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European Respiratory Review : An... Dec 2020Tracheo-oesophageal fistula (TOF) is a pathological connection between the trachea and the oesophagus that is associated with various underlying conditions including... (Review)
Review
Tracheo-oesophageal fistula (TOF) is a pathological connection between the trachea and the oesophagus that is associated with various underlying conditions including malignancies, infections, inhalation injuries and traumatic damage. As the condition spans multiple organ systems with varying aetiologies and acuities, TOF poses unique diagnostic and management challenges to pulmonologists, gastroenterologists and thoracic surgeons alike. Although stents have been a cornerstone in the management of TOF, there exists a large gap in our understanding of their efficacy and precise methodology, making stenting procedure both art and science. TOFs relating to underlying oesophageal or tracheal malignancies require advanced understanding of the airway and digestive tract anatomy, dimensions of the fistula, stent characteristics and types, and the interplay between the oesophageal stent and the airway stent if dual stenting procedure is elected. In this review article, we review the most up-to-date data on risk factors, clinical manifestations, diagnostic approaches, management methods and prognosis. Consequently, this article serves to evaluate current therapeutic strategies and the future directions in the areas of 3D-printed stents, over-the-scope clipping systems, tissue matrices and atrial septal closure devices.
Topics: Adult; Humans; Prognosis; Stents; Trachea; Tracheoesophageal Fistula
PubMed: 33153989
DOI: 10.1183/16000617.0094-2020 -
Rhode Island Medical Journal (2013) Sep 2021Idiopathic pulmonary fibrosis (IPF) is the most common of the idiopathic interstitial pneumonias. Its signs and symptoms are relatively non-specific, and patients often... (Review)
Review
Idiopathic pulmonary fibrosis (IPF) is the most common of the idiopathic interstitial pneumonias. Its signs and symptoms are relatively non-specific, and patients often present with chronic cough, progressive dyspnea, resting or exertional hypoxemia, and inspiratory crackles on lung auscultation. Definitive diagnosis requires the exclusion of known causes of pulmonary fibrosis and identification of the usual interstitial pneumonia (UIP) pattern of disease either on high-resolution computed tomography (HRCT) scan of the chest or on surgical lung biopsy. Multidisciplinary discussion involving pulmonologists, radiologists, and pathologists with expertise in the diagnosis of IPF and other forms of interstitial lung disease is recommended and often required. Management focuses on anti-fibrotic therapy and early referral to lung transplant centers for those who are candidates. This review will discuss the current recommendations for the diagnosis, prognostication, and management of patients with IPF.
Topics: Biopsy; Diagnosis, Differential; Humans; Idiopathic Pulmonary Fibrosis; Lung; Lung Diseases, Interstitial; Tomography, X-Ray Computed
PubMed: 34437662
DOI: No ID Found -
Investigative Radiology Aug 2023Interstitial lung disease (ILD) is now diagnosed by an ILD-board consisting of radiologists, pulmonologists, and pathologists. They discuss the combination of computed... (Review)
Review
Interstitial lung disease (ILD) is now diagnosed by an ILD-board consisting of radiologists, pulmonologists, and pathologists. They discuss the combination of computed tomography (CT) images, pulmonary function tests, demographic information, and histology and then agree on one of the 200 ILD diagnoses. Recent approaches employ computer-aided diagnostic tools to improve detection of disease, monitoring, and accurate prognostication. Methods based on artificial intelligence (AI) may be used in computational medicine, especially in image-based specialties such as radiology. This review summarises and highlights the strengths and weaknesses of the latest and most significant published methods that could lead to a holistic system for ILD diagnosis. We explore current AI methods and the data use to predict the prognosis and progression of ILDs. It is then essential to highlight the data that holds the most information related to risk factors for progression, e.g., CT scans and pulmonary function tests. This review aims to identify potential gaps, highlight areas that require further research, and identify the methods that could be combined to yield more promising results in future studies.
Topics: Humans; Artificial Intelligence; Lung Diseases, Interstitial; Prognosis; Tomography, X-Ray Computed; Radiologists; Lung
PubMed: 37058321
DOI: 10.1097/RLI.0000000000000974