Digital twin manifesto for the pathology laboratory.

This manuscript presents a manifesto developed by a multifaceted board of stakeholders aimed at guiding the implementation of Digital Twin (DT) technology in pathology laboratories. DTs, already transformative in other sectors, hold substantial promise for enhancing operational efficiency, diagnostic accuracy, and quality of care in pathology. We provide a comparative analysis of traditional versus DT-enhanced workflows across critical steps including accessioning, grossing, processing, embedding, cutting, staining, scanning, diagnosis, and archiving.

Attention-Based Whole-Slide Image Compression Achieves Pathologist-Level Prescreening of Multiorgan Routine Histopathology Biopsies.

Screening programs for the early detection of cancers, such as colorectal and cervical cancers, have led to an increased demand for histopathological analysis of biopsies. Advanced image analysis with deep learning has shown the potential to automate cancer detection in digital pathology whole-slide images. In particular, weakly supervised learning can achieve whole-slide image classification without the need for tedious, manual annotations, using only slide-level labels.

ARID1A mutational status in non-small cell lung cancer: from molecular pathology to clinical implications with a focus on the relationships with EGFR.

Lung cancer is the most frequently diagnosed malignancy worldwide and remains the leading cause of cancer-related mortality. Non-small-cell lung cancer (NSCLC) is the most prevalent type of lung cancer, with epidermal growth factor receptor (EGFR) gene mutations being among the most frequently reported. ARID1A (AT-Rich Interactive Domain 1A), a key component of the switch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complex, has emerged as a tumor suppressor in multiple cancers and is mutated in approximately 8 % of lung cancers, primarily as a loss-of-function (LOF) alteration, which allows the gene to be considered a potential molecular marker, predictive of poor NSCLC prognosis.

T cells in the microenvironment of solid pediatric tumors: the case of neuroblastoma.

Neuroblastoma (NB) is an immunologically "cold" tumor with poor or no inflamed substrates as most of solid pediatric tumors (SPT). Consistent data indicate that NB tumor microenvironment (TME) is dominated by myeloid cells, with little (but variable) T cell infiltration. The obstacles to lymphocyte infiltration and to their anti-tumor activity are due to different tumor immune evasion strategies, including loss of HLA Class I molecules, high expression of immune checkpoint molecular ligands leading to exhaustion of T effector (and NK) cells, induction of T regulatory, myeloid and stromal cells and secretion of immunosuppressive mediators.

The expanding role of next-generation imaging in prostate cancer management: a cross-sectional survey exploring the clinical practice of uro-oncologists in North-Eastern Italy; on behalf of GUONE (Gruppo Uro-Oncologico del Nord-Est).

Background: Next-generation imaging (NGI) technologies such as multiparametric magnetic resonance imaging (mpMRI) and total-body NGI (tbNGI) methodologies including choline, fluciclovine or PSMA positron emission tomography/computed tomography (PET/CT), whole-body MRI (wbMRI), and PET/MRI are becoming increasingly available, but their use in different prostate cancer (PCa) settings is under debate. The Gruppo Uro-Oncologico del Nord-Est (GUONE) designed a survey to explore the current clinical practice of NGI utilization in a specific macro-region in North-Eastern Italy.

Methods: A cross-sectional survey was conducted by administering an anonymous online multiple-choice questionnaire to uro-oncologists practicing in North-Eastern Italy, using the Google Forms platform.

Generating and evaluating synthetic data in digital pathology through diffusion models.

Synthetic data is becoming a valuable tool for computational pathologists, aiding in tasks like data augmentation and addressing data scarcity and privacy. However, its use necessitates careful planning and evaluation to prevent the creation of clinically irrelevant artifacts.This manuscript introduces a comprehensive pipeline for generating and evaluating synthetic pathology data using a diffusion model.

T cell landscape in the microenvironment of human solid tumors.

