Ministries of Health and funders increasingly focus on systematic screening for TB in high risk groups. Where operationally feasible multi-disease screening can be included in programs for cross-disease impact. Digital X-ray and Artificial Intelligence support these screening demands in resource-constrained settings with innovative and proven CAD systems to simultaneously detect and quantify abnormalities suggestive of TB, other lung diseases and cardiomegaly within less than 20 seconds.

Stop TB Partnership – on use of CAD

Artificial intelligence (AI) technologies offer unprecedented opportunities within a healthcare context. AI is increasingly being applied in the field of medical imaging for the computer-aided detection (CAD) of diseases, including cancer, COVID-19, and TB.

A diverse range of AI products for the recognition of TB-related abnormalities from chest X-rays are now commercially available. Evidence produced by the Stop TB Partnership informed the World Health Organization’s TB screening guideline update in April 2021, when, for the first time, AI was recommended as a triage tool for TB in adults. The potential of AI to accelerate TB detection, particularly in rural and low-resource contexts, is tremendous.

CAD presents an opportunity to improve the detection of TB by circumventing inefficiencies in the interpretation of CXR images, automating and standardizing X-ray interpretation, and supplementing existing human health workers. When used in combination with ultra-portable X-ray systems, the promise of CAD technology can be extended to hard-to-reach key populations.

The Global Fund – on procurement of CXR

“Consider the use of CAD where human readers may not be available to read Chest X-rays & to decrease the workload of radiographers. Consider CAD technologies that offer multi-disease potential given the system strengthening potential of CXR and CAD. Consider the associated cost for the entire ecosystem like installation cost, PACS, site preparations, recurrent cost, service and maintenance, local calibration of CAD thresholds”

IOM – CAD4Silicosis

Centro de Saúde Ocupacional de Ressano Garcia, Moçambique at the border with South Africa provides essential screening services for Mozambican migrant mine workers. Occupational Health Consultation Rooms include screening on symptoms and Chest X-ray abnormalities suggestive of silicosis and/or TB using CAD for presumptive silicosis and TB detection.

Silicosis is an occupational lung disease caused by chronic exposure to silica dust, primarily affecting current and former miners. As silicosis is irreversible and can be fatal, early and timely diagnosis is crucial. While there is no specific diagnostic test for silicosis, radiological abnormalities on chest X-rays, occupational history, and physical examinations can help confirm the diagnosis.

Individuals with silica dust exposure are at an increased risk for Tuberculosis (TB): the TB incidence among silicosis patients can be significantly higher than in the general population. Moreover, some develop Silicotuberculosis, being affected by both silicosis and TB at the same time.

Routine screening for silicosis and TB is essential for those exposed to silica dust. However, challenges persist due to a shortage of medical experts to assess chest X-rays accurately.

Artificial Intelligence for COVID control

The fight against COVID-19 inspired specialists in various countries to unite and collaborate to develop Artificial Intelligence software to more effectively detect COVID-19. The Dutch AI innovator Delft Imaging initiated the development of CAD4COVID at the wake of the pandemic in cooperation with Radboud University, Thirona and COVID hot spot hospitals in Europe and Mexico. Support was also provided through the Dutch Government RVO Agency and Dutch FMO Development Bank. As a social enterprise, Delft Imaging decided to make CAD4COVID available free-of-charge for both CT and X-ray COVID-19 screening. This CE Certified Artificial Intelligence software provides hospitals in over 25 countries with pro bono access to an e-Radiologist at Dutch Senior Radiologist accuracy level for rapid detection and quantification of COVID-19 signs in lungs. CAD4COVID comprises two different algorithms: CAD4COVID-XRay and CAD4COVID-CT.

As a next step in response to the public health demands in Ghana the enhanced performance of the latest released CAD4TB version is now seamlessly integrated in the CAD4TB/COVID box for bi-directional rapid screening nationwide at more than 50 sites. The user can select CAD4TB only and opt for bi-directional screening for COVID and TB as long as required during the pandemic. The use of CAD4TB is payable per use and its cost depends on the image bundle size.