Mitotic activity: A systematic literature review of the assessment methodology and prognostic value in feline tumors.

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 and Scopus and a nonsystematic search in Google Scholar were conducted. All articles on feline tumors that correlated mitotic activity with patient outcome were identified. Data analysis revealed that of the 42 eligible articles, mitotic count (MC, mitotic figures/tumor area) was evaluated in 39 studies, and mitotic index (MI, mitotic figures/tumor cells) in 3 studies. The risk of bias was considered high for most studies (26/42, 62%) based on small study populations, insufficient details of the MC/MI methods, and lack of statistical measures for diagnostic accuracy or effect on outcome. The MC/MI methods varied between studies. A significant association of MC with survival was determined in 20 of 28 (71%) studies (10 studies evaluated other outcome metrics or provided individual patient data), while 1 study found an inverse effect. Three tumor types had at least 4 studies, and a prognostic association with survival was found in 5 of 6 studies on mast cell tumors, 5 of 5 on mammary tumors, and 3 of 4 on soft-tissue sarcomas. MI was shown to correlate with survival for mammary tumors by 2 research groups; however, comparisons to MC were not conducted. Further studies with standardized mitotic activity methods and appropriate statistical analysis for discriminant ability of patient outcome are needed to infer the prognostic value of MC and MI.

Mitotic activity: A systematic literature review of the assessment methodology and prognostic value in canine tumors.

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 literature. A total of 137 articles that correlated the mitotic activity in canine tumors with patient outcome were identified through a systematic (PubMed and Scopus) and nonsystematic (Google Scholar) literature search and eligibility screening process. Mitotic activity methods encompassed the mitotic count (MC, number of mitotic figures per tumor area) in 126 studies, presumably the MC (method not specified) in 6 studies, and the mitotic index (MI, number of mitotic figures per number of tumor cells) in 5 studies. A particularly high risk of bias was identified based on the available details of the MC methods and statistical analyses, which often did not quantify the prognostic discriminative ability of the MC and only reported P values. A significant association of the MC with survival was found in 72 of 109 (66%) studies. However, survival was evaluated by at least 3 studies in only 7 tumor types/groups, of which a prognostic relevance is apparent for mast cell tumors of the skin, cutaneous melanoma, and soft tissue tumor of the skin and subcutis. None of the studies using the MI found a prognostic relevance. This review highlights the need for more studies with standardized methods and appropriate analysis of the discriminative ability to prove the prognostic value of the MC and MI in various tumor types. Future studies are needed to evaluate the influence of the performance of individual pathologists on the appropriateness of prognostic thresholds and investigate methods to improve interobserver reproducibility.

Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images.

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 accuracy and reproducibility of quantitative tasks. In this proof of principle study, we describe a machine-learning-based algorithm for the automated diagnosis of 7 of the most common canine skin tumors: trichoblastoma, squamous cell carcinoma, peripheral nerve sheath tumor, melanoma, histiocytoma, mast cell tumor, and plasmacytoma. We selected, digitized, and annotated 350 hematoxylin and eosin-stained slides (50 per tumor type) to create a database divided into training, n = 245 whole-slide images (WSIs), validation (n = 35 WSIs), and test sets (n = 70 WSIs). Full annotations included the 7 tumor classes and 6 normal skin structures. The data set was used to train a convolutional neural network (CNN) for the automatic segmentation of tumor and nontumor classes. Subsequently, the detected tumor regions were classified patch-wise into 1 of the 7 tumor classes. A majority of patches-approach led to a tumor classification accuracy of the network on the slide-level of 95% (133/140 WSIs), with a patch-level precision of 85%. The same 140 WSIs were provided to 6 experienced pathologists for diagnosis, who achieved a similar slide-level accuracy of 98% (137/140 correct majority votes). Our results highlight the feasibility of artificial intelligence-based methods as a support tool in diagnostic oncologic pathology with future applications in other species and tumor types.

