A Machine Learning Algorithm Improves the Diagnostic Accuracy of the Histologic Component of Antibody Mediated Rejection (AMR-H) in Cardiac Transplant Endomyocardial Biopsies.

BACKGROUND: Pathologic antibody mediated rejection (pAMR) remains a major driver of graft failure in cardiac transplant patients. The endomyocardial biopsy remains the primary diagnostic tool but presents with challenges, particularly in distinguishing the histologic component (pAMR-H) defined by 1) intravascular macrophage accumulation in capillaries and 2) activated endothelial cells that expand the cytoplasm to narrow or occlude the vascular lumen. Frequently, pAMR-H is difficult to distinguish from acute cellular rejection (ACR) and healing injury. With the advent of digital slide scanning and advances in machine deep learning, artificial intelligence technology is widely under investigation in the areas of oncologic pathology, but in its infancy in transplant pathology. For the first time, we determined if a machine learning algorithm could distinguish pAMR-H from normal myocardium, healing injury and ACR. MATERIALS AND METHODS: A total of 4,212 annotations (1,053 regions of normal, 1,053 pAMR-H, 1,053 healing injury and 1,053 ACR) were completed from 300 hematoxylin and eosin slides scanned using a Leica Aperio GT450 digital whole slide scanner at 40X magnification. All regions of pAMR-H were annotated from patients confirmed with a previous diagnosis of pAMR2 (>50% positive C4d immunofluorescence and/or >10% CD68 positive intravascular macrophages). Annotations were imported into a Python 3.7 development environment using the OpenSlide™ package and a convolutional neural network approach utilizing transfer learning was performed. RESULTS: The machine learning algorithm showed 98% overall validation accuracy and pAMR-H was correctly distinguished from specific categories with the following accuracies: normal myocardium (99.2%), healing injury (99.5%) and ACR (99.5%). CONCLUSION: Our novel deep learning algorithm can reach acceptable, and possibly surpass, performance of current diagnostic standards of identifying pAMR-H. Such a tool may serve as an adjunct diagnostic aid for improving the pathologist's accuracy and reproducibility, especially in difficult cases with high inter-observer variability. This is one of the first studies that provides evidence that an artificial intelligence machine learning algorithm can be trained and validated to diagnose pAMR-H in cardiac transplant patients. Ongoing studies include multi-institutional verification testing to ensure generalizability.

Patterns of Unwanted Biological and Technical Expression Variation Among 49 Human Tissues.

Tissue gene expression studies are impacted by biological and technical sources of variation, which can be broadly classified into wanted and unwanted variation. The latter, if not addressed, results in misleading biological conclusions. Methods have been proposed to reduce unwanted variation, such as normalization and batch correction. A more accurate understanding of all causes of variation could significantly improve the ability of these methods to remove unwanted variation while retaining variation corresponding to the biological question of interest. We used 17,282 samples from 49 human tissues in the Genotype-Tissue Expression data set (v8) to investigate patterns and causes of expression variation. Transcript expression was transformed to z-scores, and only the most variable 2% of transcripts were evaluated and clustered based on coexpression patterns. Clustered gene sets were assigned to different biological or technical causes based on histologic appearances and metadata elements. We identified 522 variable transcript clusters (median: 11 per tissue) among the samples. Of these, 63% were confidently explained, 16% were likely explained, 7% were low confidence explanations, and 14% had no clear cause. Histologic analysis annotated 46 clusters. Other common causes of variability included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), disease status, and age. Technical causes included blood draw timing and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens data set of single-cell expression. This is among the largest explorations of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression and demonstrated the utility of matched histologic specimens. It further demonstrated the value of acquiring meaningful tissue harvesting metadata elements to use for improved normalization, batch correction, and analysis of both bulk and single-cell RNA-seq data.

Coexistence of Light Chain and Transthyretin Cardiac Amyloidosis.

