Computer-Assisted Diagnosis of Lymph Node Metastases in Colorectal Cancers Using Transfer Learning With an Ensemble Model.

Screening of lymph node metastases in colorectal cancer (CRC) can be a cumbersome task, but it is amenable to artificial intelligence (AI)-assisted diagnostic solution. Here, we propose a deep learning-based workflow for the evaluation of CRC lymph node metastases from digitized hematoxylin and eosin-stained sections. A segmentation model was trained on 100 whole-slide images (WSIs). It achieved a Matthews correlation coefficient of 0.86 (±0.154) and an acceptable Hausdorff distance of 135.59 µm (±72.14 µm), indicating a high congruence with the ground truth. For metastasis detection, 2 models (Xception and Vision Transformer) were independently trained first on a patch-based breast cancer lymph node data set and were then fine-tuned using the CRC data set. After fine-tuning, the ensemble model showed significant improvements in the F1 score (0.797-0.949; P <.00001) and the area under the receiver operating characteristic curve (0.959-0.978; P <.00001). Four independent cohorts (3 internal and 1 external) of CRC lymph nodes were used for validation in cascading segmentation and metastasis detection models. Our approach showed excellent performance, with high sensitivity (0.995, 1.0) and specificity (0.967, 1.0) in 2 validation cohorts of adenocarcinoma cases (n = 3836 slides) when comparing slide-level labels with the ground truth (pathologist reports). Similarly, an acceptable performance was achieved in a validation cohort (n = 172 slides) with mucinous and signet-ring cell histology (sensitivity, 0.872; specificity, 0.936). The patch-based classification confidence was aggregated to overlay the potential metastatic regions within each lymph node slide for visualization. We also applied our method to a consecutive case series of lymph nodes obtained over the past 6 months at our institution (n = 217 slides). The overlays of prediction within lymph node regions matched 100% when compared with a microscope evaluation by an expert pathologist. Our results provide the basis for a computer-assisted diagnostic tool for easy and efficient lymph node screening in patients with CRC.

Multi-fungal sepsis and mucormycosis of the central nervous system in a patient treated with ibrutinib, a case report and review of the literature.

We report the case of a 71 years old patient with chronic lymphocytic leukemia (CLL), who developed a rapidly progressing multi-fungal infection including mucormycosis of the central nervous system (CNS) during treatment with ibrutinib. On autopsy mucorales species were demonstrated intravascularly by histomorphology of several organs and lymph nodes and were characterized as Rhizomucor pusillus by polymerase-chain reaction (PCR) - analysis. In addition, invasive pulmonary Aspergillus fumigatus was found and also confirmed by PCR. To the best of our knowledge, this is the first confirmation of a multi-fungal sepsis and invasive CNS-infection with mucorales species under ibrutinib. Knowing the risk for invasive fungal disease in patients under ibrutinib, identifying the pathogen and early initiation of specific treatment is crucial for a good clinical outcome especially in mucormycosis.

Epidemiology and population structure of Staphylococcus aureus in various population groups from a rural and semi urban area in Gabon, Central Africa.

Little data is available on the epidemiology of Staphylococcus aureus in Africa. In the present study we aim at characterizing the population structure of S. aureus in healthy subjects from a rural and a semi-urban area in Lambaréné, Gabon as well as in hospital staff and inpatients. In total, 500 subjects were screened for S. aureus colonization of the nares, axillae and inguinal region. Overall, 146 (29%) were positive. We found 46 different spa types. The most frequent spa types were t084 (35%) and the agr II was the most prevalent subtype of the accessory gene regulator (56%, n=82). Five isolates (3%) were methicillin resistant S. aureus (MRSA). Carriage rates of S. aureus in Gabon are comparable to developed countries. MRSA is for the first time described and could pose a significant health threat in this region with limited access to microbiological laboratory facilities and to adequate antimicrobial agents.