The American Board of Pathology (ABP) publishes performance data annually following the spring and fall anatomic pathology (AP) and clinical pathology (CP) board examinations.1 Pass rates are a hotly debated topic among trainees as well as faculty, though discussion is often based on anecdotes as opposed to objective data. I reviewed ABP examination performance data from 2009 to 2019 to better characterize trends in board performance by examinees.In the past decade, board pass rates have gone up overall though rates have remained similar among first time test takers and repeat test takers (Figures 1 and 2). Simple linear regression analysis showed a positive slope indicating an upward trend for first-time test takers, repeat test takers, and overall test takers; however, this was only significant in the overall test takers group (P = .002 AP; P = .001 CP). Overall pass rates showed the greatest upward trend, followed by first-time test takers, and repeat test takers (data not shown). The number of total test takers based on 2009 versus 2018, the last full year of data available, has decreased in AP from 781 to 664 (15%) and in CP by 791 to 588 (26%), including decreases in first time test takers (in AP by 606 to 578 [5%] and CP 543 to 534 [2%]), and repeat test takers (in AP 175 to 86 [51%] and in CP 248 to 54 [78%]). Likewise, the average pass rates from 2015 to 2019 are generally greater than pass rates from 2009 to 2014 (Table). First time test takers consistently have significantly higher pass rates than repeat test takers (P ≤ .001, Mann-Whitney U test). One limitation of this evaluation is ABP data are reported based on individual exams and as such there are no data available for which examinees took both exams; however, the majority of graduating pathology residents, as of 2019, are AP/CP track.2 Statistics were performed using PRISM 8 (GraphPad Software, San Diego, CA) and a P value < .05 was considered significant.As incremental pass rate increases are happening in other fields, including medicine, pediatrics, and surgery, as well as rising United States Medical Licensing Examination Step 1 scores among medical students, contemporary electronic study materials may be improving preparation.3–6 Numerous pathology question banks are available for free or as subscription services. Likewise Web-based pathology reference materials have expanded with free texts available on Pathology Outlines (https://www.pathologyoutlines.com/) or behind a paywall at services such as ExpertPath (https://www.expertpath.com). Social media sharing of pathology materials through Twitter and Facebook is becoming increasingly common, with numerous institutions and physicians actively participating.7 Conversations about physical study materials (such as Anatomic Pathology Board Review by Lefkowitch8 for AP and Quick Compendium of Clinical Pathology by Mais9 for CP), which traditionally occurred in-person, are being replaced by consensus recommendations on message boards or in email chains with senior residents.As more information is shared among trainees, it is unknown how much “remembrances” continue to contribute to board preparation. A number of years have elapsed since board certification was withheld from examinees for sharing board question information, though the topic comes up frequently.10 An honor code that represents a legally binding contract has been put out by the ABP by which all pathology residents sitting for boards are bound.11 Fear of repercussion has created an environment where general advice is more common, and most trainees and attending physicians remain apprehensive of revealing specific details.Efforts by training programs to better prepare residents for board examination are occurring concurrently. Lax scheduling in the latter half of senior residents' fourth year is common among training programs to allow for exam preparation. Programs have a vested interest in the education and training of residents, and institutional pass rates are reported to the Accreditation Council for Graduate Medical Education (ACGME). All United States pathology residencies currently participate in the Resident In-Service Examination (RISE).12 A 2011 study comparing spring RISE scores with pass rates showed those who did well on the RISE had superior pass rates on board exams.13 It is unclear if changes in formalized feedback, such as the ACGME milestones, have impacted results, though the practice was implemented beginning in 2012 and mirrors the recent increase in pass rates.14Repeat test takers routinely do not fare as well. This is possibly due to poor preparation during residency and prior attempts, though numerous factors likely contribute. Of note, the number of repeat test takers continues to drop by a larger percentage than overall test takers, which may also be related a higher percentage of test takers passing on the first try leading to a smaller pool of repeat test takers. However, this may also be representative of residents seeking jobs outside of pathology after unsuccessful board attempts, while the reduction in test takers overall may be indicative of fewer medical school graduates seeking careers in pathology.As it stands, pass rates have improved for first time test takers, though repeat test takers tend to do poorly on subsequent attempts. Data on residents sitting for AP and CP exams are unavailable but are likely similar among first time test takers. Additional studies are required to identify the impact of electronic study materials, correlation of RISE scores and board exam success, and the impact of ACGME milestones. Passing remains contingent on efforts both by the trainee and training program, though the trend is that most first-time test takers will pass. As it stands, the boards remain a challenging exam, a rite of passage even, though pass rates are increasing overall.
Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds. The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6-47·0) in 1990 to 63·4 years (63·1-63·7) in 2023. For males, mean age increased from 45·4 years (45·1-45·7) to 61·2 years (60·7-61·6), and for females it increased from 48·5 years (48·1-48·8) to 65·9 years (65·5-66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9-81·0) and for males 74·8 years (74·8-74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5-38·4) for females and 35·6 years (35·2-35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value. We examined global mortality patterns over the past three decades, highlighting-with enhanced estimation methods-the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales. Gates Foundation.
Established in 1973, the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute (NCI) has been a valued source of high-quality information for cancer incidence and survival in the United States. SEER data are used in a variety of research studies to explore cancer incidence and survival for etiologic and outcomes research related to cancer. These studies include exploring factors that influence trends, analyzing and understanding the cancer burden at a national and local level, and describing health disparities among subpopulations. Data are collected on approximately 450 000 cases of malignant and in situ cancers each year, including information on patient demographics, primary tumor site, tumor morphology and stage at diagnosis, first course of treatment, and mortality outcomes. The registry community strives to capture clinically relevant information by periodically expanding the scope of data collected, such as incorporating the latest staging definitions, as well as predictive and prognostic factors as they become part of standard care. Staging describes the extent of an individual's cancer at the time of diagnosis and plays a vital role in managing patient care. Cancer staging reflects prognosis and is used in determining appropriate treatment for cancer patients. It is an essential component in many areas of cancer research, from defining eligibility criteria in clinical trials to evaluating the impact of cancer interventions and treatment advances in epidemiologic and health services research. The American Joint Committee on Cancer (AJCC) leads the effort in the United States to develop a standardized staging system and collaborates with the Union for International Cancer Control (UICC) to maintain a system that is used worldwide. Cancer staging guidelines as well as classification systems for tumors continue to evolve over time and are updated periodically to reflect advances in cancer care and diagnosis. The AJCC and UICC work closely with cancer registrars to ensure that registries can capture the most current staging definitions. The SEER Program and its predecessors such as the End Results Program have collected information to stage cancers and have adapted their data collection to evolving staging requirements (Fig. 1). Staging over time. Traditionally, staging represented anatomic information regarding the scope of the disease, and this information was summarized into 3 categories: the extent to which the tumor has invaded nearby tissue (T; including size of the tumor for some sites), whether the cancer has spread to nearby lymph nodes (N), and whether the cancer has metastasized to other parts of the body (M). Together, T, N, and M form the basis for cancer staging. With advances in medical technologies and the introduction of precision medicine and targeted therapies, staging systems incorporated factors that influence prognosis and treatment decisions to reflect current medical practice. As the complexity of the components that determine prognosis continued to increase, it became increasingly challenging to maintain staging systems that would both provide consistency over time and capture the factors influencing treatment decisions in the current medical setting. To address the challenge, a set of building blocks was developed that would provide the foundation needed to translate the extent of disease information into multiple staging systems and enhance the anatomic staging information with additional clinically relevant factors such as biomarkers and prognostic factors. This new approach resulted in the creation of the Collaborative Stage Data Collection System (CS). The first version of Collaborative Stage (CSv1) was introduced for cases diagnosed in 2004 and coincided with the release of the 6th edition of the AJCC Cancer Staging Manual.1 CS is a unified data collection system designed to use a single set of data elements based on extent of disease and clinically relevant factors that both meets the needs of multiple staging systems and eliminates duplicate data collection by cancer registrars reporting to facility-based and central population-based registries. The project was sponsored by the AJCC in collaboration with NCI's SEER Program, the American College of Surgeons Commission on Cancer (CoC), the Centers for Disease Control and Prevention's National Program of Cancer Registries, the National Cancer Registrars Association, the North American Association of Central Cancer Registries, and the Canadian Cancer Society's National Cancer Institute of Canada. The Collaborative Staging system was updated in 2010 (CSv2) in conjunction with the release of the 7th edition of the AJCC Cancer Staging Manual (AJCC 7th)2. The authors of the AJCC 7th present the T, N, M, and stage descriptions along with a section on prognostic factors for which collection is recommended. These recommendations are the basis for the development and collection of the site-specific factors (SSFs) for CS. NCI and the CoC decided to require many, but not all, of these new clinically significant SSFs for their respective programs, SEER and the National Cancer Data Base. These additional data elements have great potential for expanding our understanding of patient diagnosis, stage, and outcomes. Additional information contained in the SSFs allows for the identification of more homogeneous groups of patients who share common disease characteristics beyond anatomic similarities at the cancer