High-definition hematoxylin and eosin staining in a transition to digital pathology

An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology

The application of deep learning to spatial transcriptomics (ST) can reveal relationships between gene expression and tissue architecture. Prior work has demonstrated that inferring gene expression from tissue histomorphology can discern these spatial molecular markers to enable population scale studies, reducing the fiscal barriers associated with large-scale spatial profiling. However, while most improvements in algorithmic performance have focused on improving model architectures, little is known about how the quality of tissue preparation and imaging can affect deep learning model training for spatial inference from morphology and its potential for widespread clinical adoption. Prior studies for ST inference from histology typically utilize manually stained frozen sections with imaging on non-clinical grade scanners. Training such models on ST cohorts is also costly. We hypothesize that adopting tissue processing and imaging practices that mirror standards for clinical implementation (permanent sections, automated tissue staining, and clinical grade scanning) can significantly improve model performance. An enhanced specimen processing and imaging protocol was developed for deep learning-based ST inference from morphology. This protocol featured the Visium CytAssist assay to permit automated hematoxylin and eosin staining (e.g. Leica Bond), 40×-resolution imaging, and joining of multiple patients' tissue sections per capture area prior to ST profiling. Using a cohort of 13 pathologic T Stage-III stage colorectal cancer patients, we compared the performance of models trained on slide prepared using enhanced versus traditional (i.e. manual staining and low-resolution imaging) protocols. Leveraging Inceptionv3 neural networks, we predicted gene expression across serial, histologically-matched tissue sections using whole slide images (WSI) from both protocols. The data Shapley was used to quantify and compare marginal performance gains on a patient-by-patient basis attributed to using the enhanced protocol versus the actual costs of spatial profiling. Findings indicate that training and validating on WSI acquired through the enhanced protocol as opposed to the traditional method resulted in improved performance at lower fiscal cost. In the realm of ST, the enhancement of deep learning architectures frequently captures the spotlight; however, the significance of specimen processing and imaging is often understated. This research, informed through a game-theoretic lens, underscores the substantial impact that specimen preparation/imaging can have on spatial transcriptomic inference from morphology. It is essential to integrate such optimized processing protocols to facilitate the identification of prognostic markers at a larger scale.

Cutting-edge technology and automation in the pathology laboratory

One of the goals of pathology is to standardize laboratory practices to increase the precision and effectiveness of diagnostic testing, which will ultimately enhance patient care and results. Standardization is crucial in the domains of tissue processing, analysis, and reporting. To enhance diagnostic testing, innovative technologies are also being created and put into use. Furthermore, although problems like algorithm training and data privacy issues still need to be resolved, digital pathology and artificial intelligence are emerging in a structured manner. Overall, for the field of pathology to advance and for patient care to be improved, standard laboratory practices and innovative technologies must be adopted. In this paper, we describe the state-of-the-art of automation in pathology laboratories in order to lead technological progress and evolution. By anticipating laboratory needs and demands, the aim is to inspire innovation tools and processes as positively transformative support for operators, organizations, and patients.

Role of canagliflozin in ameliorating isoprenaline induced cardiomyocyte oxidative stress via the heme oxygenase-1 mediated pathway

Canagliflozin (CZ) is commonly prescribed for management of type-2 diabetes mellitus (T2DM); it also can reduce the risk of myocardial infarction. We used 80 albino Wistar rats to investigate the cardioprotective potential of CZ against oxidative stress caused by administration of isoprenaline (ISO). We found that ISO stimulates production of reactive oxygen species and that CZ administration caused up-regulation of antioxidants and down-regulation of oxidants due to nuclear factor erythroid-2 related factor-2, as well as by enhancement of the heme oxygenase-1 mediated cascade. CZ monotherapy may play a cardioprotective role in diabetic patients. CZ possesses strong antioxidant potential that ameliorates cardiac damage induced by ISO administration.

