From Morphology to Molecules: Advances in the Distinction of Multiple Primary Lung Cancers From Intrapulmonary Metastases in Non-Small Cell Lung Cancer.

The increasing incidence of multiple lung nodules underscores the need for precise differentiation between multiple primary lung cancers (MPLCs) and intrapulmonary metastases (IPMs). This distinction impacts patient prognosis and treatment strategies. The prevalence of multiple lung nodules, ranging from 19.7% to 55.5%, highlights the clinical significance of this challenge. Historically, the role of histopathology, particularly comprehensive histology assessment (CHA), has been pivotal in differentiating MPLCs and IPMs. However, CHA has significant limitations, resulting in a constant search for a better way to distinguish those lesions. The best strategy for delineating MPLCs from IPMs is a multidisciplinary approach combining clinical data, radiology, histology, and molecular methods. Histology provides architectural and cellular characteristics, radiology contributes anatomic context and lesion characterization, and molecular methods reveal molecular features critical for accurate differentiation. Incorporating clinical data further enhances diagnostic precision. This review presents current knowledge and current approaches to multiple lung tumors. It is clear that even with a combination of pathology, radiology, and molecular data, definitive classification of multifocal lung tumors is not always possible.

Breaking Barriers: AI's Influence on Pathology and Oncology in Resource-Scarce Medical Systems.

The application of artificial intelligence to improve the access of cancer patients to high-quality medical care is one of the goals of modern medicine. Pathology constitutes the foundation of modern oncologic treatment, and its role has expanded far beyond diagnosis into predicting treatment response and overall survival. However, the funding of pathology is often an afterthought in resource-scarce medical systems. The increased digitalization of pathology has paved the way towards the potential use of artificial intelligence tools for improving pathologist efficiency and extracting more information from tissues. In this review, we provide an overview of the main research directions intersecting with artificial intelligence and pathology in relation to oncology, such as tumor classification, the prediction of molecular alterations, and biomarker quantification. We then discuss examples of tools that have matured into clinical products and gained regulatory approval for clinical use. Finally, we highlight the main hurdles that stand in the way of the digitalization of pathology and the application of artificial intelligence in pathology while also discussing possible solutions.

Exploring the pathologist's role in understanding COVID-19: from pneumonia to long-COVID lung sequelae.

The crucial role of pathologists in enhancing our understanding of SARS-CoV-2-related disease, from initial pneumonia manifestations to persistent long COVID lung symptoms, is the focus of this review. Pathological explorations have offered unprecedented insights into the early stages of severe COVID-19, shedding light on the interplay between the virus and subsequent complications, thereby shaping clinical approaches. Growing interest is directed to residual lung abnormalities of COVID-19 survivors. Although various radiological studies reported long-lasting pulmonary changes (e.g., ground glass opacities, reticulations, and bronchiectasis), the true incidence of pulmonary fibrosis and corresponding pathological findings in these patients remains largely unknown. There are a few high-impact and knowledgeable works on late complications in COVID-19 survivors, several coming from explant or autopsy cases, and rare cases from in vivo sampling. The study of biopsy samples has further deepened our knowledge of the aftermath of COVID-19 on lung tissue, uncovering alterations at the cellular level and shifts in vascular and epithelial dynamics. Despite the substantial progress made, future research is needed to devise a uniform strategy for interpreting lung biopsies, with a focus on leveraging advanced tools such as molecular and digital pathology techniques, along with artificial intelligence.

Comparative Evaluation of Breast Ductal Carcinoma Grading: A Deep-Learning Model and General Pathologists' Assessment Approach.

Breast cancer is the most prevalent neoplasia among women, with early and accurate diagnosis critical for effective treatment. In clinical practice, however, the subjective nature of histological grading of infiltrating ductal adenocarcinoma of the breast (DAC-NOS) often leads to inconsistencies among pathologists, posing a significant challenge to achieving optimal patient outcomes. Our study aimed to address this reproducibility problem by leveraging artificial intelligence (AI). We trained a deep-learning model using a convolutional neural network-based algorithm (CNN-bA) on 100 whole slide images (WSIs) of DAC-NOS from the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) dataset. Our model demonstrated high precision, sensitivity, and F1 score across different grading components in about 17.5 h with 19,000 iterations. However, the agreement between the model's grading and that of general pathologists varied, showing the highest agreement for the mitotic count score. These findings suggest that AI has the potential to enhance the accuracy and reproducibility of breast cancer grading, warranting further refinement and validation of this approach.

