Schistosomiasis Mansoni, Soil Transmitted Helminths
Conditions
Keywords
Artificial Intelligence Digital Pathology, Diagnostic Performance, Usability, Repeatability, Cost Efficiency
Brief summary
The goal of this observational study is to test a new AI diagnostic tool for detection, specification and quantification of parasitic infections (Ascaris, Trichuris, hookworm and S. Mansoni) in School aged children in Ethiopia and Uganda. The main questions it aims to answer are: * Diagnostic Performance of the AI tool and compare to traditional manual microscopy * Repeatability and reproducibility of the AI tool and compare to traditional manual microscopy * Time-to-result for the AI tool * Cost efficiency for the AI tool and traditional manual microscopy to inform programmatic decisions. * Usability of the AI tool Participants will be asked to provide a stool sample for examination by the AI tool and traditional manual microscopy. Participants with a positive test result will receive the proper treatment (Deworming drug).
Detailed description
Manual screening of a Kato-Katz (KK) thick stool smear remains the current standard to monitor the impact of large-scale deworming programs against soil-transmitted helminths (STHs). To improve this diagnostic standard, the investigators recently designed an artificial intelligence based digital pathology system (AI-DP) for digital image capture and analysis of KK thick smears. Preliminary results of its diagnostic performance are encouraging, and a comprehensive evaluation of the AI-DP as a cost-efficient end-to-end diagnostic to inform STHs control programs against the target product profiles (TPP) of the World Health Organisation (WHO) is the next step for validation. The study protocol describes a comprehensive evaluation of the AI-DP based on its (i) diagnostic performance, (ii) repeatability/reproducibility, (iii) time-to-result, (iv) cost-efficiency to inform large-scale deworming programs and (v) usability in both laboratory and field settings. For each of these five attributes, the investigators designed separate experiments with sufficient power to verify the non-inferiority of the AI-DP (KK2.0) over the manual screening of the KK smears (KK1.0). These experiments will be conducted in two STH endemic countries with national deworming programs (Ethiopia and Uganda), focusing on school-age children (SAC) only. Participants will be asked to provide a stool sample for examination by the AI tool and traditional manual microscopy. Participants with a positive test result will receive the proper treatment (Deworming drug). This comprehensive and well-designed study and accompanying protocols will provide the necessary data to make an evidence-based decision on whether the AI-DP is indeed performant and a cost-efficient end-to-end diagnostic to inform large-scale deworming programs against STHs. Following the protocolized collection of high-quality data the investigators will seek approval by WHO. Through the dissemination of the methodology and statistics, the investigators hope to support additional developments in AI-DP technologies for other neglected tropical diseases in resource-limited settings.
Interventions
DIAGNOSTIC_TESTArtificial Intelligence Digital Pathology
School aged children will be asked to leave a stool sample. The samples will be prepared with the Kato-Katz method and scanned and processed by an artificial intelligence digital pathology system to determine the infection level of soil transmitted helminths and schistosomiasis. The samples will also be analyzed by a human microscopist for comparison.
