Literature DB >> 31808382

Computerized Calculation of Mitotic Count Distribution in Canine Cutaneous Mast Cell Tumor Sections: Mitotic Count Is Area Dependent.

Christof A Bertram1, Marc Aubreville2, Corinne Gurtner1,3, Alexander Bartel4, Sarah M Corner5, Martina Dettwiler3, Olivia Kershaw1, Erica L Noland5,6, Anja Schmidt7, Dodd G Sledge5, Rebecca C Smedley5, Tuddow Thaiwong5, Matti Kiupel5,6, Andreas Maier2, Robert Klopfleisch1.   

Abstract

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.

Entities:  

Keywords:  area selection; high-power field; mitotic activity; mitotic figure distribution; tumor grading; tumor periphery

Mesh:

Year:  2019        PMID: 31808382     DOI: 10.1177/0300985819890686

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


  8 in total

1.  A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice.

Authors:  Navid Mohammad Mirzaei; Zuzana Tatarova; Wenrui Hao; Navid Changizi; Alireza Asadpoure; Ioannis K Zervantonakis; Yu Hu; Young Hwan Chang; Leili Shahriyari
Journal:  J Pers Med       Date:  2022-05-17

2.  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

3.  Canine Vaginal Cytology: A Revised Definition of Exfoliated Vaginal Cells.

Authors:  Felix Reckers; Robert Klopfleisch; Vitaly Belik; Sebastian Arlt
Journal:  Front Vet Sci       Date:  2022-03-24

Review 4.  Diagnosis, Prognosis and Treatment of Canine Cutaneous and Subcutaneous Mast Cell Tumors.

Authors:  Andrigo Barboza de Nardi; Rodrigo Dos Santos Horta; Carlos Eduardo Fonseca-Alves; Felipe Noleto de Paiva; Laís Calazans Menescal Linhares; Bruna Fernanda Firmo; Felipe Augusto Ruiz Sueiro; Krishna Duro de Oliveira; Silvia Vanessa Lourenço; Ricardo De Francisco Strefezzi; Carlos Henrique Maciel Brunner; Marcelo Monte Mor Rangel; Paulo Cesar Jark; Jorge Luiz Costa Castro; Rodrigo Ubukata; Karen Batschinski; Renata Afonso Sobral; Natália Oyafuso da Cruz; Adriana Tomoko Nishiya; Simone Crestoni Fernandes; Simone Carvalho Dos Santos Cunha; Daniel Guimarães Gerardi; Guilherme Sellera Godoy Challoub; Luiz Roberto Biondi; Renee Laufer-Amorim; Paulo Ricardo de Oliveira Paes; Gleidice Eunice Lavalle; Rafael Ricardo Huppes; Fabrizio Grandi; Carmen Helena de Carvalho Vasconcellos; Denner Santos Dos Anjos; Ângela Cristina Malheiros Luzo; Julia Maria Matera; Miluse Vozdova; Maria Lucia Zaidan Dagli
Journal:  Cells       Date:  2022-02-10       Impact factor: 6.600

5.  Evaluation of Tumor Grade and Proliferation Indices before and after Short-Course Anti-Inflammatory Prednisone Therapy in Canine Cutaneous Mast Cell Tumors: A Pilot Study.

Authors:  Shawna Klahn; Nikolaos Dervisis; Kevin Lahmers; Marian Benitez
Journal:  Vet Sci       Date:  2022-06-07

6.  Flow Cytometric Assessment of Ki-67 Expression in Lymphocytes From Physiologic Lymph Nodes, Lymphoma Cell Populations and Remnant Normal Cell Populations From Lymphomatous Lymph Nodes.

Authors:  Barbara C Rütgen; Daniel Baumgartner; Andrea Fuchs-Baumgartinger; Antonella Rigillo; Ondřej Škor; Sabine E Hammer; Armin Saalmüller; Ilse Schwendenwein
Journal:  Front Vet Sci       Date:  2021-06-29

7.  A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research.

Authors:  Marc Aubreville; Christof A Bertram; Taryn A Donovan; Christian Marzahl; Andreas Maier; Robert Klopfleisch
Journal:  Sci Data       Date:  2020-11-27       Impact factor: 6.444

8.  Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region.

Authors:  Marc Aubreville; Christof A Bertram; Christian Marzahl; Corinne Gurtner; Martina Dettwiler; Anja Schmidt; Florian Bartenschlager; Sophie Merz; Marco Fragoso; Olivia Kershaw; Robert Klopfleisch; Andreas Maier
Journal:  Sci Rep       Date:  2020-10-05       Impact factor: 4.379

  8 in total

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