Cytologic scoring of equine exercise-induced pulmonary hemorrhage: Performance of human experts and a deep learning-based algorithm.

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-based algorithm for the THS. Digitized cytological specimens stained for iron were prepared from 52 equine BALF samples. Ten annotators produced a THS for each slide according to published methods. The reference methods for comparing annotator's and algorithmic performance included a ground truth dataset, the mean annotators' THSs, and chemical iron measurements. Results of the study showed that annotators had marked interobserver variability of the THS, which was mostly due to a systematic error between annotators in grading the intracytoplasmatic hemosiderin content of individual macrophages. Regarding overall measurement error between the annotators, 87.7% of the variance could be reduced by using standardized grades based on the ground truth. The algorithm was highly consistent with the ground truth in assigning hemosiderin grades. Compared with the ground truth THS, annotators had an accuracy of diagnosing EIPH (THS of < or ≥ 75) of 75.7%, whereas, the algorithm had an accuracy of 92.3% with no relevant differences in correlation with chemical iron measurements. The results show that deep learning-based algorithms are useful for improving reproducibility and routine applicability of the THS. For THS by experts, a diagnostic uncertainty interval of 40 to 110 is proposed. THSs within this interval have insufficient reproducibility regarding the EIPH diagnosis.

Estimated incubation period distributions of mpox using cases from two international European festivals and outbreaks in a club in Berlin, May to June 2022.

BackgroundSince May 2022, an mpox outbreak affecting primarily men who have sex with men (MSM) has occurred in numerous non-endemic countries worldwide. As MSM frequently reported multiple sexual encounters in this outbreak, reliably determining the time of infection is difficult; consequently, estimation of the incubation period is challenging.AimWe aimed to provide valid and precise estimates of the incubation period distribution of mpox by using cases associated with early outbreak settings where infection likely occurred.MethodsColleagues in European countries were invited to provide information on exposure intervals and date of symptom onset for mpox cases who attended a fetish festival in Antwerp, Belgium, a gay pride festival in Gran Canaria, Spain or a particular club in Berlin, Germany, where early mpox outbreaks occurred. Cases of these outbreaks were pooled; doubly censored models using the log-normal, Weibull and Gamma distributions were fitted to estimate the incubation period distribution.ResultsWe included data on 122 laboratory-confirmed cases from 10 European countries. Depending on the distribution used, the median incubation period ranged between 8 and 9 days, with 5th and 95th percentiles ranging from 2 to 3 and from 20 to 23 days, respectively. The shortest interval that included 50% of incubation periods spanned 8 days (4-11 days).ConclusionCurrent public health management of close contacts should consider that in approximately 5% of cases, the incubation period exceeds the commonly used monitoring period of 21 days.

Validation of digital microscopy: Review of validation methods and sources of bias.

Digital microscopy (DM) is increasingly replacing traditional light microscopy (LM) for performing routine diagnostic and research work in human and veterinary pathology. The DM workflow encompasses specimen preparation, whole-slide image acquisition, slide retrieval, and the workstation, each of which has the potential (depending on the technical parameters) to introduce limitations and artifacts into microscopic examination by pathologists. Performing validation studies according to guidelines established in human pathology ensures that the best-practice approaches for patient care are not deteriorated by implementing DM. Whereas current publications on validation studies suggest an overall high reliability of DM, each laboratory is encouraged to perform an individual validation study to ensure that the DM workflow performs as expected in the respective clinical or research environment. With the exception of validation guidelines developed by the College of American Pathologists in 2013 and its update in 2021, there is no current review of the application of methods fundamental to validation. We highlight that there is high methodological variation between published validation studies, each having advantages and limitations. The diagnostic concordance rate between DM and LM is the most relevant outcome measure, which is influenced (regardless of the viewing modality used) by different sources of bias including complexity of the cases examined, diagnostic experience of the study pathologists, and case recall. Here, we review 3 general study designs used for previous publications on DM validation as well as different approaches for avoiding bias.

