Synovial myxoma or myxosarcoma? Lymph node metastasis in 2 dogs.

Synovial myxoma, a rare joint tumor in dogs, has traditionally been considered benign, acknowledging that local invasion into regional tissues including bone may be present. Given the diagnostic challenges in distinguishing synovial myxoma from other joint lesions through clinical features and diagnostic imaging, definitive diagnosis relies on characteristic gross and histologic features. Within the inner surface of the joint capsule, synovial myxomas form nodules of stellate-to-spindle cells within abundant myxomatous matrix. We present here 2 cases of synovial myxoma with metastasis to regional lymph nodes and compare these 2 cases to 3 cases without evidence of lymph node metastasis. Aside from lymphovascular invasion in one case with metastasis, there were no overt histologic features of the primary tumor to suggest aggressive biologic behavior. The finding of lymph node metastasis warrants reconsideration of the term "synovial myxoma" for this neoplasm. We suggest the term "synovial myxosarcoma," considering that histologic features of the primary tumor do not predict biologic behavior. Our case series highlights the importance of lymph node sampling in suspected synovial myxosarcoma cases as well as thorough histologic examination, emphasizing careful evaluation for lymphovascular invasion.

Flowcytometric data of intermediate-large cell gastrointestinal lymphoma presenting a gross mass in 32 cats - "let them glow in the flow".

Gastrointestinal lymphoma is the most common form of lymphoma in domestic cats. Aggressive phenotypes are much less common but do bear and unfavorable prognosis. Immunophenotyping by flow cytometry (FCM) is not systematically performed in these patients, because of difficulties in the acquisition of suitable sample material from the gastrointestinal tract. A multimodal diagnostic approach is recommended to improve identification of subtypes targeting patient tailored therapeutic strategies. The aim of this prospective study was to present results of multicolor FCM immunophenotyping in surgically removed gastrointestinal mass and relate them with histopathology using the World Health Organization (WHO) classification and clonality PCR testing. Thirty-two patients were included. Eight cats (25%) had gastric, 23 (72%) had intestinal lymphoma and 1 (3%) had gastric/jejunal lymphoma. Intestinal lymphoma sites were represented by 18 small intestinal, 4 ileocaecal, 1 large intestinal. All gastric lymphomas were diffuse large B-cell lymphoma (DLBCL). Small intestinal lymphomas were 10 enteropathy associated T-cell lymphoma type I (EATL I), 2 enteropathy associated T-cell lymphoma type II (EATL II), 2 peripheral T-cell lymphoma (PTCL), 3 DLBCL and one DLBCL+EATL II. The most common small intestinal FCM T-cell phenotype was CD3+CD21- CD4-CD8-CD18+ CD5-CD79- in 7/10 EATL I and one EATL II. The most frequent FCM B-cell phenotype was CD3-CD21+ CD4-CD8-CD18+ CD5-CD79+ in 13/17 DLBCL and the DLBCL+EATL II. Clonality PCR results were positive in 87.5% (28/32) of all cases. No cross-lineage rearrangement was observed. IHC and FCM results agreed in 87.5% (28/32) of all cases. When all 3 methods were combined, consistent results were seen in 75% (24/32). This is the first demonstration of a multicolor FCM approach set in context to the gold standard histopathology and clonality testing results.

Short colon syndrome in cats.

BACKGROUND: Shortening of the colon has been described in cats, but its imaging and clinicopathological features remain poorly understood. OBJECTIVES: Description of the signalment, clinical presentation, imaging, endoscopic and histological features of short colon syndrome in cats. ANIMALS: Ninety-three cats diagnosed with short colon. METHODS: Multi-institutional, descriptive, retrospective case series study. Medical records were searched for a diagnosis of short colon on abdominal ultrasonography, computed tomography, endoscopy, autopsy, or a combination of these modalities. RESULTS: The median age of included cats was 12 years at the time of diagnosis. Diarrhea was the most common clinical sign (60/92; 65%), followed by vomiting (36/92; 39%), weight loss (36/92; 39%), and inappetence (24/92; 26%). Thirteen percent of cats (12/92) had no signs of gastrointestinal disease at the time of diagnosis. In addition to a shortened colonic length, 79% (66/84) of cats had concomitant colonic thickening on ultrasonographic examination. On colonoscopy, mucosal ulcerations of the colonic wall were seen in 39% (9/23) of cats. Histopathologically, all cats but 1 (diagnosed simultaneously with colonic small cell lymphoma) had lymphoplasmacytic colitis, and when small intestinal biopsies were performed, concurrent lymphoplasmacytic enteritis or small cell lymphoma of the small intestine. CONCLUSIONS AND CLINICAL IMPORTANCE: Lymphoplasmacytic colitis is seen commonly in cats with short colon, suggesting a potential link between these entities.

