Advances In Anatomic Pathology最新文献

The classification of thymoma continues to be a source of controversy in pathology. The difficulties in histologic classification are evident from the number of proposals that have been offered over the years, as well as for the continuous changes and modifications introduced by the World Health Organization to their classification system over the past 20 years. We analyze here some of the issues involved in the classification of these tumors and the difficulties encountered for practicing pathologists in deciphering the "letters and numbers" system devised by the World Health Organization. We would like to propose an alternate approach to thymoma histologic classification that capitalizes on the basic observation of their cytologic features and incorporates the pattern of growth resulting from the interplay of the tumor cells with other cellular constituents as a secondary characteristic. The proposed histologic classification provides a simplified, reproducible means of histologically categorizing these tumors and can be easily understood by most practicing pathologists in simple and clear morphologic terms.

Large Language Models are forms of artificial intelligence that use deep learning algorithms to decipher large amounts of text and exhibit strong capabilities like question answering and translation. Recently, an influx of Large Language Models has emerged in the medical and academic discussion, given their potential widespread application to improve patient care and provider workflow. One application that has gained notable recognition in the literature is ChatGPT, which is a natural language processing "chatbot" technology developed by the artificial intelligence development software company OpenAI. It learns from large amounts of text data to generate automated responses to inquiries in seconds. In health care and academia, chatbot systems like ChatGPT have gained much recognition recently, given their potential to become functional, reliable virtual assistants. However, much research is required to determine the accuracy, validity, and ethical concerns of the integration of ChatGPT and other chatbots into everyday practice. One such field where little information and research on the matter currently exists is pathology. Herein, we present a literature review of pertinent articles regarding the current status and understanding of ChatGPT and its potential application in routine diagnostic pathology. In this review, we address the promises, possible pitfalls, and future potential of this application. We provide examples of actual conversations conducted with the chatbot technology that mimic hypothetical but practical diagnostic pathology scenarios that may be encountered in routine clinical practice. On the basis of this experience, we observe that ChatGPT and other chatbots already have a remarkable ability to distill and summarize, within seconds, vast amounts of publicly available data and information to assist in laying a foundation of knowledge on a specific topic. We emphasize that, at this time, any use of such knowledge at the patient care level in clinical medicine must be carefully vetted through established sources of medical information and expertise. We suggest and anticipate that with the ever-expanding knowledge base required to reliably practice personalized, precision anatomic pathology, improved technologies like future versions of ChatGPT (and other chatbots) enabled by expanded access to reliable, diverse data, might serve as a key ally to the diagnostician. Such technology has real potential to further empower the time-honored paradigm of histopathologic diagnoses based on the integrative cognitive assessment of clinical, gross, and microscopic findings and ancillary immunohistochemical and molecular studies at a time of exploding biomedical knowledge.

Cervical cancer is the fourth most common cancer among women globally. Historically, human papillomavirus (HPV) infection was considered necessary for the development of both precursor and invasive epithelial tumors of the cervix; however, studies in the last decade have shown that a significant proportion of cervical carcinomas are HPV-independent (HPVI). The 2020 World Health Organization (WHO) Classification of Female Genital Tumors separates both squamous cell carcinomas (SCCs) and endocervical adenocarcinomas (ECAs) by HPV status into HPV-associated (HPVA) and HPVI tumors. The classification further indicates that, in contrast to endocervical adenocarcinomas, HPVI and HPVA SCCs cannot be distinguished by morphological criteria alone and suggests that HPV testing or correlates thereof are required for correct classification. Moreover, while HPVA SCC precursor lesions (ie, high-grade squamous intraepithelial lesion) are well known and characterized, precursors to HPVI SCCs have only been described recently in a small number of cases. We studied 670 cases of SCCs from the International Squamous Cell Carcinoma Project (ISCCP) to analyze the reproducibility of recognition of invasive SCC growth patterns, presence of lymphovascular space invasion, tumor grade, and associations with patient outcomes. Consistent with previous studies, we found histologic growth patterns and tumor types had limited prognostic implications. In addition, we describe the wide morphologic spectrum of HPVA and HPVI SCCs and their precursor lesions, including tumor growth patterns, particular and peculiar morphologic features that can lead to differential diagnoses, and the role of ancillary studies in the diagnosis of these tumors.

The pathologic assessment of colorectal carcinoma specimens plays a crucial role in the therapeutic management of patients and disease prognostication. The TNM staging system is used globally and is a critical component of colorectal carcinoma pathology reporting. However, our experience informs us that there are significant variations in the assignment of the TNM stage, both between pathologists and between hospital centers. We identify several potential reasons for this, among them suboptimal gross and microscopic assessment of colorectal resection specimens and, later, nonuniformity in applying criteria set forth in pathologic TNM staging guidelines. In addition, some defining characteristics of the staging system remain poorly defined. We aim to enlist those issues with potential remedies to improve reproducibility and, therefore, multidisciplinary discussion.

