Christof A. Bertram

Christof A. Bertram
University of Veterinary Medicine, Vienna | vetmed · Institute of Pathology and Forensic Veterinary Medicine

Doctor of Veterinary Medicine

About

171
Publications
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1,284
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Publications

Publications (171)
Preprint
Full-text available
Assessment of the density of mitotic figures (MFs) in histologic tumor sections is an important prognostic marker for many tumor types, including breast cancer. Recently, it has been reported in multiple works that the quantity of MFs with an atypical morphology (atypical MFs, AMFs) might be an independent prognostic criterion for breast cancer. AM...
Preprint
Full-text available
Foundation models (FMs), i.e., models trained on a vast amount of typically unlabeled data, have become popular and available recently for the domain of histopathology. The key idea is to extract semantically rich vectors from any input patch, allowing for the use of simple subsequent classification networks potentially reducing the required amount...
Article
Full-text available
Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics can improve reproducibility, but current manual methods are time-consuming. The aim of this study was to explore the limitations of estima...
Article
Full-text available
The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker, as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. In a computer-aided setting, deep learning algorithms can help to mitigate this, but they require larg...
Preprint
Artificial intelligence (AI)-based decision support systems hold promise for enhancing diagnostic accuracy and efficiency in computational pathology. However, human-AI collaboration can introduce and amplify cognitive biases, such as confirmation bias caused by false confirmation when erroneous human opinions are reinforced by inaccurate AI output....
Article
Full-text available
Mitotic count (MC) is the most common measure to assess tumor proliferation in breast cancer patients and is highly predictive of patient outcomes. It is, however, subject to inter‐ and intraobserver variation and reproducibility challenges that may hamper its clinical utility. In past studies, artificial intelligence (AI)‐supported MC has been sho...
Article
Numerous prognostic factors are currently assessed histologically and immunohistochemically in canine mast cell tumors (MCTs) to evaluate clinical behavior. In addition, polymerase chain reaction (PCR) is often performed to detect internal tandem duplication (ITD) mutations in exon 11 of the c-KIT gene ( c-KIT-11-ITD) to predict the therapeutic res...
Article
Neoplasia is a common disease in guinea pigs ( Cavia porcellus); however, few studies have evaluated the prevalence of neoplasia in all organ systems. We retrospectively analyzed the tumor prevalence in pet guinea pigs and the frequency of metastasis in a multi-institutional study population of 2,474 autopsy cases. Tumors were found in 508 guinea p...
Article
Feline chronic enteropathy is a poorly defined condition of older cats that encompasses chronic enteritis to low-grade intestinal lymphoma. The histological evaluation of lymphocyte numbers and distribution in small intestinal biopsies is crucial for classification and grading. However, conventional histological methods for lymphocyte quantificatio...
Article
Feline eosinophilic sclerosing fibroplasia (FESF) is a proliferative, inflammatory disease of the gastrointestinal tract and other sites, uncommonly diagnosed in the cat. This entity of uncertain etiology typically presents as a progressive mass lesion, mimicking a neoplastic process. In this case series, we present 17 cases of FESF associated with...
Preprint
Full-text available
The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker, as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. In a computer-aided setting, deep learning algorithms can help to mitigate this, but they require larg...
Article
Full-text available
Neoplastic processes of the mandible and their treatment are rarely reported in large animal species. Specifically, giant cell tumor of bone is an uncommon tumor in animals and has been associated in humans with locally invasive behavior and a high recurrence rate. En-bloc resection is the treatment of choice, but depending on the localization of t...
Preprint
Full-text available
The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. Deep learning algorithms can standardize this task, but they require large amounts of annotated data fo...
Article
Full-text available
The integration of deep learning-based tools into diagnostic workflows is increasingly prevalent due to their efficiency and reproducibility in various settings. We investigated the utility of automated nuclear morphometry for assessing nuclear pleomorphism (NP), a criterion of malignancy in the current grading system in canine pulmonary carcinoma...