Although most patients with cardiac amyloidosis are diagnosed with either light chain (AL) or transthyretin (ATTR) disease, coexisting amyloid subtypes can occur. We present three cases of coexisting AL and ATTR cardiac amyloidosis and demonstrate the importance of clinical history and endomyocardial biopsy in diagnosis of this rare entity.

Brooklyn plots to identify co-expression dysregulation in single cell sequencing.

Altered open chromatin regions, impacting gene expression, is a feature of some human disorders. We discovered it is possible to detect global changes in genomically-related adjacent gene co-expression within single cell RNA sequencing (scRNA-seq) data. We built a software package to generate and test non-randomness using 'Brooklyn plots' to identify the percent of genes significantly co-expressed from the same chromosome in ∼10 MB intervals across the genome. These plots establish an expected low baseline of co-expression in scRNA-seq from most cell types, but, as seen in dilated cardiomyopathy cardiomyocytes, altered patterns of open chromatin appear. These may relate to larger regions of transcriptional bursting, observable in single cell, but not bulk datasets.

Bile Acid Receptor Agonist Reverses Transforming Growth Factor-ß1-Mediated Fibrogenesis in Human Induced Pluripotent Stem Cells-Derived Kidney Organoids.

Chronic kidney disease progresses through the replacement of functional tissue compartments with fibrosis, a maladaptive repair process. Shifting kidney repair toward a physiologically intact architecture, rather than fibrosis, is key to blocking chronic kidney disease progression. Much research into the mechanisms of fibrosis is performed in rodent models with less attention to the human genetic context. Recently, human induced pluripotent stem cell (iPSC)-derived organoids have shown promise in overcoming the limitation. In this study, we developed a fibrosis model that uses human iPSC-based 3-dimensional renal organoids, in which exogenous transforming growth factor-ß1 (TGF-ß1) induced the production of extracellular matrix. TGF-ß1-treated organoids showed tubulocentric collagen 1α1 production by regulating downstream transcriptional regulators, Farnesoid X receptor, phosphorylated mothers against decapentaplegic homolog 3 (p-SMAD3), and transcriptional coactivator with PDZ-binding motif (TAZ). Increased nuclear TAZ expression was confirmed in the tubular epithelium in human kidney biopsies with tubular injury and early fibrosis. A dual bile acid receptor agonist (INT-767) increased Farnesoid X receptor and reduced p-SMAD3 and TAZ, attenuating TGF-ß1-induced fibrosis in kidney organoids. Finally, we show that TAZ interacted with TEA-domain transcription factors and p-SMAD3 with TAZ and TEA-domain transcription factor 4 coregulating collagen 1α1 gene transcription. In summary, we establish a novel, readily manipulable fibrogenesis model and posit a role for bile acid receptor agonism early in renal parenchymal fibrosis.

Platelet activation and endothelial dysfunction biomarkers in acute coronary syndrome: the impact of PCSK9 inhibition.

AIMS: Platelet activation and endothelial dysfunction contribute to adverse outcomes in patients with acute coronary syndromes (ACS). The goals of this study were to assess the impact of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibition on markers of platelet activation and endothelial dysfunction in ACS patients and the interaction among PCSK9, platelets, and endothelial cells (ECs) on left internal mammary artery (LIMA) vascular endothelium using specimens obtained during coronary artery bypass surgery (CABG). METHODS AND RESULTS: Acute coronary syndromes patients enrolled in the Evolocumab in ACS trials were randomized to placebo or a single dose of 420 mg evolocumab within 24 h of hospitalization. Serum samples for analysis of platelet factor 4 (PF4) and P-selectin, markers of platelet activation, and von Willebrand factor (vWF), a marker of endothelial dysfunction, were obtained at baseline and 30 days. Additionally, LIMA segments obtained during CABG from patients who were and were not receiving evolocumab were immunostained with PCSK9; CD61, a platelet-specific marker; and CD31, an endothelial cell-specific marker. Forty-six participants were randomized to placebo or to evolocumab. Controlling for baseline levels, PF4 and vWF were significantly lower in the evolocumab, than in the placebo, group at 30 days. Immunostaining of LIMA specimens from twelve participants undergoing CABG revealed colocalization of PCSK9, CD61, and CD31 at the vascular endothelium. Administration of evolocumab was associated with decreased overlap of PCSK9, CD61, and CD31. CONCLUSIONS: Proprotein Convertase Subtilisin/Kexin 9 inhibition decreases markers of platelet activation and endothelial dysfunction in ACS patients. PCSK9 is associated with platelets and vascular ECs in LIMA segments and PCSK9 inhibition decreases that interaction.