Cutaneous Polymeric-Micelles-Based Hydrogel Containing Origanum vulgare L. Essential Oil: In Vitro Release and Permeation, Angiogenesis, and Safety Profile In Ovo.

Origanum vulgare var. vulgare essential oil (OEO) is known as a natural product with multiple beneficial effects with application in dermatology. Oregano essential oil represents a potential natural therapeutic alternative for fibroepithelial polyps (FPs), commonly known as skin tags. Innovative formulations have been developed to improve the bioavailability and stability of essential oils. In this study, we aimed to evaluate the morphology of a polymeric-micelles-based hydrogel (OEO-PbH), the release and permeation profile of oregano essential oil, as well as to assess in vivo the potential effects on the degree of biocompatibility and the impact on angiogenesis in ovo, using a chick chorioallantoic membrane (CAM). Scanning electron microscopy (SEM) analysis indicated a regular aspect after the encapsulation process, while in vitro release studies showed a sustained release of the essential oil. None of the tested samples induced any irritation on the CAM and the limitation of the angiogenic process was noted. OEO-PbH, with a sustained release of OEO, potentially enhances the anti-angiogenic effect while being well tolerated and non-irritative by the vascularized CAM, especially on the blood vessels (BVs) in the presence of leptin treatment. This is the first evidence of in vivo antiangiogenic effects of a polymeric-micelle-loaded oregano essential oil, with further mechanistic insights for OEO-PbH formulation, involving leptin as a possible target. The findings suggest that the OEO-containing polymeric micelle hydrogel represents a potential future approach in the pathology of cutaneous FP and other angiogenesis-related conditions.

Stability Profile and Clinical Evaluation of an Innovative Hydrogel Containing Polymeric Micelles as Drug Delivery Systems with Oregano Essential Oil against Fibroepithelial Polyps.

Skin tags, also known as fibroepithelial polyps (FPs) or acrochordons, are soft, pigmented excrescences, with a prevalence of 50-60% in the population, occurring especially in the fourth decade of life. To date, FPs have been efficiently eliminated using minimum invasive methods such as surgical removal, cauterization, laser irradiation, and cryosurgery. Over-the-counter treatments are also of interest for patients due to their non-invasive character, but their clinical efficiency has not been clearly demonstrated. This study was designed in order to evaluate the efficacy of a modern-pharmaceutical-formulation-type poloxamer-based binary hydrogel, having Origanum vulgare L. essential oil (OEO-PbH) as an active ingredient in the management of FPs. The formulation has been shown to possess good qualities in terms of stability and sterility. Non-invasive measurements revealed changes in some physiological skin parameters. An increase in transepidermal water loss (TEWL) and erythema index was noted, while skin surface water content (SWC) decreased during eight weeks of treatment. The macroscopic evaluation revealed that the FPs dried and shrunk after topical treatment with OEO-PbH. Clinically, patients presented a lowering of the number of lesions on the treated area of 20-30% after one month of treatment and around 50% after the second month. Histopathological examination suggests that topical treatment with OEO-PbH may induce histological changes in the epidermis, dermis, and fibrovascular cores of FPs, including a loss of thickness, reduced size and number of blood vessels, and low cellularity. These changes may contribute to the observed reduction in size of FPs after treatment with OEO-PbH.

Addressing the unmet need for a comprehensive lung cancer registry in Romania.

In this perspective article, we describe the vital need for a well-organized cancer registry in Romania, where lung cancer prevalence and mortality rates are alarmingly high. We discuss contributing factors such as increased use of chest X-rays and CT scans during the COVID-19 pandemic and delayed diagnoses due to limited medical care access. With the nation's characteristically limited access to healthcare, it is plausible that the surge in acute imaging for COVID-19 has inadvertently resulted in a higher detection rate of lung cancer. This inadvertent early detection underscores the vital need for a well-organized cancer registry in Romania, where lung cancer prevalence and mortality rates are alarmingly high. Although impactful, these factors are not the primary causes of the high lung cancer cases in the country. We provide an overview of current options and propose future perspectives for epidemiological monitoring of lung cancer patients in Romania, aiming to enhance patient care, bolster research, and promote data-driven policy-making. While our primary focus is establishing a national registry for lung cancer, we address challenges, considerations, and best practices applicable to all cancer types. Through our proposed strategies and recommendations, we aim to contribute to the development and improvement of a comprehensive national cancer registry system in Romania.

Comprehensive bronchoalveolar lavage characterization in COVID-19 associated acute respiratory distress syndrome patients: a prospective cohort study.

