Changing digital and telecytology practices post COVID-19 comparing ASC survey results from 2016 to 2023.

INTRODUCTION: During the COVID-19 pandemic, the need for digital pathology tools became more urgent. However, there needs to be more knowledge of the use in cytology. We aimed to evaluate current digital cytology practices and attitudes and compare the results with a pre-COVID-19 American Society of Cytopathology (ASC) survey. MATERIALS AND METHODS: Fourteen survey questions assessing current attitudes toward digital cytology were developed from a 2016 ASC Digital Pathology Survey. Ten new survey questions were also created to evaluate telecytology use. The survey was e-mailed to ASC members over 6 weeks in 2023. RESULTS: A total of 123 individuals responded (116 in 2016). Attitudes toward digital cytology were unchanged; most participants stated digital cytology is beneficial (87% 2023 versus 90% 2016). The percentage of individuals using digital cytology was unchanged (56% in 2016 and 2023). However, telecytology for rapid onsite assessment (ROSE) is now considered the best application (55% 2023 versus 31% 2016). Forty-three institutions reported using digital and telecytology tools; 40% made implementations after 2020; most did not feel that COVID-19 affected digital cytology (56%). Telecytology for ROSE is the most common application now (78%) compared with education (30%) in 2016. Limitations for implementing digital imaging in cytology included inability to focus (38%) and expense (33%). CONCLUSIONS: General attitudes toward digital tools by the cytology community have essentially remained the same between 2016 and now. However, telecytology for ROSE is increasingly being used, which supports a need for validation and competency guidelines.

Training pathologists to assess stromal tumour-infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research.

A growing body of research supports stromal tumour-infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin-stained slides. Artificial intelligence/machine-learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment. Visual TIL assessment may suffer from significant interobserver variability. To improve interobserver agreement, regulatory science experts at the US Food and Drug Administration partnered with academic pathologists internationally to create a freely available online continuing medical education (CME) course to train pathologists in assessing breast cancer stromal TILs using an interactive format with expert commentary. Here we describe and provide a user guide to this CME course, whose content was designed to improve pathologist accuracy in scoring breast cancer TILs. We also suggest subsequent steps to translate knowledge into clinical practice with proficiency testing.

Uses and limitations of small-volume biopsies for the diagnosis of lymphoma.

Although surgical biopsy remains the gold standard for the diagnosis of lymphoma, small-volume biopsies including fine-needle aspiration and core needle biopsy are increasingly being used as a first line diagnostic tool. Small-volume biopsies are safe, rapid and cost effective; however, diagnostic utility varies by lymphoma subtype. It is important for pathologists and clinicians to recognize both the strengths and limitations of such biopsies.

Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models.

This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing data sets. In an earlier work by other researchers, an annotation workflow and quality checklist for computational pathology annotations were proposed. In this manuscript, we operationalize this workflow into an evaluable quality checklist that applies to any reader-interpreted medical images, and we demonstrate its use for an annotation effort in digital pathology. We refer to this quality framework as the Collection and Evaluation of Annotations for Reproducible Reporting of Artificial Intelligence (CLEARR-AI).

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Pathologic Exploration of the Axillary Soft Tissue Microenvironment and Its Impact on Axillary Management and Breast Cancer Outcomes.

