Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting

PLoS One. 2019 Oct 21;14(10):e0223623. doi: 10.1371/journal.pone.0223623. eCollection 2019.

Abstract

The conventional reading of the skin prick test (SPT) for diagnosing allergies is prone to inter- and intra-observer variations. Drawing the contours of the skin wheals from the SPT and scanning them for computer processing is cumbersome. However, 3D scanning technology promises the best results in terms of accuracy, fast acquisition, and processing. In this work, we present a wide-field 3D imaging system for the 3D reconstruction of the SPT, and we propose an automated method for the measurement of the skin wheals. The automated measurement is based on pyramidal decomposition and parametric 3D surface fitting for estimating the sizes of the wheals directly. We proposed two parametric models for the diameter estimation. Model 1 is based on an inverted Elliptical Paraboloid function, and model 2 on a super-Gaussian function. The accuracy of the 3D imaging system was evaluated with validation objects obtaining transversal and depth accuracies within ± 0.1 mm and ± 0.01 mm, respectively. We tested the method on 80 SPTs conducted in volunteer subjects, which resulted in 61 detected wheals. We analyzed the accuracy of the models against manual reference measurements from a physician and obtained that the parametric model 2 on average yields diameters closer to the reference measurements (model 1: -0.398 mm vs. model 2: -0.339 mm) with narrower 95% limits of agreement (model 1: [-1.58, 0.78] mm vs. model 2: [-1.39, 0.71] mm) in a Bland-Altman analysis. In one subject, we tested the reproducibility of the method by registering the forearm under five different poses obtaining a maximum coefficient of variation of 5.24% in the estimated wheal diameters. The proposed method delivers accurate and reproducible measurements of the SPT.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Algorithms
  • Automation*
  • Female
  • Humans
  • Image Interpretation, Computer-Assisted / methods
  • Image Processing, Computer-Assisted* / methods
  • Imaging, Three-Dimensional* / methods
  • Imaging, Three-Dimensional* / standards
  • Male
  • Middle Aged
  • Models, Theoretical
  • Observer Variation
  • Reproducibility of Results
  • Skin Tests / methods*
  • Young Adult

Grants and funding

This study was supported by Colciencias (www.colciencias.gov.co, Grant 538871552485) and by Universidad Tecnológica de Bolivar (www.utb.edu.co, Grants C2018P005 and C2018P018), Colombia.