ArticlePLOS digital health2025
Comparison of different Lunit INSIGHT CXR software versions when reading chest radiographs for tuberculosis.
Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
New versions of computer-aided detection (CAD) software for chest X-ray (CXR) interpretation during tuberculosis (TB) screening are regularly released which purport to have incremental performance gains. No studies have independently assessed differences in software performance between the World Health Organization recommended INSIGHT CXR software (Lunit, South Korea). A well-characterized Digital Imaging and Communications in Medicine (DICOM) test library was compiled using data from a community-based TB screening initiative in Ho Chi Minh City, Viet Nam. The performance of Lunit CAD software versions 3.1.0.0 and 3.9.0.1 (newer version) were compared by measuring the area under the receiver operating characteristic curve (AUC), stratified by key clinical and demographic variables and using Xpert MTB/RIF Ultra (Ultra) test results as the reference standard. Median abnormality scores were compared using the Wilcoxon signed-rank test and performance characteristics were compared at clinically-relevant cut-off thresholds (e.g., 90% sensitivity) between the versions. The DICOM test library contained 2,708 participants, of whom 10.3% had a Mycobacterium tuberculosis (MTB) positive Ultra test result. The newer software version had a significantly higher AUC than its predecessor (AUC 0.76 vs 0.78, p = 0.029), and performed significantly better among people with a past history of TB (AUC 0.67 vs 0.73, p = 0.003), older individuals (0.75 vs 0.77, p = 0.040) and males (0.73 vs 0.76, p = 0.008). When using an cut-off threshold optimized for the older software version, the newer software was significantly less accurate than its predecessors. However, when the cut-off threshold was re-calibrated, there were no significant differences in sensitivity and specificity between the software versions. Although INSIGHT CXR v3.9.0.1 has some significantly improved performance characteristics compared to its predecessor, further studies should assess how these performance differences translate into real-world improvements during TB screening. As new CAD software versions are rolled out, cut-off thresholds must be re-calibrated to ensure the continued accuracy of CXR interpretation.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.