sites. CSv2 was designed to allow computer algorithms to calculate multiple staging systems, simultaneously giving the most current staging and preserving the ability to analyze longer-term trends by stage. The identification and analysis of comparable stage-specific cancer incidence trends over time are essential for assessing the impact of cancer-control interventions and for comparative effectiveness research, thus playing a vital role in cancer surveillance. This issue looks at 8 common cancer sites to describe the information collected under CSv1 and CSv2 within the SEER Program. Data analyzed are from 18 SEER registries that represent 28% of the US population. Each report first describes how changes between the AJCC 6th and 7th affect stage distributions and trends and then quantifies the potential impacts on outcomes and incidence trends stratified by stage. SSFs are described in detail with particular emphasis on the factors newly collected in 2010. To better evaluate the completeness of each SSF, 2 separate analyses were performed. The first analysis considered all cases for which the information was collected, whereas the second was restricted to the cases in which the information would be expected to be routinely found. For example, if a SSF is included in existing guidelines to determine treatment, it would be expected to be routinely found. Key questions related to the SSFs are addressed in the discussion sections of each article, such as how a factor relates to other information collected and the completeness and quality of the information. The level of completeness of SSF information for cases diagnosed in 2010 ranged from very high (over 95%) to very low. It will require additional investigation to understand the reasons for some of the low percentages of completeness. Some test results may be missed because the test was given outside the reporting facility; it is also possible that a test was not done for any number of reasons not routinely captured in the registry data, such as comorbidities or individual preference. In several instances, there were differences between laboratory values and test interpretation, which called into question whether pooling laboratory values across different laboratories without additional information associated with the test performed could be trusted to provide consistent and accurate information. Considerable resources have been spent on the collection of these data, and they should be available for research when the data are of high quality, consistent, and complete (low percentage unknown). Analyzing similar SSF data for 15 major cancers, NCI formed a Data Release Work Group composed of SEER principal investigators, SEER registry staff, and NCI staff to make recommendations on SSFs that should be released to researchers and SSFs that should no longer be collected as of 2014. The evaluation for the remaining sites/schemas continues. Additional information on issues that researchers need to understand in analyzing stage, the CS building blocks of stage (extent of disease), and the CS SSFs can be found on the SEER website: http://surveillance.cancer.gov/reports/. The aim of this report is to provide information and interpretations that will serve as a guide to users of SEER registry data. There are many ongoing efforts that will facilitate the collection of predictive and prognostic factors in the future. Central cancer registries obtaining information directly from laboratories and physician offices through the increased use of electronic pathology reports and electronic medical records will lead to more complete and consistent reporting. More defined data structure formats within electronic health records may allow for easier electronic data capture and reporting of these items in the future, removing some of the burden from the cancer registrar. Linkages to other supporting data sets, such as medical claims and pharmaceutical transaction databases, may be useful for filling in missing information. In the future, as the College of American Pathology checklists (http://www.cap.org/apps/cap.portal) and AJCC are more closely aligned, information on SSFs and basic staging information may be more readily available to cancer registrars. New and creative approaches to capturing data will continue to be needed to keep up with the ongoing advances in understanding, describing, and treating cancer. Even as AJCC 7th stage data are analyzed, groups are already meeting to design the AJCC 8th edition in order to maintain its relevance and pivotal role in patient care. This special issue was made possible by NCI's Surveillance Research Program, experts from SEER registries and other leaders from the surveillance community. These individuals spent many hours reviewing the data that were collected under CSv1 and CSv2 and are dedicated to ensuring that the data are used to their fullest potential by the research community. This study would not be possible without the dedication of the staff at the SEER population-based cancer registries and the staff at the facilities who provide data to the SEER central registries. This supplement edition of Cancer has been sponsored by the National Cancer Institute. Data used in the production of this supplement was supported under Contract HHSN261201300004I (University of Southern California), HHSN261201300005I (Cancer Prevention Institute of California, HHSN261201300009I (University of Hawaii), HHSN261201300010I (University of New Mexico), HHSN261201300021I (Rutgers University), HHSN261201300019I (Connecticut Department of Health), HHSN261201300020I (University of Iowa), HHSN261201300015I (Emory University), HHSN261201300016I (Louisiana State University), HHSN261201300017I (University of Utah), HHSN261201300011I (Wayne State University), HHSN261201300012I (Fred Hutchinson Cancer Center), HHSN261201300013O (University of Kentucky), and HHSN261201300014I (Public Health Institute). Technical support was provided under contract HHSN261201100007I (Information Management Services, Inc.). Dr. Ries was supported by contracts HHSN261201300308P and HHSN261201200422P from the National Cancer Institute for work related to the current study. The authors made no disclosures.