PURPOSE: Axillary soft tissue (AXT) involvement with tumor cells extending beyond the positive lymph node (LN+) and extracapsular extension (ECE) has been overlooked in breast pathology specimen analysis. MATERIALS AND METHODS: We analyzed 2,162 LN+ patients, dividing them into four groups on the basis of axillary pathology: (1) LN+ only, (2) LN+ and ECE only, (3) LN+ and AXT without ECE, and (4) LN+ with both AXT and ECE. The primary end points were 10-year locoregional failure (LRF), the 10-year axillary failure, and 10-year distant metastasis rates. Multivariable Cox models, accounting for clinical factors, were fitted using the entire cohort, and subgroups analyses were conducted. RESULTS: The median follow-up was 9.4 years. The 10-year distant metastasis incidence was 42% for LN + AXT + ECE, 23% for both LN + AXT and LN + ECE only, and 13% for LN+ only. The 10-year axillary failure rates were 4.5% for LN + AXT + ECE, 4.6% for LN + AXT, 0.8% for LN + ECE only, and 1.6% for LN+ only. The 10-year LRF rates were 14% for LN + AXT + ECE, 10% for LN + AXT, 5.7% for LN + ECE only, and 6.2% for LN+ only. Multivariable analysis revealed that AXT was significantly associated with distant metastasis (hazard ratio [HR], 1.6; P < .001), locoregional failure (HR, 2.3; P < .001), and axillary failure (HR, 3.3; P = .003). Subgroup analyses showed that regional LN radiation (RLNR) improved locoregional tumor outcomes with AXT, ECE, or both (HR, 0.5; P = .03). Delivering ≤50 Gy to the axilla in the presence of AXT/ECE increased axillary failure (HR, 3.0; P = .04). Moreover, when delivering RLNR, axillary LN dissection could be de-escalated to sentinel node biopsy even in the presence of features such as AXT or ECE without significantly increasing any failure outcome: (HR, 1.0; P = .92) for LRF, (HR, 1.1; P = .94) axillary failure, and (HR, 0.4; P = .01) distant metastasis. CONCLUSION: Routine reporting of axillary tissue involvement, beyond LNs and ECE, is crucial in predicting breast cancer outcomes. Ruling out the presence of AXT is imperative before any form of axillary de-escalation, especially RLNR omission.

Spectrum of histopathologic findings in risk-reducing bilateral prophylactic mastectomy in patients with and without BRCA mutations.

Many germline mutations have been implicated in breast cancer pathogenesis and despite several studies on occult atypical lesions in prophylactic mastectomy specimens from patients with BRCA1/2 mutations, there are very limited data on other genes associated with increased breast cancer risk and the distribution of lesions in patients with hereditary breast cancer. We identified 207 patients who underwent bilateral prophylactic mastectomy due to germline mutations in BRCA1/2, PALB2, CHEK2, ATM, CDH1, PTEN, BARD1, or strong family history between 2015 and 2023. Patients with biopsy-proven past or current invasive breast carcinoma or carcinoma in-situ preoperatively were excluded. In addition to multiple benign lesions, the following atypical lesions were identified: flat epithelial atypia (16.9%), atypical ductal hyperplasia (14.0%), lobular neoplasia (14.0%), ductal carcinoma in-situ (4.3%), invasive ductal carcinoma (0.4%). Both low-grade and high-grade pathway lesions were identified in this cohort, and in a subset of patients, they co-occurred. The frequency of atypical lesions identified in patients with strong family history were comparable to those with proven germline mutation. PTEN immunohistochemistry showed loss of expression in ductal carcinoma in-situ and tubular adenomas in PTEN-mutant patients. Overall, findings from this cohort support the benefit of prophylactic mastectomy in patients with germline mutations and/or strong family history. Additionally, this is the first demonstration that PTEN immunohistochemistry may be helpful in identifying germline mutations in patients with atypical or neoplastic proliferations.

Initial interactions with the FDA on developing a validation dataset as a medical device development tool.

