Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader
Measuring the colorimetric signals produced by the biospecific accumulation of colorimetric probes and recording the results is a key feature for next-generation paper-based rapid tests. Manual processing of these tests is time-consuming and prone to a loss of accuracy when interpreting faint and pa...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/5/1880 |
| _version_ | 1797473710682144768 |
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| author | Steven M. Russell Alejandra Alba-Patiño Andreu Vaquer Antonio Clemente Roberto de la Rica |
| author_facet | Steven M. Russell Alejandra Alba-Patiño Andreu Vaquer Antonio Clemente Roberto de la Rica |
| author_sort | Steven M. Russell |
| collection | DOAJ |
| description | Measuring the colorimetric signals produced by the biospecific accumulation of colorimetric probes and recording the results is a key feature for next-generation paper-based rapid tests. Manual processing of these tests is time-consuming and prone to a loss of accuracy when interpreting faint and patchy signals. Proprietary, closed-source readers and software companies offering automated smartphone-based assay readings have both been criticized for interoperability issues. Here, we introduce a minimal reader prototype composed of open-source hardware and open-source software that has the benefits of automatic assay quantification while avoiding the interoperability issues associated with closed-source readers. An image-processing algorithm was developed to automate the selection of an optimal region of interest and measure the average pixel intensity. When used to quantify signals produced by lateral flow immunoassays for detecting antibodies against SARS-CoV-2, results obtained with the proposed algorithm were comparable to those obtained with a manual method but with the advantage of improving the precision and accuracy when quantifying small spots or faint and patchy signals. |
| first_indexed | 2024-03-09T20:21:15Z |
| format | Article |
| id | doaj.art-505de005697a498198d54b82ec72a5c8 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T20:21:15Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-505de005697a498198d54b82ec72a5c82023-11-23T23:47:39ZengMDPI AGSensors1424-82202022-02-01225188010.3390/s22051880Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source ReaderSteven M. Russell0Alejandra Alba-Patiño1Andreu Vaquer2Antonio Clemente3Roberto de la Rica4Multidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma de Mallorca, SpainMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma de Mallorca, SpainMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma de Mallorca, SpainMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma de Mallorca, SpainMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma de Mallorca, SpainMeasuring the colorimetric signals produced by the biospecific accumulation of colorimetric probes and recording the results is a key feature for next-generation paper-based rapid tests. Manual processing of these tests is time-consuming and prone to a loss of accuracy when interpreting faint and patchy signals. Proprietary, closed-source readers and software companies offering automated smartphone-based assay readings have both been criticized for interoperability issues. Here, we introduce a minimal reader prototype composed of open-source hardware and open-source software that has the benefits of automatic assay quantification while avoiding the interoperability issues associated with closed-source readers. An image-processing algorithm was developed to automate the selection of an optimal region of interest and measure the average pixel intensity. When used to quantify signals produced by lateral flow immunoassays for detecting antibodies against SARS-CoV-2, results obtained with the proposed algorithm were comparable to those obtained with a manual method but with the advantage of improving the precision and accuracy when quantifying small spots or faint and patchy signals.https://www.mdpi.com/1424-8220/22/5/1880lateral flow testCOVID-19immunosensorbiosensoropen-sourceimage processing |
| spellingShingle | Steven M. Russell Alejandra Alba-Patiño Andreu Vaquer Antonio Clemente Roberto de la Rica Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader Sensors lateral flow test COVID-19 immunosensor biosensor open-source image processing |
| title | Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader |
| title_full | Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader |
| title_fullStr | Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader |
| title_full_unstemmed | Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader |
| title_short | Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader |
| title_sort | improving the quantification of colorimetric signals in paper based immunosensors with an open source reader |
| topic | lateral flow test COVID-19 immunosensor biosensor open-source image processing |
| url | https://www.mdpi.com/1424-8220/22/5/1880 |
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