Anatomical structures, cell types, and biomarkers of the healthy human blood vasculature.

More than 150 scientists from 17 consortia are collaborating on an international project to build a Human Reference Atlas, which maps all 37 trillion cells in the healthy adult human body. The initial release of this atlas provided hierarchical lists of the anatomical structures, cell types, and biomarkers in 11 organs. Here, we describe the methods we used as part of this initiative to build the first open, computer-readable, and comprehensive database of the adult human blood vasculature, called the Human Reference Atlas-Vasculature Common Coordinate Framework (HRA-VCCF). It includes 993 vessels and their branching connections, 10 cell types, and 10 biomarkers. With this paper we are releasing additional details on vessel types and subtypes, branching sequence, anastomoses, portal systems, microvasculature, functional tissue units, mappings to regions vessels supply or drain, geometric properties of vessels, and links to 3D reference objects. Future versions will add variants and connections to the lymph vasculature; and, it will iteratively expand and improve the database as additional experimental data become available through the participating consortia.

Right Ventricular Sarcomere Contractile Depression and the Role of Thick Filament Activation in Human Heart Failure With Pulmonary Hypertension.

BACKGROUND: Right ventricular (RV) contractile dysfunction commonly occurs and worsens outcomes in patients with heart failure with reduced ejection fraction and pulmonary hypertension (HFrEF-PH). However, such dysfunction often goes undetected by standard clinical RV indices, raising concerns that they may not reflect aspects of underlying myocyte dysfunction. We thus sought to characterize RV myocyte contractile depression in HFrEF-PH, identify those components reflected by clinical RV indices, and uncover underlying biophysical mechanisms. METHODS: Resting, calcium-, and load-dependent mechanics were prospectively studied in permeabilized RV cardiomyocytes isolated from explanted hearts from 23 patients with HFrEF-PH undergoing cardiac transplantation and 9 organ donor controls. RESULTS: Unsupervised machine learning using myocyte mechanical data with the highest variance yielded 2 HFrEF-PH subgroups that in turn mapped to patients with decompensated or compensated clinical RV function. This correspondence was driven by reduced calcium-activated isometric tension in decompensated clinical RV function, whereas surprisingly, many other major myocyte contractile measures including peak power and myocyte active stiffness were similarly depressed in both groups. Similar results were obtained when subgroups were first defined by clinical indices, and then myocyte mechanical properties in each group compared. To test the role of thick filament defects, myofibrillar structure was assessed by x-ray diffraction of muscle fibers. This revealed more myosin heads associated with the thick filament backbone in decompensated clinical RV function, but not compensated clinical RV function, as compared with controls. This corresponded to reduced myosin ATP turnover in decompensated clinical RV function myocytes, indicating less myosin in a crossbridge-ready disordered-relaxed (DRX) state. Altering DRX proportion (%DRX) affected peak calcium-activated tension in the patient groups differently, depending on their basal %DRX, highlighting potential roles for precision-guided therapeutics. Last, increasing myocyte preload (sarcomere length) increased %DRX 1.5-fold in controls but only 1.2-fold in both HFrEF-PH groups, revealing a novel mechanism for reduced myocyte active stiffness and by extension Frank-Starling reserve in human heart failure. CONCLUSIONS: Although there are many RV myocyte contractile deficits in HFrEF-PH, commonly used clinical indices only detect reduced isometric calcium-stimulated force, which is related to deficits in basal and recruitable %DRX myosin. Our results support use of therapies to increase %DRX and enhance length-dependent recruitment of DRX myosin heads in such patients.