Mitotic activity: A systematic literature review of the assessment methodology and prognostic value in feline tumors.

Increased proliferation is a driver of tumorigenesis, and quantification of mitotic activity is a standard task for prognostication. This systematic review is an analysis of all available references on mitotic activity in feline tumors to provide an overview of the assessment methods and prognostic value. A systematic literature search in PubMed and Scopus and a nonsystematic search in Google Scholar were conducted. All articles on feline tumors that correlated mitotic activity with patient outcome were identified. Data analysis revealed that of the 42 eligible articles, mitotic count (MC, mitotic figures/tumor area) was evaluated in 39 studies, and mitotic index (MI, mitotic figures/tumor cells) in 3 studies. The risk of bias was considered high for most studies (26/42, 62%) based on small study populations, insufficient details of the MC/MI methods, and lack of statistical measures for diagnostic accuracy or effect on outcome. The MC/MI methods varied between studies. A significant association of MC with survival was determined in 20 of 28 (71%) studies (10 studies evaluated other outcome metrics or provided individual patient data), while 1 study found an inverse effect. Three tumor types had at least 4 studies, and a prognostic association with survival was found in 5 of 6 studies on mast cell tumors, 5 of 5 on mammary tumors, and 3 of 4 on soft-tissue sarcomas. MI was shown to correlate with survival for mammary tumors by 2 research groups; however, comparisons to MC were not conducted. Further studies with standardized mitotic activity methods and appropriate statistical analysis for discriminant ability of patient outcome are needed to infer the prognostic value of MC and MI.

Mitotic activity: A systematic literature review of the assessment methodology and prognostic value in canine tumors.

One of the most relevant prognostic indices for tumors is cellular proliferation, which is most commonly measured by the mitotic activity in routine tumor sections. The goal of this systematic review was to analyze the methods and prognostic relevance of histologically measuring mitotic activity that have been reported for canine tumors in the literature. A total of 137 articles that correlated the mitotic activity in canine tumors with patient outcome were identified through a systematic (PubMed and Scopus) and nonsystematic (Google Scholar) literature search and eligibility screening process. Mitotic activity methods encompassed the mitotic count (MC, number of mitotic figures per tumor area) in 126 studies, presumably the MC (method not specified) in 6 studies, and the mitotic index (MI, number of mitotic figures per number of tumor cells) in 5 studies. A particularly high risk of bias was identified based on the available details of the MC methods and statistical analyses, which often did not quantify the prognostic discriminative ability of the MC and only reported P values. A significant association of the MC with survival was found in 72 of 109 (66%) studies. However, survival was evaluated by at least 3 studies in only 7 tumor types/groups, of which a prognostic relevance is apparent for mast cell tumors of the skin, cutaneous melanoma, and soft tissue tumor of the skin and subcutis. None of the studies using the MI found a prognostic relevance. This review highlights the need for more studies with standardized methods and appropriate analysis of the discriminative ability to prove the prognostic value of the MC and MI in various tumor types. Future studies are needed to evaluate the influence of the performance of individual pathologists on the appropriateness of prognostic thresholds and investigate methods to improve interobserver reproducibility.

Domain generalization across tumor types, laboratories, and species - Insights from the 2022 edition of the Mitosis Domain Generalization Challenge.

Recognition of mitotic figures in histologic tumor specimens is highly relevant to patient outcome assessment. This task is challenging for algorithms and human experts alike, with deterioration of algorithmic performance under shifts in image representations. Considerable covariate shifts occur when assessment is performed on different tumor types, images are acquired using different digitization devices, or specimens are produced in different laboratories. This observation motivated the inception of the 2022 challenge on MItosis Domain Generalization (MIDOG 2022). The challenge provided annotated histologic tumor images from six different domains and evaluated the algorithmic approaches for mitotic figure detection provided by nine challenge participants on ten independent domains. Ground truth for mitotic figure detection was established in two ways: a three-expert majority vote and an independent, immunohistochemistry-assisted set of labels. This work represents an overview of the challenge tasks, the algorithmic strategies employed by the participants, and potential factors contributing to their success. With an F1 score of 0.764 for the top-performing team, we summarize that domain generalization across various tumor domains is possible with today's deep learning-based recognition pipelines. However, we also found that domain characteristics not present in the training set (feline as new species, spindle cell shape as new morphology and a new scanner) led to small but significant decreases in performance. When assessed against the immunohistochemistry-assisted reference standard, all methods resulted in reduced recall scores, with only minor changes in the order of participants in the ranking.