Quantifying tumor-infiltrating lymphocytes (TILs) in breast cancer tumors is a challenging task for pathologists. With the advent of whole slide imaging that digitizes glass slides, it is possible to apply computational models to quantify TILs for pathologists. Development of computational models requires significant time, expertise, consensus, and investment. To reduce this burden, we are preparing a dataset for developers to validate their models and a proposal to the Medical Device Development Tool (MDDT) program in the Center for Devices and Radiological Health of the U.S. Food and Drug Administration (FDA). If the FDA qualifies the dataset for its submitted context of use, model developers can use it in a regulatory submission within the qualified context of use without additional documentation. Our dataset aims at reducing the regulatory burden placed on developers of models that estimate the density of TILs and will allow head-to-head comparison of multiple computational models on the same data. In this paper, we discuss the MDDT preparation and submission process, including the feedback we received from our initial interactions with the FDA and propose how a qualified MDDT validation dataset could be a mechanism for open, fair, and consistent measures of computational model performance. Our experiences will help the community understand what the FDA considers relevant and appropriate (from the perspective of the submitter), at the early stages of the MDDT submission process, for validating stromal TIL density estimation models and other potential computational models. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

INTEGRATE-Circ and INTEGRATE-Vis: unbiased detection and visualization of fusion-derived circular RNA.

MOTIVATION: Backsplicing of RNA results in circularized rather than linear transcripts, known as circular RNA (circRNA). A recently discovered and poorly understood subset of circRNAs that are composed of multiple genes, termed fusion-derived circular RNAs (fcircRNAs), represent a class of potential biomarkers shown to have oncogenic potential. Detection of fcircRNAs eludes existing analytical tools, making it difficult to more comprehensively assess their prevalence and function. Improved detection methods may lead to additional biological and clinical insights related to fcircRNAs. RESULTS: We developed the first unbiased tool for detecting fcircRNAs (INTEGRATE-Circ) and visualizing fcircRNAs (INTEGRATE-Vis) from RNA-Seq data. We found that INTEGRATE-Circ was more sensitive, precise and accurate than other tools based on our analysis of simulated RNA-Seq data and our tool was able to outperform other tools in an analysis of public lymphoblast cell line data. Finally, we were able to validate in vitro three novel fcircRNAs detected by INTEGRATE-Circ in a well-characterized breast cancer cell line. AVAILABILITY AND IMPLEMENTATION: Open source code for INTEGRATE-Circ and INTEGRATE-Vis is available at https://www.github.com/ChrisMaherLab/INTEGRATE-CIRC and https://www.github.com/ChrisMaherLab/INTEGRATE-Vis.

Regulation of RNA methylation by therapy treatment, promotes tumor survival.

Our data previously revealed that chemosurviving cancer cells translate specific genes. Here, we find that the m6A-RNA-methyltransferase, METTL3, increases transiently in chemotherapy-treated breast cancer and leukemic cells in vitro and in vivo. Consistently, m6A increases on RNA from chemo-treated cells, and is needed for chemosurvival. This is regulated by eIF2α phosphorylation and mTOR inhibition upon therapy treatment. METTL3 mRNA purification reveals that eIF3 promotes METTL3 translation that is reduced by mutating a 5'UTR m6A-motif or depleting METTL3. METTL3 increase is transient after therapy treatment, as metabolic enzymes that control methylation and thus m6A levels on METTL3 RNA, are altered over time after therapy. Increased METTL3 reduces proliferation and anti-viral immune response genes, and enhances invasion genes, which promote tumor survival. Consistently, overriding phospho-eIF2α prevents METTL3 elevation, and reduces chemosurvival and immune-cell migration. These data reveal that therapy-induced stress signals transiently upregulate METTL3 translation, to alter gene expression for tumor survival.

One procedure-one report: the Re-Imagine Cytopathology Task Force position paper on small tissue biopsy triage in anatomic pathology.

INTRODUCTION: Endoscopic biopsy procedures increasingly generate multiple tissue samples from multiple sites, and frequently retrieve concurrent cytologic specimens and small core needle biopsies. There is currently lack of consensus in subspecialized practices as to whether cytopathologists or surgical pathologists should review such samples, and whether the pathology findings should be reported together or separately. MATERIALS AND METHODS: In December 2021, the American Society of Cytopathology convened the Re-Imagine Cytopathology Task Force to examine various workflows that would facilitate unified pathology reporting of concurrently obtained biopsies and improve clinical care. RESULTS AND CONCLUSIONS: This position paper summarizes the key points and highlights the advantages, challenges, and resources available to support the implementation of such workflows that result in "one procedure-one report".

