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Research Group Prof. Klopfleisch

Digital Pathology

Pathologists use light microscopes for the diagnosis of diseases in tissue sections on glass slides since the development of the modern pathology by Rudolf Virchow in 1858. However, the rapid development of information technology during the last three decades is now also reaching this sanctuary of pathology as they have reached almost all aspects of modern life.

 The new technologies of digital pathology allow for the digitization of glass slides into Whole Slide Images (WSI), to visualize them on the screen, analyze them automatically and to exchange this information rapidly via networks. Digital pathology has been integrated in some pathological routine labs already and it is expected to be an integral component of veterinary pathology in the future. In addition, quantification of objects in tissue sections, i.e. mitotic cells or immunohistochemically positive cells, are analyzed more objectively using automated image analysis algorithms.

Our group is currently evaluating and validating the potential of digital pathology in diagnostics, research and education and aims at developing new approaches for the automated image analysis of histological and cytopathologic specimens. Specific foci of our current focus is on the automatic detection of mitotic figures in tumor tissues for a more objective tumor grading, the development automatic tumor detection and differentiation software and the automatic preselection of tissue areas affected by toxicologic effects of newly developed drugs in HE-stained slides.

 ResearchGate-Project:https://www.researchgate.net/project/Digital-Pathology-New-Approaches-to-the-Automated-Image-Analysis-of-Histologic-Slides

 Publications:

  1. Bertram CA, Aubreville M, Gurtner C, Kershaw O, Meier A, …., Kiupel M, Maier A, Klopfleisch R. Computerized Calculation of Mitotic Count Distribution in Canine Cutaneous Mast Cell Tumor Sections: Mitotic Count is Area-Dependent. Vet Pathol, 2020, doi:10.1177/0300985819890686, PMID: 31808382 (https://www.ncbi.nlm.nih.gov/pubmed/31808382)

  2.  Bertram CA, Aubreville M, Marzahl C, Maier A, Klopfleisch R. A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor. Sci Data. 2019 Nov 21;6(1):274. doi: 10.1038/s41597-019-0290-4. PMID: 31754105 (https://www.ncbi.nlm.nih.gov/pubmed/31808382).

  3. Bertram CA, Gurtner C, Dettwiler M, Kershaw O, Dietert K, Pieper L, Pischon H, Gruber AD, Klopfleisch R. Validation of Digital Microscopy Compared With Light Microscopy for the Diagnosis of Canine Cutaneous Tumors. Vet Pathol. 2018, 55(4):490-500. doi: 10.1177/0300985818755254. PMID: 29402206 (https://www.ncbi.nlm.nih.gov/pubmed/29402206).

  4. Bertram CA, Klopfleisch R. The Pathologist 2.0: An Update on Digital Pathology in Veterinary Medicine. Vet Pathol. 2017 Sep;54(5):756-766. doi:10.1177/0300985817709888. PMID: 28578626 (https://www.ncbi.nlm.nih.gov/pubmed/28578626). 

  5. Bertram CA, Firsching T, Klopfleisch R. Virtual Microscopy in Histopathology Training: Changing Student Attitudes in 3 Successive Academic Years. J Vet Med Educ. 2018; 45(2):241-249. doi: 10.3138/jvme.1216-194r1. PMID: 29099317 (https://www.ncbi.nlm.nih.gov/pubmed/29099317).

  6. Aeffner F, Adissu HA, Boyle MC, Klopfleisch R, Newbigging S, Schaudien D, Turner O, Wilson K. Digital Microscopy, Image Analysis, and Virtual Slide Repository. ILAR J. 2018; 59(1):66-79. doi: 10.1093/ilar/ily007. PMID: 30535284 (https://www.ncbi.nlm.nih.gov/pubmed/30535284).

  7. Aubreville M, Bertram CA, Jabari S, Marzahl C, Klopfleisch R, Andreas Maier. Learning New Tricks from Old Dogs -- Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment. (https://arxiv.org/pdf/1911.10873.pdf)

  8. Aubreville M, Bertram CA, Marzahl C, Gurtner C, Dettwiler M, Schmidt A, Bartenschlager F, Merz S, Fragoso M, Kershaw O, Klopfleisch R, Maier A. Field of Interest Prediction for Computer-Aided Mitotic Count, 2019. (https://arxiv.org/pdf/1902.05414.pdf)

  9. Marzahl C, Aubreville M, Bertram CA,…., Klopfleisch R, Maier A. Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides. (https://arxiv.org/pdf/1908.04767.pdf)

