TY - JOUR
T1 - Fourier-Transform Infra-Red Microspectroscopy Can Accurately Diagnose Colitis and Assess Severity of Inflammation
AU - Keung, Charlotte
AU - Heraud, Philip
AU - Kuk, Nathan
AU - Lim, Rebecca
AU - Sievert, William
AU - Moore, Gregory
AU - Wood, Bayden
N1 - Funding Information:
Funding: This research was funded by The Gutsy Group Inflammatory Bowel Disease Research Grant, 2018–2021, Australia.
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/3/1
Y1 - 2022/3/1
N2 - The diagnosis and management of inflammatory bowel disease relies on histological assessment, which is costly, subjective, and lacks utility for point-of-care diagnosis. Fourier-transform infra-red spectroscopy provides rapid, non-destructive, reproducible, and automatable label-free biochemical imaging of tissue for diagnostic purposes. This study characterises colitis using spectroscopy, discriminates colitis from healthy tissue, and classifies inflammation severity. Hyperspectral images were obtained from fixed intestinal sections of a murine colitis model treated with cell therapy to improve inflammation. Multivariate analyses and classification modelling were performed using supervised and unsupervised machine-learning algorithms. Quantitative analysis of severe colitis showed increased protein, collagen, and nucleic acids, but reduced glycogen when compared with normal tissue. A partial least squares discriminant analysis model, including spectra from all intestinal layers, classified normal colon and severe colitis with a sensitivity of 91.4% and a specificity of 93.3%. Colitis severity was classified by a stacked ensemble model yielding an average area under the receiver operating characteristic curve of 0.95, 0.88, 0.79, and 0.85 for controls, mild, moderate, and severe colitis, respectively. Infra-red spectroscopy can detect unique biochemical features of intestinal inflammation and accurately classify normal and inflamed tissue and quantify the severity of inflammation. This is a promising alternative to histological assessment.
AB - The diagnosis and management of inflammatory bowel disease relies on histological assessment, which is costly, subjective, and lacks utility for point-of-care diagnosis. Fourier-transform infra-red spectroscopy provides rapid, non-destructive, reproducible, and automatable label-free biochemical imaging of tissue for diagnostic purposes. This study characterises colitis using spectroscopy, discriminates colitis from healthy tissue, and classifies inflammation severity. Hyperspectral images were obtained from fixed intestinal sections of a murine colitis model treated with cell therapy to improve inflammation. Multivariate analyses and classification modelling were performed using supervised and unsupervised machine-learning algorithms. Quantitative analysis of severe colitis showed increased protein, collagen, and nucleic acids, but reduced glycogen when compared with normal tissue. A partial least squares discriminant analysis model, including spectra from all intestinal layers, classified normal colon and severe colitis with a sensitivity of 91.4% and a specificity of 93.3%. Colitis severity was classified by a stacked ensemble model yielding an average area under the receiver operating characteristic curve of 0.95, 0.88, 0.79, and 0.85 for controls, mild, moderate, and severe colitis, respectively. Infra-red spectroscopy can detect unique biochemical features of intestinal inflammation and accurately classify normal and inflamed tissue and quantify the severity of inflammation. This is a promising alternative to histological assessment.
KW - Colitis
KW - Inflammatory bowel disease
KW - Infra-red spectroscopy
KW - Vibrational spectroscopy
UR - http://www.scopus.com/inward/record.url?scp=85125593368&partnerID=8YFLogxK
U2 - 10.3390/ijms23052849
DO - 10.3390/ijms23052849
M3 - Article
C2 - 35269993
AN - SCOPUS:85125593368
SN - 1422-0067
VL - 23
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
IS - 5
M1 - 2849
ER -