Article
Synovial myxoma, a rare joint tumor in dogs, has traditionally been considered benign, acknowledging that local invasion into regional tissues including bone may be present. Given the diagnostic challenges in distinguishing synovial myxoma from other joint lesions through clinical features and diagnostic imaging, definitive diagnosis relies on char...
Article
Digitalization of pathology workflows has undergone a rapid evolution and has been widely established in the diagnostic field but remains a challenge in the nonclinical safety context due to lack of regulatory guidance and validation experience for good laboratory practice (GLP) use. One means to demonstrate that digital slides are fit for purpose,...
Article
Full-text available
The ability of human melanoma cells to switch from an epithelial to a mesenchymal phenotype contributes to the metastatic potential of disease. Metalloproteinases (MPs) are crucially involved in this process by promoting the detachment of tumor cells from the primary lesion and their migration to the vasculature. In gray horse melanoma, epithelial–...
Article
Full-text available
One of the most relevant prognostic indices for tumors is cellular proliferation, which is most commonly measured by the mitotic activity in routine tumor sections. The goal of this systematic review was to analyze the methods and prognostic relevance of histologically measuring mitotic activity that have been reported for canine tumors in the lite...
Article
Full-text available
Increased proliferation is a driver of tumorigenesis, and quantification of mitotic activity is a standard task for prognostication. This systematic review is an analysis of all available references on mitotic activity in feline tumors to provide an overview of the assessment methods and prognostic value. A systematic literature search in PubMed an...
Article
Patients with T- and NK-cell neoplasms frequently have somatic STAT5B gain-of-function mutations. The most frequent STAT5B mutation is STAT5BN642H, which is known to drive murine T-cell leukemia although its role in NK-cell malignancies is unclear. Introduction of the STAT5BN642H mutation into human NK-cell lines enhances their potential to induce...
Chapter
The volume-corrected mitotic index (M/V-Index) has demonstrated prognostic value in invasive breast carcinomas. However, despite its prognostic significance, it is not established as the standard method for assessing aggressive biological behaviour, due to the high additional workload associated with determining the epithelial proportion. In this w...
Chapter
Deep multiple instance learning is a popular method for classifying whole slide images, but it remains unclear how robust such models are against scanner-induced domain shifts. In this work, we studied this problem based on the classification of the mutational status of the c-Kit gene from whole slide images of canine mast cell tumors obtained with...
Article
Full-text available
Simple Summary The aim of this study was to evaluate a new microscopic parameter (atypical mitotic figures) in canine cutaneous mast cell tumors regarding the ability to predict patient survival (prognosis). Mast cell tumors are one of the most common skin tumors in dogs. Counting the number of tumor cells undergoing division (mitotic figures) is o...
Article
Full-text available
Histopathological examination of tissue samples is essential for identifying tumor malignancy and the diagnosis of different types of tumor. In the case of lymphoma classification, nuclear size of the neoplastic lymphocytes is one of the key features to differentiate the different subtypes. Based on the combination of artificial intelligence and ad...
Preprint
Full-text available
Recognition of mitotic figures in histologic tumor specimens is highly relevant to patient outcome assessment. This task is challenging for algorithms and human experts alike, with deterioration of algorithmic performance under shifts in image representations. Considerable covariate shifts occur when assessment is performed on different tumor types...
Article
Full-text available
Microscopic evaluation of hematoxylin and eosin-stained slides is still the diagnostic gold standard for a variety of diseases, including neoplasms. Nevertheless, intra- and interrater variability are well documented among pathologists. So far, computer assistance via automated image analysis has shown potential to support pathologists in improving...
Article
Full-text available
The prognostic value of mitotic figures in tumor tissue is well-established for many tumor types and automating this task is of high research interest. However, especially deep learning-based methods face performance deterioration in the presence of domain shifts, which may arise from different tumor types, slide preparation and digitization device...