COVID-19-related acute respiratory distress syndrome (CARDS) is associated with high mortality rates. We still have limited knowledge of the complex alterations developing in the lung microenvironment. The goal of the present study was to comprehensively analyze the cellular components, inflammatory signature, and respiratory pathogens in bronchoalveolar lavage (BAL) of CARDS patients (16) in comparison to those of other invasively mechanically ventilated patients (24). In CARDS patients, BAL analysis revealed: SARS-CoV-2 infection frequently associated with other respiratory pathogens, significantly higher neutrophil granulocyte percentage, remarkably low interferon-gamma expression, and high levels of interleukins (IL)-1ß and IL-9. The most important predictive variables for worse outcomes were age, IL-18 expression, and BAL neutrophilia. To the best of our knowledge, this is the first study that was able to identify, through a comprehensive analysis of BAL, several aspects relevant to the complex pathophysiology of CARDS.

Large Lung Consolidation: A Rare Presentation of Pulmonary Sarcoidosis.

Sarcoidosis is a complex inflammatory disease of uncertain origin, characterized by non-necrotizing epithelioid cell granulomas (NNEGs) affecting multiple organ systems. Although many different clinical and pathological phenotypes can be present, with different organs involved, the lung is the most common site described. In this case report, we (a) present and discuss the broad differential diagnosis of a patient presenting with a solitary lung mass with clinical and imaging features of lung cancer that ultimately was confirmed with a rare manifestation of stage II pulmonary sarcoidosis, and (b) analyze and compare similar cases from the literature.

Unique Growth Pattern Presentation of a Papillary Renal Cell Carcinoma.

Papillary renal cell carcinoma (PRCC) is defined by the WHO 2022 classification as a malignant tumor derived from the renal tubular epithelium. However, the WHO 2016 classification subdivided PRCC into two types, with type 1 PRCC showing papillae covered by a single layer of neoplastic cells, and type II PRCC, which can show multiple types of histologies and is more aggressive. The WHO 2022 classification eliminated the subcategorization of PRCC. Here, we present a histopathological case study with a 4-year follow-up diagnosed in 2018 as type I PRCC (WHO 2016) with intra-pyelocalyceal growth pattern in a 59-year-old male patient with a history of Type II diabetes mellitus, left-sided renal-ureteral lithiasis, and benign hypertrophy of the prostate. Microscopically the tumor was composed of small cuboidal cells with inconspicuous nucleoli, arranged on a single layer of tubulo-papillary cores, and scant, foamy macrophages. The tumor had a non-infiltrative, expansive pyelocalyceal growth pattern. Immunohistochemically (IHC), the tumor cells were CK7-intense and diffusely positive, and stained granular for AMACR. Next-generation sequencing (NGS) was performed for the tumor and the normal adjacent tissue for in-depth pathological characterization. To our knowledge, this is the first reported case where a PRCC displays this unique intra-pyelocalyceal growth pattern, mimicking a urothelial cell carcinoma of the renal pelvis system.

Bronchoalveolar Lavage as a Diagnostic Tool in an Atypical Pulmonary Langerhans Cell Histiocytosis.

Pulmonary Langerhans cell histiocytosis (PLCH) is an uncommon diffuse cystic lung disease that occurs almost exclusively in young adult smokers. High-resolution computed tomography of the chest allows a confident diagnosis of PLCH in typical presentation, when nodules, cavitating nodules, and cysts coexist and show a predominance for the upper and middle lung. Atypical presentations require histology for diagnosis. Histologic diagnosis rests on the demonstration of increased numbers of Langerhans cells and/or specific histological changes. PLCH is one of the few diseases in which bronchoalveolar lavage (BAL) has a high diagnostic value and can in some circumstances replace lung biopsy. We present a case of PLCH in an elderly non-smoker. Chest imaging revealed the presence of advanced interstitial lung disease with a fibrocystic pattern. BAL cellular analyses disclosed a macrophage pattern with CD1a phenotype that strongly supports the PLCH diagnosis, even in the setting of atypical clinical presentation and a lack of smoking exposure. PLCH is extremely rare in non-smokers and could represent a distinct phenotype.

Epithelioid Pleural Mesothelioma Is Characterized by Tertiary Lymphoid Structures in Long Survivors: Results from the MATCH Study.

