Recent advances in artificial intelligence, particularly in the field of deep learning, have enabled researchers to create compelling algorithms for medical image analysis. Histological slides of basal cell carcinomas (BCCs), the most frequent skin tumor, are accessed by pathologists on a daily basis and are therefore well suited for automated pre-screening by neural networks for the identification of cancerous regions and swift tumor classification.In this proof-of-concept study, we implemented an accurate and intuitively interpretable artificial neural network (ANN) for the detection of BCCs in histological whole slide images. Furthermore, we identified and compared differences in the diagnostic histological features and recognition patterns relevant for machine learning algorithms versus expert pathologists.An attention-ANN was trained with whole slide images of BCCs to identify tumor regions (n=820). The diagnosis-relevant regions used by the ANN were compared to regions of interest for pathologists, detected by eye-tracking techniques.This ANN accurately identified BCC tumor regions on images of histologic slides (AUC: 0.993, 95%

ObjectiveThe aim of this study was to assess the preoperative tumour grade of pancreatic neuroendocrine neoplasms (panNENs) by determining the Ki‐67 index in endoscopic ultrasound‐guided fine needle aspiration (EUS‐FNA) material and to correlate the preoperative tumour grade with the postoperative tumour grade in surgical specimens.MethodsWe performed a retrospective review of the institutional pathology database over a 10‐year period (2007‐2017) to identify all cases of panNENs with corresponding preoperative EUS‐FNA cytological material and surgical specimens. Fifteen cases with adequate EUS‐FNA material (more than 400 tumour cells on cellblock) were identified. The cytological and histological samples were graded based on the mitotic rate and the Ki‐67 index in accordance with the 2017 World Health Organisation grading system for panNENs. The tumour grades determined on EUS‐FNA cellblock material were compared with the histological tumour grades.ResultsMean age at diagnosis was 64.8 ± 12.7 years (range, 38‐85 years). The grading scores assigned to the cytological and histological samples were concordant in all 15 (100%) cases. Of those, two (13%) cases were scored as grade 1, nine (60%) cases as grade 2 and four (27%) cases as grade 3 tumours.ConclusionOur study shows that tumour grade in patients with PanNENs can be reliably determined by assessing the Ki‐67 index in EUS‐FNA specimens based on the 2017 World Health Organisation classification and grading system.

SummaryColorectal cancer (CRC) is a molecularly heterogeneous disease arising from gradual accumulation of genetic and epigenetic changes. In the last decade, great efforts have been made to classify CRC according to molecular features. This has led to several proposals of molecular subtyping. Recently, consensus molecular subtypes (CMS) have been proposed based on the integration of previously existing categorizations and additional comprehensive molecular studies. Microsatellite instability (MSI) is a highly specific molecular feature in CRC with a therapeutic impact, for example for immunotherapy. MSI is recognized as a separate CMS subtype. Beyond MSI, molecular subtyping may also be helpful for further differentiating CRC into prognostically distinct groups and for identifying new treatment targets, particularly for CMS with more aggressive behavior and resistance to conventional systemic treatment. Molecular subtypes may also exhibit distinctive morphological features, which may open the horizon for morphomolecular diagnostics based on digital pathology and machine learning. This review article summarizes current aspects of the molecular pathology of CRC with a focus on molecular subtyping in the context of pathological features and therapeutic applications.

Background and Objectives: Up until now, only one case of unilateral proximal tibiofibular synostosis caused by osteochondroma has been reported. This report is the first well-documented bilateral case of proximal tibiofibular synostosis caused by an osteochondroma. Case Report: A 21-year-old, highly active male patient with bilateral proximal tibiofibular synostosis caused by an osteochondroma suffering from persistent knee pain is presented. As conservative methods had failed, the patient was treated by bilateral open resection of the connecting bone. Histopathological findings confirmed the preoperative diagnosis. The patient returned to sports three weeks after surgery and continued soccer training six weeks after surgery. Discussion: The case report presents the successful treatment of a bilateral proximal tibiofibular synostosis caused by an osteochondroma by bilateral open resection of the connecting bone.