Comparative Histopathology of Bovine Acute Interstitial Pneumonia and Bovine Respiratory Syncytial Virus-Associated Interstitial Pneumonia

Chien, Rory C.; Sorensen, Nicholas J.; Payton, Mark E.; Confer, Anthony W.

doi:10.1016/j.jcpa.2022.01.005

Cited by 2 publications

(2 citation statements)

References 17 publications

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“…Besides gross diagnosis, samples submitted to histopathology were given an overall histopathology diagnosis. This process was carried out to obtain a confirmatory diagnosis, especially for the AIP class, since histopathology findings are considered the “gold standard” [ 18 , 27 , 28 ]. When unaltered images and histopathology diagnoses were used, BIP lung images were 100% correctly classified.…”

Section: Discussionmentioning

confidence: 99%

Image Classification and Automated Machine Learning to Classify Lung Pathologies in Deceased Feedlot Cattle

Bortoluzzi

Schmidt

Brown

et al. 2023

Veterinary Sciences

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Bovine respiratory disease (BRD) and acute interstitial pneumonia (AIP) are the main reported respiratory syndromes (RSs) causing significant morbidity and mortality in feedlot cattle. Recently, bronchopneumonia with an interstitial pattern (BIP) was described as a concerning emerging feedlot lung disease. Necropsies are imperative to assist lung disease diagnosis and pinpoint feedlot management sectors that require improvement. However, necropsies can be logistically challenging due to location and veterinarians’ time constraints. Technology advances allow image collection for veterinarians’ asynchronous evaluation, thereby reducing challenges. This study’s goal was to develop image classification models using machine learning to determine RS diagnostic accuracy in right lateral necropsied feedlot cattle lungs. Unaltered and cropped lung images were labeled using gross and histopathology diagnoses generating four datasets: unaltered lung images labeled with gross diagnoses, unaltered lung images labeled with histopathological diagnoses, cropped images labeled with gross diagnoses, and cropped images labeled with histopathological diagnoses. Datasets were exported to create image classification models, and a best trial was selected for each model based on accuracy. Gross diagnoses accuracies ranged from 39 to 41% for unaltered and cropped images. Labeling images with histopathology diagnoses did not improve average accuracies; 34–38% for unaltered and cropped images. Moderately high sensitivities were attained for BIP (60–100%) and BRD (20–69%) compared to AIP (0–23%). The models developed still require fine-tuning; however, they are the first step towards assisting veterinarians’ lung diseases diagnostics in field necropsies.

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Section: Discussionmentioning

confidence: 99%

Image Classification and Automated Machine Learning to Classify Lung Pathologies in Deceased Feedlot Cattle

Bortoluzzi

Schmidt

Brown

et al. 2023

Veterinary Sciences

View full text Add to dashboard Cite

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“…Hyaline membrane are characterized by eosinophilic lamellations of polymerized fibrin and necrotic debris that replace lost type I pneumocytes of the alveolar interstitium. Some cases also had type II pneumocyte hyperplasia and bronchiolitis obliterans [ 9 , 27 , 29 ]. Bronchopneumonia type lungs were categorized by neutrophils within the bronchi/bronchioles and/or alveoli.…”

Section: Methodsmentioning

confidence: 99%

Determining Frequency of Common Pulmonary Gross and Histopathological Findings in Feedyard Fatalities

Schmidt

White

Finley³

et al. 2023

Veterinary Sciences

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Pulmonary disease is often associated with feedlot cattle mortality, and the most common syndromes include bronchopneumonia, acute interstitial pneumonia, and bronchopneumonia with an interstitial pneumonia. The study objective was to utilize gross necropsy and histopathology to determine the frequency of pulmonary lesions from three major syndromes and agreement between gross and histopathological diagnosis. A cross sectional, observational study was performed at six U.S. feedyards using a full systematic necropsy to assess mortalities during summer 2022. A subset of mortalities had four lung samples submitted for histopathological diagnosis. Gross necropsy was performed on 417 mortalities, 402 received a gross diagnosis and 189 had a histopathological diagnosis. Descriptive statistics were used to evaluate pulmonary diagnosis frequency based on method (gross/histopathology), and generalized linear mixed models were used to evaluate agreement between histopathological and gross diagnoses. Using gross diagnosis, bronchopneumonia represented 36.6% of cases with acute interstitial pneumonia and bronchopneumonia with an interstitial pneumonia representing 10.0% and 35.8%, respectively. Results identified bronchopneumonia with an interstitial pneumonia as a frequent syndrome which has only been recently reported. Histopathological diagnosis had similar findings; bronchopneumonia represented 32.3% of cases, with acute interstitial pneumonia and bronchopneumonia with an interstitial pneumonia representing 12.2% and 36.0%, respectively. Histopathological diagnosis tended (p-VALUE = 0.06) to be associated with gross diagnosis. Pulmonary disease was common and both diagnostic modalities illustrated three primary syndromes: bronchopneumonia, acute interstitial pneumonia, and bronchopneumonia with an interstitial pneumonia with similar frequencies. Improved understanding of pulmonary pathology can be valuable for evaluating and adjusting therapeutic interventions.

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Comparative Histopathology of Bovine Acute Interstitial Pneumonia and Bovine Respiratory Syncytial Virus-Associated Interstitial Pneumonia

Cited by 2 publications

References 17 publications

Image Classification and Automated Machine Learning to Classify Lung Pathologies in Deceased Feedlot Cattle

Image Classification and Automated Machine Learning to Classify Lung Pathologies in Deceased Feedlot Cattle

Determining Frequency of Common Pulmonary Gross and Histopathological Findings in Feedyard Fatalities

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