Rapid Daignostic Lateral Flow Strip Test Reader

Rapid Daignostic Lateral Flow Strip Test Reader

Non-invasive rapid diagnostic tests (RDT) are commonly used to detect some kind of viruses or bacteria instead of invasive methods. Helicobacter pylori (H. Pylori) which causes gastric cancer, peptic ulcer, gastritis, mucosa-associated lymphoid tissue lymphoma diseases can be detected easily with lateral flow strip (LFS) that is one of the RDT types. The tests are evaluated whether there are control line and test line at the region of interest (ROI) by users or microbiology technicians manually. Once the test line is tentative, despite the test must be reported positive, it can be resulted as negative incorrectly. This incorrect diagnose causes incorrect treatment planning. In this work, to mitigate this problem which will be able to occur by human based, an automatic LFS-RDT reading system is developed. The computer laptop based system firstly takes image utilizing the holders that are designed with 3D printer. Whether the test have the control-test lines or not are carried out by image processing techniques straightforwardly. After feature extraction from line areas, k-NN classification method is used to evaluate the test results automatically. 100 LFS-RDTs are tested and observed that all results are correct. The system is found quite useful and approved as a second reader by medical technicians.

___

  • Carrio, A. Sampedro, C. Sanchez-Lopez, J. L. Pimienta M. and Campoy, P.Automated low-cost smartphone-based lateral flow saliva test reader for drugs-of-abuse detection, Sensors. 15, 29569-29593, 2015
  • Li ,J. J., Ouellette, A. L., Giovangrandi, L., Cooper, D. E., Ricco, A. J., and Kovacs, G. T. A., “Optical scanner for immunoassays with up-converting phosphorescent labels,” IEEE Transactions on Biomedical Engineering, vol. 55, no. 5, pp. 1560–1571, 2008
  • Nuriman, B. K., Huskens, J. and Verboom, W. “Optical sensing systems for microfluidic devices: a review,” Analytica Chimica Acta, vol. 601, no. 2, pp. 141–155, 2007
  • Lee, D.-S. Jeon, B. G. Ihm, C. Park, J.-K. and Jung, M. Y. “A simple and smart telemedicine device for developing regions: a pocket-sized colorimetric reader,” Lab on a Chip— Miniaturisation for Chemistry and Biology, vol. 11, no. 1, pp. 120– 126, 2011.
  • Zhu, H. Isikman, S. O. Mudanyali, O. Greenbaum, A. and Ozcan, A. “Optical imaging techniques for point-of-care diagnostics,” Lab on a Chip, vol. 13, no. 1, pp. 51–67, 2013.
  • Zhang, X. Li, D. Wang C. et al., “A CCD-based reader combined quantumdots-labeled lateral flow strips for ultrasensitive quantitative detection of anti-HBs antibody,” Journal of Biomedical Nanotechnology, vol. 8, no. 3, pp. 372–379, 2012
  • Li, Z. Wang, Y. Wang, J. Tang, Z. Pounds, J. G. and Lin, Y. “Rapid and sensitive detection of protein biomarker using a portable fluorescence biosensor based on quantumdots and a lateral flow test strip,” Analytical Chemistry, vol. 82, no. 16, pp. 7008–7014, 2010
  • Hou, Y., Wang, K., Xiao, K., Qin, W., Lu, W., Tao, W., & Cui, D., Smartphone-Based Dual-Modality Imaging System for Quantitative Detection of Color or Fluorescent Lateral Flow Immunochromatographic Strips. Nanoscale Research Letters, 12, 291. 2017, http://doi.org/10.1186/s11671-017-207
  • Sista, R.; Hua, Z.; Thwar, P.; Sudarsan, A.; Srinivasan, V.; Eckhardt, A.; Pollack, M.; and Pamula, V. “Development of a digital microfluidic platform for point of care testing”, Lab Chip., 8, 2091–2104, 2008
  • Lee, W. G.; Kim, Y.G.; Chung, B.G.; Demirci, U.; and Khademhosseini, A. “Nano/Microfluidics for diagnosis of infectious diseases in developing countries”, Adv. Drug Delivery Rev., 62, 449–457, 2010
  • Saez, J., Belda, S., Santibáñez, M., Rodríguez, J. C., Sola-Vera, J., Galiana, A., Royo, G., Real-Time PCR for Diagnosing Helicobacter pylori Infection in Patients with Upper Gastrointestinal Bleeding: Comparison with Other Classical Diagnostic Methods. Journal of Clinical Microbiology, 50 (10), 3233–3237, 2012, http://doi.org/10.1128/JCM.01205-12
  • Ribeiro, M. L., Ecclissato, C. C., Mattos, R. G., Mendonca, S., & Pedrazzoli Jr., J., Quantitative real-time PCR for the clinical detection of Helicobacter pylori. Genetics and Molecular Biology, 30(2), 431-434, 2007, https://dx.doi.org/10.1590/S1415-47572007000300022
  • Schabereiter-Gurtner, C., Hirschl, A. M., Dragosics, B., Hufnagl, P., Puz, S., Kovách, Z., … Makristathis, A. (). Novel Real-Time PCR Assay for Detection of Helicobacter pylori Infection and Simultaneous Clarithromycin Susceptibility Testing of Stool and Biopsy Specimens. Journal of Clinical Microbiology, 42 (10), 4512–4518, 2004, http://doi.org/10.1128/JCM.42.10.4512-4518.2004
  • Burucoa, C., Delchier, J.-C., Courillon-Mallet A., et al., “Comparative evaluation of 29 commercial Helicobacter pylori serological kits,” Helicobacter, vol. 18, no. 3, pp. 169–179, 2013
  • Muhammad M. and Yoshio Y., “Diagnostic Methods of Helicobacter pylori Infection for Epidemiological Studies: Critical Importance of Indirect Test Validation,” BioMed Research International, 2016, Article ID 4819423, vol. 201614 pages,. doi:10.1155/2016/4819423
  • Mudanyali, O. Dimitrov, S. Sikora, U. Padmanabhan, S. Navruz, I. and Ozcan, A. “Integrated rapid-diagnostic-test reader platformon a cellphone,” Lab on a Chip, vol. 12,no. 15,pp. 2678– 2686, 2012
  • Dell N. and Borriello, G. “Mobile tools for point-of-care diagnostics in the developing world,” in Proceedings of the 3rd ACM Symposium on Computing for Development (ACM DEV ’13), Bangalore, India, January 2013.
  • You, D. J. Park, T. S. and Yoon, J.-Y. “Cell-phone-basedmeasurement of TSH using Mie scatter optimized lateral flow assays,” Biosensors and Bioelectronics, vol. 40, no. 1, pp. 180–185, 2013
  • Shen, L. Hagen, J. A.andPapautsky, I. “Point-of-care colorimetric detection with a smartphone,” Lab on a Chip, vol. 12, no. 21, pp. 4240–4243, 2012
  • Feng, S. Caire, R. Cortazar, B. Turan, M. Wong A., and Ozcan, A. “Immunochromatographic diagnostic test analysis using Google glass,” ACS Nano, vol. 8, no. 3, pp. 3069–3079, 2014.
  • Ozkan, H. and Kayhan, O. S. “A Novel Automatic Rapid Diagnostic Test Reader Platform,” Computational and Mathematical Methods in Medicine, vol. 2016, Article ID 7498217, 10 pages, 2016. doi:10.1155/2016/7498217.
  • Kayhan, O. S. “Automatic reading of rapid diagnostic tests and informing the clinicians with e-report”, M.Sc. Thesis, Istanbul Technical University, Biomedical Engineering Department, 2016.