Abstract
| Original language | English |
|---|---|
| Journal | Analyst |
| Early online date | 19 Nov 2018 |
| DOIs | |
| Publication status | E-pub ahead of print - 19 Nov 2018 |
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Keywords
- Mid-IR spectroscopy
- pre-processing protocol
- biofluid ATR-FTIR spectroscopy
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Optimised spectral pre-processing for discrimination of biofluids via ATR-FTIR spectroscopy. / Butler, Holly J.; Smith, Benjamin R.; Fritzsch, Robby; Radhakrishnan, Pretheepan; Palmer, David S.; Baker, Matthew J.
In: Analyst, 19.11.2018.Research output: Contribution to journal › Article
TY - JOUR
T1 - Optimised spectral pre-processing for discrimination of biofluids via ATR-FTIR spectroscopy
AU - Butler, Holly J.
AU - Smith, Benjamin R.
AU - Fritzsch, Robby
AU - Radhakrishnan, Pretheepan
AU - Palmer, David S.
AU - Baker, Matthew J.
PY - 2018/11/19
Y1 - 2018/11/19
N2 - Pre-processing is an essential step in the analysis of spectral data. Mid-IR spectroscopy of biological samples is often subject to instrumental and sample specific variances which may often conceal valuable biological information. Whilst pre-processing can effectively reduce this unwanted variance, the plethora of possible processing steps has resulted in a lack of consensus in the field, often meaning that analysis outputs are not comparable. As pre-processing is specific to the sample under investigation, here we present a systematic approach for defining the optimum pre-processing protocol for biofluid ATR-FTIR spectroscopy. Using a trial-and-error based approach and a clinically relevant dataset describing control and brain cancer patients (3,897 spectra), the effects of pre-processing permutations on subsequent classification algorithms were observed, by assessing key diagnostic performance parameters, including sensitivity and specificity. It was found that optimum diagnostic performance correlated with the use of minimal binning and baseline correction, with derivative functions improving diagnostic performance most significantly. If smoothing is required, a Sovitzky-Golay approach was the preferred option in this investigation. Heavy binning appeared to reduce classification most significantly, alongside wavelet noise reduction (filter length ≥ 6), resulting in the lowest diagnostic performances of all pre-processing permutations tested.
AB - Pre-processing is an essential step in the analysis of spectral data. Mid-IR spectroscopy of biological samples is often subject to instrumental and sample specific variances which may often conceal valuable biological information. Whilst pre-processing can effectively reduce this unwanted variance, the plethora of possible processing steps has resulted in a lack of consensus in the field, often meaning that analysis outputs are not comparable. As pre-processing is specific to the sample under investigation, here we present a systematic approach for defining the optimum pre-processing protocol for biofluid ATR-FTIR spectroscopy. Using a trial-and-error based approach and a clinically relevant dataset describing control and brain cancer patients (3,897 spectra), the effects of pre-processing permutations on subsequent classification algorithms were observed, by assessing key diagnostic performance parameters, including sensitivity and specificity. It was found that optimum diagnostic performance correlated with the use of minimal binning and baseline correction, with derivative functions improving diagnostic performance most significantly. If smoothing is required, a Sovitzky-Golay approach was the preferred option in this investigation. Heavy binning appeared to reduce classification most significantly, alongside wavelet noise reduction (filter length ≥ 6), resulting in the lowest diagnostic performances of all pre-processing permutations tested.
KW - Mid-IR spectroscopy
KW - pre-processing protocol
KW - biofluid ATR-FTIR spectroscopy
UR - https://pubs.rsc.org/en/journals/journalissues/an#!recentarticles&adv
U2 - 10.1039/C8AN01384E
DO - 10.1039/C8AN01384E
M3 - Article
JO - Analyst
JF - Analyst
SN - 0003-2654
ER -