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1.
Vet Pathol ; 61(1): 7-19, 2024 01.
Article in English | MEDLINE | ID: mdl-37306003

ABSTRACT

Canine thyroid carcinomas are relatively common malignant endocrine neoplasms in dogs derived from either thyroid follicular cells (forming follicular thyroid carcinomas) or medullary cells (parafollicular, C-cells; forming medullary thyroid carcinomas). Older and recent clinical studies often fail to discriminate between compact cellular (solid) follicular thyroid carcinomas and medullary thyroid carcinomas, which may skew conclusions. The compact subtype of follicular thyroid carcinomas appears to be the least differentiated subtype of follicular thyroid carcinomas and needs to be differentiated from medullary thyroid carcinomas. This review includes information on the signalment, presentation, etiopathogenesis, classification, histologic and immunohistochemical diagnosis, clinical management, and biochemical and genetic derangements of canine follicular and medullary carcinomas, and their correlates with human medicine.


Subject(s)
Adenocarcinoma, Follicular , Carcinoma, Medullary , Carcinoma, Neuroendocrine , Dog Diseases , Thyroid Neoplasms , Humans , Dogs , Animals , Thyroid Neoplasms/diagnosis , Thyroid Neoplasms/veterinary , Adenocarcinoma, Follicular/diagnosis , Adenocarcinoma, Follicular/veterinary , Carcinoma, Neuroendocrine/diagnosis , Carcinoma, Neuroendocrine/veterinary , Carcinoma, Medullary/pathology , Carcinoma, Medullary/veterinary , Dog Diseases/diagnosis
2.
Toxicol Pathol ; 49(6): 1164-1173, 2021 08.
Article in English | MEDLINE | ID: mdl-34060353

ABSTRACT

The approach undertaken to deliver a Good Laboratory Practice (GLP) validation of whole slide images (WSIs) and the associated workflow for the digital primary evaluation and peer review of a GLP-compliant rodent inhalation toxicity study is described. The contract research organization (CRO) undertook validation of the slide scanner, scanner software, and associated database software. This provided a GLP validated environment within the database software for the primary histopathologic evaluation using WSI and viewed with the database software web viewer. The CRO also validated a cloud-based digital pathology platform that supported the upload and transfer of WSI and metadata to a cache within the sponsor's local area network. The sponsor undertook a separate GLP validation of the same cloud-based digital pathology platform to cover the download and review of the WSI. The establishment of a fit-for-purpose GLP-compliant workflow for WSI and successful deployment for the digital primary evaluation and peer review of a large GLP toxicology study enabled flexibility in accelerated global working and potential future reuse of digitized data for advanced artificial intelligence and machine learning image analysis.


Subject(s)
Artificial Intelligence , Rodentia , Animals , Image Processing, Computer-Assisted , Peer Review , Software
3.
Toxicol Pathol ; 44(6): 825-34, 2016 08.
Article in English | MEDLINE | ID: mdl-27343178

ABSTRACT

Historically, pathologists perform manual evaluation of H&E- or immunohistochemically-stained slides, which can be subjective, inconsistent, and, at best, semiquantitative. As the complexity of staining and demand for increased precision of manual evaluation increase, the pathologist's assessment will include automated analyses (i.e., "digital pathology") to increase the accuracy, efficiency, and speed of diagnosis and hypothesis testing and as an important biomedical research and diagnostic tool. This commentary introduces the many roles for pathologists in designing and conducting high-throughput digital image analysis. Pathology review is central to the entire course of a digital pathology study, including experimental design, sample quality verification, specimen annotation, analytical algorithm development, and report preparation. The pathologist performs these roles by reviewing work undertaken by technicians and scientists with training and expertise in image analysis instruments and software. These roles require regular, face-to-face interactions between team members and the lead pathologist. Traditional pathology training is suitable preparation for entry-level participation on image analysis teams. The future of pathology is very exciting, with the expanding utilization of digital image analysis set to expand pathology roles in research and drug development with increasing and new career opportunities for pathologists.


Subject(s)
Image Interpretation, Computer-Assisted/methods , Image Interpretation, Computer-Assisted/standards , Pathologists , Pathology, Clinical/methods , Pathology, Clinical/standards , Humans
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