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Combining Molecular And Imaging Biomarkers To Enhance Maldi Biomarker Analysis, Ayyappa Chowdary Vadlamudi
Combining Molecular And Imaging Biomarkers To Enhance Maldi Biomarker Analysis, Ayyappa Chowdary Vadlamudi
Electrical & Computer Engineering Theses & Dissertations
This thesis presents a three-step method to predict prostate cancer (PCa) regions on biopsy tissue samples based on high confident, low resolution PCa regions marked by a pathologist. First, a prediction model is designed to predict PCa regions using matrix-assisted laser desorption mass spectrometry (MALDI-MS) tissue imaging data from one prostate tissue slice. Second, a texture analysis technique is applied to a high magnification optical image for the same purpose from an adjacent tissue slice. Finally, those two results are fused to obtain the PCa regions that will assist MALDI imaging biomarker analysis. Experiments show that the texture analysis based …
Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie
Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie
Electrical & Computer Engineering Faculty Publications
For the early detection of prostate cancer, the analysis of the Prostate-specific antigen (PSA) in serum is currently the most popular approach. However, previous studies show that 15% of men have prostate cancer even their PSA concentrations are low. MALDI Mass Spectrometry (MS) proves to be a better technology to discover molecular tools for early cancer detection. The molecular tools or peptides are termed as biomarkers. Using MALDI MS data from prostate tissue samples, prostate cancer biomarkers can be identified by searching for molecular or molecular combination that can differentiate cancer tissue regions from normal ones. Cancer tissue regions are …