  10. Aubreville M,  Bertram CA, Klopfleisch R, Maier A. SlideRunner - A Tool for Massive Cell Annotations in Whole Slide Images. (https://arxiv.org/pdf/1802.02347v1.pdf)

  11. Aubreville M,  Bertram CA, Klopfleisch R, Maier A. Augmented Mitotic Cell Count using Field Of Interest Proposal. https://arxiv.org/pdf/1810.00850.pdf

  12. Aubreville M,  Bertram CA, Klopfleisch R, Maier A. Field Of Interest Proposal for Augmented Mitotic Cell Count: Comparison of two Convolutional Networks. (https://arxiv.org/pdf/1810.09197.pdf)

  13. Aubreville M, Krappmann M, Bertram CA, Klopfleisch R, Maier A. A Guided Spatial Transformer Network for Histology Cell Differentiation. Eurographics Workshop on Visual Computing for Biology and Medicine At: Bremen, Germany, 2017, DOI: 10.2312/vcbm.20171233

  14. Krappmann, M.; Aubreville, M.; Maier, A.; Bertram, C.; Klopfleisch, R. Classification of Mitotic Cells Potentials: beyond the Limits of Small Data Sets. In: Bildverarbeitung für die Medizin 2018,– Andreas Maier (Hrsg.) (1 Aufl.), Vieweg: Springer, S. 245–250, ISBN: 978-3-662-56536-0

Methods in Toxikologic Preclinical Studies and Drug Safety Analysis

In cooperation with international pharmaceutical companies and contract research organization we are currently developing innovative, more efficient methods for the preclinical studies in drug safety and efficacy. A major focus is to increase the sensitivity and reproducibility of the histopathologic analysis using digital approaches and surrogate markers to reduce the number of laboratory animas according to the 3R-principle.

In addition, new approaches to a more efficient micronucleus test (Giemsa, Acridine-Orange) and bone marrow analysis (myeloid-erythroid-ratio) in rats and mice are also developed. QuPath, Sliderunner, and occasionally Visiopharm, are used for annotation of structures in digital histologic slides. The AI-tools embedded in these software solutions or costumized solutions of our cooperating IT-specialist are used for the development of deep learning algorithmen for automatic detection of the structures of interest in the slides. 

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Veterinary Oncology

The molecular basis of carcinogenesis of mainly canine and feline tumors are investigated in several projects. A major focus is on the search for genes and their products with relevance for the development, diagnosis, prognosis and therapy of tumors in dogs and cats, including circulating tumor cells.

References:

  1. Klopfleisch R (ed.), A Short Textbook of Veterinary Oncology / Kurzlehrbuch der Veterinäronkologie, Springer, available from 08/2016

  2. Bertram CA, Aubreville M, Gurtner C, Kershaw O, Meier A, Kiupel M, Maier A, Klopfleisch R. Computerized Calculation of Mitotic Count Distribution in Canine Cutaneous Mast Cell Tumor Sections: Mitotic Count is Area-Dependent. Vet Pathol, 2020

  3.  Aupperle-Lellbach H, Törner K, Staudacher M, Müller E, Steiger K, Klopfleisch R. Characterization of 22 Canine Pancreatic Carcinomas and Review of Literature. J Comp Pathol. 2019 Nov;173:71-82.

  4. Merz SE, Kershaw O, Petrick A, Gruber AD, Klopfleisch R, Breithaupt A. Tumour, but not Age-associated, Increase of Senescence Markers γH2AX and p21 in the Canine Eye. J Comp Pathol. 2019 Nov;173:41-48.

  5. Grassinger JM, Aupperle-Lellbach H, Erhard H, Merz S, Klopfleisch R. Detection of BRAF mutation in canine prostatic diseases. Tierarztl Prax Ausg K Kleintiere Heimtiere. 2019 Oct;47(5):313-320.

  6. Grassinger JM, Merz S, Aupperle-Lellbach H, Erhard H, Klopfleisch R. Correlation of BRAF Variant V595E, Breed, Histological Grade and Cyclooxygenase-2 Expression in Canine Transitional Cell Carcinomas. Vet Sci. 2019 Mar 19;6(1).

  7. Klopfleisch R, Kohn B, Gruber AD. Mechanisms of tumour resistance against chemotherapeutic agents in veterinary oncology. Veterinary Journal, 207:63-72, 2016.

