Archives of pathology & laboratory medicine最新文献

Context.—: Accurate intraoperative assessment of macrovesicular steatosis in donor liver biopsies is critical for transplant decisions but is often limited by interobserver variability and freezing artifacts that can obscure histologic details. Artificial intelligence (AI) offers a potential solution for standardized and reproducible evaluation.

Objective.—: To evaluate the diagnostic performance of 2 self-supervised learning (SSL)-based foundation models, Prov-GigaPath and UNI, for classifying macrovesicular steatosis on frozen liver biopsy sections, compared with assessments by surgical pathologists.

Design.—: This retrospective study included 131 frozen liver biopsy specimens from 68 donors, collected between November 2022 and September 2024. Slides were digitized into whole slide images, tiled into patches, and used to extract embeddings with Prov-GigaPath and UNI; slide-level classifiers were then trained and tested. Intraoperative diagnoses by on-call surgical pathologists were compared with ground truth determined from independent reviews of permanent sections by 2 liver pathologists. Accuracy was evaluated for both a 5-category classification and a clinically significant binary threshold (<30% versus ≥30%).

Results.—: For the binary classification, Prov-GigaPath achieved 96.4% accuracy, UNI 85.7%, and surgical pathologists, 89.3% (P = .37). For the 5-category classification, accuracies were lower: Prov-GigaPath, 57.1%; UNI, 50.0%; and pathologists, 64.2% (P = .47). Misclassification occurred mainly in intermediate categories (5% to <30% steatosis).

Conclusions.—: SSL-based foundation models performed comparably to surgical pathologists at the clinically relevant threshold of less than 30% versus 30% or greater. These findings support the potential role of AI in standardizing intraoperative evaluation of donor liver biopsies; however, the small sample size limits generalizability and requires validation in larger, balanced cohorts.

Context.—: Histopathologic lymph node (LN) status has a high prognostic impact in patients with non-small cell lung cancer (NSCLC). However, there are no detailed recommendations for LN workup beyond routine hematoxylin-eosin (H&E) sections in current guidelines.

Objective.—: To systematically compare the results of routine H&E, ultrastaging (US), and immunocytology (IC) LN workup for the reporting of LN involvement in NSCLC patients.

Design.—: Extensive US including 10 additional step sections with serial sections for H&E and immunohistochemistry for pancytokeratin, BerEP4, and transcription termination factor 1 (TTF1) and/or p40 was performed on 122 LNs previously assessed as metastasis free during initial pathologic workup by H&E slides. One-half of each LN had also been examined by IC after disaggregation.

Results.—: Twenty-four of the initially negative 122 LNs (19.7%) were positive using US and 74 of 122 (60.7%) were positive by IC, resulting in a 3.1-fold higher detection rate by IC (P = .01, χ2 test). Comparisons between initiating colony detection by US and disseminated cancer cell density (number of disseminated cancer cells per million LN cells) revealed that a disseminated cancer cell density value of about 60 reflects metastatic colony formation. Applying this value for LN staging predicted poor outcome better than histopathologic routine, at least in univariate analysis in this relatively small NSCLC cohort.

Conclusions.—: Routine histopathologic workup underestimates LN spread in NSCLC patients and occasionally misses even macrometastases. US confirms and validates the significantly higher sensitivity of IC over routine histopathologic workup. In particular, IC has the potential to improve appropriate staging and prognostic stratification of patients in the future.

Context.—: Anemia is characterized by a decrease in the oxygen-carrying capacity of red blood cells. This condition negatively affects perioperative patients and surgical outcomes. Strategies to manage anemia prior to elective surgeries are needed to improve patient outcomes.

Objective.—: To provide additional evidence that preoperative anemia is associated with increased blood utilization and adverse outcomes in patients undergoing major, elective surgical procedures.

Design.—: A retrospective chart review of major elective surgical procedures at a large urban health care system during January 2024 was performed. One hundred thirty patient charts were reviewed. Patients were categorized into 2 groups: those who were transfused intraoperatively or postoperatively and those who were not transfused. Variables of interest included age, sex, length of stay, American Society of Anesthesiologists Physical Status classification, estimated blood loss and preoperative hemoglobin values, and intraoperative or postoperative blood product utilization. Associations between variables were determined via χ2, point biserial, and Pearson correlation analysis.

Results.—: There is a significant negative relationship between preoperative hemoglobin level and transfusion (-0.45; P < .001) and a significant positive relationship between hemoglobin level and length of stay (0.34; P < .001). Patients who were transfused intraoperatively or postoperatively had a lower average preoperative hemoglobin level (10.1 g/dL versus 12.5 g/dL; P < .001). Patients with lower preoperative hemoglobin levels had an increased predicted probability of transfusion and a longer length of stay.

Conclusions.—: Our results show that preoperative anemia is associated with higher intraoperative or postoperative blood utilization and longer hospitalization. Preoperative anemia clinics and patient blood management programs are strategies that can be used to improve clinical outcomes.