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

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 the development of high-performance algorithms that may improve standardization of the MC. As algorithmic predictions are not flawless, computer-assisted review by pathologists may ensure reliability. In the present study, we compared partial (MC-ROI preselection) and full (additional visualization of MF candidates and display of algorithmic confidence values) computer-assisted MC analysis to the routine (unaided) MC analysis by 23 pathologists for whole-slide images of 50 canine cutaneous mast cell tumors (ccMCTs). Algorithmic predictions aimed to assist pathologists in detecting mitotic hotspot locations, reducing omission of MFs, and improving classification against imposters. The interobserver consistency for the MC significantly increased with computer assistance (interobserver correlation coefficient, ICC = 0.92) compared to the unaided approach (ICC = 0.70). Classification into prognostic stratifications had a higher accuracy with computer assistance. The algorithmically preselected hotspot MC-ROIs had a consistently higher MCs than the manually selected MC-ROIs. Compared to a ground truth (developed with immunohistochemistry for phosphohistone H3), pathologist performance in detecting individual MF was augmented when using computer assistance (F1-score of 0.68 increased to 0.79) with a reduction in false negatives by 38%. The results of this study demonstrate that computer assistance may lead to more reproducible and accurate MCs in ccMCTs.

A shift from travel-associated cases to autochthonous transmission with Berlin as epicentre of the monkeypox outbreak in Germany, May to June 2022.

By 22 June 2022, 521 cases of monkeypox were notified in Germany. The median age was 38 years (IQR: 32-44); all cases were men. In Berlin, where 69% of all cases occurred, almost all were men who have sex with men. Monkeypox virus likely circulated unrecognised in Berlin before early May. Since mid-May, we observed a shift from travel-associated infections to mainly autochthonous transmission that predominantly took place in Berlin, often in association with visits to clubs and parties.

Teaching Outbreak Investigations with an Interactive Blended Learning Approach.

Public health is a central but often neglected component of veterinary education. German veterinary public health (VPH) education includes substantial theory-focused lectures, but practical case studies are often missing. To change this, we combined the advantages of case-based teaching and blended learning to teach these topics in a more practical and interactive way. Blended learning describes the combination of online and classroom-based teaching. With it, we created an interdisciplinary module for outbreak investigations and zoonoses, based on the epidemiology, food safety, and microbiology disciplines. We implemented this module within the veterinary curriculum of the seventh semester (in the clinical phase of the studies). In this study, we investigated the acceptance of this interdisciplinary approach and established a framework for the creation of interactive outbreak investigation cases that can serve as a basis for further cases. Over a period of 3 years, we created three interactive online cases and one interactive in-class case and observed the student-reported evaluation of the blended learning concept and self-assessed learning outcomes. Results show that 80% (75-89) of students evaluated the chosen combination of case-based and blended learning for interdisciplinary teaching positively and therefore accepted it well. Additionally, 76% (70-98) of students evaluated their self-assessed learning outcomes positively. Our results suggest that teaching VPH through interdisciplinary cases in a blended learning approach can increase the quality of teaching VPH topics. Moreover, it provides a framework to incorporate realistic interdisciplinary VPH cases into the curriculum.

Low airborne tenacity and spread of ESBL-/AmpC-producing Escherichia coli from fertilized soil by wind erosion.

