A new paradigm for clinical biomarker discovery and screening with mass spectrometry through biomedical image analysis principles

Hanqing Liao; Emmanouil Moschidis; Isabel Riba-Garcia; Yan Zhang; Richard D. Unwin; Jeffrey S. Morris; Jim Graham; Andrew W. Dowsey

A new paradigm for clinical biomarker discovery and screening with mass spectrometry through biomedical image analysis principles

Hanqing Liao, Emmanouil Moschidis, Isabel Riba-Garcia, Yan Zhang, Richard D. Unwin, Jeffrey S. Morris, Jim Graham, Andrew W. Dowsey

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

6 Citations (Scopus)

Abstract

Biomarker discovery in amenably sampled body fluids has the potential to empower clinical screening programs for the early detection of disease. Liquid Chromatography interfaced to Mass Spectrometry (LC-MS) has emerged as a central technique for sensitive and automated analysis of proteins and metabolites from these clinical samples. However, the potential of LC-MS as a precise and reliable platform for discovery and screening is dependent on robust, sensitive and specific signal extraction and interpretation. The output of LC-MS is formed as a set of quantifiable images containing thousands of biochemical signals regulated in disease and treatment. We propose to tackle this problem for the first time with a biomedical image analysis paradigm. A novel workflow of image reconstruction, groupwise image registration and Bayesian functional mixed-effects modeling is presented. Poisson counting noise and lognormal biological variation are modeled in the raw image domain, resulting in markedly improved detection limit for differential analysis.¹

Original language	English
Title of host publication	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1332-1335
Number of pages	4
ISBN (Print)	9781467319591
Publication status	Published - 29 Jul 2014
Event	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China Duration: 29 Apr 2014 → 2 May 2014

Conference

Conference	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Country/Territory	China
City	Beijing
Period	29/04/14 → 2/05/14

Research Groups and Themes

Jean Golding

Keywords

Functional mixed model
Image registration
Mass spectrometry
Proteomics
Reconstruction

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Liao, H., Moschidis, E., Riba-Garcia, I., Zhang, Y., Unwin, R. D., Morris, J. S., Graham, J., & Dowsey, A. W. (2014). A new paradigm for clinical biomarker discovery and screening with mass spectrometry through biomedical image analysis principles. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 (pp. 1332-1335). Article 6868123 Institute of Electrical and Electronics Engineers (IEEE).

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title = "A new paradigm for clinical biomarker discovery and screening with mass spectrometry through biomedical image analysis principles",

abstract = "Biomarker discovery in amenably sampled body fluids has the potential to empower clinical screening programs for the early detection of disease. Liquid Chromatography interfaced to Mass Spectrometry (LC-MS) has emerged as a central technique for sensitive and automated analysis of proteins and metabolites from these clinical samples. However, the potential of LC-MS as a precise and reliable platform for discovery and screening is dependent on robust, sensitive and specific signal extraction and interpretation. The output of LC-MS is formed as a set of quantifiable images containing thousands of biochemical signals regulated in disease and treatment. We propose to tackle this problem for the first time with a biomedical image analysis paradigm. A novel workflow of image reconstruction, groupwise image registration and Bayesian functional mixed-effects modeling is presented. Poisson counting noise and lognormal biological variation are modeled in the raw image domain, resulting in markedly improved detection limit for differential analysis.1",

keywords = "Functional mixed model, Image registration, Mass spectrometry, Proteomics, Reconstruction",

author = "Hanqing Liao and Emmanouil Moschidis and Isabel Riba-Garcia and Yan Zhang and Unwin, {Richard D.} and Morris, {Jeffrey S.} and Jim Graham and Dowsey, {Andrew W.}",

year = "2014",

month = jul,

day = "29",

language = "English",

isbn = "9781467319591",

pages = "1332--1335",

booktitle = "2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 ; Conference date: 29-04-2014 Through 02-05-2014",

}

Liao, H, Moschidis, E, Riba-Garcia, I, Zhang, Y, Unwin, RD, Morris, JS, Graham, J & Dowsey, AW 2014, A new paradigm for clinical biomarker discovery and screening with mass spectrometry through biomedical image analysis principles. in 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014., 6868123, Institute of Electrical and Electronics Engineers (IEEE), pp. 1332-1335, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Beijing, China, 29/04/14.

A new paradigm for clinical biomarker discovery and screening with mass spectrometry through biomedical image analysis principles. / Liao, Hanqing; Moschidis, Emmanouil; Riba-Garcia, Isabel et al.
2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 1332-1335 6868123.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - A new paradigm for clinical biomarker discovery and screening with mass spectrometry through biomedical image analysis principles

AU - Liao, Hanqing

AU - Moschidis, Emmanouil

AU - Riba-Garcia, Isabel

AU - Zhang, Yan

AU - Unwin, Richard D.

AU - Morris, Jeffrey S.

AU - Graham, Jim

AU - Dowsey, Andrew W.

PY - 2014/7/29

Y1 - 2014/7/29

N2 - Biomarker discovery in amenably sampled body fluids has the potential to empower clinical screening programs for the early detection of disease. Liquid Chromatography interfaced to Mass Spectrometry (LC-MS) has emerged as a central technique for sensitive and automated analysis of proteins and metabolites from these clinical samples. However, the potential of LC-MS as a precise and reliable platform for discovery and screening is dependent on robust, sensitive and specific signal extraction and interpretation. The output of LC-MS is formed as a set of quantifiable images containing thousands of biochemical signals regulated in disease and treatment. We propose to tackle this problem for the first time with a biomedical image analysis paradigm. A novel workflow of image reconstruction, groupwise image registration and Bayesian functional mixed-effects modeling is presented. Poisson counting noise and lognormal biological variation are modeled in the raw image domain, resulting in markedly improved detection limit for differential analysis.1

AB - Biomarker discovery in amenably sampled body fluids has the potential to empower clinical screening programs for the early detection of disease. Liquid Chromatography interfaced to Mass Spectrometry (LC-MS) has emerged as a central technique for sensitive and automated analysis of proteins and metabolites from these clinical samples. However, the potential of LC-MS as a precise and reliable platform for discovery and screening is dependent on robust, sensitive and specific signal extraction and interpretation. The output of LC-MS is formed as a set of quantifiable images containing thousands of biochemical signals regulated in disease and treatment. We propose to tackle this problem for the first time with a biomedical image analysis paradigm. A novel workflow of image reconstruction, groupwise image registration and Bayesian functional mixed-effects modeling is presented. Poisson counting noise and lognormal biological variation are modeled in the raw image domain, resulting in markedly improved detection limit for differential analysis.1

KW - Functional mixed model

KW - Image registration

KW - Mass spectrometry

KW - Proteomics

KW - Reconstruction

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M3 - Conference Contribution (Conference Proceeding)

AN - SCOPUS:84927945709

SN - 9781467319591

SP - 1332

EP - 1335

BT - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Y2 - 29 April 2014 through 2 May 2014

ER -

A new paradigm for clinical biomarker discovery and screening with mass spectrometry through biomedical image analysis principles

Abstract

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Research Groups and Themes

Keywords

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