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Methods Inf Med 2014; 53(04): 238-244
DOI: 10.3414/ME13-12-0142
Original Articles
Schattauer GmbH

Quantitative Conjunctival Provocation Test for Controlled Clinical Trials

I. Sárándi
1   Department of Medical Informatics, Uniklinik RWTH Aachen, Aachen, Germany
,
D. P. Claßen
2   Center of Rhinology and Allergology, Wiesbaden, Germany
,
A. Astvatsatourov
3   Institute of Medical Statistics, Informatics and Epidemiology, Cologne Ophthalmological Reading and Image Analysis Center, Experimental Ophthalmology, University Hospital Cologne, Cologne, Germany
,
O. Pfaar
2   Center of Rhinology and Allergology, Wiesbaden, Germany
,
L. Klimek
2   Center of Rhinology and Allergology, Wiesbaden, Germany
,
R. Mösges
4   Institute of Medical Statistics, Informatics and Epidemiology, University Hospital Cologne, Cologne, Germany
,
T. M. Deserno
1   Department of Medical Informatics, Uniklinik RWTH Aachen, Aachen, Germany
› Author Affiliations
Further Information

Publication History

received:12 December 2013

accepted:25 April 2014

Publication Date:
20 January 2018 (online)

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Summary

Background: The conjunctival provocation test (CPT) is a diagnostic procedure for the assessment of allergic diseases. Photographs are taken before and after provocation increasing the redness of the conjunctiva due to hyperemia.

Objective: We propose and evaluate an automatic image processing pipeline for objective and quantitative CPT.

Method: After scale normalization based on intrinsic image features, the conjunctiva region of interest (ROI) is segmented combining thresholding, edge detection and Hough transform. Redness of the ROI is measured from 0 to 1 by the average pixel redness, which is defined by truncated projection in HSV space. In total, 92 images from an observational diagnostic study are processed for evaluation. The database contains images from two visits for assessment of the test- retest reliability (46 images per visit).

Result: All images were successfully processed by the algorithm. The relative redness increment correlates between the two visits with Pearson’s r = 0.672 (p < .001). Linear correlation of the automatic measure is larger than the manual measure (r = 0.59). This indicates a higher reproducibility and stability of the automatic method.

Conclusion: We presented a robust and effective way to objectify CPT. The algorithm operates on low resolution, is fast and requires no manual input. Quantitative CPT measures can now be established as surrogate endpoint in controlled clinical trials.

Keywords

Conjunctival provocation test - allergy - image processing - Hough transform - segmentation - clinical trials