Data collected in animal cancer registries comprise extensive and valuable information, even more so when evaluated in context with precise population data. The authors evaluated 11 740 canine skin tumors collected in the Swiss Canine Cancer Registry from 2008–2013, considering data on breed, sex, age, and anatomic locations. Their incidence rate (IR) per 100 000 dogs/year in the Swiss dog population was calculated based on data from the official and mandatory Swiss dog registration database ANIS. The most common tumor types were mast cell tumors (16.35%; IR, 60.3), lipomas (12.47%; IR, 46.0), hair follicle tumors (12.34%; IR, 45.5), histiocytomas (12.10%; IR, 44.6), soft tissue sarcomas (10.86%; IR, 40.1), and melanocytic tumors (8.63%; IR, 31.8) with >1000 tumors per type. The average IR of all tumor types across the 227 registered breeds was 372.2. The highest tumor incidence was found in the Giant Schnauzer (IR, 1616.3), the Standard Schnauzer (IR, 1545.4), the Magyar Vizsla (IR, 1534.6), the Rhodesian Ridgeback (IR, 1445.0), the Nova Scotia Duck Tolling Retriever (IR, 1351.7), and the Boxer (IR, 1350.0). Mixed-breed dogs (IR, 979.4) had an increased IR compared to the average of all breeds. Previously reported breed predispositions for most tumor types were confirmed. Nevertheless, the data also showed an increased IR for mast cell tumors and melanocytic tumors in the Nova Scotia Duck Tolling Retriever and for histiocytomas in the Flat Coated Retriever. The results from this study can be taken into consideration when selecting purebred dogs for breeding to improve a breed’s health.

The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or classifying mitotic figures (MFs). Recent progress in the field of artificial intelligence has allowed the development of high-performance algorithms that may improve standardization of the MC. As algorithmic predictions are not flawless, computer-assisted review by pathologists may ensure reliability. In the present study, we compared partial (MC-ROI preselection) and full (additional visualization of MF candidates and display of algorithmic confidence values) computer-assisted MC analysis to the routine (unaided) MC analysis by 23 pathologists for whole-slide images of 50 canine cutaneous mast cell tumors (ccMCTs). Algorithmic predictions aimed to assist pathologists in detecting mitotic hotspot locations, reducing omission of MFs, and improving classification against imposters. The interobserver consistency for the MC significantly increased with computer assistance (interobserver correlation coefficient, ICC = 0.92) compared to the unaided approach (ICC = 0.70). Classification into prognostic stratifications had a higher accuracy with computer assistance. The algorithmically preselected hotspot MC-ROIs had a consistently higher MCs than the manually selected MC-ROIs. Compared to a ground truth (developed with immunohistochemistry for phosphohistone H3), pathologist performance in detecting individual MF was augmented when using computer assistance (F1-score of 0.68 increased to 0.79) with a reduction in false negatives by 38%. The results of this study demonstrate that computer assistance may lead to more reproducible and accurate MCs in ccMCTs.

Mitotic count (MC) is an important element for grading canine cutaneous mast cell tumors (ccMCTs) and is determined in 10 consecutive high-power fields with the highest mitotic activity. However, there is variability in area selection between pathologists. In this study, the MC distribution and the effect of area selection on the MC were analyzed in ccMCTs. Two pathologists independently annotated all mitotic figures in whole-slide images of 28 ccMCTs (ground truth). Automated image analysis was used to examine the ground truth distribution of the MC throughout the tumor section area, which was compared with the manual MCs of 11 pathologists. Computerized analysis demonstrated high variability of the MC within different tumor areas. There were 6 MCTs with consistently low MCs (MC<7 in all tumor areas), 13 cases with mostly high MCs (MC ≥7 in ≥75% of 10 high-power field areas), and 9 borderline cases with variable MCs around 7, which is a cutoff value for ccMCT grading. There was inconsistency among pathologists in identifying the areas with the highest density of mitotic figures throughout the 3 ccMCT groups; only 51.9% of the counts were consistent with the highest 25% of the ground truth MC distribution. Regardless, there was substantial agreement between pathologists in detecting tumors with MC ≥7. Falsely low MCs below 7 mainly occurred in 4 of 9 borderline cases that had very few ground truth areas with MC ≥7. The findings of this study highlight the need to further standardize how to select the region of the tumor in which to determine the MC.

