Pediatric Interstitial (Diffuse) Lung Disease

Developmental lung disease in a cat associated with high probability of severe pulmonary hypertension: natural history, histopathology and genetic analysis

Case summary

This report describes the diagnostic findings, natural history and genetic analysis of the candidate gene Forkhead Box F1 (FOXF1) in a young cat with developmental lung disease and high probability of pulmonary hypertension. A 1-year-old male entire Chartreux cat was referred for cardiac murmur investigation and exercise intolerance. Echocardiography identified a high-velocity tricuspid regurgitant jet with right-sided cardiac changes, supporting a high probability of pulmonary hypertension. No congenital cardiac shunts or left-sided cardiac changes were found to support a primary cardiac cause of pulmonary hypertension. Extensive laboratory work, thoracic radiographs and CT were performed. Histopathological characterisation (lung biopsy and later post mortem) was necessary to reach the final diagnosis. Eight months after diagnosis, the cat developed right-sided congestive heart failure, eventually leading to euthanasia. Survival from diagnosis to death was 12 months.

Relevance and novel information

Developmental lung disease belongs to a group of diffuse lung diseases in humans associated with pulmonary hypertension. The veterinary literature describing lung growth disorders in cats is sparse, and the present report provides information on clinical presentation and progression alongside a thorough diagnostic workup, which may aid clinicians in identifying this condition. Lung biopsy was pivotal in reaching the final diagnosis. No causal variants in FOXF1 were identified.

Environmental hazards and demographic and clinical data of childhood interstitial lung diseases in a tertiary institute in Egypt

Background

The incidence of childhood interstitial lung diseases increased in the last years in Egypt. Changes in environmental and climatic conditions may be contributing factors. Also, raising birds at home increased in the past years due to financial issues. Other environmental factors include increased industries, traffic, and pollution. Our study aimed to assess the environmental hazards and the severity of childhood interstitial lung diseases.

Results

Sixty-five percent of patients with childhood interstitial lung diseases (chILD) were exposed to cigarette smoke; 45% were exposed to birds, 30% to industrial wastes, 20% to grass and pesticides, and 10% to animals.

Conclusions

Exposure to cigarette smoke and birds increases the risk of development of chILD.

Checklist for responsible deep learning modeling of medical images based on COVID-19 detection studies

The sudden outbreak and uncontrolled spread of COVID-19 disease is one of the most important global problems today. In a short period of time, it has led to the development of many deep neural network models for COVID-19 detection with modules for explainability. In this work, we carry out a systematic analysis of various aspects of proposed models. Our analysis revealed numerous mistakes made at different stages of data acquisition, model development, and explanation construction. In this work, we overview the approaches proposed in the surveyed Machine Learning articles and indicate typical errors emerging from the lack of deep understanding of the radiography domain. We present the perspective of both: experts in the field - radiologists and deep learning engineers dealing with model explanations. The final result is a proposed checklist with the minimum conditions to be met by a reliable COVID-19 diagnostic model.