Using Transfer Learning of Convolutional Neural Network on Neck Radiographs to Identify Acute Epiglottitis.

Acute epiglottitis (AE) is a life-threatening condition and needs to be recognized timely. Diagnosis of AE with a lateral neck radiograph yields poor reliability and sensitivity. Convolutional neural networks (CNN) are powerful tools to assist the analysis of medical images. This study aimed to develop an artificial intelligence model using CNN-based transfer learning to identify AE in lateral neck radiographs. All cases in this study are from two hospitals, a medical center, and a local teaching hospital in Taiwan. In this retrospective study, we collected 251 lateral neck radiographs of patients with AE and 936 individuals without AE. Neck radiographs obtained from patients without and with AE were used as the input for model transfer learning in a pre-trained CNN including Inception V3, Densenet201, Resnet101, VGG19, and Inception V2 to select the optimal model. We used five-fold cross-validation to estimate the performance of the selected model. The confusion matrix of the final model was analyzed. We found that Inception V3 yielded the best results as the optimal model among all pre-train models. Based on the average value of the fivefold cross-validation, the confusion metrics were obtained: accuracy = 0.92, precision = 0.94, recall = 0.90, and area under the curve (AUC) = 0.96. Using the Inception V3-based model can provide an excellent performance to identify AE based on radiographic images. We suggest using the CNN-based model which can offer a non-invasive, accurate, and fast diagnostic method for AE in the future.

Epiglottitis. / Epiglottitt.

BACKGROUND: Acute epiglottitis in adults is a rare, potentially life-threatening condition caused by a bacterial infection in the epiglottis. Typical symptoms are fever, sore throat, and respiratory distress caused by upper airway obstruction. Proper treatment is needed for a good outcome. CASE PRESENTATION: We here present a 54-year-old female patient with acute epiglottitis. Her airway was secured by endotracheal intubation and she received antimicrobial therapy. She developed an abscess around the epiglottis that needed surgical drainage and tracheotomy. However, she fully recovered after nine days in hospital. INTERPRETATION: Acute epiglottitis in adults is a potentially life-threatening condition. The prognosis is good with proper treatment including selective airway intervention, antimicrobial therapy, and close monitoring.

Influenza A-Associated Epiglottitis and Compensatory Pursed Lip Breathing in an Infant.

The last 3 decades have seen a shift in the epidemiology of epiglottitis. Epiglottitis was once most commonly associated with Haemophilus influenzae type B. However, with the implementation of the H. influenzae type B vaccine in 1985, the incidence has drastically declined. There are now new emerging pathogens-bacteria, viruses, and fungi-causing epiglottitis. Here, we report the first case of epiglottitis secondary to influenza A in a former full-term, vaccinated infant who presented with cough, fever, stridor, pursed lip breathing, and progressive respiratory distress and eventual respiratory failure. This case highlights the presentation and clinical course of epiglottitis and describes a rare clinical feature, pursed lip breathing, in an infant.

Accuracy of objective parameters in acute epiglottitis diagnosis: A case-control study.

Lateral neck radiography is often used as a screening tool in emergency departments for suspected acute epiglottitis. The qualitative radiographic signs have been mainly used. The aim of this study was to evaluate the accuracy of objective radiographic parameters to aid diagnosis of acute epiglottitis.Patients who were diagnosed with acute epiglottitis from January 2006 to December 2016 were included in this case-control study. Control subjects with normal lateral neck radiograph findings were included at a 1:4 ratio during the same period. The clinical findings of the patients were assessed from electronic medical records and radiographs were interpreted by a board-certified radiologist and a board-certified emergency medicine physician. The widths of the 3rd cervical vertebral body, epiglottis base (EWB), epiglottis tip (EWT), aryepiglottic fold (AFW), and hypopharynx, as well as the dimensions of the retropharyngeal and retrotracheal soft tissues, were retrospectively measured. The sensitivity, specificity, and receiver operating characteristic (ROC) curves were analyzed for the measured parameters, and cutoff values were determined to predict acute epiglottitis. The predictive cutoff values of radiologic parameters were evaluated using 5-fold cross-validation.A total 260 epiglottitis patients and 1166 controls were included in the study. In the ROC curve analysis, the EWB had an area under the ROC curve (AUROC) of 0.99 for a cutoff value of 5.02 mm (sensitivity, 96.2%; specificity, 98.2%). The EWT had an AUROC of 0.97 for a cutoff value of 4.84 mm (sensitivity, 91.2%; specificity, 97.3%). The AFW had an AUROC of 0.88 for a cutoff value of 6.59 mm (sensitivity, 86.5%; specificity, 78.8%). The 5-fold cross-validation achieved AUROCs of 0.97 for EWB, 0.94 for EWT, and 0.83 for AFW.The objective radiographic parameters in lateral neck radiography may be useful in diagnosing acute epiglottitis. Further prospective studies may be warranted to evaluate the diagnostic performance in actual clinical practice.