Simultaneous phenotyping of five Rh red blood cell antigens on a paper-based analytical device combined with deep learning for rapid and accurate interpretation.

Journal: Analytica chimica acta
Published Date:

Abstract

Both the ABO and Rhesus (Rh) blood groups play crucial roles in blood transfusion medicine. Herein, we report a simple and low-cost paper-based analytical device (PAD) for phenotyping red blood cell (RBC) antigens. Using this Rh typing format, 5 Rh antigens on RBCs can be simultaneously detected and macroscopically visualized within 12 min. The proposed Rh phenotyping relies on the presence or absence of hemagglutination in the sample zones after immobilizing the antibodies targeting each Rh antigen. The PAD was optimized in terms of filter paper type, antibodies, and distance of the visualization zone. In this study, the optimal conditions were Whatman filter paper Grade 4; anti-D, -C, -E, -c, and -e antibodies; RBC suspension of 30%; and a visualization zone of 1 cm above the sample zone. The accuracy of simultaneously phenotyping the five Rh RBC antigens in the blood samples (n = 4692) was 99.19%, comparable with the accuracy of the gold-standard tube method used by blood bank laboratories in several regions of Thailand. Furthermore, decision making based on this method can be assisted by deep learning. After implementing a two-stage objective detection algorithm (YOLO v4-tiny) and classification model (DenseNet-201), the ambiguous images (n = 48) were interpreted with 100% accuracy. The PAD integrated with customized-region convolutional neural networks can reduce the interpretation discrepancies in RBC antigen phenotyping in any laboratory.

Authors

  • Nutcha Larpant
    Biosensors and Bioanalytical Technology for Cells and Innovative Testing Device Research Unit, Department of Clinical Chemistry, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, 10330, Thailand.
  • Wisanu Niamsi
    Biosensors and Bioanalytical Technology for Cells and Innovative Testing Device Research Unit, Department of Clinical Chemistry, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, 10330, Thailand.
  • Julaluk Noiphung
    Department of Medical Technology, Faculty of Science and Technology, Bansomdejchaopraya Rajabhat University, Bangkok, Thailand.
  • Wipada Chanakiat
    Central Chest Institute of Thailand, Nonthaburi, 11000, Thailand.
  • Tasanee Sakuldamrongpanich
    Department of Transfusion Medicine and Clinical Microbiology, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, 10330, Thailand.
  • Veerayuth Kittichai
    Faculty of Medicine, King Mongkut's Institute of Technology Ladkrabang, 1 chalongkrug road, Bangkok, Thailand.
  • Teerawat Tongloy
    College of Advanced Manufacturing Innovation, King Mongkut's Institute of Technology Ladkrabang, 1 chalongkrug road, Bangkok, Thailand.
  • Santhad Chuwongin
    College of Advanced Manufacturing Innovation, King Mongkut's Institute of Technology Ladkrabang, 1 chalongkrug road, Bangkok, Thailand.
  • Siridech Boonsang
    Department of Electrical Engineering, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, 1 chalongkrug road, Bangkok, Thailand. Siridech.bo@kmitl.ac.th.
  • Wanida Laiwattanapaisal
    Biosensors and Bioanalytical Technology for Cells and Innovative Testing Device Research Unit, Department of Clinical Chemistry, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, 10330, Thailand. Electronic address: wanida.l@chula.ac.th.