TY - JOUR
T1 - Sensitivity of Raman spectroscopy to normal patient variability
AU - Vargis, Elizabeth
AU - Byrd, Teresa
AU - Logan, Quinisha
AU - Khabele, Dineo
AU - Mahadevan-Jansen, Anita
N1 - Funding Information:
The authors acknowledge the financial support of the National Institute of Health Grant No. R01-CA-095405 and a predoctoral fellowship (Grant No. T32-HL7751-15) for E.V. Special thanks go to the nurses and staff at Meharry Medical College for their help, and to Chetan Patil and Amy Rudin for proofreading this paper.
PY - 2011/11
Y1 - 2011/11
N2 - Many groups have used Raman spectroscopy for diagnosing cervical dysplasia; however, there have been few studies looking at the effect of normal physiological variations on Raman spectra. We assess four patient variables that may affect normal Raman spectra: Raceethnicity, body mass index (BMI), parity, and socioeconomic status. Raman spectra were acquired from a diverse population of 75 patients undergoing routine screening for cervical dysplasia. Classification of Raman spectra from patients with a normal cervix is performed using sparse multinomial logistic regression (SMLR) to determine if any of these variables has a significant effect. Results suggest that BMI and parity have the greatest impact, whereas raceethnicity and socioeconomic status have a limited effect. Incorporating BMI and obstetric history into classification algorithms may increase sensitivity and specificity rates of disease classification using Raman spectroscopy. Studies are underway to assess the effect of these variables on disease.
AB - Many groups have used Raman spectroscopy for diagnosing cervical dysplasia; however, there have been few studies looking at the effect of normal physiological variations on Raman spectra. We assess four patient variables that may affect normal Raman spectra: Raceethnicity, body mass index (BMI), parity, and socioeconomic status. Raman spectra were acquired from a diverse population of 75 patients undergoing routine screening for cervical dysplasia. Classification of Raman spectra from patients with a normal cervix is performed using sparse multinomial logistic regression (SMLR) to determine if any of these variables has a significant effect. Results suggest that BMI and parity have the greatest impact, whereas raceethnicity and socioeconomic status have a limited effect. Incorporating BMI and obstetric history into classification algorithms may increase sensitivity and specificity rates of disease classification using Raman spectroscopy. Studies are underway to assess the effect of these variables on disease.
KW - Raman spectroscopy
KW - cervical dysplasia
KW - fiber-optic applications
KW - sparse multinomial logistic regression
UR - http://www.scopus.com/inward/record.url?scp=80655143456&partnerID=8YFLogxK
U2 - 10.1117/1.3646210
DO - 10.1117/1.3646210
M3 - Article
C2 - 22112136
AN - SCOPUS:80655143456
SN - 1083-3668
VL - 16
JO - Journal of biomedical optics
JF - Journal of biomedical optics
IS - 11
M1 - 117004
ER -