Yuanyuan Wu1, Anukul Boonloed1, Neal Sleszynski1, Myra Koesdjojo1, Chadd Armstrong1, Shay Bracha2, Vincent T Remcho3. 1. Department of Chemistry, Oregon State University, Corvallis, OR 97331, USA. 2. Department of Clinical Sciences, College of Veterinary Medicine, Oregon State University, Corvallis, OR 97331, USA. 3. Department of Chemistry, Oregon State University, Corvallis, OR 97331, USA. Electronic address: vince.remcho@oregonstate.edu.
Abstract
BACKGKROUND: Rapidly increasing healthcare costs in economically advantaged countries are currently unsustainable, while in many developing nations, even 50-year-old technologies are too expensive to implement. New and unconventional technologies are being explored as solutions to this problem. In this study, we examined the use of a smartphone as the detection platform for 2 well-developed, relatively inexpensive, commercially available clinical chemistry assays as a model for rapid and inexpensive clinical diagnostic testing. METHODS: An Apple iPhone 4 camera phone equipped with a color analysis application (ColorAssist) was combined with Vitros® glucose and urea colorimetric assays. Color images of assay slides at various concentrations of glucose or urea were collected with the iPhone 4 and quantitated in three different spectral ranges (red/green/blue or RGB) using the ColorAssist app. When the diffuse reflectance data was converted into absorbance, it was possible to quantitate glucose or blood urea nitrogen (BUN) over their clinically important concentration ranges (30-515mg/dl for glucose or 2-190mg/dl for BUN), with good linearity (R(2)=0.9994 or 0.9996, respectively [n=5]). RESULTS: Data collected using the iPhone 4 and canine serum samples were in agreement with results from the instrumental "gold standard" (Beckman Coulter AU480 Chemistry System) (R(2)=0.9966 and slope=1.0001 for glucose; R(2)=0.9958 and slope=0.9454 for BUN). Glucose determinations of serum samples made using this smartphone method were as accurate as or more accurate than a commercial colorimetric dry slide analyzer (Heska® Element DC Chemistry Analyzer, Loveland, CO) and 2 glucometers: ReliOn® Ultima (Abbott Diabetes Care Inc) and Presto® (AgaMatrix Inc.H). BUN determinations made using the smartphone approach were comparable in accuracy to the Heska instrument. CONCLUSION: This demonstration shows that smartphones have the potential to be used as simple, effective colorimetric detectors for quantitative diagnostic tests, and may be applicable for both point-of-care applications in the developed world and field deployment in developing nations.
BACKGKROUND: Rapidly increasing healthcare costs in economically advantaged countries are currently unsustainable, while in many developing nations, even 50-year-old technologies are too expensive to implement. New and unconventional technologies are being explored as solutions to this problem. In this study, we examined the use of a smartphone as the detection platform for 2 well-developed, relatively inexpensive, commercially available clinical chemistry assays as a model for rapid and inexpensive clinical diagnostic testing. METHODS: An Apple iPhone 4 camera phone equipped with a color analysis application (ColorAssist) was combined with Vitros® glucose and urea colorimetric assays. Color images of assay slides at various concentrations of glucose or urea were collected with the iPhone 4 and quantitated in three different spectral ranges (red/green/blue or RGB) using the ColorAssist app. When the diffuse reflectance data was converted into absorbance, it was possible to quantitate glucose or blood urea nitrogen (BUN) over their clinically important concentration ranges (30-515mg/dl for glucose or 2-190mg/dl for BUN), with good linearity (R(2)=0.9994 or 0.9996, respectively [n=5]). RESULTS: Data collected using the iPhone 4 and canine serum samples were in agreement with results from the instrumental "gold standard" (Beckman Coulter AU480 Chemistry System) (R(2)=0.9966 and slope=1.0001 for glucose; R(2)=0.9958 and slope=0.9454 for BUN). Glucose determinations of serum samples made using this smartphone method were as accurate as or more accurate than a commercial colorimetric dry slide analyzer (Heska® Element DC Chemistry Analyzer, Loveland, CO) and 2 glucometers: ReliOn® Ultima (Abbott Diabetes Care Inc) and Presto® (AgaMatrix Inc.H). BUN determinations made using the smartphone approach were comparable in accuracy to the Heska instrument. CONCLUSION: This demonstration shows that smartphones have the potential to be used as simple, effective colorimetric detectors for quantitative diagnostic tests, and may be applicable for both point-of-care applications in the developed world and field deployment in developing nations.
Authors: Amay J Bandodkar; Somayeh Imani; Rogelio Nuñez-Flores; Rajan Kumar; Chiyi Wang; A M Vinu Mohan; Joseph Wang; Patrick P Mercier Journal: Biosens Bioelectron Date: 2017-10-13 Impact factor: 10.618
Authors: I Hernández-Neuta; F Neumann; J Brightmeyer; T Ba Tis; N Madaboosi; Q Wei; A Ozcan; M Nilsson Journal: J Intern Med Date: 2018-09-12 Impact factor: 8.989