Characterization of cell-type specific circular RNAs associated with colorectal cancer metastasis.

Colorectal cancer (CRC) is the most common gastrointestinal malignancy and a leading cause of cancer deaths in the United States. More than half of CRC patients develop metastatic disease (mCRC) with an average 5-year survival rate of 13%. Circular RNAs (circRNAs) have recently emerged as important tumorigenesis regulators; however, their role in mCRC progression remains poorly characterized. Further, little is known about their cell-type specificity to elucidate their functions in the tumor microenvironment (TME). To address this, we performed total RNA sequencing (RNA-seq) on 30 matched normal, primary and metastatic samples from 14 mCRC patients. Additionally, five CRC cell lines were sequenced to construct a circRNA catalog in CRC. We detected 47 869 circRNAs, with 51% previously unannotated in CRC and 14% novel candidates when compared to existing circRNA databases. We identified 362 circRNAs differentially expressed in primary and/or metastatic tissues, termed circular RNAs associated with metastasis (CRAMS). We performed cell-type deconvolution using published single-cell RNA-seq datasets and applied a non-negative least squares statistical model to estimate cell-type specific circRNA expression. This predicted 667 circRNAs as exclusively expressed in a single cell type. Collectively, this serves as a valuable resource, TMECircDB (accessible at https://www.maherlab.com/tmecircdb-overview), for functional characterization of circRNAs in mCRC, specifically in the TME.

Multi-institutional Assessment of Pathologist Scoring HER2 Immunohistochemistry.

The HercepTest was approved 20+ years ago as the companion diagnostic test for trastuzumab in human epidermal growth factor 2 (HER2) or ERBB2 gene-amplified/overexpressing breast cancers. Subsequent HER2 immunohistochemistry (IHC) assays followed, including the now most common Ventana 4B5 assay. Although this IHC assay has become the clinical standard, its reliability, reproducibility, and accuracy have largely been approved and accepted on the basis of concordance among small numbers of pathologists without validation in a real-world setting. In this study, we evaluated the concordance and interrater reliability of scoring HER2 IHC in 170 breast cancer biopsies by 18 breast cancer-specialized pathologists from 15 institutions. We used the Observers Needed to Evaluate Subjective Tests method to determine the plateau of concordance and the minimum number of pathologists needed to estimate interrater agreement values for large numbers of raters, as seen in the real-world setting. We report substantial discordance within the intermediate categories (<1% agreement for 1+ and 3.6% agreement for 2+) in the 4-category HER2 IHC scoring system. The discordance within the IHC 0 cases is also substantial with an overall percent agreement (OPA) of only 25% and poor interrater reliability metrics (0.49 Fleiss' kappa, 0.55 intraclass correlation coefficient). This discordance can be partially reduced by using a 3-category system (28.8% vs 46.5% OPA for 4-category and 3-category scoring systems, respectively). Observers Needed to Evaluate Subjective Tests plots suggest that the OPA for the task of determining a HER2 IHC score 0 from not 0 plateaus statistically around 59.4% at 10 raters. Conversely, at the task of scoring HER2 IHC as 3+ or not 3+ pathologists' concordance was much higher with an OPA that plateaus at 87.1% with 6 raters. This suggests that legacy HER2 IHC remains valuable for finding the patients in whom the ERBB2 gene is amplified but unacceptably discordant in assigning HER2-low or HER2-negative status for the emerging HER2-low therapies.

CRISPR-Enhanced Hydrogel Microparticles for Multiplexed Detection of Nucleic Acids.