Primary and secondary leptomeningeal gliomatosis in dogs.

Leptomeningeal gliomatosis (LG) is characterized by extensive dissemination of neoplastic glial cells in the subarachnoid space either without an intraparenchymal glioma (primary LG or PLG) or secondary to an intraparenchymal glioma (secondary LG or SLG). Given the low frequency of LG in human and veterinary medicine, specific diagnostic criteria are lacking. Here, we describe 14 cases of canine LG that were retrospectively identified from 6 academic institutions. The mean age of affected dogs was 7.3 years and over 90% of patients were brachycephalic. Clinical signs were variable and progressive. Relevant magnetic resonance image findings in 7/14 dogs included meningeal enhancement of affected areas and/or intraparenchymal masses. All affected dogs were euthanized because of the poor prognosis. Gross changes were reported in 12/14 cases and consisted mainly of gelatinous leptomeningeal thickening in the brain (6/12 cases) or spinal cord (2/12 cases) and 1 or multiple, gelatinous, gray to red intraparenchymal masses in the brain (6/12 cases). Histologically, all leptomeningeal neoplasms and intraparenchymal gliomas were morphologically consistent with oligodendrogliomas. Widespread nuclear immunolabeling for OLIG2 was observed in all neoplasms. The absence of an intraparenchymal glioma was consistent with PLG in 3 cases. The remaining 11 cases were diagnosed as SLG.

A comprehensive multi-domain dataset for mitotic figure detection.

The prognostic value of mitotic figures in tumor tissue is well-established for many tumor types and automating this task is of high research interest. However, especially deep learning-based methods face performance deterioration in the presence of domain shifts, which may arise from different tumor types, slide preparation and digitization devices. We introduce the MIDOG++ dataset, an extension of the MIDOG 2021 and 2022 challenge datasets. We provide region of interest images from 503 histological specimens of seven different tumor types with variable morphology with in total labels for 11,937 mitotic figures: breast carcinoma, lung carcinoma, lymphosarcoma, neuroendocrine tumor, cutaneous mast cell tumor, cutaneous melanoma, and (sub)cutaneous soft tissue sarcoma. The specimens were processed in several laboratories utilizing diverse scanners. We evaluated the extent of the domain shift by using state-of-the-art approaches, observing notable differences in single-domain training. In a leave-one-domain-out setting, generalizability improved considerably. This mitotic figure dataset is the first that incorporates a wide domain shift based on different tumor types, laboratories, whole slide image scanners, and species.

Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images.

Microscopic evaluation of hematoxylin and eosin-stained slides is still the diagnostic gold standard for a variety of diseases, including neoplasms. Nevertheless, intra- and interrater variability are well documented among pathologists. So far, computer assistance via automated image analysis has shown potential to support pathologists in improving accuracy and reproducibility of quantitative tasks. In this proof of principle study, we describe a machine-learning-based algorithm for the automated diagnosis of 7 of the most common canine skin tumors: trichoblastoma, squamous cell carcinoma, peripheral nerve sheath tumor, melanoma, histiocytoma, mast cell tumor, and plasmacytoma. We selected, digitized, and annotated 350 hematoxylin and eosin-stained slides (50 per tumor type) to create a database divided into training, n = 245 whole-slide images (WSIs), validation (n = 35 WSIs), and test sets (n = 70 WSIs). Full annotations included the 7 tumor classes and 6 normal skin structures. The data set was used to train a convolutional neural network (CNN) for the automatic segmentation of tumor and nontumor classes. Subsequently, the detected tumor regions were classified patch-wise into 1 of the 7 tumor classes. A majority of patches-approach led to a tumor classification accuracy of the network on the slide-level of 95% (133/140 WSIs), with a patch-level precision of 85%. The same 140 WSIs were provided to 6 experienced pathologists for diagnosis, who achieved a similar slide-level accuracy of 98% (137/140 correct majority votes). Our results highlight the feasibility of artificial intelligence-based methods as a support tool in diagnostic oncologic pathology with future applications in other species and tumor types.

Fatal exposure to quaternary ammonium disinfectant in 2 dogs.