Direct observation of the evolution of cell-type-specific microRNA expression signatures supports the hematopoietic origin model of endothelial cells.

The evolution of specialized cell-types is a long-standing interest of biologists, but given the deep time-scales very difficult to reconstruct or observe. microRNAs have been linked to the evolution of cellular complexity and may inform on specialization. The endothelium is a vertebrate-specific specialization of the circulatory system that enabled a critical new level of vasoregulation. The evolutionary origin of these endothelial cells is unclear. We hypothesized that Mir-126, an endothelial cell-specific microRNA may be informative. We here reconstruct the evolutionary history of Mir-126. Mir-126 likely appeared in the last common ancestor of vertebrates and tunicates, which was a species without an endothelium, within an intron of the evolutionary much older EGF Like Domain Multiple (Egfl) locus. Mir-126 has a complex evolutionary history due to duplications and losses of both the host gene and the microRNA. Taking advantage of the strong evolutionary conservation of the microRNA among Olfactores, and using RNA in situ hybridization, we localized Mir-126 in the tunicate Ciona robusta. We found exclusive expression of the mature Mir-126 in granular amebocytes, supporting a long-proposed scenario that endothelial cells arose from hemoblasts, a type of proto-endothelial amoebocyte found throughout invertebrates. This observed change of expression of Mir-126 from proto-endothelial amoebocytes in the tunicate to endothelial cells in vertebrates is the first direct observation of the evolution of a cell-type in relation to microRNA expression indicating that microRNAs can be a prerequisite of cell-type evolution.

Contribution of S100A4-expressing fibroblasts to anti-SSA/Ro-associated atrioventricular nodal calcification and soluble S100A4 as a biomarker of clinical severity.

Background: Fibrosis and dystrophic calcification disrupting conduction tissue architecture are histopathological lesions characterizing cardiac manifestations of neonatal lupus (cardiac-NL) associated with maternal anti-SSA/Ro antibodies. Objectives: Increased appreciation of heterogeneity in fibroblasts encourages re-examination of existing models with the consideration of multiple fibroblast subtypes (and their unique functional differences) in mind. This study addressed fibroblast heterogeneity by examining expression of α-Smooth Muscle Actin (myofibroblasts) and of S100 Calcium-Binding Protein A4 (S100A4). Methods: Using a previously established model of rheumatic scarring/fibrosis in vitro, supported by the evaluation of cord blood from cardiac-NL neonates and their healthy (anti-SSA/Ro-exposed) counterparts, and autopsy tissue from fetuses dying with cardiac-NL, the current study was initiated to more clearly define and distinguish the S100A4-positive fibroblast in the fetal cardiac environment. Results: S100A4 immunostaining was observed in 4 cardiac-NL hearts with positional identity in the conduction system at regions of dystrophic calcification but not fibrotic zones, the latter containing only myofibroblasts. In vitro, fibroblasts cultured with supernatants of macrophages transfected with hY3 (noncoding ssRNA) differentiated into myofibroblasts or S100A4+ fibroblasts. Myofibroblasts expressed collagen while S100A4+ fibroblasts expressed pro-angiogenic cytokines and proteases that degrade collagen. Cord blood levels of S100A4 in anti-SSA/Ro-exposed neonates tracked disease severity and, in discordant twins, distinguished affected from unaffected. Conclusions: These findings position the S100A4+ fibroblast alongside the canonical myofibroblast in the pathogenesis of cardiac-NL. Neonatal S100A4 levels support a novel biomarker of poor prognosis.

Patterns of unwanted biological and technical expression variation across 49 human tissues.

