Evidence for Cancer Biomarkers in Exhaled Breath

Szulejko, Jan E.; McCulloch, Michael; Jackson, Jennifer; McKee, Dwight L.; Walker, Judy; Solouki, Touradj

doi:10.1109/jsen.2009.2035669

Cited by 65 publications

(55 citation statements)

References 180 publications

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“…We recently published a systematic review of all known data on the evidence for cancer biomarkers in exhaled breath [16], and a limited number of other research teams have published pilot data on exhaled breath analysis in lung cancer. There are no agreed upon standards for sampling methods or detection technology platform, each of these methods has limitations hampering their use for highly accurate lung cancer screening, and none have achieved the high sensitivity and specificity seen with dogs.…”

Section: Exhaled Breath Analysis: Dogs Are One Of Many Different Typementioning

confidence: 99%

Lung cancer detection by canine scent: will there be a lab in the lab?

McCulloch¹,

Turner²,

Broffman³

2012

European Respiratory Journal

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Section: Exhaled Breath Analysis: Dogs Are One Of Many Different Typementioning

confidence: 99%

Lung cancer detection by canine scent: will there be a lab in the lab?

McCulloch¹,

Turner²,

Broffman³

2012

European Respiratory Journal

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“…[76][77][78] Some concerted attempts to detect cancer biomarkers in exhaled breath have been made, but with limited success so far. [76][77][78] Some concerted attempts to detect cancer biomarkers in exhaled breath have been made, but with limited success so far.…”

Section: Volatile Biomarkers Of Cancer Cells In Vitro and In Vivomentioning

confidence: 99%

Recent SIFT-MS Studies of Volatile Compounds in Physiology, Medicine and Cell Biology

Španěl

Smith

2013

Volatile Biomarkers

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“…It results due to secretion of water, salt, acids, oil/wax, and proteins etc. [5][6][7][8][9][10][11][12] . in skin and hair; in addition to exterior of epidermis layer [1][2][3][4] .…”

Section: Introductionmentioning

confidence: 99%

Human body odor discrimination by GC-MS spectra data mining

et al. 2015

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Present study explores individual identity apperception by analyzing chemical peak information in gas chromatography-mass spectrometry (GC-MS) spectra of their body odor samples with standard data mining approaches. Mainly, principal component analysis (PCA) method is opted for visual discrimination of body odor samples in feature space. PCA in combination with support vector machine (SVM) method is used for quantitative recognition. GC-MS characterization confirms composition of numerous chemical species (aldehydes, acids, ketones, esters, sulfides etc.) in body odor samples. GC-MS spectra of body odor samples from armpit and neck of three persons (with dissimilar age groups) at two different sampling times (0 h and 4 h) were recorded in experiment. Few blank (non-body odor) samples were also characterized with GC-MS and included as reference in further analysis by data mining methods. Discrimination efficiency (both qualitative and quantitative) of individual body odors were evaluated for (i) three variables of chemicals information in GC-MS spectra (peak area, peak height and ratio of peak area and height); (ii) two sampling times (0 h and 4 h); and (iii) two sampling parts of body (neck and armpit). Best visual discrimination of individual body odors has been achieved using peak height as variable for neck odor in sampling time 4 h. This result has been established with class separability measures calculated with principal component (PC) scores and SVM classification outcomes (86%).

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Evidence for Cancer Biomarkers in Exhaled Breath

Cited by 65 publications

References 180 publications

Lung cancer detection by canine scent: will there be a lab in the lab?

Lung cancer detection by canine scent: will there be a lab in the lab?

Recent SIFT-MS Studies of Volatile Compounds in Physiology, Medicine and Cell Biology

Human body odor discrimination by GC-MS spectra data mining

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