Chapter
Mitotic activity is key for the assessment of malignancy in many tumors. Moreover, it has been demonstrated that the proportion of abnormal mitosis to normal mitosis is of prognostic significance. Atypical mitotic figures (MF) can be identified morphologically as having segregation abnormalities of the chromatids. In this work, we perform, for the...
Chapter
Computer vision classification tasks rely on the availability of ground truth labels. Especially in medical imaging, these are typically given by experts and can be of differing quality. To reduce the expert bias influence on labels, commonly blinded multi-expert consensus labels are used as ground truth in machine learning. In this work, we approa...
Chapter
The identification of tumor regions on cutaneous tissue sections and the subsequent differentiation into individual tumor subtypes are routine tasks for veterinary pathologists. However, manual tumor delineation can be time-consuming and morphological similarities of tumor types can make the subtyping task difficult. Deep learning-based algorithms...
Chapter
Nucleolar organizer regions (NORs) are parts of the DNA that are involved in RNA transcription. Due to the silver affinity of associated proteins, argyrophilic NORs (AgNORs) can be visualized using silver-based staining. The average number of AgNORs per nucleus has been shown to be a prognostic factor for predicting the outcome of many tumors. Sinc...
Chapter
The density of mitotic figures (MF) within tumor tissue is known to be highly correlated with tumor malignancy and thus is an important marker in tumor grading. Recognition of MF by pathologists is subject to a strong inter-rater bias, limiting its prognostic value. State-of-the-art deep learning methods can support experts but have been observed t...
Chapter
In histopathology, scanner-induced domain shifts are known to impede the performance of trained neural networks when tested on unseen data. Multidomain pre-training or dedicated domain-generalization techniques can help to develop domain-agnostic algorithms. For this, multi-scanner datasets with a high variety of slide scanning systems are highly d...
Preprint
Full-text available
One of the most relevant prognostication tests for tumors is cellular proliferation, which is most commonly measured by the mitotic activity in routine tumor sections. The goal of this systematic review is to scholarly analyze the methods and prognostic relevance of histologically measuring mitotic activity in canine tumors. A total of 137 articles...
Preprint
Full-text available
Increased proliferation is a key driver of tumorigenesis, and quantification of mitotic activity is a standard task for prognostication. The goal of this systematic review is scholarly analysis of all available references on mitotic activity in feline tumors, and to provide an overview of the measuring methods and prognostic value. A systematic lit...
Preprint
Full-text available
In histopathology, scanner-induced domain shifts are known to impede the performance of trained neural networks when tested on unseen data. Multi-domain pre-training or dedicated domain-generalization techniques can help to develop domain-agnostic algorithms. For this, multi-scanner datasets with a high variety of slide scanning systems are highly...
Preprint
Full-text available
Nucleolar organizer regions (NORs) are parts of the DNA that are involved in RNA transcription. Due to the silver affinity of associated proteins, argyrophilic NORs (AgNORs) can be visualized using silver-based staining. The average number of AgNORs per nucleus has been shown to be a prognostic factor for predicting the outcome of many tumors. Sinc...
Preprint
Full-text available
Mitotic activity is key for the assessment of malignancy in many tumors. Moreover, it has been demonstrated that the proportion of abnormal mitosis to normal mitosis is of prognostic significance. Atypical mitotic figures (MF) can be identified morphologically as having segregation abnormalities of the chromatids. In this work, we perform, for the...
Preprint
Full-text available
Computer-aided systems in histopathology are often challenged by various sources of domain shift that impact the performance of these algorithms considerably. We investigated the potential of using self-supervised pre-training to overcome scanner-induced domain shifts for the downstream task of tumor segmentation. For this, we present the Barlow Tr...
Article
Full-text available
Exercise-induced pulmonary hemorrhage (EIPH) is a relevant respiratory disease in sport horses, which can be diagnosed by examination of bronchoalveolar lavage fluid (BALF) cells using the total hemosiderin score (THS). The aim of this study was to evaluate the diagnostic accuracy and reproducibility of annotators and to validate a deep learning-ba...
