Rad-Aid International investigators have described a successful strategy for deploying chest x-ray AI to help diagnose tuberculosis in low- and middle-income countries, according to a recent study in the Journal of the American College of Radiology.
Ultimately, the approach can help avoid unintended consequences to patients and healthcare systems, noted first author Samantha Singh, MD, of Georgetown Public Hospital Corporation in Georgetown, Guyana, and colleagues at the University of Pennsylvania.
"It is critical for radiologists to remain as gatekeepers for effective and ethical use of AI in medical imaging worldwide by providing guidance on its implementation," the group wrote.
Rad-Aid is a not-for-profit global health radiology organization established in 2008 with a mission to improve and optimize access to medical imaging and radiology in low-resource regions of the world. In this study, the group used a three-pronged approach that focused on education, infrastructure implementation, and phased introduction, and used it successfully in hospitals in Guyana and Nigeria.
During a similar period, the group first installed a picture archiving and communication system (PACS) with a cloud component at both institutions. Radiology residents and attendings at the hospitals then completed an introduction to AI course to prime them to use the AI software, an algorithm developed by Qure.ai. Finally, they compared AI outputs to standardized prospectively generated reports by local radiologists and study team members.
Thirty participants completed the introduction to AI course, with an average preknowledge test score of 75% and post-test score of 95%, according to the findings. The focus of the validation process in various sites was reflective of the intended use of the AI software, the group wrote.
Specifically, in Guyana, it revealed an 87% concordance rate between radiologists and the AI model for triaging normal versus abnormal chest x-rays. In Nigeria, the researchers noted an 85% concordance rate between radiologists and the AI model for reporting tuberculosis on chest x-rays.
"The AI software was successfully deployed and is being used as intended in both institutions," the team wrote.
The group noted an important takeaway -- that having a specific task for an AI model to perform in these settings was crucial because this likely improved its use, they wrote. Conversely, AI algorithms that perform multiple tasks typically don't have the same accuracy across all tasks, and so it is prudent to limit its output to high-accuracy tasks, especially in low resource settings where supervision might be limited, they suggested.
Moving forward, the authors said they intend to conduct periodic quality assurance reviews of the AI outputs.
"Implementation of other AI solutions at these sites and expansions to other sites are in the pipeline for further work," the group concluded.
The full article can be found here.
![Examples of ultrasound findings and techniques. (A) Images in a 39-year-old male patient with a mass in the left thigh. The mass is heterogeneous on the B-mode US image (compared with the patient in D) and showed increased microvascularity (superb microvascular imaging [SMI]) and shear-wave elastography (SWE) values. Undifferentiated pleomorphic sarcoma was diagnosed at biopsy (with pleomorphic rhabdomyosarcoma in surgical specimen). (B) Images in an 18-year-old male patient with a mass in the left leg. The mass is hypoechoic on the B-mode image, with no other findings suggestive of malignancy. The lesion is in contact with the cortex of the tibia, which is slightly irregular. CT revealed a doubtful anteromedial tibial erosion. The microvascular study demonstrated high vascularization, suggestive of malignancy. Periosteal Ewing sarcoma was diagnosed with both histologic and immunohistochemical confirmation. (C) Images in a 69-year-old female patient with a lump growing on the outside of the left leg. Multiple SWE examinations were performed (please note the high values obtained in the measurements, whereas the color map highlights the stiffness relative to adjacent tissues). SMI showed areas of increased vascularization to target for sampling. Undifferentiated spindle cell sarcoma was diagnosed at biopsy, with residual leiomyosarcoma in the surgical specimen after neoadjuvant therapy. (D) Images in a 56-year-old female patient with a mass in the right thigh. The mass is heterogeneous at both B-mode ultrasound (similar to patient A) and MRI (coronal T2-weighted spectral attenuated inversion recovery [SPAIR]; T1-weighted pre-contrast and postcontrast imaging), which even shows uptake after the administration of paramagnetic contrast material, which is traditionally suggestive of malignancy. Low values at SMI and elastography are suggestive of benignity. Spindle cell lipoma was diagnosed at biopsy, with atypical spindle cell lipomatous tumor in the surgical specimen.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/08/images-radiol250278fig2.APCFLSvX6p.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
