Sitang Nirattisaikul

Objectives: To assess inter-rater agreement and diagnostic performance of six United States National Institute for Occupational Safety and Health-certified B readers (physicians certified in standardized chest X-ray (CXR) classification for pneumoconiosis) in diagnosing tuberculosis (TB) on CXR, with the goal of developing a reliable dataset to support external validation of artificial intelligence (AI) models for TB detection. Materials and methods: 1097 CXRs from five institutions were analyzed by six B readers. Patients aged ≥ 15 years were included, excluding those with HIV or opportunistic infections. CXRs were classified as unremarkable or abnormal. Abnormalities were categorized using a modified International Labor Organization classification and classified as consistent or inconsistent with TB. Microbiological references included sputum smears, cultures, or molecular tests. Descriptive statistics summarized the CXR and microbiological findings. Inter-rater agreement was assessed with Fleiss’ kappa. Diagnostic performance was evaluated by comparing CXR findings to microbiological references. Results: Of the 3117 readings, 69% of CXRs were abnormal, and 31% were unremarkable. Microbiological results confirmed that 87% of abnormal CXRs were TB cases, while 83% of unremarkable CXRs were non-TB. Inter-rater agreements were κ = 0.83 for all findings, κ = 0.67 for findings consistent with TB, and κ = 0.76 for active TB findings. For findings consistent with TB, the sensitivity, specificity, and accuracy ranged from 77.2% to 91.1%, 87.4% to 98.6%, and 84.1% to 90.1%, respectively. Conclusion: B readers exhibited strong agreement and high accuracy in diagnosing TB on CXR, providing a robust dataset that could be used for external validation of AI models in TB diagnosis. Critical relevance statement: With substantial inter-rater agreement and strong diagnostic performance, B readers’ interpretations of CXRs provide a reliable dataset to support external validation of AI models for TB diagnosis. Key Points: B readers can provide a reliable reference for validating AI models in TB diagnosis. Less variability and high accuracy were observed among B readers in CXR-based TB diagnosis.

Background: Identification of normal variations to the thoracic central venous system anatomy is essential in radiological intervention and cardiothoracic surgery to prevent complications. Purpose: To estimate the prevalence and pattern of normal variations of superior vena cava (SVC) and azygos venous system as well as factors associated with normal variations of SVC. Material and Methods: Venous-phase chest CT of 1336 patients were retrospectively reviewed. Age, sex, and underlying disease were recorded. SVC diameter and cross-sectional area were measured to evaluate for associations with normal variations. Results: The prevalence of normal anatomical variations of SVC and azygos venous system were 0.3% and 1.5%, respectively. Duplicated SVC was the most common variations. The most common variation for the azygos venous system was the connection between the hemiazygos and accessory hemiazygos veins draining into the left brachiocephalic vein (12/1336 cases, 0.9%). The median (interquartile range [IQR]) cross-sectional area compared between normal SVC (297.2 mm²) and duplicated SVC (223.5 mm²) showed a statistically significant difference ( P = 0.033). Conclusion: This study determined the prevalence of rare normal variations of the azygos venous system, a connection between the hemiazygos and accessory hemiazygos veins draining into the left brachiocephalic vein. The prevalence of normal variations of the SVC and azygos venous system in the adult Thai population was similar with that of previous publications. Cross-sectional area was the only factor with a significant association with SVC variations.

Primary pulmonary angiosarcomas (PPAs) are rare, and often, their diagnosis is delayed because of insidious clinical symptoms and imaging findings mimicking pulmonary thromboembolism (PE). A 33-year-old female patient presented with chest pain and progressive dyspnoea. Her initial diagnosis, based on clinical symptoms and CT pulmonary angiography (PA) findings, was PE. However, after treatment with anticoagulants, the patient failed to improve. A follow-up CTPA and further CT-guided biopsy results were compatible with angiosarcoma.