The transformation of anatomic pathology from microscope-based practice to digital and computational workflows has created unprecedented opportunities for artificial intelligence (AI)-driven diagnostics. Whole slide imaging systems, digital cytology, and enterprise pathology platforms now enable large-scale image analysis, quantitative tissue characterization, and integration with molecular and clinical data. In parallel, advances in machine and deep learning, and generative models have produced AI systems capable of tumor detection, grading, prognostication, biomarker assessment, and molecular inference directly from routine histologic and cytologic slides. Despite this rapid progress, translation of AI from research environments into routine clinical anatomic pathology remains limited. Barriers include data heterogeneity and limited generalizability, challenges in validation and regulatory compliance, infrastructure and interoperability constraints, workflow integration difficulties, and concerns regarding transparency, accountability, and professional trust. This review synthesizes current evidence on digital pathology and AI applications across surgical pathology and cytopathology, examines the technical, organizational, and regulatory factors that impede clinical adoption, and outlines practical recommendations for developing clinically deployable AI systems. Addressing these challenges through robust digital infrastructure, representative data sets, rigorous validation, and coordinated governance will be essential for realizing the full clinical potential of AI in anatomic pathology.
Intraepithelial penile lesions encompass non-neoplastic and preneoplastic lesions. Non-neoplastic lesions comprise condyloma acuminatum, including giant condyloma acuminatum, also known as Buschke-Löwenstein tumor. It is usually the low-risk human papillomavirus (HPV) types 6 and 11 that are most prevalent in penile condylomas. However, high-risk HPV types can be detected along with low-risk types in a subset of patients. Penile intraepithelial neoplasia (PeIN) is a preneoplastic lesion that is either HPV-associated or HPV-independent. HPV-associated PeIN represents the majority of PeIN in regions where the incidence of penile cancer is lower, as in North America and Europe. HPV-associated PeIN is subdivided into basaloid, warty, and mixed subtypes and, less commonly, into pagetoid, clear-cell, and spindle-cell subtypes based on morphologic characteristics. HPV-associated PeIN is positive for immunohistochemical stain p16 and high-risk HPV in situ hybridization (ISH). Immunohistochemical stain p53 usually exhibits a wild-type staining pattern. HPV-independent PeIN/differentiated PeIN is more frequent in countries with a high incidence of penile cancer and an uncircumcised population. It is usually associated with predisposing factors like lichen sclerosus and chronic inflammatory conditions such as lichen planus, lichen simplex chronicus, and phimosis. The degree of atypia in differentiated PeIN ranges from subtle to full-thickness proliferation of markedly atypical pleomorphic cells. Many cases are associated with TP53 mutations and other alterations involving PIK3CA and HRAS. Recently, it has been proposed to further subclassify differentiated PeIN. Extramammary Paget disease (EMPD) can involve the skin of the penis and glans mucosa in elderly men. It is either primary or secondary, and when secondary, it can be associated with prostate or urothelial carcinoma. Lastly, rare case reports of primary penile melanoma in situ have been reported. The lesions can involve either the skin or mucosa, with the glans penis being the most commonly reported site.
Cytopathology is the first field of pathology in which artificial intelligence (AI) models were successfully developed and commercialized for routine clinical screening of cervical cytology, a practice that has been in place for the past 2 to 3 decades. However, the development and deployment of AI applications for nongynecologic cytology has just begun. The variety of cytology specimen types and preparations with associated unique characteristics presents technical challenges for the complete digitization of the cytology workflow. Despite of these challenges, a few institutions have adopted a complete digital cytology workflow. Technical advancement in digital cytopathology have replaced conventional rapid onsite evaluation by a variety of virtual telecytology systems. Novel digital diagnostic solutions for cytology are evolving. Among these, Hologic Genius is the only one approved by the Food and Drug Administration (FDA) for routine clinical screening of cervical cytology in the United States. The recommendations for AI validation and best-practice guidelines for digital cytopathology are currently being developed. Prospect of technical and AI advances in digital cytopathology include automation of sample preparation, ROSE using telecytology, automation of screening of gynecologic and nongynecologic cytology specimens, automated quantitation of biomarkers, quality control, and beyond. This review article uncovers recent advances in digital cytopathology and discusses potential use cases of AI applications for routine cytopathology practice in this modern era of digital cytopathology.
