CONTEXT.—: The pathologic diagnosis of pT1 substage in conventional transurethral resection of bladder tumor specimens is inaccurate and has low interobserver reproducibility owing to fragmentation and cauterization of the specimens. En bloc resection of bladder tumor is a novel surgical procedure that improves diagnostic feasibility and accuracy in the pathologic diagnosis of bladder cancer, including depth and extent of invasion. OBJECTIVE.—: To examine the prognostic value of multiple pT1 subclassification methods, using only en bloc resection specimens. DESIGN.—: We examined 106 patients with T1 bladder cancer who underwent en bloc resection. The pT1 substages were assigned by 3 different subclassification methods by using the muscularis mucosae or stalk of the papillary lesion as diagnostic landmarks or millimetric depth of invasion. Intergroup differences in progression-free survival and recurrence-free survival rates were analyzed. The prognostic values of clinicopathologic factors for progression/recurrence were analyzed by using multivariate analysis. RESULTS.—: The pT1 substage was evaluable in all cases. Tumors with invasion into/beyond the muscularis mucosae and those beyond the stalk of the papillary lesion were associated with worse progression-free survival (P = .002 and P = .01, respectively). Notably, no patient with invasion confined to the stalk had disease progression during the 23-month median follow-up period. Only the pT1 subclassification method using the muscularis mucosae was an independent prognosticator of progression in multivariate analysis (P = .03). CONCLUSIONS.—: Precise pathologic subclassification of invasion using en bloc resection specimens may enable accurate prognosis and assessment in patients with bladder cancer with suspicious shallow invasion.

CONTEXT.—: In 2021 the World Health Organization distributed a new classification of central nervous system tumors that incorporated modern testing modalities in the diagnosis. Although universally accepted as a scientifically superior system, this schema has created controversy because its deployment globally is challenging in the best of circumstances and impossible in resource-poor health care ecosystems. Compounding this problem is the significant challenge that neuropathologists with expertise in central nervous system tumors are rare. OBJECTIVE.—: To demonstrate diagnostic use of simple unsupervised machine learning techniques using publicly available data sets. I also discuss some potential solutions to the deployment of neuropathology classification in health care ecosystems burdened by this classification schema. DATA SOURCES.—: The Cancer Genome Atlas RNA sequencing data from low-grade and high-grade gliomas. CONCLUSIONS.—: Methylation-based classification will be unable to solve all diagnostic problems in neuropathology. Information theory quantifications generate focused workflows in pathology, resulting in prevention of ordering unnecessary tests and identifying biomarkers that facilitate diagnosis.

CONTEXT.—: Although the basic principles of intraoperative diagnosis in surgical neuropathology have not changed in the last century, the last several decades have seen dramatic changes in tumor classification, terminology, molecular classification, and modalities used for intraoperative diagnosis. As many neuropathologic intraoperative diagnoses are performed by general surgical pathologists, awareness of these recent changes is important for the most accurate intraoperative diagnosis. OBJECTIVE.—: To describe recent changes in the practice of intraoperative surgical neuropathology, with an emphasis on new entities, tumor classification, and anticipated ancillary tests, including molecular testing. DATA SOURCES.—: The sources for this review include the fifth edition of the World Health Organization Classification of Tumours of the Central Nervous System, primary literature on intraoperative diagnosis and newly described tumor entities, and the authors' clinical experience. CONCLUSIONS.—: A significant majority of neuropathologic diagnoses require ancillary testing, including molecular analysis, for appropriate classification. Therefore, the primary goal for any neurosurgical intraoperative diagnosis is the identification of diagnostic tissue and the preservation of the appropriate tissue for molecular testing. The intraoperative pathologist should seek to place a tumor in the most accurate diagnostic category possible, but specific diagnosis at the time of an intraoperative diagnosis is often not possible. Many entities have seen adjustments to grading criteria, including the incorporation of molecular features into grading. Awareness of these changes can help to avoid overgrading or undergrading at the time of intraoperative evaluation.

CONTEXT.—: Clinician feedback is an important source of information for laboratory quality improvement programs. OBJECTIVE.—: To pilot a program for nearly real-time solicitation and analysis of physician feedback regarding clinical laboratory services. DESIGN.—: Laboratories distributed either electronic or paper survey forms to physicians. Results were tabulated by College of American Pathologists staff. Free-text comments were shared promptly with the participating laboratories to facilitate follow-up. RESULTS.—: Forty-seven clinical laboratories participated in the study and submitted results for 987 physician surveys, including both paper and electronic forms. Of 694 responses submitted electronically within the study period, 460 (66.3%) included at least 1 free-text entry, for a total of 951 free-text comments. CONCLUSIONS.—: Point-of-service solicitation of physician feedback regarding clinical laboratory services is feasible and can provide a substantial quantity of potentially useful information regarding laboratory performance from the customer perspective.