OBJECTIVE: To describe the clinical course and necropsy findings of 2 dogs after exposure to quaternary ammonium disinfectants. CASE SERIES SUMMARY: Two dogs were treated after accidental exposure to quaternary ammonium disinfectants in kennel settings. Both dogs developed ulcerative upper gastrointestinal lesions, severe pulmonary disease, and skin lesions. In the second case, the skin lesions were severe and became necrotizing. Both patients were ultimately euthanized due to severity of illness and lack of response to therapy. NEW OR UNIQUE INFORMATION PROVIDED: Quaternary ammonium compounds are commonly used as disinfectants in veterinary hospitals and boarding facilities. This is the first report detailing presentation, clinical picture, case management, and necropsy findings in dogs exposed to these chemicals. Awareness of the severity of these poisonings and the potential for fatal outcome is imperative.

CT features of rounded atelectasis in chronic inflammatory pleural effusions in cats and dogs.

Rounded atelectasis is well described in human medicine as focal lung deformation and collapse secondary to inflammatory pleural effusions and pleuritis. Specific CT features (round to ovoid soft tissue pulmonary attenuations, creation of an acute angle with the adjoining visceral pleura, and the presence of perinodular comet tail signs) support the diagnosis of rounded atelectasis in humans so that further diagnostic workup is not necessary in defining the nodules. In this retrospective case series, we described the CT characteristics of rounded atelectasis in eight cats and three dogs diagnosed with restrictive pleuritis secondary to either a chylothorax or pyothorax. Thirty-six soft tissue attenuating pulmonary nodular lesions were identified on CT. Comet tail signs, consisting of bundles of bronchi and vessels coalescing into the pulmonary nodules, were associated with 92% of the nodules (33/36), and 92% of the nodules abutted and created an acute angle with the pleura (33/36). Other prevalent features included location in gravity-dependent regions of the lung lobes (33/36, 92%), blurred hilar margins with sharper pleural margins of the nodules (33/36, 92%), presence of air bronchograms (30/36, 83%), homogeneous contrast-enhancement (23/36, 64%), and volume loss of the affected lung lobe (22/36, 61%). Pulmonary malignant neoplasms were not found cytologically (6/11 patients) or histologically (5/11 patients). To avoid a misdiagnosis of neoplasia, veterinary radiologists should be aware of the CT features of rounded atelectasis and consider it as a differential for pulmonary nodular lesions in patients with concurrent inflammatory pleural effusion and pleuritis.

Mitosis domain generalization in histopathology images - The MIDOG challenge.

The density of mitotic figures (MF) within tumor tissue is known to be highly correlated with tumor proliferation and thus is an important marker in tumor grading. Recognition of MF by pathologists is subject to a strong inter-rater bias, limiting its prognostic value. State-of-the-art deep learning methods can support experts but have been observed to strongly deteriorate when applied in a different clinical environment. The variability caused by using different whole slide scanners has been identified as one decisive component in the underlying domain shift. The goal of the MICCAI MIDOG 2021 challenge was the creation of scanner-agnostic MF detection algorithms. The challenge used a training set of 200 cases, split across four scanning systems. As test set, an additional 100 cases split across four scanning systems, including two previously unseen scanners, were provided. In this paper, we evaluate and compare the approaches that were submitted to the challenge and identify methodological factors contributing to better performance. The winning algorithm yielded an F1 score of 0.748 (CI95: 0.704-0.781), exceeding the performance of six experts on the same task.

Doublecortin immunolabeling in canine gliomas with distinct degrees of tumor infiltration.

Increased doublecortin (DCX) immunolabeling at the tumor margins has been associated with tumor infiltration in human glioma and canine anaplastic meningioma. No association between DCX immunolabeling and glioma infiltration has been reported in dogs, to our knowledge. Here we compare the DCX immunolabeling in 14 diffusely infiltrating gliomas (gliomatosis cerebri) and 14 nodular gliomas with distinct degrees of tumor infiltration. Cytoplasmic DCX immunolabeling was classified according to intensity (weak, moderate, strong), distribution (1 = <30% immunolabeling, 2 = 30-70% immunolabeling, 3 = >70% immunolabeling), and location within the neoplasm (random or at tumor margins). Immunolabeling was detected in 6 of 14 (43%) diffusely infiltrating gliomas and 8 of 14 (57%) nodular gliomas. Diffusely infiltrating gliomas had moderate and random immunolabeling, with distribution scores of 1 (4 cases) or 2 (2 cases). Nodular gliomas had strong (6 cases) or moderate (2 cases) immunolabeling, with distribution scores of 1 (3 cases), 2 (3 cases), and 3 (2 cases), and random (6 cases) and/or marginal (3 cases) immunolabeling. Increased DCX immunolabeling within neoplastic cells palisading around necrosis occurred in 4 nodular gliomas. DCX immunolabeling was not increased at the margins of diffusely infiltrating gliomas, indicating that DCX should not be used as an immunomarker for glioma infiltration in dogs.

