Computational neuroanatomy: ontology-based representation of neural components and connectivity

Background: A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. Results: We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Conclusion: Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future

Management of Low-Grade Glioma

The optimal management of patients with low-grade glioma (LGG) is controversial. The controversy largely stems from the lack of well-designed clinical trials with adequate follow-up to account for the relatively long progression-free survival and overall survival of patients with LGG. Nonetheless, the literature increasingly suggests that expectant management is no longer optimal. Rather, there is mounting evidence supporting active management including consideration of surgical resection, radiotherapy, chemotherapy, molecular and histopathologic characterization, and use of modern imaging techniques for monitoring and prognostication. In particular, there is growing evidence favoring extensive surgical resection and increasing interest in the role of chemotherapy (especially temozolomide) in the management of these tumors. In this review, we critically analyze emerging trends in the literature with respect to management of LGG, with particular emphasis on reports published during the past year