Since its initial description in 1943,1 autism has been primarily conceptualized as a behavioral disorder, and for many years it was believed to be the result of parental and environmental influences. With heightened clinical interest in the disorder, coincident with advances in medical technology, however, evidence for an underlying neurologic basis for autism has become increasingly apparent. HISTORICAL NEUROPATHOLOGIC PERSPECTIVE Based largely on the constellation of symptoms that characterize the disorder, various anatomical sites within the brain have been suggested as a possible primary source of pathology in autism. Suspected regions have included the medial temporal lobe,2-5 the thalamic nuclei,6 the basal ganglia,7 and the vestibular system.8 Computed tomographic imaging studies have shown inconsistent findings.9-14 More recently, however, magnetic resonance imaging studies have described abnormalities in portions of the cerebellum and posterior fossa.15-17 Direct microscopic examination of the autistic brain has, until recently, yielded little information. Aarkrog18 reported thickening of the arterioles, slight connective tissue in the leptomeninges, and some cell increase in a frontal lobe biopsy performed on an autistic patient. Later, in 1976, 33 cases of childhood psychosis were reviewed by Darby.19 Although he suggested a possible correlation between limbic system lesions and the affective symptomatology of autism, no consistent neuropathologic findings were found. In 1980, Williams et al20 studied sections of brain from four patients with autistic-like behavior; looking primarily for cell loss and gliosis, they failed to find any consistent abnormalities. MICROSCOPIC NEUROANATOMIC OBSERVATIONS In 1984, anatomic abnormalities were reported in the brain of a 29-year-old man with well-documented autism; the technique of whole brain serial section was used, and the patient was studied in comparison with an identically processed age- and sex-matched control subject.21,22
Horseshoe kidney is a rare congenital anomaly with an unusually higher frequency of neuroendocrine tumors. Symptoms are rare, and, in most of the cases, are incidentally diagnosed. The clinical behavior of these tumors is heterogeneous and can be difficult to predict based on histology alone. Necrosis and percentage of Ki-67 may have a role in prognosis. Almost all tumors are carcinoids (well-differentiated neuroendocrine tumors) observed at an early age and with no sex dominance. It is not known the reason for the higher frequency of neuroendocrine tumors in horseshoe kidneys and the histogenesis is unknown. One of the hypotheses supports that renal carcinoid tumors may arise from neuroendocrine cells within foci of metaplastic or teratomatous epithelium within the kidney. With consonance with this hypothesis, there are reports of carcinoids in horseshoe kidneys associated with a cystic lesion lined by the intestinal epithelium, with mucinous differentiation and osseous metaplasia, arising in a mature teratoma of the kidney, arising within mature teratoma and clear cell renal cell carcinoma, with a mucinous cystadenoma element, and arising within mature cystic teratoma synchronous with primary adenocarcinoma. There is only one reported large cell neuroendocrine carcinoma of a horseshoe kidney in a 57-year-old Chinese woman. Herein, we report a patient that to the best of our knowledge is the first case of a combined well-differentiated neuroendocrine tumor and large-cell neuroendocrine carcinoma with rhabdoid features in horseshoe kidney. The histologic component of rhabdoid features expands the morphologic spectrum of neuroendocrine tumors in the horseshoe kidney. We provide a comprehensive review of the literature summarizing pertinent key clinical and pathologic aspects.
The Dublin ISUP Consensus Conference covered the proceedings on the best practice recommendations on nonurachal glandular lesions of the urinary bladder, bladder diverticular cancers, and molecular features of bladder and urachal glandular lesions. The conference proceedings on urachal neoplasms (except for their molecular features) are published elsewhere. The rationale for convening this conference was the lack of structured and consented pathologic recommendations in these rare lesions. Consensus by participants was reached on the following statements: (1) intestinal metaplasia with dysplasia is considered to be a precursor to primary bladder adenocarcinoma; (2) dysplasia arising from cystitis glandularis should be reported in terms of focality (focal or nonfocal) and grade (low or high); (3) the term "adenocarcinoma" should only be used for carcinomas showing pure (nonurothelial) morphology and should not be used interchangeably in urothelial carcinoma with "glandular differentiation" because of the pathobiological differences and management implications; (4) the different histologic subtypes of bladder adenocarcinoma should be specified in the report; (5) immunohistochemistry has an ancillary role in the work up of bladder adenocarcinoma versus gastrointestinal or Müllerian-type adenocarcinomas; (6) lymphovascular invasion should be included as a parameter when reporting bladder adenocarcinoma; (7) representative or targeted sampling will be sufficient for bladder diverticulum resection specimens; and (8) molecular analysis in genomic profiling should be performed only in advanced or metastatic bladder and urachal adenocarcinomas for targetable therapy. This report on glandular (nonurachal) lesions of the bladder from the Dublin ISUP consensus conference will serve as a best practice recommendation and as a guide for future research on these relatively rare lesions.
This review focuses on the purported applications of multimodal Gen-AI models for anatomic pathology image analysis and interpretation to predict future directions. A scoping review was conducted to explore the applications of multimodal Gen-AI models in advancing histopathology image analysis. A comprehensive search was conducted using electronic databases for relevant articles published within the past year (July 1, 2023 to June 30, 2024). The selected articles were critically analyzed to identify and summarize the applications of multimodal Gen-AI in anatomic pathology image analysis. Multimodal Gen AI models reported in the literature claim moderate to high accuracy on tasks including image classification, segmentation, and text-to-image retrieval. This review demonstrates the potential of multimodal Gen AI models for useful applications in pathology, including assisting with diagnoses, generating data for education and research, and detection of molecular features from anatomic pathology images. These models use data from a few academic institutions thus they require validation on diverse real-world data. There is an urgent need to build consensus models for optimal model performance through multicenter collaboration using a federated learning approach and the use of carefully curated synthetic anatomic pathology data. These models also need to achieve reliability, generalizability and meet the standards required for clinical use. Despite the rigorous need for evaluation and the need to address genuine concerns, multimodal GenAI models present a promising perspective for the advancement and scalability of anatomic pathology.