CONTEXT: The World Health Organization classification of tumors of the breast recognizes several special type carcinomas and benign lesions with features comparable to those of salivary gland tumors. OBJECTIVE: To discuss the histologic, immunophenotypic, molecular, and clinical features of salivary gland-like carcinomas of the breast. These breast tumors are often negative for hormone receptors and human epidermal growth factor receptor 2 (HER2), that is, triple-negative, but they generally have a much better prognosis than triple-negative breast carcinomas of no special type. We compare the immunophenotypic, molecular, and clinical features of these breast tumors with their salivary gland counterparts, highlighting similarities and differences. We also discuss benign salivary gland-like breast tumors. Finally, we highlight recent developments in understanding the molecular pathogenesis of these breast tumors and novel ancillary studies that can be used to support their diagnosis. DATA SOURCES: A literature review was conducted, and papers were selected for further analysis and discussion by the authors of this review based on their novelty, applicability, and impact in the field. CONCLUSIONS: Breast tumors that exhibit morphologic overlap with salivary gland tumors have been recognized by pathologists for decades, but the similarities and differences in their molecular pathogenesis have not been understood until more recently. These developments have led to novel diagnostic tools and further knowledge of these rare breast lesions.

CONTEXT.—: Increasing implementation of whole slide imaging together with digital workflow and advances in computing capacity enable the use of artificial intelligence (AI) in pathology, including breast pathology. Breast pathologists often face a significant workload, with diagnosis complexity, tedious repetitive tasks, and semiquantitative evaluation of biomarkers. Recent advances in developing AI algorithms have provided promising approaches to meet the demand in breast pathology. OBJECTIVE.—: To provide an updated review of AI in breast pathology. We examined the success and challenges of current and potential AI applications in diagnosing and grading breast carcinomas and other pathologic changes, detecting lymph node metastasis, quantifying breast cancer biomarkers, predicting prognosis and therapy response, and predicting potential molecular changes. DATA SOURCES.—: We obtained data and information by searching and reviewing literature on AI in breast pathology from PubMed and based our own experience. CONCLUSIONS.—: With the increasing application in breast pathology, AI not only assists in pathology diagnosis to improve accuracy and reduce pathologists' workload, but also provides new information in predicting prognosis and therapy response.

CONTEXT.—: Breast pathology has many mimics and diagnostic pitfalls. Evaluation of malignant breast lesions, particularly in the biopsy setting, can be especially challenging, with diagnostic errors having significant management implications. OBJECTIVE.—: To discuss the pitfalls encountered when evaluating ductal carcinoma in situ and invasive breast carcinomas, providing histologic clues and guidance for appropriate use and interpretation of immunohistochemistry to aid in the correct diagnosis. DATA SOURCES.—: Data were obtained from review of pertinent literature of ductal carcinoma in situ and invasive breast carcinomas and from the experience of the authors as practicing breast pathologists. CONCLUSIONS.—: Awareness of the pitfalls in diagnosing breast cancers is important when creating a differential diagnosis for each breast lesion evaluated. This review will cover some of these scenarios to aid in the diagnostic process.

PURPOSE.—: To update the American Society of Clinical Oncology-College of American Pathologists (ASCO-CAP) recommendations for human epidermal growth factor receptor 2 (HER2) testing in breast cancer. An Update Panel is aware that a new generation of antibody-drug conjugates targeting the HER2 protein is active against breast cancers that lack protein overexpression or gene amplification. METHODS.—: The Update Panel conducted a systematic literature review to identify signals for updating recommendations. RESULTS.—: The search identified 173 abstracts. Of 5 potential publications reviewed, none constituted a signal for revising existing recommendations. RECOMMENDATIONS.—: The 2018 ASCO-CAP recommendations for HER2 testing are affirmed. DISCUSSION.—: HER2 testing guidelines have focused on identifying HER2 protein overexpression or gene amplification in breast cancer to identify patients for therapies that disrupt HER2 signaling. This update acknowledges a new indication for trastuzumab deruxtecan when HER2 is not overexpressed or amplified but is immunohistochemistry (IHC) 1+ or 2+ without amplification by in situ hybridization. Clinical trial data on tumors that tested IHC 0 are limited (excluded from DESTINY-Breast04), and evidence is lacking that these cancers behave differently or do not respond similarly to newer HER2 antibody-drug conjugates. Although current data do not support a new IHC 0 versus 1+ prognostic or predictive threshold for response to trastuzumab deruxtecan, this threshold is now relevant because of the trial entry criteria that supported its new regulatory approval. Therefore, although it is premature to create new result categories of HER2 expression (eg, HER2-Low, HER2-Ultra-Low), best practices to distinguish IHC 0 from 1+ are now clinically relevant. This update affirms prior HER2 reporting recommendations and offers a new HER2 testing reporting comment to highlight the current relevance of IHC 0 versus 1+ results and best practice recommendations to distinguish these often subtle differences. Additional information is available at www.asco.org/breast-cancer-guidelines.