Thoracic ultrasound reveals hidden bovine respiratory disease in calves before symptoms emerge

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Stonehaven Analytics
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Sep 21, 2026

New research shows thoracic ultrasound detects subclinical pneumonia in calves as young as five weeks, enabling targeted treatment and better disease management, despite the absence of visible symptoms.

Thoracic ultrasound is emerging as a practical way to spot bovine respiratory disease in calves that still look well, according to new work from the Agri-Food and Biosciences Institute. The findings matter because pneumonia remains one of the costliest calf health problems in the UK, eroding growth, welfare and margins before visible symptoms appear.

AFBI researchers at Hillsborough, working on a calf nutrition study funded by Feed For Growth, scanned 108 calves between five and six weeks old and again at 12 to 13 weeks. At the earlier scan, 5.6 per cent showed moderate pneumonia; by the second scan, that figure had risen to 14.8 per cent, yet none of those affected calves showed obvious clinical signs. The institute said this underlines how respiratory disease can be present without the usual coughing, nasal discharge or depression that farmers rely on.

Dr Gillian Scoley of AFBI said the scans could identify subclinical disease and support more targeted treatment, rather than treating entire groups indiscriminately. Dr Jessica Cooke of Feed For Growth said nutrition may influence immune resilience, while Iain Smith of Lisburn Veterinary Clinic said the technique can also help assess vaccine performance and future prevention.

The result fits a wider body of recent research. A Journal of Dairy Science review and meta-analysis has described lung ultrasonography as a valuable on-farm diagnostic tool, though it also notes the need for more standardised scoring.

Reference: S. Buczinski, V. Gomes, G. Vergnes, M.C. Poirier, S. Owusu-Afryie, J. Berman, N. Dendukuri,
Lung ultrasonography used as a diagnostic test for respiratory disease diagnosis in calves: Systematic review and meta-analysis using a Bayesian latent-class modeling approach. Journal of Dairy Science, Volume 109, Issue 8, 2026, Pages 8748-8765,
https://doi.org/10.3168/jds.2025-28206.

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