Preprint
Full-text available
In histology, the presence of collagen in the extra-cellular matrix has both diagnostic and prognostic value for cancer malignancy, and can be highlighted by adding Saffron (S) to a routine Hematoxylin and Eosin (HE) staining. However, Saffron is not usually added because of the additional cost and because pathologists are accustomed to HE, with th...
Article
The density of mitotic figures (MF) within tumor tissue is known to be highly correlated with tumor proliferation and thus is an important marker in tumor grading. Recognition of MF by pathologists is subject to a strong inter-rater bias, limiting its prognostic value. State-of-the-art deep learning methods can support experts but have been observe...
Article
Full-text available
Due to morphological similarities, the differentiation of histologic sections of cutaneous tumors into individual subtypes can be challenging. Recently, deep learning-based approaches have proven their potential for supporting pathologists in this regard. However, many of these supervised algorithms require a large amount of annotated data for robu...
Article
Full-text available
Pulmonary hemorrhage (P-Hem) occurs among multiple species and can have various causes. Cytology of bronchoalveolar lavage fluid (BALF) using a 5-tier scoring system of alveolar macrophages based on their hemosiderin content is considered the most sensitive diagnostic method. We introduce a novel, fully annotated multi-species P-Hem dataset, which...
Article
A free ranging, fledged common buzzard (Buteo buteo) was found with severe feather damage and left periorbital swelling. Clinical examination revealed a 3.0 × 2.5 × 1.5 cm left medial subconjunctival mass. The abnormal tissue extended over most of the left cornea, severely impairing the bird's vision in that eye. Additionally, the left globe was di...
Article
An adult female, entire domestic rat (Rattus norvegicus forma domestica) presented with swollen auricles and incoordination. The rat was diagnosed with bilateral otitis externa. Radiographs of the skull revealed bilateral otitis externa/media. Bacterial culture of a swap from the external ear canals identified large numbers of Pasteurella pneumotro...
Preprint
Full-text available
The density of mitotic figures within tumor tissue is known to be highly correlated with tumor proliferation and thus is an important marker in tumor grading. Recognition of mitotic figures by pathologists is known to be subject to a strong inter-rater bias, which limits the prognostic value. State-of-the-art deep learning methods can support the e...
Technical Report
Full-text available
Digital pathology is a fast-growing field that has seen strong scientific advances in recent years. Especially the accurate diagnosis and prognosis of tumors is a topic of particular interest, as documented by recent challenges on MICCAI, ICPR and elsewhere. In this context, the detection of cells undergoing division (mitotic figures) in histologic...
Poster
Full-text available
Introduction: The mitotic count (MC, number of mitotic figures per unit tumor area) is a method routinely used for prognostication of aggressive tumors. The objective is to summarize the MC methods described in previous prognostic studies. Material and Methods: Relevant peer reviewed literature was identified through an online search. Critical as...
Preprint
Full-text available
Exercise-induced pulmonary hemorrhage (EIPH) is a relevant respiratory disease in sport horses which can be diagnosed by examination of bronchoalveolar lavage fluid (BALF) cells using the total hemosiderin score (THS). The aim of this study was to evaluate the diagnostic accuracy and reproducibility of trained annotators and to validate a deep lear...
Preprint
Full-text available
Due to morphological similarities, the differentiation of histologic sections of cutaneous tumors into individual subtypes can be challenging. Recently, deep learning-based approaches have proven their potential for supporting pathologists in this regard. However, many of these supervised algorithms require a large amount of annotated data for robu...
Article
Full-text available
The density of mitotic figures within tumor tissue is known to be highly correlated with tumor proliferation and thus is an important marker in tumor grading. Recognition of mitotic figures by pathologists is known to be subject to a strong inter-rater bias, which limits the prognostic value. State-of-the-art deep learning methods can support the e...
Article
Full-text available
The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or classifying mitotic figures (MFs). Recent progress in the field of artificial intelligence has allowed...