The advantages of the digital methodology are well known. In this paper, we provide a detailed description of the process for the digital transformation of the pathology laboratory at IPATIMUP, the major modifications that operate throughout the processing pipeline, and the advantages of its implementation. The model of digital workflow implementation at IPATIMUP demonstrates that careful planning and adoption of simple measures related to time, space, and sample management can be adopted by any pathology laboratory to achieve higher quality and easy digital transformation.

Breast cancer is the most common malignancy in women worldwide, and is responsible for more than half a million deaths each year. The appropriate therapy depends on the evaluation of the expression of various biomarkers, such as the human epidermal growth factor receptor 2 (HER2) transmembrane protein, through specialized techniques, such as immunohistochemistry or in situ hybridization. In this work, we present the HER2 on hematoxylin and eosin (HEROHE) challenge, a parallel event of the 16th European Congress on Digital Pathology, which aimed to predict the HER2 status in breast cancer based only on hematoxylin–eosin-stained tissue samples, thus avoiding specialized techniques. The challenge consisted of a large, annotated, whole-slide images dataset (509), specifically collected for the challenge. Models for predicting HER2 status were presented by 21 teams worldwide. The best-performing models are presented by detailing the network architectures and key parameters. Methods are compared and approaches, core methodologies, and software choices contrasted. Different evaluation metrics are discussed, as well as the performance of the presented models for each of these metrics. Potential differences in ranking that would result from different choices of evaluation metrics highlight the need for careful consideration at the time of their selection, as the results show that some metrics may misrepresent the true potential of a model to solve the problem for which it was developed. The HEROHE dataset remains publicly available to promote advances in the field of computational pathology.

Background and Objectives: Breast cancer is the most common malignancy in women and is responsible for more than half a million deaths each year. Early and accurate diagnosis is therefore of utmost importance. Human expertise is required to diagnose and correctly classify breast cancer and determine appropriate therapy, which depends on evaluating the expression of various biomarkers such as the transmembrane protein receptor HER2. This evaluation requires several steps, including specialized techniques such as immunohistochemistry or in situ hybridization to assess HER2 status. In this work, we present the HEROHE challenge, a parallel event of the 16th European Congress on Digital Pathology, which aims to automate the assessment of HER2 status based only on hematoxylin and eosin stained tissue samples from invasive breast cancer. Methods: The organizational protocol is presented, from sample preparation to timeline and evaluation metric. The best-performing models are presented by detailing the network architectures and key parameters. Results: Models for assessing HER2 status were presented by 21 teams worldwide. Their results in the main dataset and in the subset of cases classified as equivocal by the immunohistochemistry test were evaluated. Methods were compared and approaches, core methodologies, and software choices were contrasted. Conclusions: Promising results were obtained, especially for the subset of equivocal cases. The performance of each model was evaluated according to multiple evaluation metrics highlighting that the chosen metric may be misleading and, in some extreme scenarios, may distort the perception of the adequacy of the model to solve the problem.

Background: Human papillomavirus (HPV), a leading cause of cervical cancer, is present in most cases of the disease and ranks as the fourth most common cancer in women globally. Among the HPV types, fourteen (HPV 16/18/31/33/35/39/45/51/52/56/58/59/66/68) are recognized as high-risk (hrHPV), each with varying levels of oncogenic potential. Detecting and genotyping these hrHPV types in cervical lesions is crucial, requiring the development of new diagnostic methods. Methods: This study focuses on a retrospective analysis conducted on 44 women from the Cova da Beira Local Health Unit. We used the Anyplex™ II hrHPV Detection kit for hrHPV genotyping from paraffin-embedded cervical tissue samples. Results: hrHPV types were identified in 38 out of the 44 women. Genotyping revealed HPV-16 (55.3%), HPV-18/39/56/58/59 (5.3%), HPV-31 (21.1%), HPV-35 (7.9%), HPV-51/66 (2.6%), and HPV-52 (10.5%). Conclusions: This study demonstrates that the Anyplex™ II hrHPV Detection kit, originally designed for cervical cancer screening, is also effective for hrHPV genotyping in histological analyses. This methodology offers a simpler and more cost-effective approach for cervical cancer risk stratification. Its implementation in clinical practice could enhance the detection of hrHPV in cervical lesions, thereby contributing to more precise diagnoses and potentially more informed treatment strategies.

Background: Human papillomavirus (HPV) is diagnosed in most cervical cancers and is the fourth cause of cancer worldwide. Currently, fourteen HPV types are considered carcinogenic (HPV 16/18/31/33/35/39/45/51/52/56/58/59/66/68) with different oncogenicity. Cervical lesions might be due to HR (high risk)-HPV for what is important to identify new methods to genotype cervical lesions. The main goal was to identify, for the first time, HPV-HR in cervical lesions using Anyplex™ Detection kit in paraffin-embedded tissue. (2) Methods: It was performed a retrospective study in 45 women from Academic Hospital of Cova da Beira (CHUCB). DNA extraction was performed and through Anyplex™ II HPV-HR Detection kit HPV-HR were genotyped. (3) Results: HPV-HR were identified in 38 women; HPV-16 (55,26%), HPV-18/39/56/58/59 (5,26%), HPV-31 (21,05%), HPV-35 (7,89%), HPV-51/6 (2,63%) and HPV-52 (10,53%). (4) Conclusions: Our results reflect that Anyplex™ II HPV-HR Detection kit, designed for HR-HPV genotyping of cervical cancer screening, might be properly used to HR-HPV genotyping in histology. The proposed methodology allows an easy and cheaper technique that should be used as a future cervical risk stratification. It is a strong tool to be implemented in clinical practice in order to detect HR-HPV detection in cervical lesions, contributing to a more accurate diagnosis.

The unicompartmental knee arthroplasty (UKA) has demonstrated good medium to long-term results. However, conversion of UKA to total Knee arthroplasty (TKA) results in poorer outcomes than primary TKA. We report a case of a 59 years-old woman with a UKA failure, with tibial component migration to the popliteal fossa. A knee posterior approach was performed to extract this component and a parapatellar approach for conversion to TKA with a tibial component with sleeve and stem. At 6 months follow-up the patient has no pain, no inflammatory signs, functional range of motion (5-100º) and the radiographic study show no complication. This case highlights the importance of a celerity revision, since time can lead to loss of bone stock and component migration, making the surgery more demanding.