Tuberculosis screening of chest radiographs

Tuberculosis (TB) is one of the most common causes of death by an infectious agent,1 with an estimated nine million new cases appearing every year. About one-third of the world’s population is infected with Mycobacterium tuberculosis, the bacterial strain that causes the majority of cases. TB is most prevalent in sub-Saharan Africa and Southeast Asia, where widespread poverty and malnutrition reduce resistance to the disease. Despite progress made in prevention, diagnosis, and treatment, the emergence of multi-drug-resistant bacterial strains and opportunistic infections in immunocompromised patients, for example, those with HIV (human immunodeficiency virus), has exacerbated the problem. However, the likelihood of curing TB is improved when it is diagnosed at an early stage. Computer-aided screening and diagnosis have received increasing attention with the advent of digital chest x-rays (CXRs), which allow image processing that traditional film x-rays do not. Here, we describe our progress—in collaboration with the Academic Model Providing Access to Healthcare (AMPATH)—toward improving TB diagnosis with intelligent software designed for portable scanners that can easily be used in remote locations. Several skin tests are available—based on immune response— for determining whether an individual has been exposed to TB. However, it is often not possible to make a final diagnosis based on these tests alone. Thus, physicians typically use additional tests—including posteroanterior x-rays of the patient’s chest—to confirm or rule out infection. The abnormalities displayed in radiographs in TB are generally diffuse, and the distinction between normal anatomical structures and abnormal patterns is difficult to determine. Furthermore, low-contrast images complicate identification of the subtle radiographic manifestations of TB. The lack of adequate radiological services in the worst-affected areas necessitates an automated, Figure 1. Contrast-enhanced chest x-ray, normalized with a histogramequalization technique, showing a nodule in the right lower lobe.2