All tissue-based gene expression studies are impacted by biological and technical sources of variation. Numerous methods are used to normalize and batch correct these datasets. A more accurate understanding of all causes of variation could further optimize these approaches. We used 17,282 samples from 49 tissues in the Genotype Tissue Expression (GTEx) dataset (v8) to investigate patterns and causes of expression variation. Transcript expression was normalized to Z-scores and only the most variable 2% of transcripts were evaluated and clustered based on co-expression patterns. Clustered gene sets were solved to different biological or technical causes related to metadata elements and histologic images. We identified 522 variable transcript clusters (median 11 per tissue) across the samples. Of these, 64% were confidently explained, 15% were likely explained, 7% were low confidence explanations and 14% had no clear cause. Common causes included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), muscle atrophy, diabetes status, and menopause. Technical causes included brain pH and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens dataset of single cell expression. This is the largest exploration of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression. These identified sources of variation will inform which metadata to acquire with tissue harvesting and can be used to improve normalization, batch correction, and analysis of both bulk and single cell RNA-seq data.

Right Ventricular Sarcomere Contractile Depression and the Role of Thick Filament Activation in Human Heart Failure with Pulmonary Hypertension.

Rationale: Right ventricular (RV) contractile dysfunction commonly occurs and worsens outcomes in heart failure patients with reduced ejection fraction and pulmonary hypertension (HFrEF-PH). However, such dysfunction often goes undetected by standard clinical RV indices, raising concerns that they may not reflect aspects of underlying myocyte dysfunction. Objective: To determine components of myocyte contractile depression in HFrEF-PH, identify those reflected by clinical RV indices, and elucidate their underlying biophysical mechanisms. Methods and Results: Resting, calcium- and load-dependent mechanics were measured in permeabilized RV cardiomyocytes isolated from explanted hearts from 23 HFrEF-PH patients undergoing cardiac transplantation and 9 organ-donor controls. Unsupervised machine learning using myocyte mechanical data with the highest variance yielded two HFrEF-PH subgroups that in turn mapped to patients with depressed (RVd) or compensated (RVc) clinical RV function. This correspondence was driven by reduced calcium-activated isometric tension in RVd, while surprisingly, many other major myocyte contractile measures including peak power, maximum unloaded shortening velocity, and myocyte active stiffness were similarly depressed in both groups. Similar results were obtained when subgroups were first defined by clinical indices, and then myocyte mechanical properties in each group compared. To test the role of thick-filament defects, myofibrillar structure was assessed by X-ray diffraction of muscle fibers. This revealed more myosin heads associated with the thick filament backbone in RVd but not RVc, as compared to controls. This corresponded to reduced myosin ATP turnover in RVd myocytes, indicating less myosin in a cross-bridge ready disordered-relaxed (DRX) state. Altering DRX proportion (%DRX) affected peak calcium-activated tension in the patient groups differently, depending on their basal %DRX, highlighting potential roles for precision-guided therapeutics. Lastly, increasing myocyte preload (sarcomere length) increased %DRX 1.5-fold in controls but only 1.2-fold in both HFrEF-PH groups, revealing a novel mechanism for reduced myocyte active stiffness and by extension Frank-Starling reserve in human HF. Conclusions: While there are multiple RV myocyte contractile deficits In HFrEF-PH, clinical indices primarily detect reduced isometric calcium-stimulated force related to deficits in basal and recruitable %DRX myosin. Our results support use of therapies to increase %DRX and enhance length-dependent recruitment of DRX myosin heads in such patients.

Expression Microdissection for the Analysis of miRNA in a Single-Cell Type.

