, therefore, seem well suited for clinical-research applications under the premise of approval by an ethics committee, informed consent of the patient, and clinical judgment of the surgeon.

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Robot-assisted stereoelectroencephalography electrode placement in twenty-three pediatric patients: a high-resolution analysis of individual lead placement time and accuracy at a single institution

Cited by 10 publications

References 28 publications

Stereoelectroencephalography in the very young: Case report

Stereoelectroencephalography in the very young: Case report

Stereoelectroencephalography before 2 years of age

FreeSurfer and 3D Slicer-Assisted SEEG Implantation for Drug-Resistant Epilepsy

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