CRISPR/Cas systems offer a powerful sensing mechanism to transduce sequence-specific information into amplified analytical signals. However, performing multiplexed CRISPR/Cas assays remains challenging and often requires complex approaches for multiplexed assays. Here, a hydrogel-based CRISPR/Cas12 system termed CLAMP (Cas-Loaded Annotated Micro-Particles) is described. The approach compartmentalizes the CRISPR/Cas reaction in spatially-encoded hydrogel microparticles (HMPs). Each HMP is identifiable by its face code and becomes fluorescent when target DNA is present. The assay is further streamlined by capturing HMPs inside a microfluidic device; the captured particles are then automatically recognized by a machine-learning algorithm. The CLAMP assay is fast, highly sensitive (attomolar detection limits with preamplification), and capable of multiplexing in a single-pot assay. As a proof-of-concept clinical application, CLAMP is applied to detect nucleic acid targets of human papillomavirus in cervical brushing samples.

Utilization of Oil Red O staining for assessing aspiration risk in lung transplant patients: A multidisciplinary prospective study with clinical practice insights.

BACKGROUND: Gastroesophageal reflux disease with microaspiration has been associated with graft dysfunction in lung transplant patients. Identifying patients with aspiration is clinically important because it enables implementation of appropriate interventions like antireflux therapy. Oil Red O (ORO) staining with determination of the lipid-laden macrophage index (LLMI) has been proposed as a noninvasive surrogate marker in the detection of aspiration. The aim of this study was to prospectively evaluate clinical utilization of ORO staining in the assessment of aspiration risk. METHODS: All transbronchial surgical pathology biopsies obtained in lung transplant patients undergoing routine surveillance from August 2020 through November 2021 were included in this study. Clinical team members prospectively ascertained the aspiration risk category (ARC) of each patient both before and after biopsy findings and recorded reasons for change in ARC. RESULTS: A total of 132 transbronchial biopsies with concurrent LLMI were included in the study. LLMI was low in 51 cases (38.6%), including 21 of the 54 cases (38.9%) where aspiration was suggested based on the transbronchial biopsy findings. In total, 19 cases (14.4%) underwent a change in ARC post-biopsy including 10 that were upgraded and nine cases that were downgraded. Transbronchial biopsy findings were noted as the reason for change in ARC in the majority (15/19; 79%) of cases; only a minority (2/19; 10.5%) were due to the LLMI. Notably, 16 cases (12.1%) had a low LLMI with high-risk post-biopsy ARC and nine cases (6.8%) had a high LLMI with low-risk post-biopsy ARC. CONCLUSIONS: This study observed that clinical evaluation for aspiration relied more heavily on transbronchial biopsy findings. Although LLMI may retain clinical utility in some scenarios, reevaluation of the clinical value of ORO testing would be prudent.

Diagnostic Discrepancies in Small-volume Biopsy for the Initial Diagnosis, Recurrence, and Transformation of Follicular Lymphoma: A Multi-Institutional Collaborative Study.

Small-volume biopsies (SVBs) including fine-needle aspiration (FNA), cell block, and needle core biopsies (NCB) are increasingly utilized to diagnose and guide the clinical management of lymphoma. We established a multi-institutional interdisciplinary collaboration of cytopathologists, hematopathologists, and oncologists focused on the role of SVB in the management of patients with follicular lymphoma (FL). To assess the performance characteristics of SVB in this setting, we evaluated all consecutive SVBs performed for clinical indications of initial diagnosis, recurrence, or transformation of FL over a 5-year period and focused on the 182 that had at least one subsequent biopsy within 3 months as part of the same clinical work-up. The most common outcome of a subsequent biopsy as part of the same clinical work-up was a more specific diagnosis usually assigning the pathologic grade (111/182, 61%), followed by a complete agreement with the SVB (24/182, 13%), and change from nondiagnostic on initial biopsy to diagnostic on subsequent biopsy (21/182, 12%). A minority resulted in a diagnostic change from benign to lymphoma (17/182, 9%), a change in FL grade (5/182, 3%), or change in the lymphoma diagnostic category (4/182, 2%). There were no cases where an initial diagnosis of lymphoma was overturned. The distribution of discrepancies was similar across initial SVB types (FNA, FNA + cell block, NCB with or without FNA). Tissue limitations were noted in a minority of cases (53/182, 29%) and were enriched among initially nondiagnostic biopsies (16/21, 76%). Flow cytometry immunophenotyping was performed in the majority of cases both at the first and last biopsy (147/182, 81%). SVB can be a powerful method to detect FL in various clinical indications, with discrepant cases mostly resulting from a refinement in the initial diagnosis.

