Review on the methodology to assess respiratory tract lesions in pigs and their production impact

Pathological analysis and etiological assessment of pulmonary lesions and its association with pleurisy in slaughtered pigs

The intensification of pig farming has posed significant challenges in managing and preventing sanitary problems, particularly diseases of the respiratory complex. Monitoring at slaughter is an important control tool and cannot be overstated. Hence, this study aimed at characterizing both macroscopical and microscopical lesions and identifying the Actinobacillus pleuropneumoniae (APP), Mycoplasma hyopneumoniae (Mhyo), and Pasteurella multocida (PM) associated with pleurisy in swine. For this, a selected slaughterhouse in São Paulo State underwent a thorough examination of carcasses on the slaughter line, followed by lung sampling. The carcasses and lungs underwent macroscopical examination and were classified according to the score of pleurisy and lung samples were allocated into five groups, being: G0: score 0 - no lesions; G1: score 1; G2: score 2; G3: score 3; and G4: score 4. In total, 217 lung fragments were collected, for the histopathological evaluation and detection of the following respiratory pathogens: APP, Mhyo, and PM by qPCR. The results demonstrated that Mhyo and APP were the most prevalent etiological agents (single and co-identification) in lung samples, in different scores of pleurisies, while bronchopneumonia and bronchus-associated lymphoid tissue (BALT) hyperplasia lesions were the most frequent histopathological findings. Positive correlations were found between the quantification of APP DNA with 1) the score of pleurisy (R=0.254); 2) with the score of lung consolidation in all lung lobes (R=0.181 to R=0.329); and 3) with the score of lung consolidation in the entire lung (R=0.389). The study brings relevant information regarding the main bacterial pathogens associated with pleurisy in pigs and helps with understanding the relationship between the abovementioned pathogens and their impact on the respiratory health of pigs.

Feasibility of Near-Infrared Spectroscopy in the Classification of Pig Lung Lesions

Respiratory diseases significantly affect intensive pig farming, causing production losses and increased antimicrobial use. Accurate classification of lung lesions is crucial for effective diagnostics and disease management. The integration of non-destructive and rapid techniques would be beneficial to enhance overall efficiency in addressing these challenges. This study investigates the potential of near-infrared (NIR) spectroscopy in classifying pig lung tissues. The NIR spectra (908-1676 nm) of 101 lungs from weaned pigs were analyzed using a portable instrument and subjected to multivariate analysis. Two distinct discriminant models were developed to differentiate normal (N), congested (C), and pathological (P) lung tissues, as well as catarrhal bronchopneumonia (CBP), fibrinous pleuropneumonia (FPP), and interstitial pneumonia (IP) patterns. Overall, the model tailored for discriminating among pathological lesions demonstrated superior classification performances. Major challenges arose in categorizing C lungs, which exhibited a misclassification rate of 30% with N and P tissues, and FPP samples, with 30% incorrectly recognized as CBP samples. Conversely, IP and CBP lungs were all identified with accuracy, precision, and sensitivity higher than 90%. In conclusion, this study provides a promising proof of concept for using NIR spectroscopy to recognize and categorize pig lungs with different pathological lesions, offering prospects for efficient diagnostic strategies.

Scoring Enzootic Pneumonia-like Lesions in Slaughtered Pigs: Traditional vs. Artificial-Intelligence-Based Methods

Artificial-intelligence-based methods are regularly used in the biomedical sciences, mainly in the field of diagnostic imaging. Recently, convolutional neural networks have been trained to score pleurisy and pneumonia in slaughtered pigs. The aim of this study is to further evaluate the performance of a convolutional neural network when compared with the gold standard (i.e., scores provided by a skilled operator along the slaughter chain through visual inspection and palpation). In total, 441 lungs (180 healthy and 261 diseased) are included in this study. Each lung was scored according to traditional methods, which represent the gold standard (Madec's and Christensen's grids). Moreover, the same lungs were photographed and thereafter scored by a trained convolutional neural network. Overall, the results reveal that the convolutional neural network is very specific (95.55%) and quite sensitive (85.05%), showing a rather high correlation when compared with the scores provided by a skilled veterinarian (Spearman's coefficient = 0.831, p < 0.01). In summary, this study suggests that convolutional neural networks could be effectively used at slaughterhouses and stimulates further investigation in this field of research.