The Overlooked Role of Specimen Preparation in Bolstering Deep Learning-Enhanced Spatial Transcriptomics Workflows

The application of deep learning methods to spatial transcriptomics has shown promise in unraveling the complex relationships between gene expression patterns and tissue architecture as they pertain to various pathological conditions. Deep learning methods that can infer gene expression patterns directly from tissue histomorphology can expand the capability to discern spatial molecular markers within tissue slides. However, current methods utilizing these techniques are plagued by substantial variability in tissue preparation and characteristics, which can hinder the broader adoption of these tools. Furthermore, training deep learning models using spatial transcriptomics on small study cohorts remains a costly endeavor. Necessitating novel tissue preparation processes enhance assay reliability, resolution, and scalability. This study investigated the impact of an enhanced specimen processing workflow for facilitating a deep learning-based spatial transcriptomics assessment. The enhanced workflow leveraged the flexibility of the Visium CytAssist assay to permit automated H&E staining (e.g., Leica Bond) of tissue slides, whole-slide imaging at 40x-resolution, and multiplexing of tissue sections from multiple patients within individual capture areas for spatial transcriptomics profiling. Using a cohort of thirteen pT3 stage colorectal cancer (CRC) patients, we compared the efficacy of deep learning models trained on slide prepared using an enhanced workflow as compared to the traditional workflow which leverages manual tissue staining and standard imaging of tissue slides. Leveraging Inceptionv3 neural networks, we aimed to predict gene expression patterns across matched serial tissue sections, each stemming from a distinct workflow but aligned based on persistent histological structures. Findings indicate that the enhanced workflow considerably outperformed the traditional spatial transcriptomics workflow. Gene expression profiles predicted from enhanced tissue slides also yielded expression patterns more topologically consistent with the ground truth. This led to enhanced statistical precision in pinpointing biomarkers associated with distinct spatial structures. These insights can potentially elevate diagnostic and prognostic biomarker detection by broadening the range of spatial molecular markers linked to metastasis and recurrence. Future endeavors will further explore these findings to enrich our comprehension of various diseases and uncover molecular pathways with greater nuance. Combining deep learning with spatial transcriptomics provides a compelling avenue to enrich our understanding of tumor biology and improve clinical outcomes. For results of the highest fidelity, however, effective specimen processing is crucial, and fostering collaboration between histotechnicians, pathologists, and genomics specialists is essential to herald this new era in spatial transcriptomics-driven cancer research.

Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association

Tissue biomarkers have been of increasing utility for scientific research, diagnosing disease, and treatment response prediction. There has been a steady shift away from qualitative assessment toward providing more quantitative scores for these biomarkers. The application of quantitative image analysis has thus become an indispensable tool for in-depth tissue biomarker interrogation in these contexts. This white paper reviews current technologies being employed for quantitative image analysis, their application and pitfalls, regulatory framework demands, and guidelines established for promoting their safe adoption in clinical practice.

Profiling chromatin accessibility in formalin-fixed paraffin-embedded samples

Archived formalin-fixed paraffin-embedded (FFPE) samples are the global standard format for preservation of the majority of biopsies in both basic research and translational cancer studies, and profiling chromatin accessibility in the archived FFPE tissues is fundamental to understanding gene regulation. Accurate mapping of chromatin accessibility from FFPE specimens is challenging because of the high degree of DNA damage. Here, we first showed that standard ATAC-seq can be applied to purified FFPE nuclei but yields lower library complexity and a smaller proportion of long DNA fragments. We then present FFPE-ATAC, the first highly sensitive method for decoding chromatin accessibility in FFPE tissues that combines Tn5-mediated transposition and T7 in vitro transcription. The FFPE-ATAC generates high-quality chromatin accessibility profiles with 500 nuclei from a single FFPE tissue section, enables the dissection of chromatin profiles from the regions of interest with the aid of hematoxylin and eosin (H&E) staining, and reveals disease-associated chromatin regulation from the human colorectal cancer FFPE tissue archived for more than 10 years. In summary, the approach allows decoding of the chromatin states that regulate gene expression in archival FFPE tissues, thereby permitting investigators, to better understand epigenetic regulation in cancer and precision medicine.

Whole Slide Imaging: Technology and Applications

Pathology has benefited from advanced innovation with novel technology to implement a digital solution. Whole slide imaging is a disruptive technology where glass slides are scanned to produce digital images. There have been significant advances in whole slide scanning hardware and software that have allowed for ready access of whole slide images. The digital images, or whole slide images, can be viewed comparable to glass slides in a microscope, as digital files. Whole slide imaging has increased in adoption among pathologists, pathology departments, and scientists for clinical, educational, and research initiatives. Worldwide usage of whole slide imaging has grown significantly. Pathology regulatory organizations (ie, College of American Pathologists) have put forth guidelines for clinical validation, and the US Food and Drug Administration have also approved whole slide imaging for primary diagnosis. This article will review the digital pathology ecosystem and discuss clinical and nonclinical applications of its use.

A Study of the Effect of Platelet-Rich Plasma on Outcomes After Aspirated Human Fat Grafting With Experimental Design

INTRODUCTION

Over the past decade, some studies have focused on whether platelet-rich plasma (PRP) can promote the survival of fat grafts after transplantation. However, the results of these studies have been controversial because of the variations in research methods and assessment methodologies.

METHODS

In this study, the authors aspirated fat particles from the abdomen of a healthy woman, mixed them with PRP, and injected them into the backs of nude mice subcutaneously, which simulates the clinical model. The control group was designed to mix aspired fat with normal saline. The fat grafts were removed 10 weeks after transplantation, stained with hematoxylin and eosin, and sliced into pathological sections, which were subsequently scanned and analyzed using the Digital Slide Scanning System (PRECICE, Beijing, China).

RESULTS

The total area of the graft section and the necrotic adipose tissue area in the control group were significantly larger than that in the PRP group. The fibrosis tissue area in the PRP group was significantly larger than that in the control group. There were no statistically significant differences in the viable adipocyte area, the cyst area, and the mature blood vessel number between the PRP and control groups.

CONCLUSION

In this study, PRP did not cause an increase in the number of viable adipocytes; however, it did increase the amount of inflammation, which promoted necrotic tissue absorption and the proliferation of granulation tissue. Further research, including research on normalization of fat preparation and grafting, unification of the PRP preparation and application scheme, and optimization of histological measurement and analysis methods, is needed to assess the effect of PRP on fat grafting.

Computational imaging of aortic vasa vasorum and neovascularization in rabbits using contrast-enhanced intravascular ultrasound: Association with histological analysis

Objective:

Neoangiogenesis is pathophysiologically related to atherosclerotic plaque growth and vulnerability. We examined the in vivo performance of a computational method using contrast-enhanced intravascular ultrasound (CE-IVUS) to detect and quantify aortic wall neovascularization in rabbits. We also compared these findings with histological data.

Methods:

Nine rabbits were fed with a hyperlipidemic diet. IVUS image sequences were continuously recorded before and after the injection of a contrast agent. Mean enhancement of intensity of a region of interest (MEIR) was calculated using differential imaging algorithm. The percent difference of MEIR before and after the injection of microbubbles (d_MEIR) was used as an index of the density of plaque or/and adventitial neovascularization. Aortic segments were excised for histological analysis.

Results:

CE-IVUS and histological analysis were performed in 11 arterial segments. MEIR was significantly increased (~20%) after microbubble injection (from 8.1±0.9 to 9.7±1.8, p=0.016). Segments with increased VV/neovessels in the tunica adventitia (histological scores 2 and 3) had significantly higher d_MEIR compared with segments with low presence of VV/neovessels (score 1); 40.5±22.9 vs. 8±14.6, p=0.024, respectively.

Conclusion:

It is possible to detect VV or neovessels in vivo using computational analysis of CE-IVUS images, which is in agreement with histological data. These findings may have critical implications on vulnerable plaque assessment and risk stratification.