Small volume biopsy diagnostic yield at initial diagnosis versus recurrence/transformation of follicular lymphoma: A retrospective Cyto-Heme Interinstitutional Collaborative study.

BACKGROUND: Few studies have evaluated diagnostic yield of small volume biopsies (SVB) for the diagnosis and management of follicular lymphoma (FL). METHODS: The authors performed a multi-institutional retrospective analysis of SVBs including fine-needle aspiration (FNA) and needle core biopsy (NCB) for initial FL diagnosis and suspected recurrence or transformation of FL. A total of 676 workups beginning with SVB were assessed for the mean number of biopsies per workup, the proportion of workups requiring multiple biopsies, and the proportion with a complete diagnosis including grade, on initial biopsy. RESULTS: Compared to workups performed for question transformation/recurrence, those done for initial FL diagnosis were significantly more likely to require multiple biopsies (p < .01), had a higher mean number of biopsies per workup (1.7 vs. 1.1, absolute standardized difference = 1.1), and a lower complete diagnosis rate at initial biopsy (39% vs. 56%). At initial FL diagnosis, NCB +/- FNA was associated with fewer biopsies per workup compared to FNA +/- CB (1.2 vs. 1.9), fewer workups requiring multiple biopsies (23% vs. 83%), and a higher complete diagnosis rate (71% vs. 18%). In contrast, during assessment for transformation/recurrence, NCB and FNA showed a similar mean number of biopsies per workup (1.2 vs. 1.2) and few workups required multiple biopsies (6% vs. 19%). CONCLUSIONS: SVB at initial FL diagnosis often required additional biopsies to establish a complete diagnosis. In contrast, when assessing for transformed/recurrent FL, additional biopsies were generally not obtained regardless of SVB type, suggesting that in these clinical settings SVB may be sufficient for clinical decision-making.

Pilot study to evaluate tools to collect pathologist annotations for validating machine learning algorithms.

Purpose: Validation of artificial intelligence (AI) algorithms in digital pathology with a reference standard is necessary before widespread clinical use, but few examples focus on creating a reference standard based on pathologist annotations. This work assesses the results of a pilot study that collects density estimates of stromal tumor-infiltrating lymphocytes (sTILs) in breast cancer biopsy specimens. This work will inform the creation of a validation dataset for the evaluation of AI algorithms fit for a regulatory purpose. Approach: Collaborators and crowdsourced pathologists contributed glass slides, digital images, and annotations. Here, "annotations" refer to any marks, segmentations, measurements, or labels a pathologist adds to a report, image, region of interest (ROI), or biological feature. Pathologists estimated sTILs density in 640 ROIs from hematoxylin and eosin stained slides of 64 patients via two modalities: an optical light microscope and two digital image viewing platforms. Results: The pilot study generated 7373 sTILs density estimates from 29 pathologists. Analysis of annotations found the variability of density estimates per ROI increases with the mean; the root mean square differences were 4.46, 14.25, and 26.25 as the mean density ranged from 0% to 10%, 11% to 40%, and 41% to 100%, respectively. The pilot study informs three areas of improvement for future work: technical workflows, annotation platforms, and agreement analysis methods. Upgrades to the workflows and platforms will improve operability and increase annotation speed and consistency. Conclusions: Exploratory data analysis demonstrates the need to develop new statistical approaches for agreement. The pilot study dataset and analysis methods are publicly available to allow community feedback. The development and results of the validation dataset will be publicly available to serve as an instructive tool that can be replicated by developers and researchers.

