Automated generation of epilepsy surgery resection masks: The RAMPS pipeline.

MRI-based delineation of brain tissue removed by epilepsy surgery can be challenging due to post-operative brain shift. In consequence, most studies use manual approaches which are prohibitively time-consuming for large sample sizes, require expertise, and can be prone to errors. We propose RAMPS (Resections And Masks in Preoperative Space), an automated pipeline to generate a 3D resection mask of pre-operative tissue. Our pipeline leverages existing software including FreeSurfer, SynthStrip, Sythnseg and ANTs to generate a mask in the same space as the patient's pre-operative T1 weighted MRI. We compare our automated masks against manually drawn masks and two other existing pipelines (Epic-CHOP and ResectVol). Comparing to manual masks (N = 87), RAMPS achieved a median (IQR) dice similarity of 0.86 (0.078) in temporal lobe resections, and 0.72 (0.32) in extratemporal resections. In comparison to other pipelines, RAMPS had higher dice similarities (N = 62) (RAMPS: 0.86, Epic-CHOP: 0.72, ResectVol: 0.72). We release a user-friendly, easy-to-use pipeline, RAMPS, open source for accurate delineation of resected tissue.