Comparing Visual-Only and Visual-Palpation Post-Mortem Lung Scoring Systems in Slaughtering Pigs

Respiratory diseases continue to pose significant challenges in pig production, and the assessment of lung lesions at the abattoir can provide valuable data for epidemiological investigations and disease surveillance. The evaluation of lung lesions at slaughter is a relatively simple, fast, and straightforward process but variations arising from different abattoirs, observers, and scoring methods can introduce uncertainty; moreover, the presence of multiple scoring systems complicates the comparisons of different studies, and currently, there are limited studies that compare these systems among each other. The objective of this study was to compare validated, simplified, and standardized schemes for assessing surface-related lung lesions in slaughtered pigs and analyze their reliability under field conditions. This study was conducted in a high-throughput abattoir in Italy, where two different scoring methods (Madec and Blaha) were benchmarked using 637 plucks. Statistical analysis revealed a good agreement between the two methods when severe or medium lesions were observed; however, their ability to accurately identify healthy lungs and minor injuries diverged significantly. These findings demonstrate that the Blaha method is more suitable for routine surveillance of swine respiratory diseases, whereas the Madec method can give more detailed and reliable results for the respiratory and welfare status of the animals at the farm level.

Value of simplified lung lesions scoring systems to inform future codes for routine meat inspection in pigs

BACKGROUND

Across the European Union (EU), efforts are being made to achieve modernisation and harmonisation of meat inspection (MI) code systems. Lung lesions were prioritised as important animal based measures at slaughter, but existing standardized protocols are difficult to implement for routine MI. This study aimed to compare the informative value and feasibility of simplified lung lesion scoring systems to inform future codes for routine post mortem MI.

RESULTS

Data on lung lesions in finisher pigs were collected at slaughter targeting 83 Irish pig farms, with 201 batches assessed, comprising 31,655 pairs of lungs. Lungs were scored for cranioventral pulmonary consolidations (CVPC) and pleurisy lesions using detailed scoring systems, which were considered the gold standard. Using the data collected, scenarios for possible simplified scoring systems to record CVPC (n = 4) and pleurisy (n = 4) lesions were defined. The measurable outcomes were the prevalence and (if possible) severity scoring at batch level for CVPC and pleurisy. An arbitrary threshold was set to the upper quartile (i.e., the top 25% of batches with high prevalence/severity of CVPC or pleurisy, n = 50). Each pair of measurable outcomes was compared by calculating Spearman rank correlations and assessing if batches above the threshold for one measurable outcome were also above it for their pairwise comparison. All scenarios showed perfect agreement (k = 1) when compared among themselves and the gold standard for the prevalence of CVPC. The agreement among severity outcomes and the gold standard showed moderate to perfect agreement (k = [0.66, 1]). The changes in ranking were negligible for all measurable outcomes of pleurisy for scenarios 1, 2 and 3 when compared with the gold standard (rs ≥ 0.98), but these changes amounted to 50% for scenario 4.

CONCLUSIONS

The best simplified CVPC scoring system is to simply count the number of lung lobes affected excluding the intermediate lobe, which provides the best trade-off between value of information and feasibility, by incorporating information on CVPC prevalence and severity. While for pleurisy evaluation, scenario 3 is recommended. This simplified scoring system provides information on the prevalence of cranial and moderate and severe dorsocaudal pleurisy. Further validation of the scoring systems at slaughter and by private veterinarians and farmers is needed.

Associations between Pleurisy and the Main Bacterial Pathogens of the Porcine Respiratory Diseases Complex (PRDC)

Porcine Respiratory Diseases Complex (PRDC) is a multifactorial disease that involves several bacterial pathogens, including Mycoplasma hyopneumoniae (M. hyopneumoniae), Actinobacillus pleuropneumoniae (A. pleuropneumoniae), Pasteurella multocida (P. multocida), Glaesserella parasuis (G. parasuis), and Streptococcus suis (S. suis). In pigs, the infection may cause lesions such pleurisy, which can lead to carcass condemnation. Hence, 1015 carcasses were selected from three different commercial pig farms, where the respiratory conditions were evaluated using slaughterhouse pleurisy evaluation system (SPES) and classified into five groups. In total, 106 pleural and lung fragments were collected for qPCR testing to identify the five abovementioned pathogens. A moderate correlation between the severity of the lesions and the presence of P. multocida (R = 0.38) and A. pleuropneumoniae (R = 0.28) was observed. Concerning the lung samples, the severity of the lesions was moderately correlated with the presence of P. multocida (R = 0.43) and M. hyopneumoniae (R = 0.35). Moreover, there was a strong correlation between the presence of P. multocida and M.hyopneumoniae in the pleura (R = 0.82). Finally, this approach may be a useful tool to identify and quantify causative agents of PRDC using qPCR, providing a comprehensive evaluation of its relevance, strength, and potential application in the field as a surveillance tool for veterinarians.