The performance of computer-aided detection for chest radiography in tuberculosis screening: a population-based retrospective cohort study.

From 2020 to 2022, a pulmonary tuberculosis (PTB) active case finding project based on chest X-ray (CXR) examination was conducted targeting individuals aged ≥65 years old in Jiangshan County, Quzhou City. The current study used computer-aided detection (CAD) software (JF CXR-1 v2) to retrospectively analyze the CXR images and to estimate its potential capacity for identifying PTB cases. The information of notified microbiologically confirmed PTB among the participants were exported from the Tuberculosis Information Management System. A total of 49,919 subjects participated in the 2020 examinations. Of these, 40,741 and 39,185 completed the follow-up surveys in 2021 and 2022, respectively. The pooled prevalence of suspected PTB reported by radiologists was 1.21% (1579/129,776), compared with 12.43% (16,129/129,776) reported by CAD. Of 101 bacteriologically confirmed PTB cases notified over three years, radiologists and CAD reported 45.54% (46/101) and 83.16% (84/101) as suspected cases, respectively. Among subjects with abnormal CAD (CAD score>0.35), the majority of the notified confirmed PTB patients (63/84) had their CAD scores >75% quantiles (as>0.75). With 3 years' results, their CAD scores exhibited dynamic changes along with disease progression or treatment with median scores peaking in the year of diagnosis. This intriguing finding suggests that CAD for CXR reading assisted radiologists in PTB screening by reducing workload and improving case finding. The CAD primary score may have the potential to identify high-risk individuals and early PTB patients, adding a new dimension to our understanding of disease progression.