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Pulmonary sarcoidosis is a multisystem granulomatous interstitial lung disease (ILD) with a variable presentation and prognosis. The early accurate detection of pulmonary sarcoidosis may prevent progression to pulmonary fibrosis, a serious and potentially life-threatening form of the disease. However, the lack of a gold-standard diagnostic test and specific radiographic findings poses challenges in diagnosing pulmonary sarcoidosis. Chest computed tomography (CT) imaging is commonly used but requires expert, chest-trained radiologists to differentiate pulmonary sarcoidosis from lung malignancies, infections, and other ILDs. In this work, we develop a multichannel, CT and radiomics-guided ensemble network (RadCT-CNNViT) with visual explainability for pulmonary sarcoidosis vs. lung cancer (LCa) classification using chest CT images. We leverage CT and hand-crafted radiomics features as input channels, and a 3D convolutional neural network (CNN) and vision transformer (ViT) ensemble network for feature extraction and fusion before a classification head. The 3D CNN sub-network captures the localized spatial information of lesions, while the ViT sub-network captures long-range, global dependencies between features. Through multichannel input and feature fusion, our model achieves the highest performance with accuracy, sensitivity, specificity, precision, F1-score, and combined AUC of 0.93 ± 0.04, 0.94 ± 0.04, 0.93 ± 0.08, 0.95 ± 0.05, 0.94 ± 0.04, and 0.97, respectively, in a five-fold cross-validation study with pulmonary sarcoidosis (n = 126) and LCa (n = 93) cases. A detailed ablation study showing the impact of CNN + ViT compared to CNN or ViT alone, and CT + radiomics input, compared to CT or radiomics alone, is also presented in this work. Overall, the AI model developed in this work offers promising potential for triaging the pulmonary sarcoidosis patients for timely diagnosis and treatment from chest CT. [ABSTRACT FROM AUTHOR]

Skeletal muscles of the head and trunk originate in distinct lineages with divergent regulatory programmes converging on activation of myogenic determination factors. Branchiomeric head and neck muscles share a common origin with cardiac progenitor cells in cardiopharyngeal mesoderm (CPM). The retinoic acid (RA) signalling pathway is required during a defined early time window for normal deployment of cells from posterior CPM to the heart. Here, we show that blocking RA signalling in the early mouse embryo also results in selective loss of the trapezius neck muscle, without affecting other skeletal muscles. RA signalling is required for robust expression of myogenic determination factors in posterior CPM and subsequent expansion of the trapezius primordium. Lineage-specific activation of a dominant-negative RA receptor reveals that trapezius development is not regulated by direct RA signalling to myogenic progenitor cells in CPM, or through neural crest cells, but indirectly through the somitic lineage, closely apposed with posterior CPM in the early embryo. These findings suggest that trapezius development is dependent on precise spatiotemporal interactions between cranial and somitic mesoderm at the head/trunk interface., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)