Combining prostate cancer region predictions from MALDI spectra processing and texture analysis

Jiang Li; Ayyappa Vadlamudi; Shao Hui Chuang; Xiaoyan Sun; Bo Sun; Frederic D. McKenzie; Lisa Cazares; Julius Nyalwidhe; Dean Troyer; O. John Semmes

doi:10.1109/BIBE.2010.20

Combining prostate cancer region predictions from MALDI spectra processing and texture analysis

Jiang Li, Ayyappa Vadlamudi, Shao Hui Chuang, Xiaoyan Sun, Bo Sun, Frederic D. McKenzie, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

We present a three-step method to predict Prostate cancer (PCa) regions on biopsy tissue samples based on high confidence, low resolution PCa regions marked by a pathologist. First, we apply a texture analysis technique on a high magnification optical image to predict PCa regions on an adjacent tissue slice. Second, we design a prediction model for the same purpose using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data from the adjacent slice. Finally, we fuse those two results to obtain the PCa regions that will assist MALDI imaging biomarker identification. Experiment results show that the texture analysis based prediction is sensitive (sen. 87.45%) but not specific (spe. 75%), and the prediction based on the MALDI spectra data is specific (spe. 100%) but less sensitive (sen. 50.98%). By combining those two results, a much better prediction for PCa regions on the adjacent slice can be achieved (sen. 80.39%, spe. 93.09%).

Original language	English (US)
Title of host publication	10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010
Pages	73-78
Number of pages	6
DOIs	https://doi.org/10.1109/BIBE.2010.20
State	Published - 2010
Externally published	Yes
Event	10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010 - Philadelphia, PA, United States Duration: May 31 2010 → Jun 3 2010

Publication series

Name	10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010

Conference

Conference	10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010
Country/Territory	United States
City	Philadelphia, PA
Period	5/31/10 → 6/3/10

Keywords

Biomarker identification
Imaging biomarker
MALDI
Prostate cancer

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics

Access to Document

10.1109/BIBE.2010.20

Cite this

Li, J., Vadlamudi, A., Chuang, S. H., Sun, X., Sun, B., McKenzie, F. D., Cazares, L., Nyalwidhe, J., Troyer, D., & Semmes, O. J. (2010). Combining prostate cancer region predictions from MALDI spectra processing and texture analysis. In 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010 (pp. 73-78). [5521709] (10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010). https://doi.org/10.1109/BIBE.2010.20

Combining prostate cancer region predictions from MALDI spectra processing and texture analysis. / Li, Jiang; Vadlamudi, Ayyappa; Chuang, Shao Hui et al.

10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010. 2010. p. 73-78 5521709 (10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, J, Vadlamudi, A, Chuang, SH, Sun, X, Sun, B, McKenzie, FD, Cazares, L, Nyalwidhe, J, Troyer, D & Semmes, OJ 2010, Combining prostate cancer region predictions from MALDI spectra processing and texture analysis. in 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010., 5521709, 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010, pp. 73-78, 10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010, Philadelphia, PA, United States, 5/31/10. https://doi.org/10.1109/BIBE.2010.20

Li J, Vadlamudi A, Chuang SH, Sun X, Sun B, McKenzie FD et al. Combining prostate cancer region predictions from MALDI spectra processing and texture analysis. In 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010. 2010. p. 73-78. 5521709. (10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010). doi: 10.1109/BIBE.2010.20

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title = "Combining prostate cancer region predictions from MALDI spectra processing and texture analysis",

abstract = "We present a three-step method to predict Prostate cancer (PCa) regions on biopsy tissue samples based on high confidence, low resolution PCa regions marked by a pathologist. First, we apply a texture analysis technique on a high magnification optical image to predict PCa regions on an adjacent tissue slice. Second, we design a prediction model for the same purpose using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data from the adjacent slice. Finally, we fuse those two results to obtain the PCa regions that will assist MALDI imaging biomarker identification. Experiment results show that the texture analysis based prediction is sensitive (sen. 87.45%) but not specific (spe. 75%), and the prediction based on the MALDI spectra data is specific (spe. 100%) but less sensitive (sen. 50.98%). By combining those two results, a much better prediction for PCa regions on the adjacent slice can be achieved (sen. 80.39%, spe. 93.09%).",

keywords = "Biomarker identification, Imaging biomarker, MALDI, Prostate cancer",

author = "Jiang Li and Ayyappa Vadlamudi and Chuang, {Shao Hui} and Xiaoyan Sun and Bo Sun and McKenzie, {Frederic D.} and Lisa Cazares and Julius Nyalwidhe and Dean Troyer and Semmes, {O. John}",

year = "2010",

doi = "10.1109/BIBE.2010.20",

language = "English (US)",

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AU - Li, Jiang

AU - Vadlamudi, Ayyappa

AU - Chuang, Shao Hui

AU - Sun, Xiaoyan

AU - Sun, Bo

AU - McKenzie, Frederic D.

AU - Cazares, Lisa

AU - Nyalwidhe, Julius

AU - Troyer, Dean

AU - Semmes, O. John

PY - 2010

Y1 - 2010

N2 - We present a three-step method to predict Prostate cancer (PCa) regions on biopsy tissue samples based on high confidence, low resolution PCa regions marked by a pathologist. First, we apply a texture analysis technique on a high magnification optical image to predict PCa regions on an adjacent tissue slice. Second, we design a prediction model for the same purpose using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data from the adjacent slice. Finally, we fuse those two results to obtain the PCa regions that will assist MALDI imaging biomarker identification. Experiment results show that the texture analysis based prediction is sensitive (sen. 87.45%) but not specific (spe. 75%), and the prediction based on the MALDI spectra data is specific (spe. 100%) but less sensitive (sen. 50.98%). By combining those two results, a much better prediction for PCa regions on the adjacent slice can be achieved (sen. 80.39%, spe. 93.09%).

AB - We present a three-step method to predict Prostate cancer (PCa) regions on biopsy tissue samples based on high confidence, low resolution PCa regions marked by a pathologist. First, we apply a texture analysis technique on a high magnification optical image to predict PCa regions on an adjacent tissue slice. Second, we design a prediction model for the same purpose using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data from the adjacent slice. Finally, we fuse those two results to obtain the PCa regions that will assist MALDI imaging biomarker identification. Experiment results show that the texture analysis based prediction is sensitive (sen. 87.45%) but not specific (spe. 75%), and the prediction based on the MALDI spectra data is specific (spe. 100%) but less sensitive (sen. 50.98%). By combining those two results, a much better prediction for PCa regions on the adjacent slice can be achieved (sen. 80.39%, spe. 93.09%).

KW - Biomarker identification

KW - Imaging biomarker

KW - MALDI

KW - Prostate cancer

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Combining prostate cancer region predictions from MALDI spectra processing and texture analysis

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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