Prognostic significance of Wilms' tumor 1 expression in patients with pancreatic ductal adenocarcinoma

The only current curative treatment for patients with pancreatic ductal adenocarcinoma (PDA) is surgical resection, and certain patients still succumb to disease shortly after complete surgical resection. Wilms' tumor 1 (WT1) serves an oncogenic role in various types of tumors; therefore, in the present study, WT1 protein expression in patients with PDA was analyzed and the association with overall survival (OS) and disease-free survival (DFS) time in patients with PDA was assessed following surgical resection. A total of 50 consecutive patients with PDA who received surgical resection between January 2005 and December 2015 at the Jikei University Kashiwa Hospital (Kashiwa, Chiba, Japan) were enrolled. WT1 protein expression in PDA tissue was measured using immunohistochemical staining. Furthermore, laboratory parameters were measured within 2 weeks of surgery, and systemic inflammatory response markers were evaluated. WT1 protein expression was detected in the nucleus and cytoplasm of all PDA cells and in tumor vessels. WT1 exhibited weak staining in the nuclei of all PDA cells; however, the cytoplasmic expression of WT1 levels was classified into four groups: Negative (n=0), weak (n=19), moderate (n=23) and strong (n=8). In patients with PDA, it was demonstrated that the OS and DFS times of patients with weak cytoplasmic WT1 expression were significantly prolonged compared with those of patients with moderate-to-strong cytoplasmic WT1 expression, as determined by log-rank test (P=0.0005 and P=0.0001, respectively). Furthermore, an association between the density of WT1-expressing tumor vessels and worse OS/DFS times was detected. Multivariate analysis also indicated a significant association between the overexpression of WT1 in PDA tissue and worse OS/DFS times. To the best of our knowledge, the present study is the first to demonstrate that moderate-to-strong overexpression of WT1 in the cytoplasm of PDA cells is significantly associated with worse OS/DFS times. Therefore, overexpression of WT1 in the cytoplasm of PDA cells may impact the recurrence and prognosis of patients with PDA following surgical resection. The results further support the development of WT1-targeted therapies to prolong survival in all patients with PDA.

Detection of p53 and Bcl-2 expression in cutaneous hemangioma through the quantum dot technique

Hemangioma is one of the most common types of infantile vascular benign tumor. The aim of the present study was to investigate the role of B-cell lymphoma 2 (Bcl-2) and tumor protein p53 (p53) in the proliferation and apoptosis of hemangioma cells. A total of 38 paraffin-embedded hemangioma specimens (16 males and 22 females) and another 5 paraffin-embedded healthy surrounding tissue samples, collected between January 2007 and December 2010, were obtained from the Department of Pathology at Renmin Hospital of Wuhan University (Wuhan, China). Immunohistochemistry, hematoxylin and eosin staining, and quantum dot double staining were used to detect the expression of proliferating cell nuclear antigen (PCNA), Bcl-2 and p53 in hemangioma and healthy surrounding skin tissue samples. All hemangioma specimens were classified into proliferative or the involuting stage hemangioma according to Mulliken's criteria and their expression of PCNA. The results of the quantum dot double staining were analyzed using a multi-spectral imaging system. One-way analysis of the variance and the Student-Newman-Keuls q test were performed to statistically analyze the data. There were 24 cases of proliferative stage and 14 cases of involuting stage hemangioma among the specimens. Immunohistochemical analysis results indicated a high expression of Bcl-2 and p53 in proliferative stage hemangioma tissue samples, and low expression in involuting stage hemangioma and healthy tissue samples. Statistical analysis of the results from quantum dot double staining demonstrated that the expression of Bcl-2 and p53 in proliferative hemangioma was significantly increased compared with that in involuting stage specimens (P<0.05) and healthy tissue samples (P<0.05). No significant difference in Bcl-2 and p53 expression was identified between the involuting hemangioma and healthy surrounding tissue samples. The higher expression of Bcl-2 and p53 in proliferative hemangioma suggests that Bcl-2 may cause an imbalance between endothelial cell proliferation and apoptosis through the inhibition of endothelial cell apoptosis. Furthermore, p53 may promote the proliferation of endothelial cells in proliferative hemangioma.