ESBL-/AmpC-producing Escherichia coli from organic fertilizers were previously detected on soil surfaces of arable land and might be emitted by wind erosion. To investigate this potential environmental transmission path, we exposed ESBL-/AmpC-positive chicken litter, incorporated in agricultural soils, to different wind velocities in a wind tunnel and took air samples for microbiological analysis. No data exist concerning the airborne tenacity of ESBL-/AmpC-producing E. coli. Therefore, we explored the tenacity of two ESBL/AmpC E. coli strains and E. coli K12 in aerosol chamber experiments at different environmental conditions. In the wind tunnel, ESBL/AmpC-producing E. coli were detected in none of the air samples (n = 66). Non-resistant E. coli were qualitatively detected in 40.7% of air samples taken at wind velocities exceeding 7.3 m s-1 . Significantly increased emission of total viable bacteria with increasing wind velocity was observed. In the aerosol chamber trials, recovery rates of airborne E. coli ranged from 0.003% to 2.8%, indicating a low airborne tenacity. Concluding, an emission of ESBL/AmpC E. coli by wind erosion in relevant concentrations appears unlikely because of the low concentration in chicken litter compared with non-resistant E. coli and their low airborne tenacity, proven in the aerosol chamber trials.

Internal Tandem Duplication of Exon 8 of c-kit Is Associated With Longer Total Survival in Canine Cutaneous Mast Cell Tumors.

Canine cutaneous mast cell tumors (ccMCTs) have a highly variable biological behavior and accurate prognostication is essential for therapeutic intervention. Internal tandem duplications (ITD) of exon 11 are the most commonly detected c-kit mutation in ccMCTs and are associated with poor prognosis and increased cellular proliferation. The prognostic value of detecting mutations in other exons of c-kit has not been systematically examined. In this study, we analyzed the prognostic value of ITD mutations of exon 8 in c-kit of ccMCTs in comparison to ccMCTs with ITD mutations of exon 11 and ccMCTs without mutations of exon 8 or 11. The mutational status, histological grade, KIT expression pattern, Ki67 index, AgNOR (argyrophilic nucleolar organizing region) score, and Ag67 score were determined in 221 ccMCTs, and outcome was available for 101 dogs. ITD mutations of exon 8 were found in 73/221 (33%), of exon 11 in 100/221 (45%), and none of these mutations in 50/221 (22%) of ccMCTs. None of the dogs with mutations of exon 8 died due to suspected ccMCT-related cause, but 23% dogs with ccMCTs with mutations of exon 11 died due to suspected ccMCT-related cause. Prognostic parameters in ccMCTs with exon 11 mutations were commonly associated with a high proliferative activity and poor prognosis, while prognostic markers in ccMCTs with mutations of exon 8 had lower values similar to those observed in ccMCTs without mutations in exons 8 or 11 of c-kit. This study indicates that screening for ITD mutations in exon 8 in ccMCTs may be helpful to identify less aggressive ccMCTs and may be recommended as a supplementary prognostic test.

Neoplasia and Tumor-Like Lesions in Pet Rabbits (Oryctolagus cuniculus): A Retrospective Analysis of Cases Between 1995 and 2019.

Prevalence and age distribution of tumors is largely unknown in pet rabbits. Currently available studies focused on specific organ systems or specific tumor types and never covered a comparative examination of all tumor types. Previous studies on laboratory rabbits suggested a low tumor prevalence but were mostly limited to young adult animals. In the present study, all tumor types and several tumor-like lesions of all organ systems were analyzed retrospectively in archived pet rabbit samples of all ages. Cases included necropsy cases (n = 2,014) or postmortem tissue samples (n = 102) as well as surgical biopsies (n = 854). All lesions suspicious of neoplasia were reevaluated by histopathology and, when indicated, by immunohistochemistry. Necropsy cases had a tumor prevalence of 14.4% in both sexes or 19.8% in female intact rabbits of all age groups, and up to 47.2% or 66.7%, respectively, in rabbits older than 6 years. Overall, the most common tumor types were uterine adenocarcinoma (prevalence in female intact animals: 13.1%), lymphoma (prevalence: 2.8%), and thymoma (prevalence: 2.1%). Lymphoma, the most common tumor of rabbits ≤24 months of age, were of B-cell immunophenotype in 96% of cases and most commonly located in the lymph nodes (57%), gastrointestinal tract (54%), kidneys (48%), spleen (42%), and liver (41%). Tumors accounted for 81.1% of surgical biopsies and mostly comprised cutaneous, mammary, and uterine tumors. In conclusion, tumor types and prevalence varied significantly with respect to age, revealing some differences from previous studies on laboratory rabbits.

