Computer-Aided Diagnostic for Use in Multiparametric MRI for Prostate Cancer

Multiparametric MRI improves image detail and prostate cancer detection rates compared to standard MRI. Computer aided diagnostics (CAD) used in combination with multiparametric MRI images may further improve prostate cancer detection and visualization. The technology, developed by researchers at the National Institutes of Health Clinical Center (NIHCC), is an automated CAD system for use in processing and visualizing prostate lesions on multiparametric MRI images.

Video Monitoring and Analysis System for Vivarium Cage Racks

This invention pertains to a system for continuous observation of rodents in home-cage environments with the specific aim to facilitate the quantification of activity levels and behavioral patterns for mice housed in a commercial ventilated cage rack.  The home-cage in-rack provides daytime and nighttime monitoring with the stability and consistency of a home cage environment.

Zirconium-89 PET Imaging Agent for Cancer

Researchers at the NCI Radiation Oncology Branch  and NIH CIT Center for Molecular Modeling developed a tetrahydroxamate chelation technology that provides a more-stable Zr-89 complex as an immuno-PET cancer imaging agent. In either the linear or the macrocyclic form, the tetrahydroxamate complexes exhibit greater stability as chelating agents compared to Zr-89 complexed to the siderophore desferrioxamine B (DFB), a trihydroxamate, which represent

Methods of Treating Diffuse Large B Cell Lymphoma Based on Particular Genetic Subtype (LymphGen) - A Genetic Classifier to Aid in the Molecular Diagnosis and Treatment of Diffuse Large B-cell Lymphoma

The development of precision medicine approaches for DLBCL (Diffuse Large B Cell Lymphoma) is complicated by its genetic, phenotypic and clinical heterogeneity. Current classification methods do not fully explain the observed differences in clinical outcomes to current chemotherapy and targeted therapy. Therefore, better analytical methods to classify and predict DLBCL patients’ treatment response are needed.