Atypical Mitotic Figures Are Prognostically Meaningful for Canine Cutaneous Mast Cell Tumors.

Cell division through mitosis (microscopically visible as mitotic figures, MFs) is a highly regulated process. However, neoplastic cells may exhibit errors in chromosome segregation (microscopically visible as atypical mitotic figures, AMFs) resulting in aberrant chromosome structures. AMFs have been shown to be of prognostic relevance for some neoplasms in humans but not in animals. In this study, the prognostic relevance of AMFs was evaluated for canine cutaneous mast cell tumors (ccMCT). Histological examination was conducted by one pathologist in whole slide images of 96 cases of ccMCT with a known survival time. Tumor-related death occurred in 11/18 high-grade and 2/78 low-grade cases (2011 two-tier system). The area under the curve (AUC) was 0.859 for the AMF count and 0.880 for the AMF to MF ratio with regard to tumor-related mortality. In comparison, the AUC for the mitotic count was 0.885. Based on our data, a prognostically meaningful threshold of ≥3 per 2.37 mm2 for the AMF count (sensitivity: 76.9%, specificity: 98.8%) and >7.5% for the AMF:MF ratio (sensitivity: 76.9%, specificity: 100%) is suggested. While the mitotic count of ≥ 6 resulted in six false positive cases, these could be eliminated when combined with the AMF to MF ratio. In conclusion, the results of this study suggests that AMF enumeration is a prognostically valuable test, particularly due to its high specificity with regard to tumor-related mortality. Additional validation and reproducibility studies are needed to further evaluate AMFs as a prognostic criterion for ccMCT and other tumor types.

Radiographic features of subungual keratoacanthomas in dogs.

Subungual keratoacanthoma (SK) is a digital neoplasm that has rarely been reported in dogs and carries an excellent prognosis following surgical removal. Radiographic features of canine SK have only been briefly discussed in two prior case reports. Both articles described extensive distal phalangeal osteolysis, a feature more commonly associated with malignant digital neoplasms (e.g., subungual squamous cell carcinoma (SCC) or melanoma). This retrospective case series aimed to further characterize radiographic findings of histologically confirmed canine SK. Seven dogs met the inclusion criteria, with a total of seven affected digits. All seven digits (100%) had osteolysis of the distal phalanx's ungual process and crest, as well as regional soft tissue swelling. Osteolysis of the ungual process was severe in all cases, with complete destruction in six of seven digits (86%). Partial ungual crest geographic and expansile osteolysis was noted in four of seven digits (57%), while two digits (28%) had complete ungual crest destruction. Seven of seven digits (100%) had a radiographically thickened claw, and two of seven digits (28%) had associated lysis of the distal aspect of the middle phalanx. Based on these findings, an osteolytic subungual mass should not be considered pathognomonic for malignant neoplasia. Observing the imaging features previously described should prompt veterinarians to consider SK as a differential diagnosis.

Computer-assisted mitotic count using a deep learning-based algorithm improves interobserver reproducibility and accuracy.

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.

Chaphamaparvovirus antigen and nucleic acids are not detected in kidney tissues from cats with chronic renal disease or immunocompromised cats.

Chronic kidney disease (CKD) is a common cause of morbidity and mortality in domestic cats, but the cause is still largely elusive. While some viruses have been associated with this disease, none have been definitively implicated as causative. Recently, Rodent chaphamaparvovirus 1 was recognized as the cause of murine inclusion body nephropathy, a disease reported for over 40 years in laboratory mice. A novel virus belonging to the same genus, Carnivore chaphamaparvovirus 2, was recently identified in the feces of cats with diarrhea. The goal of this study was to investigate the possible role of chaphamaparvoviruses including members of Rodent chaphamaparvovirus 1 and Carnivore chaphamaparvovirus 2 in the development of feline CKD. The presence of these viruses was retrospectively investigated in formalin-fixed paraffin-embedded feline kidney samples using polymerase chain reaction, in situ hybridization, and immunohistochemistry. Cats were divided into 3 groups: normal (N = 24), CKD (N = 26), and immunocompromised (N = 25). None of the kidney tissues from any of the 75 cats revealed the presence of chaphamaparvovirus DNA, RNA, or antigen. We conclude that viruses belonging to the chaphamaparvovirus genus are unlikely to contribute to the occurrence of feline CKD.