OvaSpec – A vision-based instrument for assessing concentration and developmental stage of Trichuris suis parasite egg suspensions

• A scalable, objective method for in-process drug testing was developed.
• OvaSpec automatically assess concentration and embryonation percentage of TSO.
• Algorithms were tested on a large, annotated dataset of 42,894 eggs in 2970 images.
• Darkfield scattering and larval morphology enables classification accuracies of 99%.
• Computer vision agrees with manual microscopy but has superior precision.

BackgroundOvaSpec is a new, fully automated, vision-based instrument for assessing the quantity (concentration) and quality (embryonation percentage) of Trichuris suis parasite eggs in liquid suspension. The eggs constitute the active pharmaceutical ingredient in a medicinal drug for the treatment of immune-mediated diseases such as Crohn׳s disease, ulcerative colitis, and multiple sclerosis.MethodsThis paper describes the development of an automated microscopy technology, including methodological challenges and design decisions of relevance for the future development of comparable vision-based instruments. Morphological properties are used to distinguish eggs from impurities and two features of the egg contents under brightfield and darkfield illumination are used in a statistical classification to distinguish eggs with undifferentiated contents (non-embryonated eggs) from eggs with fully developed larvae inside (embryonated eggs).ResultsFor assessment of the instrument׳s performance, six egg suspensions of varying quality were used to generate a dataset of unseen images. Subsequently, annotation of the detected eggs and impurities revealed a high agreement with the manual, image-based assessments for both concentration and embryonation percentage (both error rates <1.0%). Similarly, a strong correlation was demonstrated in a final, blinded comparison with traditional microscopic assessments performed by an experienced laboratory technician.ConclusionsThe present study demonstrates the applicability of computer vision in the production, analysis, and quality control of T. suis eggs used as an active pharmaceutical ingredient for the treatment of autoimmune diseases.