A Study to Validate and Improve an Automated Image Analysis Algorithm to Detect Tuberculosis in Sputum Smear Slides

June 8, 2023 updated by: Diascopic, LLC
A Study to Validate and Improve an Automated Image Analysis Algorithm to Detect Tuberculosis in Sputum Smear Slides

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Actual)

400

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Uganda
      • Kampala, Uganda
        • Makerere University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

400 Male and Female Ugandan Africans

Description

Inclusion Criteria:

  • Samples sourced from Makerere University's Joint Clinical Research Clinic (JCRC) and Laboratory

Exclusion Criteria:

  • No samples from outside Makerere's Domain

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Study Group
400 Male and Female Ugandan Africans
Diagnostic test: Diascopic iON Image Analysis System
A scanning digital optical train that images sputum slides for automated analysis by a tuberculosis detecting algorithm

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Determined sensitivity and specificity of the iON device by comparing MTB slide results to their associated bacterial culture results from the same specimen(s).
Time Frame: Study completed over the grant period 2019 - 2022
Sensitivity, specificity, and average analysis time were determined. An image database of >40,000 images was also created for internal use.
Study completed over the grant period 2019 - 2022

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Diascopic, LLC

Collaborators

National Institutes of Health (NIH)
National Institute for Biomedical Imaging and Bioengineering (NIBIB)

Investigators

  • Study Director: Moses Joloba, MD, PhD, Makerere University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 15, 2019

Primary Completion (Actual)

October 31, 2022

Study Completion (Actual)

December 31, 2022

Study Registration Dates

First Submitted

May 31, 2023

First Submitted That Met QC Criteria

June 8, 2023

First Posted (Actual)

June 12, 2023

Study Record Updates

Last Update Posted (Actual)

June 12, 2023

Last Update Submitted That Met QC Criteria

June 8, 2023

Last Verified

June 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • Diascopic
  • 1R43EB028736-01 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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