Cell-specific microRNA (miRNA) expression estimates are important in characterizing the localization of miRNA signaling within tissues. Much of these data are obtained from cultured cells, a process known to significantly alter miRNA expression levels. Thus, our knowledge of in vivo cell miRNA expression estimates is poor. We previously demonstrated expression microdissection-miRNA-sequencing (xMD-miRNA-seq) to acquire in vivo estimates, directly from formalin-fixed tissues, albeit with a limited yield. In this study, we optimized each step of the xMD process, including tissue retrieval, tissue transfer, film preparation, and RNA isolation, to increase RNA yields and ultimately show strong enrichment for in vivo miRNA expression by qPCR array. These method improvements, such as the development of a noncrosslinked ethylene vinyl acetate membrane, resulted in a 23- to 45-fold increase in miRNA yield, depending on the cell type. By qPCR, miR-200a increased by 14-fold in xMD-derived small intestine epithelial cells, with a concurrent 336-fold reduction in miR-143 relative to the matched nondissected duodenal tissue. xMD is now an optimized method to obtain robust in vivo miRNA expression estimates from cells. xMD will allow formalin-fixed tissues from surgical pathology archives to make theragnostic biomarker discoveries.

Transcriptomic Analysis of Human Podocytes In Vitro: Effects of Differentiation and APOL1 Genotype.

Introduction: The mechanisms in podocytes that mediate the pathologic effects of the APOL1 high-risk (HR) variants remain incompletely understood, although various molecular and cellular mechanisms have been proposed. We previously established conditionally immortalized human urine-derived podocyte-like epithelial cell (HUPEC) lines to investigate APOL1 HR variant-induced podocytopathy. Methods: We conducted comprehensive transcriptomic analysis, including mRNA, microRNA (miRNA), and transfer RNA fragments (tRFs), to characterize the transcriptional profiles in undifferentiated and differentiated HUPEC with APOL1 HR (G1/G2, 2 cell lines) and APOL1 low-risk (LR) (G0/G0, 2 cell lines) genotypes. We reanalyzed single-cell RNA-seq data from urinary podocytes from focal segmental glomerulosclerosis (FSGS) subjects to characterize the effect of APOL1 genotypes on podocyte transcriptomes. Results: Differential expression analysis showed that the ribosomal pathway was one of the most enriched pathways, suggesting that altered function of the translation initiation machinery may contribute to APOL1 variant-induced podocyte injury. Expression of genes related to the elongation initiation factor 2 pathway was also enriched in the APOL1 HR urinary podocytes from single-cell RNA-seq, supporting a prior report on the role of this pathway in APOL1-associated cell injury. Expression of microRNA and tRFs were analyzed, and the profile of small RNAs differed by both differentiation status and APOL1 genotype. Conclusion: We have profiled the transcriptomic landscape of human podocytes, including mRNA, miRNA, and tRF, to characterize the effects of differentiation and of different APOL1 genotypes. The candidate pathways, miRNAs, and tRFs described here expand understanding of APOL1-associated podocytopathies.

Myocarditis and endomyocardial biopsy: achieving consensus diagnosis on 100 cases.

The two histopathology benchmarks used to diagnose myocarditis are the Dallas Criteria, developed in 1984 and the European Society of Cardiology criteria, developed in 2013, which added immunohistochemistry for the detection of CD3+ T cells (lymphocytes) and CD68+ macrophages. Despite their near universal acceptance, the extent to which pathologists use these criteria or their own criteria to consistently render the diagnosis of myocarditis on endomyocardial biopsy (EMB) is unknown. We digitally scanned slides from 100 heart biopsies, including a trichrome stain and immunostaining, that were chosen as representative of myocarditis, non-myocarditis, and borderline myocarditis, as diagnosed per one institution's use of the Dallas Criteria. Eight blinded international cardiovascular experts were asked to render diagnoses and offer a confidence score on each case. No clinical histories were shared. There was full initial agreement across all experts on 37 cases (16 myocarditis and 21 non-myocarditis) and moderate consensus on 35 cases. After individual inquiries and group discussion, consensus was reached on 90 cases. Diagnostic confidence was highest among the myocarditis diagnoses, lowest for borderline cases, and significantly different between the three diagnostic categories (myocarditis, borderline myocarditis, non-myocarditis; P-value=8.49 × 10-57; ANOVA). Diagnosing myocarditis, particularly in cases with limited inflammation and injury, remains a challenge even for experts in the field. Intermediate cases, termed "borderline" in the Dallas Criteria, represent those for which consensus is particularly hard to achieve. To increase consistency for the histopathologic diagnosis of myocarditis, we will need more specifically defined criteria, more granular descriptions of positive and negative features, clarity on how to incorporate immunohistochemistry findings, and improved nomenclature.

