Solers Wavelet Fingerprinting Technique

DESCRIPTION (provided by applicant): We propose to test a novel Wavelet-Fingerprinting (WFP) technique to identify and characterize unique signatures of angiogenesis and apoptosis obscured within diagnostic ultrasonic signals. The WFP classifier combines wavelet analysis with a new way of organizing the wavelet coefficients over time and scale to create a fingerprint-like image of the signal that reveals subtle characteristic features embedded in the signal. Both angiogenesis and apoptosis are required fo r neoplastic disease development so that the ability to detect and quantify these cellular processes provides an early disease detection mechanism and a method for monitoring therapeutic response. We will use the WFP to analyze ultrasound data from excised breast tissue exhibiting normal and abnormal physiology. We will determine if angiogenetic and apoptotic physiology presents as unique, discernable signatures within the WFP fingerprint image so that they can be automatically identified and classi fied by intelligent software. In contrast to classical Fourier analysis, wavelet analysis preserves temporal information so that the location of the physiology can be easily determined. Currently, tissue based techniques such as immunohistochemistr y and molecular methods including polymerase chain reaction (PCR), Northern blots and fluorescent in-situ hybridization (FISH) are the mainstay to investigate angiogenesis and apoptosis. These methods bear an inherent degree of error in reproducibility and there is an issue of standardization of angiogenesis quantification. Newer techniques to identify and monitor angiogenesis and apoptosis (molecular imaging, PET, SPECT, MRI, ultrasound imaging etc.) all suffer from significant limitations that compromise one or more metrics of effectiveness including: user subjectivity, accuracy, speed/efficiency, patient health/comfort, complication/difficulty of use, broadness of information provided, and cost. Consequently, these techniques by themselves do not provide an optimal capability for early detection, treatment, or ongoing assessment of treatment/disease progress. The WFP technique offers an improved capability to detect and monitor neoplastic physiology and consequently, greatly enhance disease treatme nt and survivability. PUBLIC HEALTH RELEVANCE According to the SEER data base approximately 570,000 deaths were attributable to cancer in 2005 and 41,000 of these were associated with cancer of the breast. Development of the Wavelet-Fingerprinting Processor (WFP) will contribute to early detection and treatment of neoplastic diseases and greatly increase treatment efficacy and disease survivability. This technology will also allow in vivo evaluation of treatment effects which will allow the clinicia n to modify the therapy regimen if necessary.