Implementation and Clinical Adoption of Precision Oncology Workflows Across a Healthcare Network.

BACKGROUND: Precision oncology relies on molecular diagnostics, and the value-proposition of modern healthcare networks promises a higher standard of care across partner sites. We present the results of a clinical pilot to standardize precision oncology workflows. METHODS: Workflows are defined as the development, roll-out, and updating of disease-specific molecular order sets. We tracked the timeline, composition, and effort of consensus meetings to define the combination of molecular tests. To assess clinical impact, we examined order set adoption over a two-year period (before and after roll-out) across all gastrointestinal and hepatopancreatobiliary (GI) malignancies, and by provider location within the network. RESULTS: Development of 12 disease center-specific order sets took ~9 months, and the average number of tests per indication changed from 2.9 to 2.8 (P = .74). After roll-out, we identified significant increases in requests for GI patients (17%; P < .001), compliance with testing recommendations (9%; P < .001), and the fraction of "abnormal" results (6%; P < .001). Of 1088 GI patients, only 3 received targeted agents based on findings derived from non-recommended orders (1 before and 2 after roll-out); indicating that our practice did not negatively affect patient treatments. Preliminary analysis showed 99% compliance by providers in network sites, confirming the adoption of the order sets across the network. CONCLUSION: Our study details the effort of establishing precision oncology workflows, the adoption pattern, and the absence of harm from the reduction of non-recommended orders. Establishing a modifiable communication tool for molecular testing is an essential component to optimize patient care via precision oncology.

Vasculopathy and Increased Vascular Congestion in Fatal COVID-19 and Acute Respiratory Distress Syndrome.

Rationale: The leading cause of death in coronavirus disease 2019 (COVID-19) is severe pneumonia, with many patients developing acute respiratory distress syndrome (ARDS) and diffuse alveolar damage (DAD). Whether DAD in fatal COVID-19 is distinct from other causes of DAD remains unknown. Objective: To compare lung parenchymal and vascular alterations between patients with fatal COVID-19 pneumonia and other DAD-causing etiologies using a multidimensional approach. Methods: This autopsy cohort consisted of consecutive patients with COVID-19 pneumonia (n = 20) and with respiratory failure and histologic DAD (n = 21; non-COVID-19 viral and nonviral etiologies). Premortem chest computed tomography (CT) scans were evaluated for vascular changes. Postmortem lung tissues were compared using histopathological and computational analyses. Machine-learning-derived morphometric analysis of the microvasculature was performed, with a random forest classifier quantifying vascular congestion (CVasc) in different microscopic compartments. Respiratory mechanics and gas-exchange parameters were evaluated longitudinally in patients with ARDS. Measurements and Main Results: In premortem CT, patients with COVID-19 showed more dilated vasculature when all lung segments were evaluated (P = 0.001) compared with controls with DAD. Histopathology revealed vasculopathic changes, including hemangiomatosis-like changes (P = 0.043), thromboemboli (P = 0.0038), pulmonary infarcts (P = 0.047), and perivascular inflammation (P < 0.001). Generalized estimating equations revealed significant regional differences in the lung microarchitecture among all DAD-causing entities. COVID-19 showed a larger overall CVasc range (P = 0.002). Alveolar-septal congestion was associated with a significantly shorter time to death from symptom onset (P = 0.03), length of hospital stay (P = 0.02), and increased ventilatory ratio [an estimate for pulmonary dead space fraction (Vd); p = 0.043] in all cases of ARDS. Conclusions: Severe COVID-19 pneumonia is characterized by significant vasculopathy and aberrant alveolar-septal congestion. Our findings also highlight the role that vascular alterations may play in Vd and clinical outcomes in ARDS in general.