Chronic Nonasphyxiating Bronchial Foreign Body Removal: Bronchoscopic Debridement With Tracheal Window Extraction

Optimized Fuzzy C-Means Algorithm-Based Coronal Magnetic Resonance Imaging Scanning in Tracheal Foreign Bodies of Children

In order to provide theoretical support for clinical diagnosis, the diagnostic value of the optimized fuzzy C-means (FCM) algorithm combined with coronal magnetic resonance imaging (MRI) scan was investigated in the diagnosis of tracheal foreign bodies in children. The anisotropic filtering was applied to optimize the traditional FCM algorithm, so as to construct a new MRI image segmentation algorithm, namely, AFFCM algorithm. Then, the traditional FCM algorithm, the FCM algorithm based on the kernel function (KFCM), and the FCM algorithm based on the spatial neighborhood information (RFCM) were introduced for comparison with the AFFCM. 28 children diagnosed with foreign bodies in the trachea were selected for MRI diagnosis, and AFFCM was used for segmentation. The partition coefficient, segmentation entropy, and the correlation degree between classes after fuzzy division of the four algorithms were recorded, and the location and distribution of foreign bodies in the trachea and the types of foreign bodies were also collected. Besides, the MRI scanning and chest X-rays of the children with foreign bodies in the trachea should also be recorded in terms of the positive rate, diagnosis rate, and indirect signs. The class division coefficient and interclass correlation degree after fuzzy division of AFFCM were markedly greater than those of FCM, KFCM, and RFCM (P < 0.05), while the segmentation entropy of AFFCM was less sharp than the entropies of FCM, KFCM, and RFCM (P < 0.05). Among the 28 children, there were 5 cases with foreign bodies in the trachea (17.86%), 10 cases in the left bronchus (35.71%), and 13 cases in the right bronchus (46.43%). Among the foreign body types, there were 10 cases of melon seeds (35.71%), 6 cases of peanuts (21.43%), and 5 cases of beans (17.86%). The positive rate (89.29%) and diagnosis rate (96.43%) of MRI for bronchial foreign bodies increased obviously in contrast to the rates of X-ray chest radiographs (57.14% and 67.86%) (P < 0.05). Therefore, it was indicated that AFFCM showed higher partition coefficient value, lower segmentation entropy, larger similarity among classes, and better image segmentation effect. Furthermore, AFFCM-based coronal MRI scan had a higher positive rate and diagnosis rate for children's tracheal foreign bodies, and the main signs were emphysema and atelectasis.

An unusual tracheal foreign body in a middle-aged male with a 15-year history of coal use: a case report

BACKGROUND

Long-term exposure to coal dust causes respiratory disease. In chest computer tomography (CT), pulmonary nodules, pulmonary interstitial fibrosis and emphysema manifest themselves. However, tracheal foreign bodies caused by coal dust are rarely reported. In this study, we report a special case of a tracheal coal foreign body, in which the patient has neither a history of coal work nor foreign body inhalation.

CASE PRESENTATION

A 49-year-old man was diagnosed with chronic obstructive pulmonary disease (COPD) due to chronic cough and exertional dyspnoea. His symptoms gradually worsened despite treatment for COPD. Chest radiograph and CT images showed an irregular high-density nodule inserting fromthe trachea into the right thyroid at approximately the level of the 7th cervical vertebra. Fiberoptic bronchoscopy revealed that the tracheal lumen was mostly blocked. After the surgery, the energy spectrum CT quantitative analysis showed that the foreign body was likely that of a bituminous coal specimen.

CONCLUSIONS

For cases in which a foreign body in the airway is highly suspected, early fiberoptic bronchoscopy and radiographic examinations should be performed as soon as possible to avoid misdiagnosis and ensure timely treatment.