Nanodiamond-Manganese dual mode MRI contrast agents for enhanced liver tumor detection.

Contrast agent-enhanced magnetic resonance (MR) imaging is critical for the diagnosis and monitoring of a number of diseases, including cancer. Certain clinical applications, including the detection of liver tumors, rely on both T1 and T2-weighted images even though contrast agent-enhanced MR imaging is not always reliable. Thus, there is a need for improved dual mode contrast agents with enhanced sensitivity. We report the development of a nanodiamond-manganese dual mode contrast agent that enhanced both T1 and T2-weighted MR imaging. Conjugation of manganese to nanodiamonds resulted in improved longitudinal and transverse relaxivity efficacy over unmodified MnCl2 as well as clinical contrast agents. Following intravenous administration, nanodiamond-manganese complexes outperformed current clinical contrast agents in an orthotopic liver cancer mouse model while also reducing blood serum concentration of toxic free Mn2+ ions. Thus, nanodiamond-manganese complexes may serve as more effective dual mode MRI contrast agent, particularly in cancer.

Automated gamma knife radiosurgery treatment planning with image registration, data-mining, and Nelder-Mead simplex optimization.

Gamma knife treatments are usually planned manually, requiring much expertise and time. We describe a new, fully automatic method of treatment planning. The treatment volume to be planned is first compared with a database of past treatments to find volumes closely matching in size and shape. The treatment parameters of the closest matches are used as starting points for the new treatment plan. Further optimization is performed with the Nelder-Mead simplex method: the coordinates and weight of the isocenters are allowed to vary until a maximally conformal plan specific to the new treatment volume is found. The method was tested on a randomly selected set of 10 acoustic neuromas and 10 meningiomas. Typically, matching a new volume took under 30 seconds. The time for simplex optimization, on a 3 GHz Xeon processor, ranged from under a minute for small volumes (<1000 cubic mm, 2-3 isocenters), to several tens of hours for large volumes (>30,000 cubic mm, >20 isocenters). In 8/10 acoustic neuromas and 8/10 meningiomas, the automatic method found plans with conformation number equal or better than that of the manual plan. In 4/10 acoustic neuromas and 5/10 meningiomas, both overtreatment and undertreatment ratios were equal or better in automated plans. In conclusion, data-mining of past treatments can be used to derive starting parameters for treatment planning. These parameters can then be computer optimized to give good plans automatically.