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

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.

Teaching small animal reproduction via virtual patients.

Virtual patients have become an interesting alternative in medical education. Due to increasing demands regarding theoretical and clinical teaching and to improve an interdisciplinary approach, a new blended learning concept including virtual patients was developed and implemented in the veterinary curriculum of the Freie Universität Berlin. In the presented project, three virtual patients from the field of canine reproduction were developed. They focus on pregnancy diagnosis with suspected luteal insufficiency, pyometra and benign prostatic hyperplasia, respectively. The results of an evaluation by veterinary students of the 7th semester showed a high acceptance of virtual patients in a blended learning reproduction module in the interdisciplinary lectures. Students especially preferred videos, such as video lectures, hands-on videos and animations as well as a glossary for background information, to successfully and autonomously work on a virtual case. The content covered by the new modules that were developed in the context of this project is part of a spiral curriculum; they will be revised and enhanced during the clinical year.

Impact of air humidity on the tenacity of different agents in bioaerosols.

Despite the variety of pathogens that are transmitted via the airborne route, few data are available on factors that influence the tenacity of airborne pathogens. In order to better understand and thus control airborne infections, knowledge of these factors is important. In this study, three agents, S. aureus, G. stearothermophilus spores and the MS2 bacteriophage, were aerosolized at relative humidities (RH) varying between 30% and 70%. Air samples were then analyzed to determine the concentration of the agents. S. aureus was found to have significantly lower survival rate in the aerosol at RH above 60%. It showed the lowest recovery rates of the three agents, ranging from 0.13% at approximately 70% RH to 4.39% at 30% RH. G. stearothermophilus spores showed the highest tenacity with recovery rates ranging from 41.85% to 61.73% with little effect of RH. For the MS2 bacteriophage, a significantly lower tenacity in the aerosol was observed with a recovery rate of 4.24% for intermediate RH of approximately 50%. The results of this study confirm the significant influence of the RH on the tenacity of airborne microorganisms depending on the specific agent. These data show that the behavior of microorganism in bioaerosols is varies under different environmental conditions.

Blood-based assessment of oxidative stress, inflammation, endocrine and metabolic adaptations in eventing horses accounting for plasma volume shift after exercise.

BACKGROUND: After submaximal exercise, blood values of eventing horses show physiological reactions. OBJECTIVES: This prospective longitudinal study investigated blood parameters in 20 elite eventing horses before and after two-four-star cross-country rides. METHODS: Using a mixed model adjusting for plasma volume shift, we assessed exercise-dependent parameters and compared blood values with reference ranges for healthy horses at rest. RESULTS: Following exercise, cortisol, triiodothyronine (T3) and thyroxine (T4) showed short-term increases, and superoxide-dismutase showed a small short-term increase. Hepatic values showed short-term (haemoglobin [HGB], globulins) or sustained increases (bilirubin, glutamate dehydrogenase, alanine aminotransferase). Digestion-related parameters showed small short-term increases (α-amylase, triglycerides) or decreases (cholesterol, DGGR-lipase), apparent through plasma shift adjustment. Zinc decreased in the short term, and iron showed a delayed decrease. White blood cell count increased persistently after training, whereas serum amyloid A remained unchanged. CONCLUSIONS: Exercised eventing horses had consistently elevated HGB and cortisol levels 10 and 30 min after submaximal exercise, exceeding the reference ranges for healthy horses at rest. Exercise activates the hypothalamic-pituitary-adrenocortical and hypothalamic-pituitary-thyroid axes. Antioxidant activity was observed. Increased energy requirements led to the mobilization of energy reserves, and a sustained increase in liver enzymes indicated hepatocellular injury. Mild haemolysis suggested increased muscle metabolism, whereas signs of inflammation were subtle. Further research is needed to identify which horses deviate from mean values.

