Intracranial metastases surgery
Automated classification of brain metastases and healthy brain tissue is feasible using optical coherence tomography imaging, extracted texture features, and machine learning with principal component analysis (PCA) and support-vector machines (SVM). The established approach can prospectively provide the surgeon with additional information about the tissue, thus optimizing the extent of tumor resection and minimizing the risk of local recurrences 1).
Wolpert et al. defined risk profiles for the development of BM-related epilepsy and derived a score which might help to estimate the risk of post-operative seizures and identify individuals at risk who might benefit from primary prophylactic antiepileptic drug therapy 2).