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Context.--Pulmonary carcinoids are classified as typical or atypical by assessing necrosis and mitoses, which usually cannot be adequately assessed on small biopsies. Ki-67 is not currently used to grade pulmonary carcinoids, but it may be helpful to determine preliminary grade in biopsies. However, the rate at which Ki-67 could underestimate or overestimate grade on small biopsies has not been well studied. Objective.--To compare Ki-67 labeling obtained on small biopsies to subsequent resection. Design.--Ki-67 was performed on paired biopsy and resection specimens from 55 patients. Slides were scanned using Aperio ScanScope. Labeling index was determined using automated hot spot and tumor tracing methods. Results.--The study included 41 typical and 14 atypical carcinoids. Atypical carcinoids were larger and had more distant metastases. Death from disease occurred in 3 patients (all had atypical carcinoids). Median hot spot Ki67 labeling index was greater in resection compared with biopsy by 0.7% (P = .02). Median tumor tracing Ki-67 was lower in resection compared with biopsy by 0.5% (P < .001). Receiver-operating characteristic analysis showed similar hot spot Ki-67 cutoffs to predict atypical histology (3.5% for biopsy, 3.6% for resection; area under the curve [AUC], 0.75 and 0.74, respectively). Different optimal cutoffs were needed for tracing method based on biopsy (2.1%; AUC, 0.75) compared with resection (1.0%; AUC, 0.67). Conclusions.--Hot spot Ki-67 tends to underestimate grade on small biopsies, whereas grade is overestimated by tumor tracing. Hot spot Ki-67 cutoff of 3.5% predicted atypical histology for both biopsy and resection. Different biopsy and resection cutoffs were necessary for tumor tracing, which would make clinical implementation more difficult. doi: 10.5858/arpa.2019-0374-OA, Pulmonary neuroendocrine tumors are a heterogeneous group of neoplasms that includes carcinoid tumors, which have somewhat unpredictable but relatively indolent behavior, as well as small cell and large cell neuroendocrine [...]

Context.—: Artificial intelligence is a transforming technology for anatomic pathology. Involvement within the workforce will foster support for algorithm development and implementation., Objective.—: To develop a supportive ecosystem that enables pathologists with variable expertise in artificial intelligence to create algorithms in a development environment with seamless transition to a production environment., Results.—: The development team considered internal development and vended solutions. Because of the extended timeline and resource requirements for internal development, a decision was made to use a vended solution. Vendor proposals were solicited and reviewed by pathologists, IT, and security groups. A vendor was selected and pipelines for development and production were established. Proposals for development were solicited from the pathology department. Eighty-four investigators were selected for the initial cohort, receiving training and access to dedicated subject matter experts. A total of 30 of 31 projects progressed through the model development process of annotating, training, and validation. Based on these projects, 15 abstracts were submitted to national meetings., Conclusions.—: Democratizing artificial intelligence by creating an ecosystem to support pathologists with varying levels of expertise can break down entry barriers, reduce overall cost of algorithm development, improve algorithm quality, and enhance the speed of adoption., Competing Interests: Stetzik, Lee, Samiei, Beamer, and Westerling-Bui are employees of Aiforia Technologies, and Westerling-Bui has options in Aiforia Technologies. The other authors have no relevant financial interest in the products or companies described in this article., (© 2024 College of American Pathologists.)

Introduction  Vestibular schwannoma (VS) behavior following subtotal resection (STR) is highly variable. Overall progression rates have been reported as high as 44%, and optimal treatment is controversial. Correspondingly, identification of a reliable clinical or pathologic marker associated with progression after STR would help guide decision-making. Methods  A prospectively maintained institutional VS registry from 1999 to 2014 was retrospectively reviewed for sporadic VS patients who underwent primary STR without preceding stereotactic radiosurgery (SRS) by a single neurosurgery-neurotology team. Primary endpoints included tumor progression and postoperative facial nerve function. Pathologic specimens were stained for Ki67, CD68, S100, and SOX10 and were quantitated by digital imaging analysis. Macrophage density was defined as the ratio of CD68 + macrophages to S100 + macrophages and Schwannian tumor cells. Clinical outcomes were correlated with pathologic markers. Results  Forty-six patients met the study inclusion criteria. Thirteen (28%) progressed during a mean 57 months of follow-up (range 15-149). Favorable postoperative facial nerve function (House-Brackmann I-II) was achieved in 37 (80%). CD68 + cells were present at significantly higher concentrations in tumors that progressed ( p  = 0.03). Higher macrophage density was significantly associated with both tumor progression ( p  = 0.02) and unfavorable facial nerve function ( p  = 0.02). Ki67 percent positivity was not significantly associated with either primary endpoint ( p  = 0.83; p  = 0.58). Conclusions   Macrophage density may provide an important marker for individuals at the highest risk for progression of VS after STR, potentially prompting closer surveillance or consideration for upfront SRS following STR. This finding supports preceding conclusions that an intratumoral macrophage-predominant inflammatory response may be a marker for tumor growth and a potential therapeutic target.