Mini-Open Partial Callosotomy in Pediatric Patients

Oper Neurosurg. 2026 Jun 2. doi: 10.1227/ons.0000000000002050. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVES: Dissection of the corpus callosum is a well-established treatment option for patients with pharmaco-resistant epilepsy. Both partial and complete callosotomies are performed to reduce seizure burden. In recent years, multiple minimally invasive variations of corpus callosotomy have been suggested. These techniques, however, can be cost and time demanding, which limits their use to specialized centers in high-resource settings. We present our experience with a mini-open microsurgical technique.

METHODS: Our technique employs a parasagittal longitudinal incision followed by a small craniotomy and retractorless interhemispheric dissection. Neuronavigation was used to find an operative corridor between bridging veins to the sagittal sinus. Postoperative computed tomography and magnetic resonance images were analyzed to describe the size of craniotomies and the disconnected area of the corpus callosum.

RESULTS: We performed 38 partial callosotomies in 24 patients over a period of 5 years. The median age at the initial surgery was 8.5 years (IQR 5.9-11.9). In 15 patients (62.5%), the first surgery was a posterior callosotomy. The average size of the craniotomy since adoption of this technique was 43.6 mm by 27.8 mm but decreased to an average of 35.8 mm by 24.2 mm in the last 2 years. The mean operating time per procedure was 99.6 minutes (SD ±28.9 minutes). Surgeries were performed by attendings, fellows, and residents in 28, 6, and 4 cases, respectively. We experienced no complications with this approach in the investigated period.

CONCLUSION: Mini-open partial callosotomy is a safe and efficient procedure that minimizes the morbidity associated with a larger approach. It can be performed and taught in conventionally equipped microsurgical neurosurgery units, thus contributing to further emphasize the use of epilepsy surgery also in resource constrained environments.

PMID:42228462 | DOI:10.1227/ons.0000000000002050