Sponsors
Jimma University
Ministry of Health, Uganda
University Ghent
Enaiblers AB
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
5 Years to 14 Years
Healthy volunteers
Yes
Inclusion criteria
* Subject, male or female, is 5-14 years of age * Parent(s)/guardian(s) of subject signed an informed consent document indicating that they understand the purpose and procedures required for the study and that they are willing to have their child participate in the study * Subject of ≥6 (Ethiopia) /8 (Uganda) years old has assented to participate in the study\* * Subject of ≥12 years old has signed an informed consent document indicating that they understand the purpose of the study and procedures required for the study, and are willing to participate in the study (Ethiopia only)\* * Subject has provided a stool sample of minimum 5 grams
Exclusion criteria
* Subject has active diarrhoea (defined as the passage of 3 or more loose or liquid stools per day) at baseline or follow-up. * Subject is experiencing a severe concurrent medical condition or has an acute medical condition * Subject has received anthelmintic treatment within 90 days prior to the start of the study
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic performance, P1.1-2 | up to 10 months | the clinical sensitivity of Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0) to detect low, moderate and heavy intensity infections of Ascaris, Trichuris and hookworms |
| Diagnostic Performance P1.3-4 | up to 10 months | The clinical specificity of Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0) to detect low, moderate and heavy intensity infections of Ascaris, Trichuris and hookworms |
| Repeatability and Reproducibility Performance P2 | up to 10 months | The repeatability and the reproducibility of the scanning process, the AI verification process, the Kato-Katz 2.0 (KK2.0) system as a whole and the manual counting by a microscopist (Kato-Katz 1.0 (KK1.0)). |
| Time to Result P3 | up to 10 months | Time to result for the artificial intelligence digital pathology diagnostic (Kato-Katz 2.0 (KK2.0)) result. |
| Cost Efficiency P4.1 | up to 10 months | The total survey cost to reliably inform a stop decision to the program for Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0). |
| Cost Efficiency P4.2 | up to 10 months | The total survey cost to reliably inform a declaration that STH are eliminated as a public health problem for Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0). |
| Usability observation P5 | up to 10 months | The ease-of-use of the complete AI-DP work process for the identified end-users assessed by observations of user groups and user interviews. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Time to Result S3.2 | up to 10 months | the correlation between time-to-result and Ascaris, Trichuris and S. mansoni egg counts recorded by Kato-Katz 2.0 (KK2.0) |
| Time to Result S3.3 | up to 10 months | time-to-result of the AI-DP when the AI verification process is simplified (only objects for which the AI is uncertain) or even omitted |
| Cost Efficiency S4.1 | up to 10 months | the total survey cost to make reliable program decisions on the frequency of large-scale deworming programs for Kato-Katz 2.0 (KK2.0) and KK1.0 |
| Cost Efficiency S4.2 | up to 10 months | the total survey cost to reliably monitor the therapeutic drug efficacy of anthelmintic against STHs for Kato-Katz 2.0 (KK2.0) |
| Cost Efficiency S4.3 | up to 10 months | the total survey cost to make reliable program decisions on the frequency of large-scale deworming programs for Kato-Katz 2.0 (KK2.0) when the AI verification process is simplified (only objects for which the AI is uncertain) or even omitted |
| Diagnostic performance S1.1 | up to 10 months | the clinical sensitivity and specificity of Kato-Katz 2.0 (KK2.0)KK2.0 and Kato-Katz 1.0 (KK1.0) to detect infections of S. Mansoni |
| Cost Efficiency S4.5 | up to 10 months | the optimal set-up for Kato-Katz 2.0 (KK2.0) (sample throughput; number of AI-DP devices; number of operators) to inform large-scale deworming programs when deployed in a fully equipped laboratory and M&E setting |
| Usability observation S5.1 | up to 10 months | identification of barriers for a successful outcome of the complete work process with the AI-DP device by the identified end-users |
| Usability observation S5.2 | up to 10 months | The task completion time for novel users of the AI-DP device |
| Usability observation S5.3 | up to 10 months | Outcome rates (Success/failure) for novel users of the AI-DP device. |
| Cost Efficiency S4.4 | up to 10 months | the required performance of AI to make reliable program decisions on the frequency of large-scale deworming programs for Kato-Katz 2.0 (KK2.0) |
| Diagnostic performance S1.2 | up to 10 months | The detection limit that yields a positive test result for both Kato-Katz 2.0 (KK2.0) and Kato-Katz 1.0 (KK1.0) and Ascaris, Trichuris, hookworm and S. Mansoni separately |
| Diagnostic performance S1.3 | up to 10 months | The egg recovery rate of KK1.0 and Kato-Katz 2.0 (KK2.0) when compared to the ground truth for Ascaris, Trichuris, hookworms and S. mansoni |
| Diagnostic performance S1.4 | up to 10 months | the clinical sensitivity and clinical specificity of the AI-DP when the AI verification process is simplified (only objects for which the AI is uncertain) or even omitted |
| Repeatability and Reproducibility Performance S2.1 | up to 10 months | the agreement between repeated egg counts for Ascaris, Trichuris and S. mansoni |
| Repeatability and Reproducibility Performance S2.2 | up to 10 months | the repeatability and reproducibility in test results when the AI verification process is simplified (only objects for which the AI is uncertain) |
| Time to Result S3.1 | up to 10 months | time for participant registration using Electronic Data Capture (EDC) tools and quick response (QR) code printing |
Contacts
Primary ContactPeter Dahlberg, MSc
Backup ContactPeter Ward, PhD Student
Outcome results
None listed