Over the last 2 to 3 decades, we have seen incremental movement from the "Rule of 10s" for pheochromocytomas, particularly those regarding tumor bilaterality, malignancy, and patterns of inheritance. The biology and prevalence of these tumors have not changed, but there has been a great deal of progress in terms of our understanding of tumor genetics, variable modes of acquiring of both pheochromocytomas and paragangliomas (PPGL), and our approach to clinical management of these unpredictable neoplasias. Although these non-epithelial neuroendocrine tumors are rare, they are clinically significant due to their hormonal activity, association with hereditary syndromes, and biological potential. Their detection has increased in recent decades with improved biochemical testing and advanced imaging modalities, yet predicting clinical behavior continues to be a major challenge. Histologically, PPGL typically shows classic neuroendocrine architecture but may display morphologic diversity, occasionally mimicking other adrenal or paraganglionic tumors. Immunohistochemistry remains essential for diagnostic confirmation and as a surrogate for genetic alterations, offering valuable genotype-phenotype correlations. With increasing knowledge of tumor genetics, additional emphasis has been placed on histology-based risk-stratification for these lesions, particularly those prone to metastasis or multifocality, and the 2022 WHO endorses no individual risk-stratification system, as none seems to be of definitive merit over another. Instead, it promotes a comprehensive approach integrating morphologic, molecular, and clinical factors. Approximately 40% of PPGL harbor germline mutations, whereas somatic alterations account for additional subsets. Mutations in SDH x, VHL , RET , NF1 , and other susceptibility genes define molecular clusters with distinct signaling pathways and clinical behavior, underscoring the importance of multidisciplinary, lifelong management.
The list of genetically defined causes of cholestatic liver diseases continues to expand; it currently includes mutations affecting bile acid synthesis, basolateral and apical membrane transporters, bile duct development, canalicular tight junctions, and bile acid conjugation, among others. The most frequently identified mutations in large multi-institutional studies of cholestasis occur in JAG1, ATP8B1, ABCB11, ABCB4, SERPINA1 , and CFTR . Mutations in JAG1 , SERPINA1 , and CFTR cause Alagille syndrome, alpha-1 antitrypsin deficiency, and cystic fibrosis, respectively. Mutations in ATP8B1 , ABCB11 , and ABCB4 cause a spectrum of diseases that range from the episodic, nonprogressive benign recurrent intrahepatic cholestasis and intrahepatic cholestasis of pregnancy to the severe and rapidly progressive familial intrahepatic cholestasis. These cholestatic disorders present a wide range of symptoms and overlapping clinical features. However, in contemporary practice, diagnosis is often easily and rapidly established by clinically available comprehensive gene panels. In addition to diagnosis, these panels also aid in the discovery of novel genes or variants as potential causes of cholestasis. Genetic mutations may also be responsible for drug-induced cholestasis, as the liver plays a vital role in metabolism of drugs and xenobiotics. Uptake into hepatocytes and elimination into the bloodstream or bile of drugs and xenobiotics involve transporters across the basolateral and apical hepatocellular membranes, respectively. Therefore, mutations in any of the transporters lead to impaired metabolism and/or elimination of these substances. Furthermore, a large number of drugs and xenobiotics have a transcriptional or functional inhibitory effect on transporters such as BSEP and MDR3, setting the stage for the all-too-common drug-induced cholestasis.
Ex vivo digital microscopy uses light in the visible and adjacent spectra to obtain digital images of tissues. They are optical imaging techniques that allow the acquisition of digital images of tissues with minimal or no tissue preparation and are currently available for evaluation of fresh and/or fixed tissues. This review will provide an overview of the different types of ex vivo digital microscopy techniques, including confocal microscopy (CM), optical coherence tomography (OCT), stimulated Raman Spectroscopy (SRS), light sheet microscopy (LSM), microscopy with ultraviolet excitation (MUSE), structured illumination microscopy (SIM), and nonlinear microscopy (NLM). Except for OCT and SRS, all the other tissue imaging techniques require labeling of tissues with fluorescent dyes to obtain digital images. An advantage of several of these techniques, including fluorescence CM, SRS, LSM, MUSE, SIM, and NLM, is that they can produce hematoxylin and eosin-like images. The promising potential of ex vivo digital microscopy techniques in surgical pathology practice is supported by several retrospective and limited prospective studies. Applications of ex vivo digital microscopy techniques include real-time evaluation of fresh tissue at the bedside in clinics and radiology suites, as well as intraoperatively in pathology laboratories. These techniques have great potential for incorporation into standard-of-care surgical pathology practice.