A robust nonlinear tissue-component discrimination method for computational pathology

Advances in digital pathology, specifically imaging instrumentation and data management, have allowed for the development of computational pathology tools with the potential for better, faster, and cheaper diagnosis, prognosis, and prediction of disease. Images of tissue sections frequently vary in color appearance across research laboratories and medical facilities because of differences in tissue fixation, staining protocols, and imaging instrumentation, leading to difficulty in the development of robust computational tools. To address this challenge, we propose a novel nonlinear tissue-component discrimination (NLTD) method to register automatically the color space of histopathology images and visualize individual tissue components, independent of color differences between images. Our results show that the NLTD method could effectively discriminate different tissue components from different types of tissues prepared at different institutions. Further, we demonstrate that NLTD can improve the accuracy of nuclear detection and segmentation algorithms, compared with using conventional color deconvolution methods, and can quantitatively analyze immunohistochemistry images. Together, the NLTD method is objective, robust, and effective, and can be easily implemented in the emerging field of computational pathology.

Caloric restriction coupled with radiation decreases metastatic burden in triple negative breast cancer

PURPOSE

Metastatic breast cancer is devastating and triple negative breast cancers (TNBC) have a higher propensity for metastasis. Improved local control upfront in this aggressive cancer could potentially decrease its propensity toward metastasis. We sought to determine if using caloric restriction (CR) as a systemic therapy, combined with radiation therapy (IR) to the primary tumor, may impact metastatic disease.

METHODS

An orthotopic mouse model using a highly metastatic, luciferase-tagged TNBC cell line (4T1), was used to generate palpable tumors. Mice were then treated with CR, IR, and a combination of the two. In vivo imaging was performed for metastatic evaluation. Molecular evaluation of the tumors was performed, generating a mechanistic hypothesis for CR, which was then tested with pertinent pathway inhibition in the model.

RESULTS

CR significantly increased the time to developing metastases, decreased the overall number and volume of lung metastases, and increased survival. CR decreased proliferation, increased apoptosis and globally downregulated the IGF-1R signaling pathway. Adding an IGF-1R/INSR inhibitor to local IR in vivo accomplished a decrease in metastases similar to CR plus IR, demonstrating the importance of the IGF-1R signaling pathway, and underscoring it as a possible mechanism for CR.

CONCLUSIONS

CR decreased metastatic burden and therefore may complement cytotoxic therapies being used in the clinical setting for metastatic disease. Downregulation of the IGF-1R pathway, is in part responsible for this response and modulating IGF-1R directly resulted in similar improved progression-free survival. The novel use of CR has the potential to enhance clinical outcomes for patients with metastatic breast cancer.

Nesprin-1 has key roles in the process of mesenchymal stem cell differentiation into cardiomyocyte-like cells in vivo and in vitro

The aim of the present study was to investigate the expression of nesprin-1 protein in MSCs and its effects on the differentiation of rat bone-marrow mesenchymal stem cells (MSCs). Surface-associated antigens of MSCs were detected by flow cytometry. MSC differentiation was induced by treatment with 10 μmol/l 5-azacytidine. Sprague-Dawley rats were anesthetized prior to thoracotomy and subsequent ligation of the left anterior descending coronary artery to establish a model of myocardial infarction. Two weeks following myocardial infarction, DAPI-marked MSCs were injected into the infarcted region in the experimental group, while DMEM was injected into the infarcted region of the control group. Characteristics of the putative cardiac-myogenic cells were evaluated using immunohistochemical and immunofluorescent analysis. The messenger RNA expression levels of cardiac-myogenic specific genes; desmin, α-actinin and cardiac troponin I (cTnI) were detected by reverse transcription quantitative polymerase chain reaction. The expression of nesprin-1 protein in MSCs was identified by immunofluorescence and western blot analysis, prior to and following MSC differentiation. Following differentiation, the MSCs appeared spindle-shaped with irregular processes and were positive for CD90 and CD29, but negative for CD45. Cardiomyocyte-like cells were positive for desmin, α-sarcomeric actin and cTnI. Nesprin protein was detected in the nuclear membrane via immunofluorescence, and following MSC differentiation into cardiomyocyte-like cells, the expression of nesprin protein was significantly higher (^*P=0.03<0.05). The results of the present study indicated that MSCs may be differentiated in vitro and in vivo into cells with characteristics commonly attributed to cardiomyocytes. Cardiomyocyte-like cells cultured from bone marrow sources may be potentially useful for repairing the injured myocardium. The results also suggested that, consistent with the results of previous studies, the expression of nesprin-1 protein was higher during the differentiation process of MSCs and may have an important role in mediating MSC differentiation. Elucidation of the role of nesprin-1 in MSC differentiation may aid in the development of novel therapies for the treatment of myocardial ischemia and nesprin-1 genetic deficiencies.

