Search Results (5)

Radiomic feature (RF) analysis of computed tomography (CT) images may aid the diagnosis and staging of ovine pulmonary adenocarcinoma (OPA). We assessed the RF characteristics of OPA tumours in JSRV-infected sheep compared to non-tumour lung tissues, examined their stability over time, and analysed RF variations in the nascent tumour field (NTF) and nascent tumour margin field (NTmF). In monthly CT scans, lung tissues were automatically segmented by density, and lung tumours were manually segmented. RFs were calculated for each imaging session, selected according to stability and reproducibility, and adjusted for volume dependence where appropriate. Comparisons between scans within sheep were facilitated through fiducial registration and spatial transformations. Initially, 9/36 RFs differed significantly from non-tumour lung tissue of similar density. Predominant RF changes included ngtdm_Complexity, glrlm_RunLNUnif_VN, and gldm_SmDHGLE. RFs in lung tumour segments showed time-dependent changes, whereas non-tumour lung tissue of similar density remained consistent. OPA lung tumour RF characteristics are distinct from those of other lung tissues of similar density and evolve as the tumour develops. Such characteristics suggest that radiomic analysis offers potential for the early detection and management of JSRV-related lung tumours. This research enhances the understanding of OPA imaging, potentially informing better diagnosis and control measures for naturally occurring infections. Full article

Ovine pulmonary adenocarcinoma (OPA) is a contagious lung tumour caused by the Jaagsiekte Sheep Retrovirus (JSRV). Histopathological diagnosis is the gold standard for OPA diagnosis. However, interpretation of traditional pathology images is complex and operator dependent. The mask regional convolutional neural network (Mask R-CNN) has emerged as a valuable tool in pathological diagnosis. This study utilized 54 typical OPA whole slide images (WSI) to extract 7167 typical lesion images containing OPA to construct a Common Objects in Context (COCO) dataset for OPA pathological images. The dataset was categorized into training and test sets (8:2 ratio) for model training and validation. Mean average specificity (mASp) and average sensitivity (ASe) were used to evaluate model performance. Six WSI-level pathological images (three OPA and three non-OPA images), not included in the dataset, were used for anti-peeking model validation. A random selection of 500 images, not included in the dataset establishment, was used to compare the performance of the model with assessment by pathologists. Accuracy, sensitivity, specificity, and concordance rate were evaluated. The model achieved a mASp of 0.573 and an ASe of 0.745, demonstrating effective lesion detection and alignment with expert annotation. In Anti-Peeking verification, the model showed good performance in locating OPA lesions and distinguished OPA from non-OPA pathological images. In the random 500-image diagnosis, the model achieved 92.8% accuracy, 100% sensitivity, and 88% specificity. The agreement rates between junior and senior pathologists were 100% and 96.5%, respectively. In conclusion, the Mask R-CNN-based OPA diagnostic model developed for OPA facilitates rapid and accurate diagnosis in practical applications. Full article

Ovine pulmonary adenocarcinoma (OPA) is an infectious, neoplastic lung disease of sheep that causes significant animal welfare and economic issues throughout the world. Understanding OPA pathogenesis is key to developing tools to control its impact. Central to this need is the availability of model systems that can monitor and track events after Jaagsiekte sheep retrovirus (JSRV) infection. Here, we report the development of an experimentally induced OPA model intended for this purpose. Using three different viral dose groups (low, intermediate and high), localised OPA tumour development was induced by bronchoscopic JSRV instillation into the segmental bronchus of the right cardiac lung lobe. Pre-clinical OPA diagnosis and tumour progression were monitored by monthly computed tomography (CT) imaging and trans-thoracic ultrasound scanning. Post mortem examination and immunohistochemistry confirmed OPA development in 89% of the JSRV-instilled animals. All three viral doses produced a range of OPA lesion types, including microscopic disease and gross tumours; however, larger lesions were more frequently identified in the low and intermediate viral groups. Overall, 31% of JSRV-infected sheep developed localised advanced lesions. Of the sheep that developed localised advanced lesions, tumour volume doubling times (calculated using thoracic CT 3D reconstructions) were 14.8 ± 2.1 days. The ability of ultrasound to track tumour development was compared against CT; the results indicated a strong significant association between paired CT and ultrasound measurements at each time point (R² = 0.799, p < 0.0001). We believe that the range of OPA lesion types induced by this model replicates aspects of naturally occurring disease and will improve OPA research by providing novel insights into JSRV infectivity and OPA disease progression. Full article

Ovine pulmonary adenocarcinoma (OPA), also known as sheep pulmonary adenomatosis and jaagsiekte, is a contagious pulmonary tumor of sheep, characterized by neoplastic proliferation of type II pneumocyte and club cells. OPA is induced by the oncogenic activity of the envelope glycoprotein (Env) of exogenous jaagsiekte sheep retrovirus (JSRV). This disease is associated with significant economic losses in numerous sheep raising countries. The onset of suggestive clinical signs is often late, making difficult the early diagnosis of the disease and timely implementation of control measures on the affected farms. Further, the lack of diagnostic tests that can be performed routinely by veterinary clinicians to accurately assess infected animals (e.g., serological or others) means that the true prevalence at flock level is not known. Imaging diagnostic methods (e.g., ultrasound, X-ray and computed tomography) can be used to support the clinical diagnosis, even in pre-clinical stages in affected flocks. The diagnosis must be confirmed by PCR of nasal excretions or immunohistochemistry and PCR of tumor lesions. No vaccine for OPA has yet been developed. Thus, in this work, we review the main methods of diagnosis of OPA in order to support the clinician in the identification of the disease, avoid underdiagnosis and allow the implementation of suitable measures to prevent and control its spread. Full article

We review three neoplastic wasting diseases affecting sheep generally recorded under common production cycles and with epidemiological and economic relevance in sheep-rearing countries: small intestinal adenocarcinoma (SIA), ovine pulmonary adenocarcinoma (OPA) and enzootic nasal adenocarcinoma (ENA). SIA is prevalent in Australia and New Zealand but present elsewhere in the world. This neoplasia is a tubular or signet-ring adenocarcinoma mainly located in the middle or distal term of the small intestine. Predisposing factors and aetiology are not known, but genetic factors or environmental carcinogens may be involved. OPA is a contagious lung cancer caused by jaagsiekte sheep retrovirus (JSRV) and has been reported in most sheep-rearing countries, resulting in significant economic losses. The disease is clinically characterized by a chronic respiratory process as a consequence of the development of lung adenocarcinoma. Diagnosis is based on the detection of JSRV in the tumour lesion by immunohistochemistry and PCR. In vivo diagnosis may be difficult, mainly in preclinical cases. ENA is a neoplasia of glands of the nasal mucosa and is associated with enzootic nasal tumour virus 1 (ENTV-1), which is similar to JSRV. ENA enzootically occurs in many countries of the world with the exception of Australia and New Zealand. The pathology associated with this neoplasia corresponds with a space occupying lesion histologically characterized as a low-grade adenocarcinoma. The combination of PCR and immunohistochemistry for diagnosis is advised. Full article