Attanoos, Richard

ABSTRACTBackground and ObjectiveThe diagnosis of interstitial lung diseases (ILDs) often relies on the integration of various clinical, radiological, and histopathological data. Achieving high diagnostic accuracy in ILDs, particularly for distinguishing usual interstitial pneumonia (UIP), is challenging and requires a multidisciplinary approach. Therefore, this study aimed to develop a multimodal artificial intelligence (AI) algorithm that combines computed tomography (CT) and histopathological images to improve the accuracy and consistency of UIP diagnosis.MethodsA dataset of CT and pathological images from 324 patients with ILD between 2009 and 2021 was collected. The CT component of the model was trained to identify 28 different radiological features. The pathological counterpart was developed in our previous study. A total of 114 samples were selected and used for testing the multimodal AI model. The performance of the multimodal AI was assessed through comparisons with expert pathologists and general pathologists.ResultsThe developed multimodal AI demonstrated a substantial improvement in distinguishing UIP from non‐UIP, achieving an AUC of 0.92. When applied by general pathologists, the diagnostic agreement rate improved significantly, with a post‐model κ score of 0.737 compared to 0.273 pre‐model integration. Additionally, the diagnostic consensus rate with expert pulmonary pathologists increased from κ scores of 0.278–0.53 to 0.474–0.602 post‐model integration. The model also increased diagnostic confidence among general pathologists.ConclusionCombining CT and histopathological images, the multimodal AI algorithm enhances pathologists' diagnostic accuracy, consistency, and confidence in identifying UIP, even in cases where specialised expertise is limited. image

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.

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.

Abstract Objectives Numerous studies on malignant mesothelioma (MM) highlight the prognostic importance of histologic subtype, nuclear grade, and necrosis. This study compares these parameters in paired biopsy and resection specimens of pleural MM. Methods Histologic subtype, percentage of epithelioid morphology, nuclear grade, and the presence or absence of necrosis were compared in 429 paired biopsies and resection specimens of pleural MM from 19 institutions. Results Histologic subtype was concordant in 81% of cases (κ = 0.58). When compared with resection specimens, epithelioid morphology at biopsy had a positive predictive value (PPV) of 78.9% and a negative predictive value (NPV) of 93.5%; sarcomatoid morphology showed high PPV (92.9%) and NPV (99.3%), and biphasic morphology PPV was 89.7% and NPV was 79.7%. Agreement of the percentage of epithelioid morphology was fair (κ = 0.27). Nuclear grade and necrosis were concordant in 75% (κ = 0.59) and 81% (κ = 0.53) of cases, respectively. Nuclear grade showed moderate (κ = 0.53) and substantial (κ = 0.67) agreement from patients with and without neoadjuvant therapy, respectively, and necrosis showed moderate (κ = 0.47 and κ = 0.60) agreement, respectively, in the same subsets of paired specimens. Conclusions Paired biopsy-resection specimens from pleural MM show overall moderate agreement in pathologic parameters. These findings may help guide postbiopsy management and triage of patients with MM.

Context.— Accurate diagnosis of idiopathic pulmonary fibrosis (IPF) requires multidisciplinary diagnosis that includes clinical, radiologic, and often pathologic assessment. In 2018, the American Thoracic Society, European Respiratory Society, Japanese Respiratory Society, and the Latin American Thoracic Society (ATS/ERS/JRS/ALAT) and the Fleischner Society each published guidelines for the diagnosis of IPF, which include criteria for 4 categories of confidence of a histologic usual interstitial pneumonia (UIP) pattern. Objective.— To (1) identify the role of the guidelines in pathologic assessment of UIP; (2) analyze the 4 guideline categories, including potential areas of difficulty; and (3) determine steps the Pulmonary Pathology Society and the greater pulmonary pathology community can take to improve current guideline criteria and histopathologic diagnosis of interstitial lung disease. Data Sources.— Data were derived from the guidelines, published literature, and clinical experience. Conclusions.— Both guidelines provide pathologists with a tool to relay to the clinician the likelihood that a biopsy represents UIP, and serve as an adjunct, not a replacement, for traditional histologic diagnosis. There are multiple challenges with implementing the guidelines, including (1) lack of clarity on the quantity and quality of histologic findings required, (2) lack of recognition that histologic features cannot be assessed independently, and (3) lack of guidance on how pathologists should incorporate clinical and radiographic information. Current criteria for “probable UIP” and “indeterminate for UIP” hinder accurate reflection of the likelihood of IPF. These challenges highlight the need for further morphologic-based investigations in the field of pulmonary pathology.

Context .—Malignant mesothelioma (MM) is an uncommon tumor that can be difficult to diagnose. Objective .—To provide updated practical guidelines for the pathologic diagnosis of MM. Data Sources .—Pathologists involved in the International Mesothelioma Interest Group and others with an interest in the field contributed to this update. Reference material includes peer-reviewed publications and textbooks. Conclusions .—There was consensus opinion regarding (1) distinction of benign from malignant mesothelial proliferations (both epithelioid and spindle cell lesions), (2) cytologic diagnosis of MM, (3) key histologic features of pleural and peritoneal MM, (4) use of histochemical and immunohistochemical stains in the diagnosis and differential diagnosis of MM, (5) differentiation of epithelioid MM from various carcinomas (lung, breast, ovarian, and colonic adenocarcinomas, and squamous cell and renal cell carcinomas), (6) diagnosis of sarcomatoid mesothelioma, (7) use of molecular markers in the diagnosis of MM, (8) electron microscopy in the diagnosis of MM, and (9) some caveats and pitfalls in the diagnosis of MM. Immunohistochemical panels are integral to the diagnosis of MM, but the exact makeup of panels used is dependent on the differential diagnosis and on the antibodies available in a given laboratory. Immunohistochemical panels should contain both positive and negative markers. It is recommended that immunohistochemical markers have either sensitivity or specificity greater than 80% for the lesions in question. Interpretation of positivity generally should take into account the localization of the stain (eg, nuclear versus cytoplasmic) and the percentage of cells staining (>10% is suggested for cytoplasmic membranous markers). These guidelines are meant to be a practical reference for the pathologist.