Literature DB >> 33769136

Review of Histological Grading Systems in Veterinary Medicine.

Giancarlo Avallone1, Roberta Rasotto2, James K Chambers3, Andrew D Miller4, Erica Behling-Kelly5, Paola Monti6, Davide Berlato7, Paola Valenti8, Paola Roccabianca9.   

Abstract

Tumor grading is a method to quantify the putative clinical aggressiveness of a neoplasm based on specific histological features. A good grading system should be simple, easy to use, reproducible, and accurately segregate tumors into those with low versus high risk. The aim of this review is to summarize the histological and, when available, cytological grading systems applied in veterinary pathology, providing information regarding their prognostic impact, reproducibility, usefulness, and shortcomings. Most of the grading schemes used in veterinary medicine are developed for common tumor entities. Grading systems exist for soft tissue sarcoma, osteosarcoma, multilobular tumor of bone, mast cell tumor, lymphoma, mammary carcinoma, pulmonary carcinoma, urothelial carcinoma, renal cell carcinoma, prostatic carcinoma, and central nervous system tumors. The prognostic relevance of many grading schemes has been demonstrated, but for some tumor types the usefulness of grading remains controversial. Furthermore, validation studies are available only for a minority of the grading systems. Contrasting data on the prognostic power of some grading systems, lack of detailed instructions in the materials and methods in some studies, and lack of data on reproducibility and validation studies are discussed for the relevant grading systems. Awareness of the limitations of grading is necessary for pathologists and oncologists to use these systems appropriately and to drive initiatives for their improvement.

Entities:  

Keywords:  carcinoma; cats; dogs; grading; histopathology; lymphoma; mast cell tumor; prognosis; review; sarcoma; standardization; tumor

Year:  2021        PMID: 33769136     DOI: 10.1177/0300985821999831

Source DB:  PubMed          Journal:  Vet Pathol        ISSN: 0300-9858            Impact factor:   2.221


  8 in total

1.  Deep learning for necrosis detection using canine perivascular wall tumour whole slide images.

Authors:  Taranpreet Rai; Ambra Morisi; Barbara Bacci; Nicholas J Bacon; Michael J Dark; Tawfik Aboellail; Spencer Angus Thomas; Miroslaw Bober; Roberto La Ragione; Kevin Wells
Journal:  Sci Rep       Date:  2022-06-23       Impact factor: 4.996

2.  Cutaneous spindle cell tumors with features of peripheral nerve sheath tumors and concurrent cardiac involvement: neurofibromatosis type 1-like presentation in a Labrador Retriever dog.

Authors:  Vittoria Castiglioni; Carla Caielli; Giambattista Guenzi; Federico Sacchini
Journal:  J Vet Diagn Invest       Date:  2022-03-15       Impact factor: 1.569

Review 3.  Grading Systems for Canine Urothelial Carcinoma of the Bladder: A Comparative Overview.

Authors:  Eleonora Brambilla; Veronica M Govoni; Alexandre Matheus Baesso Cavalca; Renée Laufer-Amorim; Carlos Eduardo Fonseca-Alves; Valeria Grieco
Journal:  Animals (Basel)       Date:  2022-06-04       Impact factor: 3.231

4.  Performance of lymph node cytopathology in diagnosis and characterization of lymphoma in dogs.

Authors:  Valeria Martini; Giuseppe Marano; Luca Aresu; Ugo Bonfanti; Patrizia Boracchi; Mario Caniatti; Francesco Cian; Matteo Gambini; Laura Marconato; Carlo Masserdotti; Arturo Nicoletti; Fulvio Riondato; Paola Roccabianca; Damiano Stefanello; Erik Teske; Stefano Comazzi
Journal:  J Vet Intern Med       Date:  2021-11-27       Impact factor: 3.333

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

Authors:  Christof A Bertram; Marc Aubreville; Taryn A Donovan; Alexander Bartel; Frauke Wilm; Christian Marzahl; Charles-Antoine Assenmacher; Kathrin Becker; Mark Bennett; Sarah Corner; Brieuc Cossic; Daniela Denk; Martina Dettwiler; Beatriz Garcia Gonzalez; Corinne Gurtner; Ann-Kathrin Haverkamp; Annabelle Heier; Annika Lehmbecker; Sophie Merz; Erica L Noland; Stephanie Plog; Anja Schmidt; Franziska Sebastian; Dodd G Sledge; Rebecca C Smedley; Marco Tecilla; Tuddow Thaiwong; Andrea Fuchs-Baumgartinger; Donald J Meuten; Katharina Breininger; Matti Kiupel; Andreas Maier; Robert Klopfleisch
Journal:  Vet Pathol       Date:  2021-12-30       Impact factor: 2.221

6.  P-Glycoprotein Activity at Diagnosis Does Not Predict Therapy Outcome and Survival in Canine B-Cell Lymphoma.

Authors:  Valéria Dékay; Edina Karai; András Füredi; Kornélia Szebényi; Gergely Szakács; Péter Vajdovich
Journal:  Cancers (Basel)       Date:  2022-08-13       Impact factor: 6.575

7.  Pathological Findings in Gastrointestinal Neoplasms and Polyps in 860 Cats and a Pilot Study on miRNA Analyses.

Authors:  Alexandra Kehl; Katrin Törner; Annemarie Jordan; Mareike Lorenz; Ulrike Schwittlick; David Conrad; Katja Steiger; Benjamin Schusser; Heike Aupperle-Lellbach
Journal:  Vet Sci       Date:  2022-09-03

8.  Vet-ICD-O-Canine-1, a System for Coding Canine Neoplasms Based on the Human ICD-O-3.2.

Authors:  Katia Pinello; Valeria Baldassarre; Katja Steiger; Orlando Paciello; Isabel Pires; Renée Laufer-Amorim; Anna Oevermann; João Niza-Ribeiro; Luca Aresu; Brian Rous; Ariana Znaor; Ian A Cree; Franco Guscetti; Chiara Palmieri; Maria Lucia Zaidan Dagli
Journal:  Cancers (Basel)       Date:  2022-03-16       Impact factor: 6.639

  8 in total

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