An open presurgery MRI dataset of people with epilepsy and focal cortical dysplasia type II

Abstract

Automated detection of lesions using artificial intelligence creates new standards in medical imaging. For people with epilepsy, automated detection of focal cortical dysplasias (FCDs) is widely used because subtle FCDs often escape conventional neuroradiological diagnosis. Accurate recognition of FCDs, however, is of outstanding importance for affected people, as surgical resection of the dysplastic cortex is associated with a high chance of postsurgical seizure freedom. Here, we make publicly available a dataset of 85 people affected by epilepsy due to FCD type II and 85 healthy control persons. We publish 3D-T1 and 3D-FLAIR, manually labeled regions of interest, and carefully selected clinical features. The open presurgery MRI dataset may be used to validate existing automated algorithms of FCD detection as well as to create new approaches. Most importantly, it will enable comparability of already existing approaches and support a more widespread use of automated lesion detection tools.

Deep learning-based automated lesion segmentation on pediatric focal cortical dysplasia II preoperative MRI: a reliable approach

“…As we know, preoperative lesion detection is the key to the success of surgery, which is the major assignment of radiologists. Nevertheless, artificial intelligence is gradually revolutionizing this job [ 23 ]. Conventionally, for refractory epilepsy brain MRI, neuroradiologists inevitably miss subtle lesions which can be detected by neural networks.…”

A Public Benchmark for Human Performance in FCD Detection

“…It is described in detail in a previous work (Walger et al 2024). Here, we only analyze a subset of 85 FCD cases, which are part of the "open presurgery MRI dataset of people with epilepsy and focal cortical dysplasia type II" made publicly available by Schuch and colleagues (Schuch et al 2023) IIb 34…”

“…We showed that human performance depends on the presence of FCDspeci c MRI features; it is especially in uenced by FLAIR hyperintensity and cortical thickening. 85 of the FCD cases were made publicly available in a different work (Schuch et al 2023). The public dataset includes the defaced T1 and FLAIR images, the ground-truth lesion masks and other clinical information.…”