Automated methods for the analysis of skeletal muscle fiber size and metabolic type

It is of interest to quantify the size, shape, and metabolic subtype of skeletal muscle fibers in many areas of biomedical research. To do so, skeletal muscle samples are sectioned transversely to the length of the muscle and labeled for extracellular or membrane proteins to delineate the fiber boundaries and additionally for biomarkers related to function or metabolism. The samples are digitally photographed and the fibers "outlined" for quantification of fiber cross-sectional area (CSA) using pointing devices interfaced to a computer, which is tedious, prone to error, and can be nonobjective. Here, we review methods for characterizing skeletal muscle fibers and describe new automated techniques, which rapidly quantify CSA and biomarkers. We discuss the applications of these methods to the characterization of mitochondrial dysfunctions, which underlie a variety of human afflictions, and we present a novel approach, utilizing images from the online Human Protein Atlas to predict relationships between fiber-specific protein expression, function, and metabolism.

A static-image telepathology system for dermatopathology consultation in East Africa: the Massachusetts General Hospital Experience

BACKGROUND

The histologic diagnosis of skin lesions in the developing world is complicated by the shortage of pathologists with subspecialty training in dermatopathology, limited access to ancillary diagnostic testing, and costly referrals for expert glass slide consultation in challenging cases.

OBJECTIVE

In this study we evaluate the feasibility of a static-image telepathology platform in Africa for performing accurate dermatopathology consultations.

METHODS

A static-image telepathology platform using the iPath server was utilized by referring pathologists in 4 African hospitals. Diagnostic interpretations were provided by Massachusetts General Hospital dermatopathologists at no cost. The diagnostic accuracy and interobserver correlation was evaluated.

RESULTS

The static histopathologic images were diagnostic in 22 of 29 (76%) cases. Diagnostic accuracy between static image and glass slide diagnosis in 22 cases was 91%, ranging from 86% to 95% according to years of dermatopathology subspecialty expertise. Comparison with the glass slides showed that the telepathology diagnosis was limited by inappropriate field selection in only one case. Interobserver concordance between two pathologists was high (K = 0.86) suggesting that this platform is easy to use with minimal training of both referring and consulting pathologists.

LIMITATIONS

Concordance between conventional microscopy and static image telepathology was performed in 22 of 29 cases for which glass slides were received. Interobserver concordance was performed for two pathologists.

CONCLUSION

Static-image telepathology is a feasible means of rendering diagnoses on dermatopathology cases and is a cost-effective technology for obtaining much-needed second opinions in resource-poor settings.

Pathology Imaging Informatics for Clinical Practice and Investigative and Translational Research

Pathologists routinely interpret gross and microscopic specimens to render diagnoses and to engage in a broad spectrum of investigative research. Multiple studies have demonstrated that imaging technologies have progressed to a level at which properly digitized specimens provide sufficient quality comparable to the traditional glass slides examinations. Continued advancements in this area will have a profound impact on the manner in which pathology is conducted from this point on. Several leading institutions have already undertaken ambitious projects directed toward digitally imaging, archiving, and sharing pathology specimens. As a result of these advances, the use of informatics in diagnostic and investigative pathology applications is expanding rapidly. In addition, the advent of novel technologies such as multispectral imaging makes it possible to visualize and analyze imaged specimens using multiple wavelengths simultaneously. As these powerful technologies become increasingly accepted and adopted, the opportunities for gaining new insight into the underlying mechanisms of diseases as well as the potential for discriminating among subtypes of pathologies are growing accordingly.