An emerging trend in AD research is brain network development including graphic metrics and graph mining techniques. To construct a brain structural network, Diffusion Tensor Imaging (DTI) in conjunction with T1 weighted Magnetic Resonance Imaging (MRI) can be used to isolate brain regions as nodes, white matter tracts as the edge, and the density of the tracts as the weight to the edge. To study such network, its sub-network is often obtained by excluding unrelated nodes or edges. Existing research has heavily relied on domain knowledge or single-thresholding individual subject based network metrics to identify the sub network. In this research, we develop a bi-threshold frequent subgraph mining method (BT-FSG) to automatically filter out less important edges in responding to the clinical questions. Using this method, we are able to discover a subgraph of human brain network that can significantly reveal the difference between cognitively unimpaired APOE-4 carriers and noncarriers based on the correlations between the age vs. network local metric and age vs. network or global metric. This can potentially become a brain network marker for evaluating the AD risks for preclinical individuals.
MRI protocols are instruction sheets that radiology technologists use in routine clinical practice for guidance (e.g., slice
position, acquisition parameters etc.). In Mayo Clinic Arizona (MCA), there are over 900 MR protocols (ranging across
neuro, body, cardiac, breast etc.) which makes maintaining and updating the protocol instructions a labor intensive effort.
The task is even more challenging given different vendors (Siemens, GE etc.). This is a universal problem faced by all
the hospitals and/or medical research institutions. To increase the efficiency of the MR practice, we designed and
implemented a web-based platform (eProtocol) to automate the management of MRI protocols. It is built upon a database
that automatically extracts protocol information from DICOM compliant images and provides a user-friendly interface to
the technologists to create, edit and update the protocols. Advanced operations such as protocol migrations from scanner
to scanner and capability to upload Multimedia content were also implemented. To the best of our knowledge, eProtocol
is the first MR protocol automated management tool used clinically. It is expected that this platform will significantly
improve the radiology operations efficiency including better image quality and exam consistency, fewer repeat
examinations and less acquisition errors. These protocols instructions will be readily available to the technologists during
scans. In addition, this web-based platform can be extended to other imaging modalities such as CT, Mammography, and
Interventional Radiology and different vendors for imaging protocol management.
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