A multicenter survey of pediatric flexible bronchoscopy in western China

Flexible bronchoscopy insufflated and high-flow nasal oxygen pilot trial (BUFFALO protocol pilot trial)

BACKGROUND

Hypoxaemia occurs in approximately 30% of children during anaesthesia for flexible bronchoscopy. High-flow nasal oxygen (HFNO) can prolong safe apnoea time and be used in children with abnormal airways. During flexible bronchoscopy, there is limited evidence if HFNO confers advantages over current standard practice in avoiding hypoxaemia. The aim is to investigate feasibility of HFNO use during anaesthesia for flexible bronchoscopy to reduce frequency of rescue oxygenation and hypoxaemia.

METHODS

BUFFALO is a bi-centre, unmasked, randomised controlled, parallel group, protocol for a pilot trial comparing HFNO techniques to standard practice during anaesthesia. Children (n = 81) aged > 37 weeks to 16 years presenting for elective bronchoscopy who fulfil inclusion but not exclusion criteria will be randomised prior to the procedure to HFNO or standard care oxygenation post induction of anaesthesia. Maintenance of anaesthesia with HFNO requires total venous anaesthesia (TIVA) and with standard, either inhalational or TIVA at discretion of anaesthetist in charge of the patient. Outcomes will include the feasibility of recruitment and adherence to trial procedures, acceptability of the intervention of the protocol and completion rates of data collection methods.

DISCUSSION

Findings of this trial will determine feasibility to plan for a larger multicentre randomised clinical trial and support the feasibility of the proposed study procedures.

TRIAL REGISTRATION

BUFFALO trial was registered with Australia and New Zealand Clinical Trials Registry (TRN12621001635853) on 29 November 2021 and commenced recruitment in May 2022. https://www.anzctr.org.au/ . The primary manuscript will be submitted for publication in a peer-reviewed journal.

A survey of pediatric flexible bronchoscopy in India

BACKGROUND

A bronchoscopy is an essential tool in pediatric pulmonology. However, the practices involved in the procedure are variable.

OBJECTIVE

To evaluate prevalent practices and variations in pediatric flexible bronchoscopy in India.

METHODS

An online survey was conducted via Google forms between September 2018 and March 2019. We circulated the survey among members of various respiratory societies and personal contacts. Physicians performing pediatric flexible bronchoscopy were requested to respond. The survey had 95 questions in seven domains: demographics, patient preparation, sedation, procedural aspects, monitoring, bronchoscope cleaning, and complications.

RESULTS

The survey received 24 complete responses; the respondents were from 14 cities. Pediatric bronchoscopy was done mainly for diagnostic purposes. Most (19, 79%) respondents reported using conscious sedation for the procedure. The preferred regimen for sedation was midazolam plus fentanyl [9 (37.5%)]. Atropine was used routinely by 4 (16%). For topical anesthesia, nebulized lignocaine only, both nebulized and spray as go lignocaine, and spray as go lignocaine only were used by 1 (4.2%), 6 (25%), and 17 (71%) respondents, respectively. The methods of providing oxygen during bronchoscopy were free flow (9, 37.5%), nasal prongs (8, 33.3%), mask (6, 25%), and laryngeal mask airway (1, 4.2%). The common therapeutic procedures included removal of mucus plugs (17, 71%), bronchoscopic intubation (11, 45%), and foreign body removal (10, 41%). The number of aliquots used by respondents for bronchoalveolar lavage varied from 2 to 6, and the volume for each aliquot was also varied (1-2 ml/kg or 5-10 ml). Almost all the respondents reported complication rates of less than 5%.

CONCLUSION

There is a considerable variation in pediatric flexible bronchoscopy practices across the country, highlighting the need to develop a uniform guideline.

Development and validation of the artificial intelligence (AI)-based diagnostic model for bronchial lumen identification

BACKGROUND

Bronchoscopy is a key step in the diagnosis and treatment of respiratory diseases. However, the level of expertise varies among different bronchoscopists. Artificial intelligence (AI) may help them identify bronchial lumens. Thus, a bronchoscopy quality-control system based on AI was built to improve the performance of bronchoscopists.

METHODS

This single-center observational study consecutively collected bronchoscopy videos from Shanghai Chest Hospital and segmented each video into 31 different anatomical locations to develop an AI-assisted system based on a convolutional neural network (CNN) model. We then designed a single-center trial to compare the accuracy of lumen recognition by bronchoscopists with and without the assistance of the AI system.

RESULTS

A total of 28,441 qualified images of bronchial lumen were used to train the CNNs. In the cross-validation set, the optimal accuracy of the six models was between 91.83% and 96.62%. In the test set, the visual geometry group 16 (VGG-16) achieved optimal performance with an accuracy of 91.88%, and an area under the curve of 0.995. In the clinical evaluation, the accuracy rate of the AI system alone was 54.30% (202/372). For the identification of bronchi except for segmental bronchi, the accuracy was 82.69% (129/156). In group 1, the recognition accuracy rates of doctors A, B, a and b alone were 42.47%, 34.68%, 28.76%, and 29.57%, respectively, but increased to 57.53%, 54.57%, 54.57%, and 46.24% respectively when combined with the AI system. Similarly, in group 2, the recognition accuracy rates of doctors C, D, c, and d were 37.90%, 41.40%, 30.91%, and 33.60% respectively, but increased to 51.61%, 47.85%, 53.49%, and 54.30% respectively, when combined with the AI system. Except for doctor D, the accuracy of doctors in recognizing lumen was significantly higher with AI assistance than without AI assistance, regardless of their experience (P<0.001).

CONCLUSIONS

Our AI system could better recognize bronchial lumen and reduce differences in the operation levels of different bronchoscopists. It could be used to improve the quality of everyday bronchoscopies.