Canine cutaneous epitheliotropic T-cell lymphoma is a neoplasm with heterogeneous clinical and histopathological presentations. Survival times and responses to therapy are variable, and indicators to predict outcomes are lacking. Clinical and histopathological parameters from 176 archival cases from the University of Pennsylvania and University of Bern (2012–2018) were investigated for associations with clinical outcomes. Histopathological evaluation used digitized whole slide images and QuPath software. Cases included 107 female and 69 male dogs from 48 breeds, with a mean age of 10.4 years. Most common clinical signs were erythema ( n = 131), crusting ( n = 108), and scaling ( n = 102). Affected sites were haired skin ( n = 159), lip ( n = 74), nasal planum ( n = 49), and paw pads ( n = 48). The median survival time (MST) was 95 days (1–850). Dogs had 4.26-fold and 2.82-fold longer MST when treated with chemotherapy and prednisone, respectively, than when receiving supportive care. Haired skin involvement (hazard ratio [HR]: 2.039, 95% confidence interval [CI]: 1.180–3.523), erosions/ulcers (HR: 1.871, 95% CI: 1.373–2.548), nodules (HR: 1.496, 95% CI: 1.056–2.118), and crusting (HR: 1.454, 95% CI: 1.061–1.994) were clinical parameters predicting poor outcomes, whereas complete posttherapeutic clinical remission (HR: 0.469, 95% CI: 0.324–0.680) and a stable disease (HR: 0.323, 95% CI: 0.229–0.456) were associated with longer survival. Histopathological features associated with the increased risk of death were extensive infiltration of the panniculus (HR: 2.865, 95% CI: 1.565-4.809), mitotic count ≥7/high-power field (HR: 3.027, 95% CI: 2.065–4.439), cell diameter ≥10.0 µm (HR: 2.078, 95% CI: 1.281–3.372), and nuclear diameter ≥8.3 µm (HR: 3.787, 95% CI: 1.647–8.707).

Integration of new technologies, such as digital microscopy, into a highly standardized laboratory routine requires the validation of its performance in terms of reliability, specificity, and sensitivity. However, a validation study of digital microscopy is currently lacking in veterinary pathology. The aim of the current study was to validate the usability of digital microscopy in terms of diagnostic accuracy, speed, and confidence for diagnosing and differentiating common canine cutaneous tumor types and to compare it to classical light microscopy. Therefore, 80 histologic sections including 17 different skin tumor types were examined twice as glass slides and twice as digital whole-slide images by 6 pathologists with different levels of experience at 4 time points. Comparison of both methods found digital microscopy to be noninferior for differentiating individual tumor types within the category epithelial and mesenchymal tumors, but diagnostic concordance was slightly lower for differentiating individual round cell tumor types by digital microscopy. In addition, digital microscopy was associated with significantly shorter diagnostic time, but diagnostic confidence was lower and technical quality was considered inferior for whole-slide images compared with glass slides. Of note, diagnostic performance for whole-slide images scanned at 200× magnification was noninferior in diagnostic performance for slides scanned at 400×. In conclusion, digital microscopy differs only minimally from light microscopy in few aspects of diagnostic performance and overall appears adequate for the diagnosis of individual canine cutaneous tumors with minor limitations for differentiating individual round cell tumor types and grading of mast cell tumors.

Thyrotropin receptor (TSHR), sodium iodide symporter (NIS), pendrin, and thyroid peroxidase (TPO) are essential for the uptake of iodine by follicular thyroid cells. The aim of this study was to establish immunohistochemistry (IHC) protocols for TSHR, NIS, pendrin, and TPO in canine tissues and characterize their expression in organoids derived from canine follicular cell thyroid carcinoma (FTC) and in the respective primary tumors. This constitutes a fundamental step to establish organoids as a model to study the uptake of iodine in canine FTC. Commercially available antibodies directed against human proteins were selected. Antibody specificity was confirmed by western blot using lysates of the HTori-3 human thyroid cell line and healthy canine thyroid gland. IHC was validated using HTori-3 cells and a set of canine normal tissues including healthy thyroid gland. The expression of TSHR, NIS, pendrin, and TPO was evaluated in 3 organoid lines derived from FTC and respective primary tumors. All 4 antibodies produced specific bands by western blot and cytoplasmic labeling in follicular cells by IHC in both human HTori-3 cells and canine thyroid gland. NIS also showed basolateral membrane immunolabeling in follicular cells. All 4 proteins were highly expressed in organoids derived from FTC. The expression was similar or higher compared to the primary tumors. The results of this study characterize organoids derived from canine FTC as a suitable in vitro model to investigate iodine uptake, opening new research possibilities in the field of canine thyroid cancer therapy.