Context.—: The US Food and Drug Administration (FDA) Emergency Use Authorization (EUA) for SARS-CoV-2 assays encompassed both in vitro diagnostic and laboratory-developed tests. Related testing data and documents from EUAs were published on the FDA website as PDF files, constituting a rich data resource.

Objective.—: To highlight the value of structured descriptive and validation data and provide recommendations on improving the quality, accessibility, and shareability of the FDA's digital resources.

Design.—: SARS-CoV-2 diagnostics EUAs and related files were acquired from the FDA, and data were extracted through an iterative manual or automated process with quality assurance in accordance with a set of data entry definitions to generate a data product (ie, data analysis and presentation of data into tables, graphs, and reports, optionally including different data sets) that could be disseminated.

Results.—: Four challenges limited the usability of FDA EUA data, including (1) distinguishing EUA tests owing to similar names or inconsistent naming conventions; (2) document location and tracking owing to inconsistent EUA document identifiers, resource locators, and versioning; (3) data location and retrieval owing to heterogeneous structure and data formatting within EUA documentation; (4) and maintenance of existing data owing to lack of clear and traceable communication around EUA amendments.

Conclusions.—: Converging efforts from disparate groups to extract and synthesize FDA test data reveal an unaddressed need for better organization and communication. Existing FDA data reporting systems must be improved and adapted for the demands of the connected data science era.

Context.—: The World Health Organization (WHO) Classification of Tumours series is a comprehensive guide to tumor classification in various organ systems. The digital release of the 5th edition on endocrine and neuroendocrine tumors occurred in 2022, while the print volume is still pending publication.

Objective.—: To summarize the changes in the 5th edition of the Endocrine and Neuroendocrine Tumours Blue Book compared to the 2017 edition, highlighting updated diagnostic criteria and terminology.

Data sources.—: The 2017 WHO Classification of Tumours of Endocrine and the 2022 WHO Classification of Endocrine and Neuroendocrine Tumours.

Conclusions.—: The 5th edition refines the understanding of neuroendocrine cell relationships in various organs, incorporating the proposed International Agency for Research on Cancer/WHO classification for neuroendocrine neoplasms from 2018. This includes a more detailed cytogenesis-based classification of pituitary neuroendocrine tumors. Key revisions include the reclassification of thyroid neoplasms, based on cytogenesis and pathogenesis, particularly for follicular cell-derived tumors. The text introduces new terminology for benign endocrine proliferations, emphasizing the distinction between hyperplasia and neoplasia. Changes include the reclassification of multifocal, multiglandular parathyroid disease in primary hyperparathyroidism as multiple adenomas in genetic tumor syndromes. The terminologies thyroid follicular nodular disease and adrenocortical nodular disease are introduced. This edition underscores the critical role of accurate immunohistochemistry in endocrine pathology. Standards for quantifying cellular proliferations, including assessing mitotic activity and Ki-67 labeling indices, are discussed across various tumor types. The classification concludes with a chapter on genetic tumor syndromes associated with endocrine tumors. This edition advances our knowledge in endocrine tumors, incorporating cutting-edge molecular information and addressing essential technical considerations in diagnosis and classification.

Context.—: The International Collaboration on Cancer Reporting is a not-for-profit organization whose goal is to develop evidence-based, internationally agreed standardized data sets for each anatomic site to be used throughout the world.

Objective.—: To update the changes in the 2nd edition of the data set suite, including carcinomas of the hypopharynx, larynx and trachea, major salivary glands, nasal cavity and paranasal sinuses, oropharynx and nasopharynx, and oral cavity, and ear and temporal bone tumors, malignant odontogenic tumors, mucosal melanomas of the head and neck, and nodal excisions and neck dissection specimens.

Design.—: International consensus by expert data set authoring committees, especially authors of the World Health Organization head and neck tumor classification.

Results.—: The unique features have been updated based on current research and developments in histologic classification and standardized reporting guidelines. Separation between core and noncore elements is based on data meaningful to prognosis and stratification. The changes are in conjunction with publication of the 5th edition of the World Health Organization head and neck tumor classification.

Conclusions.—: Increased harmonization of reporting and benchmarking improves patient outcomes and international collaborative research.

Context.—: Optical genome mapping (OGM) represents a promising cytogenomic technology that detects structural variants, including fusions, rearrangements, copy number variants, and loss of heterozygosity, in a single assay. Unlike karyotyping, fluorescence in situ hybridization, or chromosomal microarray, OGM leverages long-molecule imaging to map the whole genome with high resolution. This positions OGM as a novel tool for constitutional and somatic/cancer genomics. However, its current and planned utilization in clinical and research settings remains unknown, necessitating further investigation.

Objective.—: To investigate the current utilization of OGM in clinical and research laboratories, assess its applications, and evaluate future utilization strategies.

Design.—: In 2024, a supplemental questionnaire was incorporated into 6 College of American Pathologists proficiency testing programs to evaluate OGM's utilization.

