A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing.

Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein-based subtypes. However, if and how these findings extend to UTUC remains unclear. Artificial intelligence-based approaches could help elucidate UTUC's biology and extend access to targeted treatments to a wider patient audience. Here, UTUC protein-based subtypes were identified, and a deep-learning (DL) workflow was developed to predict them directly from routine histopathological H&E slides. Protein-based subtypes in a retrospective cohort of 163 invasive tumors were assigned by hierarchical clustering of the immunohistochemical expression of three luminal (FOXA1, GATA3, and CK20) and three basal (CD44, CK5, and CK14) markers. Cluster analysis identified distinctive luminal (N = 80) and basal (N = 42) subtypes. The luminal subtype mostly included pushing, papillary tumors, whereas the basal subtype diffusely infiltrating, non-papillary tumors. DL model building relied on a transfer-learning approach by fine-tuning a pre-trained ResNet50. Classification performance was measured via three-fold repeated cross-validation. A mean area under the receiver operating characteristic curve of 0.83 (95% CI: 0.67-0.99), 0.8 (95% CI: 0.62-0.99), and 0.81 (95% CI: 0.65-0.96) was reached in the three repetitions. High-confidence DL-based predicted subtypes showed significant associations (p < 0.001) with morphological features, i.e. tumor type, histological subtypes, and infiltration type. Furthermore, a significant association was found with programmed cell death ligand 1 (PD-L1) combined positive score (p < 0.001) and FGFR3 mutational status (p = 0.002), with high-confidence basal predictions containing a higher proportion of PD-L1 positive samples and high-confidence luminal predictions a higher proportion of FGFR3-mutated samples. Testing of the DL model on an independent cohort highlighted the importance to accommodate histological subtypes. Taken together, our DL workflow can predict protein-based UTUC subtypes, associated with the presence of targetable alterations, directly from H&E slides.

[Chest Tube in Thoracic Trauma - Recommendations of the Interdisciplinary Thoracic Trauma Task Group of the German Society for Thoracic Surgery (DGT) and the German Trauma Society (DGU)]. / Thoraxdrainage beim Thoraxtrauma ­ Empfehlungen der interdisziplinären Arbeitsgemeinschaft Thoraxtrauma der Deutschen Gesellschaft für Thoraxchirurgie (DGT) und der Deutschen Gesellschaft für Unfallchirurgie (DGU).

For unstable patients with chest trauma, the chest tube is the method of choice for the treatment of a relevant pneumothorax or haemothorax. In the case of a tension pneumothorax, needle decompression with a cannula of at least 5 cm length should be performed, directly followed by the insertion of a chest tube. The evaluation of the patient should be performed primarily with a clinical examination, a chest X-ray and sonography, but the gold standard of diagnostic testing is computed tomography (CT).A small-bore chest tube (e.g. 14 French) should be used in stable patients, while unstable patients should receive a large-bore drain (24 French or larger). Insertion of chest drains has a high complication rate of between 5% and 25%, and incorrect positioning of the tube is the most common complication. However, incorrect positioning can usually only be reliably detected or ruled out with a CT scan, and chest X-rays proofed to be insufficient to answer this question. Therapy should be carried out with mild suction of approximately 20 cmH2O, and clamping the chest tube before removal showed no beneficial effect. The removal of drains can be safely performed, either at the end of inspiration or at the end of expiration. In order to reduce the high complication rate, in the future the focus should be more on the education and training of medical staff members.

[Occult and Retained Haemothorax - Recommendations of the Interdisciplinary Thoracic Trauma Task Group of the German Trauma Society (DGU - Section NIS) and the German Society for Thoracic Surgery (DGT)]. / Okkulter und residueller Hämatothorax nach Thoraxtrauma ­ Empfehlungen der interdisziplinären Arbeitsgruppe Thoraxtrauma der Sektion NIS der Deutschen Gesellschaft für Unfallchirurgie (DGU) und der Deutschen Gesellschaft für Thoraxchirurgie (DGT).

The management of occult and retained haemothorax is challenging for all involved in the care of polytrauma patients in terms of diagnosis and treatment. The focus of decision making is preventing sequelae such as pleural empyema and avoiding a trapped lung. An interdisciplinary task force of the German Society for Thoracic Surgery (DGT) and the German Trauma Society (DGU) on thoracic trauma offers recommendations for post-trauma care of patients with occult and/or retained haemothorax, as based on a comprehensive literature review.