Significant advancements over the past 2 decades have reshaped our understanding and diagnostic capabilities for hepatocellular carcinoma (HCC). These advancements span molecular insights into key driver gene mutations and chromosomal aberrations, refined recognition of distinct histologic subtypes, improved differentiation from precursor and benign hepatic lesions, and enhanced strategies for interpreting challenging biopsy samples. The discovery of driver mutations such as TERT promoter, CTNNB1 , and TP53 , along with chromosomal alterations, has provided essential tools for identifying malignancy and understanding tumor behavior. Concurrently, the recognition of distinct morphomolecular HCC subtypes has underscored the importance of integrating histologic and molecular findings for accurate diagnosis and prognostic assessment. In addition, differentiating HCC from dysplastic nodule and hepatocellular adenoma remains a diagnostic challenge, often requiring a combination of morphologic, immunohistochemical, and molecular approaches. Moreover, the interpretation of biopsy samples from borderline hepatocellular neoplasms highlights the limitations of conventional pathology alone and the need for comprehensive diagnostic strategies. This review aims to provide an updated overview of these interconnected aspects, emphasizing their collective role in advancing the precision diagnosis of HCC.
Primary liver carcinoma (PLC) is the sixth most common malignancy worldwide and the third leading cause of cancer-related mortalities. Hepatocellular carcinoma (HCC) is the most prevalent form of PLC, followed by intrahepatic cholangiocarcinoma (iCCA). In addition, there is a group of rarer PLCs that do not fit neatly into the HCC or iCCA categories. This review explores this heterogeneous group, including combined hepatocellular-cholangiocarcinoma (cHCC-CCA), intermediate cell carcinoma (ICC), mixed hepatocellular-neuroendocrine carcinoma, and undifferentiated primary liver carcinoma. cHCC-CCA is a rare subtype of PLC, characterized by both hepatocytic and cholangiocytic differentiation within the same tumor. The latest WHO classification (2019, fifth edition) redefined cHCC-CCA by eliminating the "stem cell subtypes" and emphasized that diagnosis should primarily rely on morphologic features, supported by immunohistochemical staining to better define subtypes. Intermediate cell carcinoma is a subtype of cHCC-CCA and is comprised of monomorphic tumor cells that exhibit characteristics intermediate between hepatocytes and cholangiocytes, with immunohistochemical expression of hepatocytic and cholangiocytic markers within the same cell. Another rare entity, combined HCC and neuroendocrine carcinoma (NEC), contains an admixture of HCC and NEC components within the same tumor. Undifferentiated primary liver carcinoma, on the other hand, lacks definitive lineage differentiation beyond an epithelial phenotype. These heterogeneous PLCs pose diagnostic challenges owing to their mixed/unusual histologic features and overlapping immunohistochemical markers. They tend to have poor prognoses, highlighting the critical importance of accurate and timely diagnosis.
The approach to eosinophilia and mast cell disorders in the bone marrow is diverse and depends on multiple factors including access to ancillary testing, resources to support testing, type of practice setting (eg, community, remote, tertiary care center or specialized referral center for these disorders) and whether there are options for clinical trial enrollment. That said, while there are some basic principles to the workup that we can all likely agree upon, individual practice habits will need to be tailored to suit an individual setting. As such, the approach presented in this manuscript is meant to serve as a practical guide and not as dogma per se. Importantly, an in-depth discussion of individual diseases and International Consensus Classification diagnostic criteria will not be covered, as the main focus of this article is the approach to these disorders. The reader is referred to a comprehensive discussion of these diseases and diagnostic criteria in several excellent articles. While there are clear areas of overlap between eosinophilia and mast cell conditions (eg, systemic mastocytosis associated with eosinophilia, myeloid neoplasm with eosinophilia, and tyrosine kinase rearrangements), it is the authors' opinion that it is perhaps easier to navigate these entities separately (eg, eosinophilia as one broad topic and mast cell conditions as another) and to recognize the settings in which overlap may exist and what testing might be considered. Eosinophilia and mast cell conditions will be discussed separately supplemented by generous use of figures and tables to highlight key points.
Aggressive B-cell lymphomas are a biologically and clinically very heterogeneous group of tumors that may be related to different stages of B-cell differentiation development. This review aims to summarize recent advances in the understanding of these tumors with a focus on the practical approach to the diagnosis of these entities. We analyze the defining characteristics of the different subtypes of aggressive B-cell lymphomas, including nodal and extranodal diffuse large B-cell lymphoma, virus-associated lymphomas, terminally differentiated B-cell lymphomas, high-grade B-cell lymphomas, and Burkitt lymphoma. This review particularly explores the integration of morphologic, immunophenotypic, and genetic data that refine diagnostic accuracy and prognostic stratification, underscoring the necessity for a standardized approach in clinical practice. By synthesizing current knowledge, this review aims to enhance the understanding of aggressive B-cell lymphomas within the context of the evolving classification system, paving the way for future research and clinical advancements.