Results.—: Of 921 returned questionnaires, 712 were analyzed after duplicates were removed. Sixty-seven (9.4%) currently offered OGM testing: 5.2% (37) for research only, 1.8% (13) for only clinical use, and 2.4% (17) for both. Future adoption plans showed 7.6% (53 of 700 laboratories) and 7.9% (55 of 700 laboratories) aiming to implement OGM clinically within 12 and 24 months, respectively. The most common applications included hematologic malignancies and constitutional/germline postnatal disorders, followed by prenatal testing. International laboratories demonstrated statistically higher utilization rates than domestic laboratories (P = .001).

Conclusions.—: This first survey on OGM clinical utilization reveals its status as a niche technology, with 67 laboratories currently using it. Its primary clinical applications are in constitutional/germline analysis and hematologic malignancies. Although international laboratories led in 2024, 108 laboratories (domestic and international) plan clinical adoption within 24 months, signaling OGM's potential for broader integration.

Context.—: Cancers in children show incidence distributions by age that cannot be explained by mathematical models designed to understand carcinogenesis in adults. Unlike carcinomas that tend to increase in incidence with age, pediatric cancers demonstrate unique phases of increasing incidence with a peak age of incidence followed by declining incidence. To date, mathematical models of this phenomenon are limited to statistical representations describing the frequency of oncogenic second genetic alterations in genetically susceptible individuals.

Objective.—: To develop a mathematical description of pediatric cancer incidence, we created an algebraic model based on the concept that a limited cell population is available to become Ewing sarcoma.

Design.—: Our algebraic models for the incidence of Ewing sarcoma express incidence as a function of both the risk of oncogenic genetic events and the number of available cells capable of becoming Ewing sarcoma.

Results.—: Our models allow predictions about changes in the abundance of available cells capable of undergoing oncogenesis. This concept can explain the anatomic distribution and incidence by age of Ewing sarcoma. We believe that this concept also explains how the same genetic alterations can be seen in diverse cancer types.

Conclusions.—: Verification of our models for Ewing sarcoma with experimental data can predict how the risk of oncogenic events for pediatric cancers changes with age. Our algebraic model is a novel articulation of the biological concepts that drive pediatric oncogenesis and can be applied to the observed age distributions of nearly all pediatric cancer types.

Context.—: Immune checkpoint inhibitors (ICIs) can trigger severe cutaneous adverse reactions that mimic Stevens-Johnson syndrome/toxic epidermal necrolysis. Reports describe a wide spectrum of cutaneous reactions, including epidermal necrosis, raising questions about whether this represents a distinct clinicopathologic entity.

Objective.—: To review the literature on ICI-related epidermal necrosis (ICIREN), examining terminology, histopathologic features, clinical course, pathophysiology, the pathologist's role in diagnosis, and implications for management.

Data sources.—: A systematic literature search of PubMed and relevant conference proceedings was conducted. Key sources include case series, retrospective reviews, and mechanistic studies detailing ICIREN.

Conclusions.—: ICIs have transformed cancer therapy but are associated with a spectrum of immune-related adverse events, notably cutaneous toxicities. Among the most severe is ICIREN, a reaction that can clinically resemble Stevens-Johnson syndrome and toxic epidermal necrolysis but may follow a distinct, more indolent course. Emerging terminology, including progressive immunotherapy-related mucocutaneous eruption, reflects growing recognition that not all cases fit the paradigm of classic drug-induced Stevens-Johnson syndrome/toxic epidermal necrolysis. ICIREN often presents with delayed onset, variable progression, limited mucosal involvement, and distinct histopathologic features such as lichenoid interface dermatitis and adnexal involvement. Understanding these differences is crucial, as early recognition and management may allow patients to safely continue ICI therapy. The underlying pathogenesis involves checkpoint blockade-driven T-cell activation with potential amplification by additional drug exposures. This review aims to equip pathologists and clinicians with a structured approach to the diagnosis, reporting, and multidisciplinary management of ICIREN, emphasizing the need for clinicopathologic correlation to optimize patient outcomes.

Context.—: Treatments are available for common forms of systemic amyloidosis that show promise for extending and improving the quality of life for patients. Early diagnosis and accurate identification of amyloid fibril type are crucial for successful treatment, but the diagnosis and workup of amyloidosis, is inconsistent among pathologists and laboratories. Thus, the goal of this guideline is to offer recommendations for proper testing and workup for amyloidosis to optimize patient care.

Objective.—: To establish evidence-based recommendations for appropriate laboratory testing to detect amyloidosis and identify the specific amyloidogenic protein.

Design.—: The College of American Pathologists convened a panel of experts to develop recommendations following the standards established by the National Academy of Medicine for developing trustworthy clinical practice guidelines. The panel conducted a systematic literature review addressing 6 key questions. Using the Grading of Recommendations Assessment, Development and Evaluation framework, recommendations were created based on the available evidence, certainty of that evidence, and key judgments as defined in the framework.

Results.—: Four conditional recommendations and 3 good practice statements were established to provide guidance for proper testing and workup of amyloidosis.

Conclusions.—: This guideline summarizes the available evidence on the diagnosis and workup of systemic amyloidosis in tissue samples, including the challenges and limitations of common approaches and techniques. Recommendations for pathologists and laboratories receiving these samples are provided.