Pathological quality control chips for tuberculosis

Abstract Globally, approximately 10 million new tuberculosis (TB) cases are reported annually. Delayed diagnosis due to low detection rates is the primary cause of mortality. Although pathological examination is commonly used for diagnosing TB, 5%–30% of cases remain undiagnosed, emphasizing the urgent need to establish quality control (QC) standards to reduce rates of misdiagnosis and missed diagnoses. To address this, we introduced a novel QC chip for detecting Mycobacterium tuberculosis (MTB). A quantitative pathological QC model was constructed by precisely and uniformly integrating MTB and HeLa cells into a photocurable hydrogel. This model was then sliced into uniform sections to create QC chips. It demonstrated that the QC chips exhibited no significant differences in intra-batch or inter-batch variation (coefficient of variation <5%), and remained stable at −80 °C for one year. Furthermore, these chips were found to be 100% effective when tested with 240 clinical samples (200 with special staining and 40 with polymerase chain reaction). In addition to enhancing TB detection rates, this approach offers visualization, quantification, and sustainable production. Overall, this work provides a novel framework for developing QC chips for pathological testing, offering a reliable solution to enhance clinical diagnostic workflows.