Document Type

Conference Paper

Publication Date

2010

DOI

10.1117/12.844494

Publication Title

Medical Imaging 2010: Computer-Aided Diagnosis, Proceedings of SPIE Vol. 7624

Volume

762422

Pages

762422

Conference Name

SPIE Medical Imaging 2010: Computer Aided Diagnosis, February 13-18, 2010,San Diego, California

Abstract

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 usually identified by pathologists after examining H&E stained histological microscopy images. Unfortunately, histopathological examination is currently done on an adjacent slice because the H&E staining process will change tissue's protein structure and it will derogate MALDI analysis if the same tissue is used, while the MALDI imaging process will destroy the tissue slice so that it is no longer available for histopathological exam. For this reason, only the most confident cancer region resulting from the histopathological examination on an adjacent slice will be used to guide the biomarker identification. It is obvious that a better cancer boundary delimitation on the MALDI imaging slice would be beneficial. In this paper, we proposed methods to predict the true cancer boundary, using the MALDI MS data, from the most confident cancer region given by pathologists on an adjacent slice.

Rights

Copyright 2010 Society of Photo‑Optical Instrumentation Engineers (SPIE).

One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.

Original Publication Citation

Vadlamudi, A., Chuang, S.-H., Sun, X., Cazares, L., Nyalwidhe, J., Troyer, D., Semmes, O. J., Li, J., & McKenzie, F. (2010) Prostate cancer region prediction using MALDI mass spectra. In N. Karssemeijer & R. M. Summers (Eds.), Medical Imaging 2010: Computer-Aided Diagnosis, Proceedings of SPIE Vol. 7624 (762422). SPIE of Bellingham, WA. https://doi.org/10.1117/12.844494

ORCID

0000-0003-0091-6986 (Li), 0000-0002-0160-5605 (McKenzie)

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