There are several challenges to widespread adoption of these techniques into standard clinical practice, including: 1) MR scanning protocol variability, hardware, and software, which may impair generalization of any "learning" across centers; 2) limited availability of large patient and normative training sets at single institutions, particularly with ongoing evolution of acquisition protocols; and 3) significant technical expertise required to implement these approaches. This work, like others, is limited by the relatively small size of normative and lesional training sets. Open source efforts such as this and the
MELD Project (
https://meldproject.github.io/) wil hopefully continue to increase adoption and allow for pooling of data across centers, which may increase the performance of these methods by better accounting for variability despite differences in the data available across centers
\cite{Jin2018}.
Conclusions
We implemented a novel normative modeling approach to FCD identification, providing a robust characterization of normal cortical variability for comparison with FCD lesions. In keeping with their often subtle appearance, FCD lesions are outliers but only to a similar degree as some normal cortical regions. In our feature space, FCDs appear quite similar to some of these regions, such as paralimbic and sensorimotor cortices. These similarities should be kept in mind when visually inspecting images to detect possible FCDs. They also help to explain the utility of local normalization procedures in reducing false positive detections. Our resulting approach to automated FCD detection is 80% sensitive and 70% specific, similar to or better than many previously proposed methods, despite the relatively small size of the training and testing data. Our normative modeling approach also promises to be of use in the detection of other types of pathology or to study normal cortical variability.
Acknowledgements
We are indebted to all patients and their families who have selflessly volunteered their time to participate in this study.
Funding: This work was supported by the Intramural Research Program of the National Institute of Neurological Disorders and Stroke, NIH.