Peer-reviewed veterinary case report
Benign abdominal fibroma diagnosed in 7-year-old dog using AI analysis
By Djallal Eddine Rahmoun et al.·Published in Theoretical and Applied Veterinary Medicine·2025·Veterinary Science institute, University of Souk Ahras, Algeria, UA·View original on DOAJ →
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Original publication title: AI-assisted digital morphometry application for the diagnosis of a benign peritoneal fibroma in a dog
- Species:
- dog
Plain-English summary
A 7-year-old dog was brought in with a swollen belly that was getting worse over time. During surgery, the vet found a well-defined mass on the lining of the abdomen, which was identified as a benign fibroma (a type of non-cancerous tumor). The vet used advanced AI technology to help analyze the tumor's characteristics, confirming it was not aggressive. After the surgery, the dog recovered well and showed no signs of the tumor returning at a check-up three months later.
People also search for: dog abdominal swelling · benign tumor in dog · dog surgery recovery · AI in veterinary diagnosis
Abstract
This paper reports a rare benign peritoneal fibroma in a 7-year-old dog and demonstrates the use of artificial intelligence (AI)–assisted digital morphometry in veterinary pathology. The dog had presented with progressive abdominal distention. Upon examination, a well-encapsulated mass was found attached to the parietal peritoneum on a small vascular pedicle during exploratory laparotomy. A histopathological examination revealed interlacing bundles of spindle-shaped fibroblasts arranged within a stroma with abundant collagen. There was slight evidence of vascular proliferation, and no mitotic figures were observed, consistent with a benign fibromatous lesion. AI-based image analysis employed U-Net for segmentation and ResNet-based feature extraction to create quantitative morphometry parameters such that nuclear eccentricity, cytoplasmic area, and vascularization index were all consistent with a low proliferative rate and mostly organized stromal architecture observed on routine histopathology. Here, both AI-derived measures strengthened diagnostic confidence by reducing subjectivity and providing an objective foundation for evaluating canine soft-tissue tumors. The recovery after the operation was normal, and there was no recurrence noted at the follow-up visit 90 days later. This case demonstrates the benefit of introducing AI-based digital morphometry into routine histopathology to improve diagnostic accuracy, decrease interobserver variation, and facilitate data-driven characterization of soft tissue tumors in veterinary pathology.
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Search related cases →Original publication on DOAJ: https://doi.org/10.32819/2025.13014