Toward "bigger" data for neurosurgical anatomical research: a single centralized quantitative neurosurgical anatomy platform.

Quantitative neurosurgical anatomy research aims to produce surgically applicable knowledge for improving operative decision-making using measurements from anatomical dissection and tools such as stereotaxis. Although such studies attempt to answer similar research questions, there is little standardization between them, offering minimal comparability. Modern technology has been incorporated into the research methodology, but many scientific principles are lacking, and results are not broadly applicable or suitable for evaluating big-data trends. Advances in information technology and the concept of big data permit more accessible and robust means of producing valuable, standardized, reliable research. A technology project, "Inchin," is presented to address these needs for neurosurgical anatomy research. This study applies the concept of big data to neurosurgical anatomy research, specifically in quantifying surgical metrics. A remote-hosted web application was developed for computing standard neurosurgical metrics and storing measurement data. An online portal (Inchin) was developed to produce a database to facilitate and promote neurosurgical anatomical research, applying optimal scientific methodology and big-data principles to this recent and evolving field of research. Individual data sets are not insignificant, but a collective of data sets present advantages. Large data sets allow confidence in data trends that are usually obscured in smaller numbers of samples. Inchin, a single centralized software platform, can act as a global database of results of neurosurgical anatomy studies. A calculation tool ensuring standardized peer-reviewed methodology, Inchin is applied to the analysis of neurosurgical metrics and may promote efficient study collaboration within and among neurosurgical laboratories.