The aim is to develop a highly accurate non-invasive determination of lead in bone by means of a sophisticated multistage signal processing technique, which is driven by case-based reasoning and a hybrid neural network. The validity and processing gain of the method shall be proven on Atlantex In-Vivo Lead Spectrometer (INVILS) data. The objective is to allow INVILS to quantify lead spectral peaks more accurately with less data. This will reduce x-ray exposure and allow accurate measurement at low lead levels where prior systems were unable to measure. The signal processing algorithm will be composed of four stages: a noise filter, a peak locator, a neural network peak identifier, and a case-based expert system for peak ratios enhancement. The research will also prototype a user friendly window-driven interface. This will enable future versions of INVILS to be employed at different locations such as hospitals, clinics, factories, etc. The device will supplement the use of blood-lead tests and will largely replace the use of provocative chelation testing. INVILS will be used for screening children at high risk of lead poisoning, industrially exposed workers, and for certain classes of the general population, such as those suffering from renal disease.Awardee's statement of the potential commercial applications of the research: INVILS will be needed for screening of 2-4,000,000 children at risk from lead poisoning and about 500,000 industrially-exposed lead workers. In-vivo K-XRF will also be needed for determining cumulative bone lead stores in at least 3,000,000 Americans in whom lead may contribute to neurological and cardiovascular-renal disease because of unrecognized excessive absorption from deteriorating interior paint, imported glazed or crystal wares, and contaminated food and water.National Institute of Environmental Health sciences (NIEHS)