T cells are the main effectors involved in anti-tumor immunity, mediating most of the adaptive response towards cancer. After priming in lymph nodes, tumor antigens-specific naïve T lymphocytes proliferate and differentiate into effector CD4+ and CD8+ T cells that migrate from periphery into tumor sites aiming to eliminate cancer cells. Then while most effector T cells die, a small fraction persists and recirculates as long-lived memory T cells which generate enhanced immune responses when re-encountering the same antigen.

Histopathological evaluation and grading for prostate cancer: current issues and crucial aspects.

A crucial aspect of prostate cancer grading, especially in low- and intermediate-risk cancer, is the accurate identification of Gleason pattern 4 glands, which includes ill-formed or fused glands. However, there is notable inconsistency among pathologists in recognizing these glands, especially when mixed with pattern 3 glands. This inconsistency has significant implications for patient management and treatment decisions.

Human NK cells and cancer.

The long story of NK cells started about 50 y ago with the first demonstration of a natural cytotoxic activity within an undefined subset of circulating leukocytes, has involved an ever-growing number of researchers, fascinated by the apparently easy-to-reach aim of getting a "universal anti-tumor immune tool". In fact, in spite of the impressive progress obtained in the first decades, these cells proved far more complex than expected and, paradoxically, the accumulating findings have continuously moved forward the attainment of a complete control of their function for immunotherapy. The refined studies of these latter years have indicated that NK cells can epigenetically calibrate their functional potential, in response to specific environmental contexts, giving rise to extraordinarily variegated subpopulations, comprehensive of memory-like cells, tissue-resident cells, or cells in various differentiation stages, or distinct functional states.

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images.

Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability. Multiple papers have presented systems for the automatic quantification of TPS, but none report on the task of determining cell-level PD-L1 expression and often reserve their evaluation to a single PD-L1 monoclonal antibody or clinical center. In this paper, we report on a deep learning algorithm for detecting PD-L1 negative and positive tumor cells at a cellular level and evaluate it on a cell-level reference standard established by six readers on a multi-centric, multi PD-L1 assay dataset.

CD34DNAM-1CXCR4 haemopoietic precursors circulate after chemotherapy, seed lung tissue and generate functional innate-like T cells and NK cells.

Background: There is little information on the trajectory and developmental fate of LinCD34DNAM-1 CXCR4 progenitors exiting bone marrow during systemic inflammation.

Objective: To study LinCD34DNAM-1 CXCR4 cell circulation in cancer patients, to characterize their entry into involved lung tissue and to characterize their progenies.

Methods: Flow cytometric analysis of PBMC from 18 patients with lung cancer on samples collected immediately before the first and the second treatment was performed to study LinCD34DNAM-1 CXCR4 precursors.

Pathological Complete Response to Pembrolizumab plus Axitinib Combination following Serious Immune-Related Adverse Events in an Advanced Renal Cell Carcinoma Patient with a History of Rheumatoid Arthritis.

Immune checkpoint inhibitors (ICIs)-based combinations have improved survival outcomes of advanced renal cell carcinoma (RCC) patients and are currently recommended as first-line treatment options. Rheumatoid arthritis (RA) is a systemic autoimmune disease (AD) of unknown etiology characterized by a chronic inflammatory process involving joints and extra-articular organs. Patients with AD are usually excluded from large randomized clinical trials investigating immunotherapeutic drugs.

Natural Language Processing to extract SNOMED-CT codes from pathological reports.

Objective: The use of standardized structured reports (SSR) and suitable terminologies like SNOMED-CT can enhance data retrieval and analysis, fostering large-scale studies and collaboration. However, the still large prevalence of narrative reports in our laboratories warrants alternative and automated labeling approaches. In this project, natural language processing (NLP) methods were used to associate SNOMED-CT codes to structured and unstructured reports from an Italian Digital Pathology Department.

Evolving educational landscape in pathology: a comprehensive bibliometric and visual analysis including digital teaching and learning resources.