The standard of care for invasive cancers of the breast has been and continues to be to evaluate them for breast prognostic markers: estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 by immunohistochemistry. Over 2 decades ago, a study was the first to report on the molecular subtypes of breast cancer. Four main subtypes were reported. Since then there have been some changes in the molecular subtype classification, but overall many studies have shown that this subtyping has clinical prognostic and predictive value. More recently, molecular assays have been developed and studies have shown similar clinical prognostic and predictive value. We reviewed the literature for studies evaluating the clinical significance of all 3 of these methods of evaluation and the follow-up findings of that review are presented below.

As the leading cause of cancer morbidity and the second leading cause of cancer mortality among women, breast cancer continues to remain a major global public health problem. Consequently, significant attention has been directed toward early breast cancer detection and prevention. As a result, the number of image-detected biopsies has increased, and minimally invasive diagnostic procedures have almost replaced open surgical biopsies. Therefore, pathologists are expected to provide more information with less tissue and diagnose increasing numbers of atypical proliferative breast lesions, in situ lesions, and small breast carcinomas. This is a difficult task, as reflected by continuous reports highlighting the challenges associated with morphologic distinction between atypical ductal hyperplasia and low-grade ductal carcinoma in situ. The current interobserver variability among pathologists to accurately define these two entities often leads to silent overdiagnosis and overtreatment. Up to now, there are no reproducible morphologic features and/or any reliable biomarkers that can accurately separate the above-mentioned entities. Despite these reports, patients diagnosed with low-grade ductal carcinoma in situ are subject to cancer therapy regardless of the fact that low-grade ductal carcinoma in situ is known to be an indolent lesion. Studies have shown that low and high-grade ductal carcinoma in situ are genetically different forms of breast cancer precursors; however, the term ductal carcinoma in situ is followed by cancer therapy regardless of the grade and biology of the tumor. In contrast, patients with the diagnoses of atypical ductal hyperplasia do not undergo cancer therapy. In the current article, attempts are made to highlight the continuous dilemma in distinction between atypical ductal hyperplasia and low-grade ductal carcinoma in situ. Going forward, we suggest that low-grade ductal carcinoma in situ be referred to as ductal neoplasia. This alternative terminology allows for different management and follow-up strategies by eliminating the word carcinoma.

Pathology clinical practice has evolved by adopting technological advancements initially regarded as potentially disruptive, such as electron microscopy, immunohistochemistry, and genomic sequencing. Breast pathology has a critical role as a medical domain, where the patient's pathology diagnosis has significant implications for prognostication and treatment of diseases. The advent of digital and computational pathology has brought about significant advancements in the field, offering new possibilities for enhancing diagnostic accuracy and improving patient care. Digital slide scanning enables to conversion of glass slides into high-fidelity digital images, supporting the review of cases in a digital workflow. Digitization offers the capability to render specimen diagnoses, digital archival of patient specimens, collaboration, and telepathology. Integration of image analysis and machine learning-based systems layered atop the high-resolution digital images offers novel workflows to assist breast pathologists in their clinical, educational, and research endeavors. Decision support tools may improve the detection and classification of breast lesions and the quantification of immunohistochemical studies. Computational biomarkers may help to contribute to patient management or outcomes. Furthermore, using digital and computational pathology may increase standardization and quality assurance, especially in areas with high interobserver variability. This review explores the current landscape and possible future applications of digital and computational techniques in the field of breast pathology.

Some histologic special types of breast carcinoma harbor specific recurrent genetic alterations that are not seen in other types of breast carcinoma (no special type), namely adenoid cystic carcinoma, secretory carcinoma, and tall cell carcinoma with reversed polarity. These tumors have unique morphologic features, are triple-negative, that is, do not express hormone receptors or HER2, and are generally associated with a favorable prognosis. Adenoid cystic carcinoma, like its counterpart in other organs, shows a MYB-NFIB fusion gene that is the result of a recurrent t(6;9)(q22-23;p23-24) translocation. Other MYB alterations have been described that result in overexpression of MYB . Secretory carcinoma is characterized by an ETV6-NTRK3 gene fusion that is the result of recurrent (12;15);(p13;q25) translocation, which is also seen in mammary analog secretory carcinoma of the salivary gland. Tall cell carcinoma with reversed polarity shows IDH2 p.Arg172 hotspot mutations. Immunohistochemical antibodies have emerged that identify the underlying genetic alterations in these tumors and serve as useful diagnostic tools. This review will provide an update on the molecular features and diagnostic immunohistochemical markers that have become increasingly popular to aid in diagnosing these uncommon triple-negative breast tumors.