Pleural mesothelioma (PM) is an aggressive tumor with few therapeutic options. Although patients with epithelioid PM (ePM) survive longer than non-epithelioid PM (non-ePM), heterogeneity of tumor response in ePM is observed. The role of the tumor immune microenvironment (TIME) in the development and progression of PM is currently considered a promising biomarker. A few studies have used high-throughput technologies correlated with TIME evaluation and morphologic and clinical data. This study aimed to identify different morphological, immunohistochemical, and transcriptional profiles that could potentially predict the outcome. A retrospective multicenter cohort of 129 chemonaive PM patients was recruited. Tissue slides were reviewed by dedicated pathologists for histotype classification and immunophenotype of tumor-infiltrating lymphocytes (TILs) and lymphoid aggregates or tertiary lymphoid structures (TLS). ePM (n = 99) survivors were further classified into long (>36 months) or short (<12 months) survivors. RNAseq was performed on a subset of 69 samples. Distinct transcriptional profiling in long and short ePM survivors was found. An inflammatory background with a higher number of B lymphocytes and a prevalence of TLS formations were detected in long compared to short ePM survivors. These results suggest that B cell infiltration could be important in modulating disease aggressiveness, opening a pathway for novel immunotherapeutic approaches.

Optimization of Complete Rat Heart Decellularization Using Artificial Neural Networks.

Whole organ decellularization techniques have facilitated the fabrication of extracellular matrices (ECMs) for engineering new organs. Unfortunately, there is no objective gold standard evaluation of the scaffold without applying a destructive method such as histological analysis or DNA removal quantification of the dry tissue. Our proposal is a software application using deep convolutional neural networks (DCNN) to distinguish between different stages of decellularization, determining the exact moment of completion. Hearts from male Sprague Dawley rats (n = 10) were decellularized using 1% sodium dodecyl sulfate (SDS) in a modified Langendorff device in the presence of an alternating rectangular electric field. Spectrophotometric measurements of deoxyribonucleic acid (DNA) and total proteins concentration from the decellularization solution were taken every 30 min. A monitoring system supervised the sessions, collecting a large number of photos saved in corresponding folders. This system aimed to prove a strong correlation between the data gathered by spectrophotometry and the state of the heart that could be visualized with an OpenCV-based spectrometer. A decellularization completion metric was built using a DCNN based classifier model trained using an image set comprising thousands of photos. Optimizing the decellularization process using a machine learning approach launches exponential progress in tissue bioengineering research.

Analysis of Tumor Depth Invasion With Anti-Smoothelin Antibody in Equivocal Transurethral Resection of Urinary Bladder Tumor Surgical Specimens.

OBJECTIVE: To examine the expression and value of the smoothelin marker in control cases, to standardize the working method, and to analyze its application in pathologic staging process of problematic transurethral resection of bladder tumor (TURBT) cases. MATERIAL AND METHODS: Immunohistochemical (IHC) staining was performed on tumor-free bladder wall sections, tumor-free large bowel sections, TURBTs with unequivocal tumor stage, and TURBTs with equivocal stage. The IHC staining of muscularis mucosa (MM), muscularis propria (MP), and blood vessels was evaluated semiquantitatively. RESULTS: Smoothelin IHC staining pattern ranged from negative (30% to 67% cases) to 2+ (0% to 15% cases) in MM and from 1+ (10% to 50% cases) to 3+ (9% to 48% cases) in MP. When compared on the same slide, the smoothelin expression of MP showed a stronger staining intensity than the one of the MM in all the analyzed cases. Blood vessel muscle cells stained in a constant intensity as the MM (r = 0.9808; r = 0.9604). Smoothelin determined restaging of 33% of the problematic TURBT cases. CONCLUSION: Smoothelin is an IHC marker that shows differential staining between coexistent MM and MP; however, variations in staining intensity and pattern may occur, aspects that can be influenced by different technique variables. We recommend using this marker as a diagnostic tool in problematic TURBT cases only when there is sufficient experience in control cases with this antibody.

The natural adaptive evolution of cancer: The metastatic ability of cancer cells.

The ability of cancer to adapt renders it one of the most challenging pathologies of all time. It is the most dreaded pathological entity because of its capacity to metastasize to distant sites in the body, and 90% of all cancer-related deaths recorded to date are attributed to metastasis. Currently, three main theories have been proposed to explain the metastatic pathway of cancer: the epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) hypothesis (1), the cancer stem cell hypothesis (2), and the macrophage-cancer cell fusion hybrid hypothesis (3). We propose a new hypothesis, i.e., under the effect of particular biochemical and/or physical stressors, cancer cells can undergo nuclear expulsion with subsequent macrophage engulfment and fusion, with the formation of cancer fusion cells (CFCs). The existence of CFCs, if confirmed, would represent a novel metastatic pathway and a shift in the extant dogma of cancer; consequently, new treatment targets would be available for this adaptive pathology.