  8. Klopfleisch R. Personalized medicine in veterinary oncology: one to cure just one. Veterinary Journal, 205:128-35, 2015.
  9. Klopfleisch R, von Euler H, Sarli G, Pinho SS, Gärtner F, Gruber AD. Molecular carcinogenesis of canine mammary tumors: news from an old disease. Veterinary Pathology,48:98-116, 2011.
  10. Delcour N.M., Klopfleisch R., Gruber A.D. and Weiss A.T.A. (2013). Canine Cutaneous Histiocytomas are Clonal Lesions as Defined by X-linked Clonality Testing. Journal of Comparative Pathology 149: 192-198. 
Cutaneous Lupus erythematosus and Pemphigus diseases in Dogs, Cats and Horses

Autoimmune diseases are rather rare diesease in animals. However, they are important differential diagnosis in clinical veterinary dermathology and dermatopathology and therefore have to be confirmed or excluded with regularity. For systemic Lupus erythemathosus the serology for detectionof anti-nuclear antibodies (ANA) is often helpful in the diagnosis but ANA detection is often not sensitive und spezific enough for cutaneous Lupus und Pemphigus in animals. For these latter diseases the histopathology of dermal biopsies and detection of antibodies bound to the dermal structures in the histologic section is currently the method of choice. In variety of projects we are currently testing methods to refine the detection of autoantibodies in dermal sections and try to correlate the results more precisely with clinical outcome and therapeutic success to give better recommendations to the clinical colleaques. 

Foreign body reaction and M1 / M2 Macrophage Polarization in vivo

The foreign body reaction during the implantation of biomaterials is a two-sided sword. The reaction is clearly necessary to integration the implant at the implantation site. On the other hand, a strong foreign body reaction leads to scarring and rejection of the implant.

Recent progress in macrophage research describe macrophages as more than pure antigen phagocytosing and presenting and thus pro-inflammatory cells involved in immune reactions. Quite contrary, both, pro-inflammatory M1 macrophages, the diverse regulatory M2 macrophage subtypes and even foreign body giant cells (FBGC) are necessary for the defense against against most noxae but also for repair and regeneration of the damaged tissue. Depending on the purpose and nature of the implanted material, a different macrophage composition is desirable.

Most data and distinguishing markers for the multiple macrophage subgroups are obtained by in vitro models. In our current research we are aiming at the analysis of the macrophage dichotomy in the murine and canine model in vivo. In a first step we are currently testing numerous proposed M1- and M2-marker mainly in formalin-fixed and paraffin-embedded tissue samples of different disease models in an explorative and descriptive approach.

References:

  1. R. Klopfleisch, Macrophage reaction against biomaterials in the mouse model – phenotypes, functions and markers, Acta Biomaterialia, 1;43:3-13, 2016 https://www.ncbi.nlm.nih.gov/pubmed/27395828.
  2. R. Klopfleisch, F. Jung. The pathology of the foreign body reaction against biomaterials, submitted.
  3. Frede A, Neuhaus B, Klopfleisch R, Walker C, Buer J, Müller W, Epple M, Westendorf AM. Colonic gene silencing using siRNA-loaded calcium phosphate/PLGA nanoparticles ameliorates intestinal inflammation in vivo. Journal of Controlled Release, 222:86-96, 2016
  4. Haase T, Klopfleisch R, Krost A, Sauter T, Kratz K, Peter J, Jung F, Lendlein A, Zohlnhöfer D, Rüder C. In vivo biocompatibility study of degradable homo- versus multiblock copolymers and their (micro)structure compared to an established biomaterial. Clin Hemorheol Microcirc. 2020 Jan 4. doi: 10.3233/CH-190748
Aging in Domestic Animals

Ageing is a physiologic process, which is associated with an increases the susceptibility to develop to several disease, including civilization diseases including neoplasia. For instance, it is thought that the ageing of the microenvironment has an major impact on the progression of tumors. The accumulation of senescent cells, which are in permanent arrest of cell proliferation, is thought to make an important contribution to tumor development. In several projects we are currently investigating the occurrence and association of senescent cells in age associated disease, including neoplasia.

References:

  1. Merz SE, Kershaw O, Petrick A, Gruber AD, Klopfleisch R, Breithaupt A. Tumour, but not Age-associated, Increase of Senescence Markers γH2AX and p21 in the Canine Eye. J Comp Pathol. 201;173:41-48. doi: 10.1016/j.jcpa.2019.10.004
  2. Merz SE, Klopfleisch R, Breithaupt A, Gruber AD. Aging and Senescence in Canine Testes. Vet Pathol. 2019;56(5):715-724. doi: 10.1177/0300985819843683