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Context.—: Mesothelioma is an uncommon tumor that can be difficult to diagnose., Objective.—: To provide updated, practical guidelines for the pathologic diagnosis of mesothelioma., Data Sources.—: Pathologists involved in the International Mesothelioma Interest Group and others with expertise in mesothelioma contributed to this update. Reference material includes peer-reviewed publications and textbooks., Conclusions.—: There was consensus opinion regarding guidelines for (1) histomorphologic diagnosis of mesothelial tumors, including distinction of epithelioid, biphasic, and sarcomatoid mesothelioma; recognition of morphologic variants and patterns; and recognition of common morphologic pitfalls; (2) molecular pathogenesis of mesothelioma; (3) application of immunohistochemical markers to establish mesothelial lineage and distinguish mesothelioma from common morphologic differentials; (4) application of ancillary studies to distinguish benign from malignant mesothelial proliferations, including BAP1 and MTAP immunostains; novel immunomarkers such as Merlin and p53; fluorescence in situ hybridization (FISH) for homozygous deletion of CDKN2A; and novel molecular assays; (5) practical recommendations for routine reporting of mesothelioma, including grading epithelioid mesothelioma and other prognostic parameters; (6) diagnosis of mesothelioma in situ; (7) cytologic diagnosis of mesothelioma, including use of immunostains and molecular assays; and (8) features of nonmalignant peritoneal mesothelial lesions., Competing Interests: The authors have no relevant financial interest in the products or companies described in this article., (© 2024 College of American Pathologists.)

Background: Around the world, individuals are living longer, but an increased average lifespan does not always equate to an increased healthspan. With advancing age, the increased prevalence of ageing-related diseases can have a significant impact on health status, functional capacity, and quality of life. It is therefore vital to develop comprehensive classification and staging systems for ageing-related pathologies, diseases and syndromes. This will allow societies to better identify, quantify, understand, and meet the healthcare, workforce, wellbeing, and socioeconomic needs of ageing populations, while supporting the development and utilisation of interventions to prevent or to slow, halt or reverse the progression of ageing-related pathologies., Methods: The foundation for developing such classification and staging systems is to define the scope of what constitutes an ageing-related pathology, disease or syndrome. To this end, a consensus meeting was hosted by the International Consortium to Classify Ageing-Related Pathologies (ICCARP), on February 19 th , 2024, in Cardiff, UK, and was attended by 150 recognised experts. Discussions and voting were centred on provisional criteria that had been distributed prior to the meeting. The participants debated and voted on these. Each criterion required a consensus agreement of ≥70% for approval., Results: The accepted criteria for an ageing-related pathology, disease or syndrome were: Develops and/or progresses with increasing chronological age.Should be associated with, or contribute to, functional decline, or an increased susceptibility to functional decline.Evidenced by studies in humans., Conclusions: Criteria for an ageing-related pathology, disease or syndrome have been agreed by an international consortium of subject experts. These criteria will now be used by the ICCARP for the classification and ultimately staging of ageing-related pathologies, diseases and syndromes.

Occupational lung/thoracic diseases are a major global public health issue. They comprise a diverse spectrum of health conditions with complex pathology, most of which arise following chronic heavy workplace exposures to various mineral dusts, metal fumes, or following inhaled organic particulate reactions. Many occupational lung diseases could become irreversible; thus accurate diagnosis is mandatory to minimize dust exposure and consequently reduce damage to the respiratory system. Lung biopsy is usually required when exposure history is inconsistent with imaging, in case of unusual or new exposures, in case of unexpected malignancy, and in cases in which there are claims for personal injury and legal compensation. In this paper, we provide an overview of the most frequent occupational lung diseases with a focus on pathological diagnosis. This is a paper that summarizes the expert opinion from a group of European pathologists, together with contributions from other specialists who are crucial for the diagnosis and management of these diseases. Indeed, tight collaboration of all specialists involved in the workup is mandatory as many occupational lung diseases are misdiagnosed or go unrecognized. This document provides a guide for pathologists in practice to facilitate the accurate diagnosis of occupational lung disease. The review article reports relevant topics discussed during an educational course held by expert pathologists, active members of the Pulmonary Pathology Working Group of the European Society of Pathology. The course was endorsed by the University of Padova as a "winter school" (selected project in the call for "Shaping a World-class University" 2022)., (© 2024. The Author(s).)