The relationship between lameness prevalence and pasture access in 659 dairy herds in Germany.

Lameness in dairy cows is an expression of pain most likely originating from a claw disorder, causing impaired animal wellbeing and substantial economic losses for farmers. The aim of this study was to investigate the effects of access to pasture, time spent on pasture, and season on farm level lameness prevalence. The survey was part of a cross-sectional observational study, in which farms in three regions of Germany (North, East and South) were visited by study veterinarians. On each farm (total: 659, N: 240, E: 247, S: 172), management data were recorded, and cows were scored for locomotion, according to Sprecher. Median farm-level lameness prevalence (Score 3/5 or higher) was 29.4% (IQR: 18.7% - 42.0%), and 8.2% (IQR: 3.7% - 14.0%) for severe lameness (Score 4/5 or higher). Farm-level lameness prevalence continuously decreased with increasing time spent on pasture (up to approximately 10 hours per cow per day). On farms that did not offer their cows access to pasture lameness prevalence did not show a seasonal variation. On farms where cows had pasture access for up to three hours per day lameness prevalence peaked in autumn. In contrast, on farms offering their cows access to pasture beyond three hours per day the peak of lameness was observed in spring. Our results revealed that even short periods of pasture access of at least two hours per cow and day (on average per year) are beneficial for the locomotion of dairy cows.

Timely Monitoring of SARS-CoV-2 RNA Fragments in Wastewater Shows the Emergence of JN.1 (BA.2.86.1.1, Clade 23I) in Berlin, Germany.

The importance of COVID-19 surveillance from wastewater continues to grow since case-based surveillance in the general population has been scaled back world-wide. In Berlin, Germany, quantitative and genomic wastewater monitoring for SARS-CoV-2 is performed in three wastewater treatment plants (WWTP) covering 84% of the population since December 2021. The SARS-CoV-2 Omicron sublineage JN.1 (B.2.86.1.1), was first identified from wastewater on 22 October 2023 and rapidly became the dominant sublineage. This change was accompanied by a parallel and still ongoing increase in the notification-based 7-day-hospitalization incidence of COVID-19 and COVID-19 ICU utilization, indicating increasing COVID-19 activity in the (hospital-prone) population and a higher strain on the healthcare system. In retrospect, unique mutations of JN.1 could be identified in wastewater as early as September 2023 but were of unknown relevance at the time. The timely detection of new sublineages in wastewater therefore depends on the availability of new sequences from GISAID and updates to Pango lineage definitions and Nextclade. We show that genomic wastewater surveillance provides timely public health evidence on a regional level, complementing the existing indicators.

Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility.

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 (cPC), and its prognostic implications. We developed a deep learning-based algorithm for evaluating NP (variation in size, i.e., anisokaryosis and/or shape) using a segmentation model. Its performance was evaluated on 46 cPC cases with comprehensive follow-up data regarding its accuracy in nuclear segmentation and its prognostic ability. Its assessment of NP was compared to manual morphometry and established prognostic tests (pathologists' NP estimates (n = 11), mitotic count, histological grading, and TNM-stage). The standard deviation (SD) of the nuclear area, indicative of anisokaryosis, exhibited good discriminatory ability for tumor-specific survival, with an area under the curve (AUC) of 0.80 and a hazard ratio (HR) of 3.38. The algorithm achieved values comparable to manual morphometry. In contrast, the pathologists' estimates of anisokaryosis resulted in HR values ranging from 0.86 to 34.8, with slight inter-observer reproducibility (k = 0.204). Other conventional tests had no significant prognostic value in our study cohort. Fully automated morphometry promises a time-efficient and reproducible assessment of NP with a high prognostic value. Further refinement of the algorithm, particularly to address undersegmentation, and application to a larger study population are required.