AI-assisted screening tool that reduces technologist average read time from 5 minutes to under 30 seconds.
Fecal Ova & Parasite Detection


Overview
CE-IVDD marked in Europe
Our O&P solution will classify and count the following objects (for a full list see below):


Challenges & Solutions
Up to 95% of O&P cases are negative. Reading them requires skilled technologists that can be difficult to find and retain. It’s monotonous, and peering eight hours a day through a microscope can cause repetitive stress injuries.
Our solution helps technologists quickly eliminate negative samples using a computer monitor, allowing them to focus more on the positive cases.
How it works
4-step process:
Prepare slides
Scan slides
Technicians load slides into the chosen scanner. Slides are then scanned and the resulting images are automatically uploaded to the Techcyte platform for AI analysis. Our Trichrome and modified acid fast (MAF) O&P fecal tests accept any good-quality 80x image from a compatible scanner (for a list of compatible scanners, see below). Our wet mount iodine solution is under development and will accept 40x images.
Process images
Our AI algorithm uses a convolutional neural network to identify differentiating features and determine which combinations indicate a certain ova, parasites, or other diagnostically significant objects. It then places them into the most likely classification for technologist review. This algorithm is deterministic, making the same classification every time it is shown the same image. The whole process takes just minutes.
Review results
A technologist logs into Techcyte on any web-enabled device and reviews available samples, confirming presence of objects of interest and, if required, their prevalence. They can also add notes or request an additional consult.
Positive samples are manually reviewed by a technologist who confirms the assessment on the microscope and confirms results in their LIS.
Cells & Organisms Identified
- Blastocystis sp.
- Giardia duodenalis
- Combined D.frag, Ib, E.nana troph
- Dientamoeba fragilis
- Endolimax nana
- Iodamoeba buetschlii
- Entamoeba hartmanni
- Entamoeba coli
- Entamoeba polecki
- Entamoeba histolytica-complex (4 other morphologically similar species)
- Chilomastix mesnili
- Cyclospora cayetanensis (advisory)
- White Blood Cells
- Red Blood Cells
- Cryptosporidium sp. oocysts
- Cyclospora cayetanensis oocysts
- Ascaris lumbricoides, fertile egg mammillated
- Ascaris lumbricoides, infertile egg mammillated
- Balantioides coli cyst
- Balantioides coli troph
- Blastocystis
- Capillaria phillippinensis egg
- Chilomastix mesnili cyst
- Chilomastix mesnili troph
- Clonorchis / Opisthorchis spp. egg
- Cyclospora Cayetanensis oocysts
- Cystoisospora belli oocysts
- Combined D.frag, I.buetschlii, E.nana troph
- Dientamoeba fragilis
- Endolimax nana troph
- Iodamoeba buetschlii
- Entamoeba cysts
- Entamoeba nana cysts
- Entamoeba trophs
- Enterobius vermicularis egg (Pinworm)
- Fish tapeworm egg
- Giardia Cysts
- Giardia Trophs
- Hookworm egg
- Hymenolepis diminuta
- Hymenolepis nana egg
- Paragonimus spp. egg
- Schistosoma mansoni egg
- Schistosoma japonicum/mekongi egg
- Strongyloides stercoralis larvae
- Taenia spp. egg
- Trichostrongylus sp
Supported scanners
Trichrome



Hamamatsu S360



3DHistech P250, P1000
Modified Acid Fast (MAF)



3DHistech P250, P1000
Wet Mount Iodine (under development)



Hamamatsu S360, S20


Grundium Ocus 40


Features
- State-of-the-art platform
- AI-proposed images of parasites and objects of interest, grouped by class and sorted by confidence
- 30-second average read times
- Sensitivity 98.9%, slide-level specificity 98.1%*
- 5x more sensitive than manual examination*
- No daily cycle of fatigue, distraction, or confirmation bias
- Levels out sample and stain variations
- Excels at low-prevalence samples
- High volume, high reliability scanners produce 80x equivalent digital images
*These claims have not been examined by the FDA. These results are from a single study in a US based reference lab.
Benefits
Partners






Related Resources
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Video
Mayo Clinic ‘Hot Topic’ – AI and Digital Slide Scanning: Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens
Sep 2023 -
Publications
JCM Article: Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens by Use of a Deep Convolutional Neural Network
May 2020 -
Publications
JCM Commentary: Computer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist
May 2020 -
Press Release
Techcyte announces the release of their second generation AI for Human Parasites
Jul 2022 -
Press Release
A Whole New Microscopic World: ARUP/Techcyte Publish First Peer-Reviewed Study on AI-based Protozoa Detection
Jun 2020 -
Press Release
ARUP Laboratories Deploys World’s First AI-Augmented Ova and Parasite Assay
Aug 2019 -
Press Release
Techcyte and ARUP Laboratories partner to deliver AI-based Digital Diagnostics
Jan 2019