Aims: Pathology education is a core component of medical training, and its literature is critical for refining educational modalities. We performed a cross-sectional bibliometric analysis to explore publications on pathology education, focusing on new medical education technologies.

Methods: The analysis identified 64 pathology journals and 53 keywords.

Perspective of a Pathologist on Benchmark Strategies for Artificial Intelligence Development in Organ Transplantation.

Transplant pathology of donors is a highly specialized field comprising both the evaluation of organ donor biopsy for the oncological risk transmission and to guide the organ allocation. Timing is critical in transplant procurement since organs must be recovered as soon as possible to ensure the best possible outcome for the recipient. To all this is added the fact that the evaluation of a donor causes difficulties in many cases and the impact of these assessments is paramount, considering the possible recovery of organs that would have been erroneously discarded or, conversely, the possibly correct discarding of donors with unacceptable risk profiles.

PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.

Background: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict treatment response before administering the therapy.

Methods: In this retrospective study, we developed hypothesis-driven interpretable biomarkers based on deep learning, to predict the pathological complete response (pCR, i.

Cutting-edge technology and automation in the pathology laboratory.

One of the goals of pathology is to standardize laboratory practices to increase the precision and effectiveness of diagnostic testing, which will ultimately enhance patient care and results. Standardization is crucial in the domains of tissue processing, analysis, and reporting. To enhance diagnostic testing, innovative technologies are also being created and put into use.

Analysis of the mechanisms regulating soluble PD-1 production and function in human NK cells.

NK cells represent important effectors that play a major role in innate defences against pathogens and display potent cytolytic activity against tumor cells. An array of surface receptors finely regulate their function and inhibitory checkpoints, such as PD-1, can dampen the immune response inducing an immunosuppressive state. Indeed, PD-1 expression in human NK cells correlated with impaired effector function and tumor immune evasion.

Cost analysis of archives in the pathology laboratories: from safety to management.

Context: Despite the reluctance to invest and the challenging estimation of necessary supporting costs, optimising the archives seems to be one of the hottest topics in the future management of the pathology laboratories. Historically, archives were only partially designed to securely store and organise tissue specimens, and tracking systems were often flawed, posing significant risks to patients' health and legal ramifications for pathologists.

Objective: The current review explores the available data from the literature on archives' management in pathology, including comprehensive business plans, structure setup, outfit, inventories, ongoing conservation and functional charges.

Delphi expert consensus for whole slide imaging in thyroid cytopathology.

Objective: Despite an increase in thyroid fine needle aspiration (FNA) and advances in whole slide imaging (WSI) adoption, digital pathology is still considered inadequate for primary diagnosis of these cases. Herein, we aim to validate the utility of WSI in thyroid FNAs employing the Delphi method strategy.

Methods: A panel of experts from seven reference cytology centres was recruited.

The roles of different forms of IL-15 in human melanoma progression.

Background: Melanoma is a lethal skin cancer, and the risk of developing it is increased by exposure to ultraviolet (UV) radiation. The production of cytokines such as interleukin-15 (IL-15), induced by the exposure of skin cells to UV rays, could also promote melanoma development. The aim of this study is to investigate the possible role of Interleukin-15/Interleukin-15 Receptor α (IL-15/IL-15Rα) complexes in melanoma development.

Effect of Radio-Chemotherapy on PD-L1 Immunohistochemical Expression in Head and Neck Squamous Cell Carcinoma.

Background: Programmed death-ligand 1 (PD-L1) checkpoint inhibitors represent a mainstay of therapy in head and neck squamous cell cancer (HNSCC). However, little is known about the influence of combined therapy on PD-L1 expression. The study aims to gather evidence on this topic.

Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases.

Infectious diseases still threaten the global community, especially in resource-limited countries. An accurate diagnosis is paramount to proper patient and public health management. Identification of many microbes still relies on manual microscopic examination, a time-consuming process requiring skilled staff.