Diagnosing myocarditis in endomyocardial biopsies: survey of current practice.

BACKGROUND: Dallas criteria (DC) and European Society of Cardiology criteria (ESCC) have provided valuable frameworks for the histologic diagnosis and classification of myocarditis in endomyocardial biopsy (EMB) specimens. However, the adaptation and the usage of these criteria are variable and depend on local practice settings and regions/countries. Moreover, several ancillary tests that are not included in the current criteria, such as immunohistochemistry (IHC) or viral polymerase chain reaction (PCR), have proven useful for the diagnosis of myocarditis. METHOD: As a joint effort from the Association for European Cardiovascular Pathology (AECVP) and the Society for Cardiovascular Pathology (SCVP), we conducted an online survey to understand the current practice of diagnosing myocarditis. RESULT: A total of 100 pathologists from 23 countries responded to the survey with the majority practicing in North America (45%) and Europe (45%). Most of the pathologists reported to examine less than 200 native heart biopsies per year (85%), and to routinely receive 3-5 fragments of tissue per case (90%). The number of hematoxylin-eosin-stained levels for each case varies from 1 to more than 9 levels, with 20% of pathologists routinely asking for more than 9 levels per case. Among the 100 pathologists, 52 reported to use the DC alone, 12 the ESCC alone, 28 both DC and ESCC and 8 reported to use neither the DC nor the ESCC. Overall, 80 pathologists reported to use the DC and 40 the ESCC. Use of DC alone is more common among North American pathologists compared to European ones (80% vs 32.6%) while use of ESCC alone is more common in Europe (20.9% vs 2.5%). IHC is utilized in either every case or selected cases by 79% of participants, and viral PCR is performed by 35% of participants. Variable terminologies are used in reporting, including both histological and clinical terms. The diagnosis of myocarditis is rendered even in the absence of myocyte injury (e.g., in cases of borderline or inactive/chronic myocarditis) by 46% respondents. The majority of the participants think it is time to update the current criteria (83%). CONCLUSIONS: The survey data demonstrated that pathologists who render a myocarditis diagnosis practice with variable tissue preparation methods, use of ancillary studies, guideline usage, and reporting. This result highlights the clinically unmet need to update and standardize the current diagnostic criteria for myocarditis on EMB. Additional studies are warranted to establish standard of practice.

A Comparison of Tissue Dissection Techniques for Diagnostic, Prognostic, and Theragnostic Analysis of Human Disease.

Histopathology has historically been the critical technique for the diagnosis and treatment of human disease. Today, genomics, transcriptomics, and proteomics from specific cells, rather than bulk tissue, have become key to understanding underlying disease mechanisms and rendering useful diagnostic information. Extraction of desired analytes, i.e., nucleic acids or proteins, from easily accessible formalin-fixed paraffin-embedded tissues allows for clinically relevant activities, such as sequencing biomarker mutations or typing amyloidogenic proteins. Genetic profiling has become routine for cancers as varied as non-small cell lung cancer and prostatic carcinoma. The five main tissue dissection techniques that have been developed thus far include: bulk scraping, manual macrodissection, manual microdissection, laser-capture microdissection, and expression microdissection. In this review, we discuss the importance of tissue dissection in clinical practice and research, the basic methods, applications, as well as some advantages and disadvantages for each modality.