Submission ID 131923
| Issue/Objective | Tuberculosis (TB) remains a leading cause of morbidity and mortality globally, with the greatest burden borne by low- and middle-income countries. In Nigeria, persistent gaps in early detection are driven by limited access to radiology services, shortages of trained specialists, and fragmented diagnostic systems. These inequities contribute to delayed diagnosis, ongoing transmission, and poor treatment outcomes. In a fragmented and resource-constrained global health landscape, scalable digital innovations are critical to restoring commitment to equitable access to essential health services. The X-ray Medical Analysis Platform (XMAP) was implemented as a teleradiology solution to expand access to chest X-ray (CXR) interpretation and strengthen TB screening pathways. |
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| Methodology/Approach | Between January and December 2025, digital chest X-ray images from TB screening activities across health facilities and mobile diagnostic units in Nigeria were uploaded to the XMAP platform for centralized interpretation. Images were transmitted via secure cloud-based systems and reviewed remotely by trained radiologists using standardized reporting templates. Computer-aided detection (CAD4TB) was integrated to support triage and prioritization of abnormal images. Individuals with CXR findings suggestive of TB were referred for confirmatory bacteriological testing in line with national guidelines. Programmatic data were analyzed to assess screening outcomes and operational performance. |
| Results | A total of 115,176 chest X-rays were interpreted through the platform. Radiologists identified 29,308 (25.4%) images as suggestive of TB requiring further diagnostic evaluation. CAD4TB scores >40 were observed in 94,020 (81.6%) images, while 20,750 (18.0%) had scores ≤40, indicating opportunities for triaged review. The platform enabled rapid, centralized interpretation of radiographs from geographically dispersed sites, reducing delays in diagnosis and facilitating timely referral for confirmatory testing. |
| Discussion/Conclusion | The XMAP teleradiology model demonstrates a scalable approach to addressing inequities in TB screening by expanding access to expert radiological services in underserved settings. By integrating digital imaging, artificial intelligence, and remote specialist networks, this model strengthens diagnostic pathways and supports earlier TB detection. Scaling such innovations can play a critical role in advancing global health equity and restoring coordinated action toward TB control in fragmented health systems |
| Presenters and Affiliations | Kehinde Jimoh Agbaiyero Instant Health Services Clement Adesigbin National TB and Leprosy Control Program Emperor Ubochioma National TB and Leprosy Control Program Kehinde Jimoh Agbaiyero Instant Health Services |