The histopathologic distinction of lung adenocarcinoma (LADC) subtypes is subject to high interobserver variability, which can compromise the optimal assessment of patient prognosis. Therefore, this study developed convolutional neural networks capable of distinguishing LADC subtypes and predicting disease-specific survival, according to the recently established LADC tumor grades. Consensus LADC histopathologic images were obtained from 17 expert pulmonary pathologists and one pathologist in training. Two deep learning models (AI-1 and AI-2) were trained to predict eight different LADC classes. Furthermore, the trained models were tested on an independent cohort of 133 patients. The models achieved high precision, recall, and F1 scores exceeding 0.90 for most of the LADC classes. Clear stratification of the three LADC grades was reached in predicting the disease-specific survival by the two models, with both Kaplan-Meier curves showing significance (P = 0.0017 and 0.0003). Moreover, both trained models showed high stability in the segmentation of each pair of predicted grades with low variation in the hazard ratio across 200 bootstrapped samples. These findings indicate that the trained convolutional neural networks improve the diagnostic accuracy of the pathologist and refine LADC grade assessment. Thus, the trained models are promising tools that may assist in the routine evaluation of LADC subtypes and grades in clinical practice., (Copyright © 2023 American Society for Investigative Pathology. All rights reserved.)

Context.—: The accurate identification of different lung adenocarcinoma histologic subtypes is important for determining prognosis but can be challenging because of overlaps in the diagnostic features, leading to considerable interobserver variability., Objective.—: To provide an overview of the diagnostic agreement for lung adenocarcinoma subtypes among pathologists and to create a ground truth using the clustering approach for downstream computational applications., Design.—: Three sets of lung adenocarcinoma histologic images with different evaluation levels (small patches, areas with relatively uniform histology, and whole slide images) were reviewed by 17 international expert lung pathologists and 1 pathologist in training. Each image was classified into one or several lung adenocarcinoma subtypes., Results.—: Among the 4702 patches of the first set, 1742 (37%) had an overall consensus among all pathologists. The overall Fleiss κ score for the agreement of all subtypes was 0.58. Using cluster analysis, pathologists were hierarchically grouped into 2 clusters, with κ scores of 0.588 and 0.563 in clusters 1 and 2, respectively. Similar results were obtained for the second and third sets, with fair-to-moderate agreements. Patches from the first 2 sets that obtained the consensus of the 18 pathologists were retrieved to form consensus patches and were regarded as the ground truth of lung adenocarcinoma subtypes., Conclusions.—: Our observations highlight discrepancies among experts when assessing lung adenocarcinoma subtypes. However, a subsequent number of consensus patches could be retrieved from each cluster, which can be used as ground truth for the downstream computational pathology applications, with minimal influence from interobserver variability., Competing Interests: This paper is based on results obtained from a project, 19100971-0, commissioned by the New Energy and Industrial Technology Development Organization (NEDO)., (© 2023 College of American Pathologists.)

The molecular alterations of pleomorphic mesotheliomas are largely unknown. In the present study, we performed whole-exome sequencing (WES) on 24 pleomorphic mesotheliomas in order to better characterize the molecular profile of this rare histologic variant. BAP1 protein expression and CDKN2A deletion by FISH were also evaluated. Significantly mutated genes included BAP1 (35%), NF2 (13%), LATS2 (8%), TP53 (5%), and LATS1 (3%). BAP1 alterations most frequently co-occurred with deletions of chromosomes 4, 9, and 13. Other important genetic alterations in pleomorphic mesotheliomas included truncating mutations in NF2 (3 of 24; 12.5%), LATS2 (2 of 24; 8%), TP53 (1 of 24; 4%), and PBRM1 (1 of 24; 4%). Focal losses of chromosome 9p21 were most common copy number alterations (11 of 24 cases; 46%), and were assessed by WES and targeted FISH. The second most common were deletions of chromosome 4 (8 of 24; 33% pleomorphic mesotheliomas). Three cases of pleomorphic mesothelioma did not show any mutations, copy number alterations, or LOH. This first WES analysis of pleomorphic mesotheliomas did not identify novel or unique mutations. In contrast to transitional mesothelioma that was reclassified as sarcomatoid variant based on transcriptome data, pleomorphic mesotheliomas are molecularly heterogeneous and therefore their reclassification into single subtype is more difficult., (© 2021. The Author(s), under exclusive licence to United States & Canadian Academy of Pathology.)