Molecular profiling is becoming crucial for accurate classification, prognostication, and therapeutic stratification for central nervous system (CNS) tumor classification since the advent of the WHO 2021 CNS tumor classification. However, in most of the low-income countries and middle-income countries, access to advanced molecular platforms remains limited due to cost, technical complexity, and turnaround time. Surrogate immunohistochemistry markers for mutation-specific or fusion-specific antibodies that reliably predict underlying genetic alterations offer a rapid, cost-effective alternative. The manuscript systematically discusses a spectrum of CNS tumor entities where morphology supplemented with immunohistochemistry can, in many cases, support an integrated molecular diagnosis, including "Astrocytoma, IDH-mutant" (IDH R132H, ATRX, and p53), "Oligodendroglioma, IDH-mutant, and 1p/19q codeleted" (HIP1R, H3K27me3 loss, and vimentin), "Diffuse midline glioma, H3K27-altered" (H3K27M, EZHIP), "Diffuse hemispheric glioma, H3G34-mutant" (H3G34R/V), "Infant-type hemispheric glioma" (Pan-TRK, ALK), "Epithelioid glioblastoma" and "Pleomorphic xanthoastrocytoma" (BRAF V600E)), "Astroblastoma, MN1-altered" (MN1), "Ependymoma" subtypes (p65, L1CAM, EZHIP), "Medulloblastoma" subgroups (β-catenin, LEF1, YAP1, GAB1), "Atypical teratoid/rhabdoid tumor" (SMARCB1, SMARCA4), "CNS neuroblastoma, FOXR2-activated" (FOXR2), "CNS tumor with BCOR ITD" (BCOR), and various sarcomas and sellar tumors (STAT6, NKX2.2, DUX4, β-catenin, BRAF V600E). For each entity, detailed morphologic features, immunoprofiles, sensitivity/specificity data, and diagnostic caveats have been described. The review emphasizes that when interpreted alongside histomorphology and conventional markers, surrogate immunohistochemistry can significantly reduce reliance on molecular testing, expedite diagnosis, and improve accessibility of precision diagnostics. Standardization, validation, and awareness of pitfalls remain essential to maximizing their clinical utility in neuropathology practice.
Despite the growing availability of noninvasive and faster diagnostic modalities, biopsy remains an important tool in the diagnosis and management of liver diseases. However, it is not uncommon that liver biopsies reveal normal or near normal histologic findings in patients with abnormal liver biochemistries, elevated autoantibodies, clinical findings suggestive of portal hypertension, systemic autoimmune or inflammatory diseases, hepatomegaly, cirrhosis by imaging, or other indications. These scenarios present significant diagnostic challenges and are rarely discussed in detail in the literature or textbooks. This article aims to provide a comprehensive review of a group of selected rare liver diseases, with a focus on metabolic, storage and inclusion disorders, that may exhibit a near-normal histology on biopsy. By recognizing subtle histologic features and correlating with clinical history, laboratory results and imaging findings, it is often possible to narrow down the differential diagnosis. In many cases, this integrative approach can yield a definitive diagnosis, allowing for tailored treatment and better patient outcomes.
Tumors resembling conventional, somatic-type malignancies arise infrequently (<10%) in association with malignant, postpubertal-type testicular germ cell tumors, mainly at the metastatic sites (less frequently at primary), and often after treatment. Historically, the pathogenetic framework for these tumors, indeed their current classification and nomenclature under the WHO 5 th Edition, contemplated their arising from (malignant) postpubertal-type teratomatous components undergoing oncogenic changes homologous to conventional somatic malignancies of the relevant tissue lineages. Recent scholarship questions the specificity of their provenance to postpubertal-type teratoma, with strong evidence relating them also to postpubertal-type yolk sac tumor as well. In tandem, molecular studies support a close relationship to their associated postpubertal-type testicular germ cell tumor rather than identifying any of the known molecular drivers of the somatic-type malignancies they resemble. The histologic patterns observed include sarcoma-like tumors, carcinoma-like tumors, primitive-appearing embryonic-type neuroectodermal tumor, nephroblastoma-like tumors, neuroglial-like neoplasms, leukemia-like malignancies, and combined forms incorporating 2 or more of the foregoing. Although greater experience will be required to validate the changing conceptualization of their origin, from a management standpoint when seen at metastatic sites these somatic tumors-like neoplasms may be poorly responsive to cisplatin-based chemotherapy regimens whereas when seen in the primary site they behave favorably. Surgical resection, if feasible, may provide the best chance for sure at metastatic sites.