Dataset Information

A retrospective study of salivary gland diseases in 179 dogs (2010-2018).

ABSTRACT: Salivary gland diseases are well characterized in human medicine but are uncommonly reported in dogs. Herein we describe the clinical and pathologic features of 179 canine salivary gland biopsy submissions to the Athens Veterinary Diagnostic Laboratory from 2010 to 2018. The mean age of affected dogs was 8.5 y; no sex or breed predisposition was evident. The main reason for sample submission was regional swelling (107 cases; 59.7%). Extraoral (major) salivary glands were affected in 125 cases (69.8%), and oral (minor) salivary glands were affected in 43 cases (24% of cases). The location of the lesion (extraoral or oral) was not specified in 11 cases (6.1%). The diagnoses included nonspecific sialoadenitis (89 cases; 49.7%), normal salivary gland (42 cases; 23.4%), neoplasia (36 cases; 20.1%), salivary gland lipomatosis (7 cases; 3.9%), necrotizing sialometaplasia (4 cases; 2.2%), and traumatic hemorrhage (1 case; 0.5%). Most cases of sialoadenitis (63 cases), neoplasia (23 cases), and lipomatosis (5 cases), as well as all cases of necrotizing sialometaplasia and the only case of traumatic hemorrhage, affected extraoral glands. Most neoplasms (32 cases, 88.8% of the tumors) were epithelial and malignant, followed by round cell tumors (2 cases; 5.5%), a carcinosarcoma (1 case; 2.7%), and a tumor of undetermined histogenesis (1 case; 2.7%).

SUBMITTER: Lieske DE

PROVIDER: S-EPMC7438648 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:We analyzed the diagnostic performance of prostate-specific membrane antigen (PSMA) PET/CT and the dosimetry, efficacy, and safety of 177Lu-PSMA-617 radioligand therapy (RLT) in salivary gland malignancies (SGMs). Methods: We identified 28 SGM patients with PSMA PET/CT from our database. CT and PSMA PET/CT images were evaluated separately by 3 masked readers in joint reading sessions. Pathologic findings were grouped into 6 TNM regions, and lesion-based disease extent was classified as no disease (n = 1, 4%), unifocal (n = 2, 7%), oligometastatic (n = 9, 32%), multifocal (n = 3, 11%), or disseminated (n = 13, 47%). For each region, the SUVmax of the lesion with the highest uptake was measured and the visual PSMA expression score was evaluated on a per-patient basis using PROMISE criteria. The association between PSMA expression and clinical and histopathologic markers was tested using the Student t test. Five patients underwent PSMA RLT with intratherapeutic dosimetry. Response was assessed using RECIST 1.1, and adverse events were graded according to version 5.0 of the Common Terminology Criteria for Adverse Events. Results: Compared with CT, PSMA PET/CT demonstrated additional metastatic lesions in 11 of 28 (39%) patients, leading to upstaging of TNM and lesion-based disease extent in 3 (11%) and 6 (21%) patients, respectively. PSMA PET/CT detected CT-occult local tumor, regional lymph nodes, nonregional lymph nodes, and bone metastases in 1 (4%), 4 (14%), 2 (7%), and 4 (14%) patients, respectively; no additional lesions were detected in the other predefined regions. PSMA expression level was higher than liver in 6 patients (25%). A significantly higher SUVmax was observed in male than female patients (15.8 vs. 8.5, P = 0.007) and in bone than lung lesions (14.2 vs. 6.4, P = 0.006). PSMA RLT was discontinued after 1 cycle in 3 of 5 patients because of insufficient tumor doses. No adverse events of grade 4 or higher occurred. Conclusion: In SGMs, PSMA PET/CT demonstrated a superior detection rate and led to upstaging in about one third of patients when compared with CT. The male sex and the presence of bone metastases were associated with significantly higher PSMA expression. PSMA RLT was well tolerated, but most patients did not have more than 1 cycle because of insufficient tumor doses.

Dataset Information

A retrospective study of salivary gland diseases in 179 dogs (2010-2018).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets