Digital Pathology Initiatives and Experience of a Large Academic Institution During the Coronavirus Disease 2019 (COVID-19) Pandemic.

CONTEXT.­: Pathology practices have begun integrating digital pathology tools into their routine workflow. During 2020, the coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged as a pandemic, causing a global health crisis that significantly affected the world population in several areas, including medical practice, and pathology was no exception. OBJECTIVE.­: To summarize our experience in implementing digital pathology for remote primary diagnosis, education, and research during this pandemic. DESIGN.­: We surveyed our pathologists (all subspecialized) and trainees to gather information about their use of digital pathology tools before and during the pandemic. Quality assurance and slide distribution data were also examined. RESULTS.­: During the pandemic, the widespread use of digital tools in our institution allowed a smooth transition of most clinical and academic activities into remote with no major disruptions. The number of pathologists using whole slide imaging (WSI) for primary diagnosis increased from 20 (62.5%) to 29 (90.6%) of a total of 32 pathologists, excluding renal pathology and hematopathology, during the pandemic. Furthermore, the number of pathologists exclusively using whole slide imaging for primary diagnosis also increased from 2 (6.3%) to 5 (15.6%) during the pandemic. In 35 (100%) survey responses from attending pathologists, 21 (60%) reported using whole slide imaging for remote primary diagnosis following the Centers for Medicare and Medicaid Services waiver. Of these 21 pathologists, 18 (86%) responded that if allowed, they will continue using whole slide imaging for remote primary diagnosis after the pandemic. CONCLUSIONS.­: The pandemic served as a catalyst to pathologists adopting a digital workflow into their daily practice and realizing the logistic and technical advantages of such tools.

Modulation of immune checkpoint molecule expression in mantle cell lymphoma.

Mantle cell lymphoma (MCL) is an aggressive B-cell malignancy for which novel therapeutics with improved efficacy are greatly needed. To provide support for clinical immune checkpoint blockade, we comprehensively evaluated the expression of therapeutically targetable immune checkpoint molecules on primary MCL cells. MCL cells showed constitutive expression of Programmed Death 1 (PD-1) and Programmed Death Ligand 1 (PD-L1), variable CD200, absent PD-L2, Lymphocyte Activation Gene 3 (LAG-3), and Cytotoxic T-cell Associated Protein 4 (CTLA-4). Effector cells from MCL patients expressed PD-1. Co-culture of MCL cells with T-cells induced PD-L1 surface expression, a phenomenon regulated by IFNγ and CD40:CD40L interaction. Induction of PD-L1 was attenuated by concurrent treatment with ibrutinib or duvelisib, suggesting BTK and PI3K are important mediators of PD-L1 expression. Overall, our data provide further insight into the expression of checkpoint molecules in MCL and support the use of PD-L1 blocking antibodies in MCL patients.

Nuclear IHC enumeration: A digital phantom to evaluate the performance of automated algorithms in digital pathology.

Automatic and accurate detection of positive and negative nuclei from images of immunostained tissue biopsies is critical to the success of digital pathology. The evaluation of most nuclei detection algorithms relies on manually generated ground truth prepared by pathologists, which is unfortunately time-consuming and suffers from inter-pathologist variability. In this work, we developed a digital immunohistochemistry (IHC) phantom that can be used for evaluating computer algorithms for enumeration of IHC positive cells. Our phantom development consists of two main steps, 1) extraction of the individual as well as nuclei clumps of both positive and negative nuclei from real WSI images, and 2) systematic placement of the extracted nuclei clumps on an image canvas. The resulting images are visually similar to the original tissue images. We created a set of 42 images with different concentrations of positive and negative nuclei. These images were evaluated by four board certified pathologists in the task of estimating the ratio of positive to total number of nuclei. The resulting concordance correlation coefficients (CCC) between the pathologist and the true ratio range from 0.86 to 0.95 (point estimates). The same ratio was also computed by an automated computer algorithm, which yielded a CCC value of 0.99. Reading the phantom data with known ground truth, the human readers show substantial variability and lower average performance than the computer algorithm in terms of CCC. This shows the limitation of using a human reader panel to establish a reference standard for the evaluation of computer algorithms, thereby highlighting the usefulness of the phantom developed in this work. Using our phantom images, we further developed a function that can approximate the true ratio from the area of the positive and negative nuclei, hence avoiding the need to detect individual nuclei. The predicted ratios of 10 held-out images using the function (trained on 32 images) are within ±2.68% of the true ratio. Moreover, we also report the evaluation of a computerized image analysis method on the synthetic tissue dataset.

Computer-assisted quantification of CD3+ T cells in follicular lymphoma.

The advance of high resolution digital scans of pathology slides allowed development of computer based image analysis algorithms that may help pathologists in IHC stains quantification. While very promising, these methods require further refinement before they are implemented in routine clinical setting. Particularly critical is to evaluate algorithm performance in a setting similar to current clinical practice. In this article, we present a pilot study that evaluates the use of a computerized cell quantification method in the clinical estimation of CD3 positive (CD3+) T cells in follicular lymphoma (FL). Our goal is to demonstrate the degree to which computerized quantification is comparable to the practice of estimation by a panel of expert pathologists. The computerized quantification method uses entropy based histogram thresholding to separate brown (CD3+) and blue (CD3-) regions after a color space transformation. A panel of four board-certified hematopathologists evaluated a database of 20 FL images using two different reading methods: visual estimation and manual marking of each CD3+ cell in the images. These image data and the readings provided a reference standard and the range of variability among readers. Sensitivity and specificity measures of the computer's segmentation of CD3+ and CD- T cell are recorded. For all four pathologists, mean sensitivity and specificity measures are 90.97 and 88.38%, respectively. The computerized quantification method agrees more with the manual cell marking as compared to the visual estimations. Statistical comparison between the computerized quantification method and the pathologist readings demonstrated good agreement with correlation coefficient values of 0.81 and 0.96 in terms of Lin's concordance correlation and Spearman's correlation coefficient, respectively. These values are higher than most of those calculated among the pathologists. In the future, the computerized quantification method may be used to investigate the relationship between the overall architectural pattern (i.e., interfollicular vs. follicular) and outcome measures (e.g., overall survival, and time to treatment). © 2017 International Society for Advancement of Cytometry.

Classification of follicular lymphoma: the effect of computer aid on pathologists grading.

BACKGROUND: Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL cases are stratified into three histological grades based on the average centroblast count per high power field (HPF). The centroblast count is performed manually by the pathologist using an optical microscope and hematoxylin and eosin (H&E) stained tissue section. Although this is the current clinical practice, it suffers from high inter- and intra-observer variability and is vulnerable to sampling bias. METHODS: In this paper, we present a system, called Follicular Lymphoma Grading System (FLAGS), to assist the pathologist in grading FL cases. We also assess the effect of FLAGS on accuracy of expert and inexperienced readers. FLAGS automatically identifies possible HPFs for examination by analyzing H&E and CD20 stains, before classifying them into low or high risk categories. The pathologist is first asked to review the slides according to the current routine clinical practice, before being presented with FLAGS classification via color-coded map. The accuracy of the readers with and without FLAGS assistance is measured. RESULTS: FLAGS was used by four experts (board-certified hematopathologists) and seven pathology residents on 20 FL slides. Access to FLAGS improved overall reader accuracy with the biggest improvement seen among residents. An average AUC value of 0.75 was observed which generally indicates "acceptable" diagnostic performance. CONCLUSIONS: The results of this study show that FLAGS can be useful in increasing the pathologists' accuracy in grading the tissue. To the best of our knowledge, this study measure, for the first time, the effect of computerized image analysis on pathologists' grading of follicular lymphoma. When fully developed, such systems have the potential to reduce sampling bias by examining an increased proportion of HPFs within follicle regions, as well as to reduce inter- and intra-reader variability.

Long-Term Therapy with Lenalidomide in a Patient with POEMS Syndrome.

Lenalidomide is an effective therapy against malignant plasma cells and a potent agent against proinflammatory and proangiogenic cytokines. The use of lenalidomide in POEMS (polyneuropathy, organomegaly, endocrinopathy, monoclonal protein with plasma cells, skin changes) has been reported, but its benefit in long-term use is not well established. A 55-year-old man with POEMS and debilitating polyneuropathy was treated with lenalidomide and dexamethasone followed by maintenance lenalidomide. He remains in haematologic remission and in complete recovery of functional status 3.5 years after diagnosis. This case supports the long-term use of lenalidomide in patients with POEMS syndrome.

Rare presentation of post-transplant lymphoproliferative disorder isolated to gastroesophageal junction.

Post transplant lymphoproliferative disorder (PTLD) represents a life threatening disorder occurring after transplantation, ranging from a polyclonal mononucleosis like illness to a monomorphic high grade neoplasm with cytologic and histopathologic evidence indicative of transformation to lymphoma. PTLD of diffuse large B-cell lymphoma (DLBCL) subtype, isolated to the esophagus is a rare diagnosis. We describe the first case of an immunocompromised adult patient diagnosed with DLBCL-PTLD limited to his esophagus without an associated mass or locoregional lymphadenopathy on imaging since the institution of the revised Cheson criteria, which includes positron emission tomography-computed tomography as the standard staging modality. Even more unique to our case was the suggestion of underlying cytomegalovirus (CMV) gastritis leading to a hypothesis about a less well understood relationship between CMV and Epstein Barr virus (EBV). In the post transplant setting, immunocompromised state, or EBV positive state, upper gastrointestinal symptoms should prompt investigation with an upper endoscopy (EGD). Additionally, specific to our case, the fact that the patients' presentation was suspicious for CMV gastritis raises the possibility that the CMV infection predated his PTLD increasing his risk of acquiring PTLD. This reemphasizes the importance and diagnostic utility of early screening with EGD in patients after transplantation.

Inter-reader variability in follicular lymphoma grading: Conventional and digital reading.

CONTEXT: Pathologists grade follicular lymphoma (FL) cases by selecting 10, random high power fields (HPFs), counting the number of centroblasts (CBs) in these HPFs under the microscope and then calculating the average CB count for the whole slide. Previous studies have demonstrated that there is high inter-reader variability among pathologists using this methodology in grading. AIMS: The objective of this study was to explore if newly available digital reading technologies can reduce inter-reader variability. SETTINGS AND DESIGN: IN THIS STUDY, WE CONSIDERED THREE DIFFERENT READING CONDITIONS (RCS) IN GRADING FL: (1) Conventional (glass-slide based) to establish the baseline, (2) digital whole slide viewing, (3) digital whole slide viewing with selected HPFs. Six board-certified pathologists from five different institutions read 17 FL slides in these three different RCs. RESULTS: Although there was relative poor consensus in conventional reading, with lack of consensus in 41.2% of cases, which was similar to previously reported studies; we found that digital reading with pre-selected fields improved the inter-reader agreement, with only 5.9% lacking consensus among pathologists. CONCLUSIONS: Digital whole slide RC resulted in the worst concordance among pathologists while digital whole slide reading selected HPFs improved the concordance. Further studies are underway to determine if this performance can be sustained with a larger dataset and our automated HPF and CB detection algorithms can be employed to further improve the concordance.

Regulation of acute graft-versus-host disease by microRNA-155.

Acute graft-versus-host disease (aGVHD) remains a major complication of allogeneic hematopoietic stem cell transplant (alloHSCT), underscoring the need to further elucidate its mechanisms and develop novel treatments. Based on recent observations that microRNA-155 (miR-155) is up-regulated during T-cell activation, we hypothesized that miR-155 is involved in the modulation of aGVHD. Here we show that miR-155 expression was up-regulated in T cells from mice developing aGVHD after alloHSCT. Mice receiving miR-155-deficient donor lymphocytes had markedly reduced lethal aGVHD, whereas lethal aGVHD developed rapidly in mice recipients of miR-155 overexpressing T cells. Blocking miR-155 expression using a synthetic anti-miR-155 after alloHSCT decreased aGVHD severity and prolonged survival in mice. Finally, miR-155 up-regulation was shown in specimens from patients with pathologic evidence of intestinal aGVHD. Altogether, our data indicate a role for miR-155 in the regulation of GVHD and point to miR-155 as a novel target for therapeutic intervention in this disease.

Tumor site immune markers associated with risk for subsequent basal cell carcinomas.

BACKGROUND: Basal cell carcinoma (BCC) tumors are the most common skin cancer and are highly immunogenic. OBJECTIVE: The goal of this study was to assess how immune-cell related gene expression in an initial BCC tumor biopsy was related to the appearance of subsequent BCC tumors. MATERIALS AND METHODS: Levels of mRNA for CD3ε (a T-cell receptor marker), CD25 (the alpha chain of the interleukin (IL)-2 receptor expressed on activated T-cells and B-cells), CD68 (a marker for monocytes/macrophages), the cell surface glycoprotein intercellular adhesion molecule-1 (ICAM-1), the cytokine interferon-γ (IFN-γ) and the anti-inflammatory cytokine IL-10 were measured in BCC tumor biopsies from 138 patients using real-time PCR. RESULTS: The median follow-up was 26.6 months, and 61% of subjects were free of new BCCs two years post-initial biopsy. Patients with low CD3ε CD25, CD68, and ICAM-1 mRNA levels had significantly shorter times before new tumors were detected (p = 0.03, p = 0.02, p = 0.003, and p = 0.08, respectively). Furthermore, older age diminished the association of mRNA levels with the appearance of subsequent tumors. CONCLUSIONS: Our results show that levels of CD3ε, CD25, CD68, and ICAM-1 mRNA in BCC biopsies may predict risk for new BCC tumors.

Computer-aided detection of centroblasts for follicular lymphoma grading using adaptive likelihood-based cell segmentation.

Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL has a variable clinical course, and important clinical treatment decisions for FL patients are based on histological grading, which is done by manually counting the large malignant cells called centroblasts (CB) in ten standard microscopic high-power fields from H&E-stained tissue sections. This method is tedious and subjective; as a result, suffers from considerable inter and intrareader variability even when used by expert pathologists. In this paper, we present a computer-aided detection system for automated identification of CB cells from H&E-stained FL tissue samples. The proposed system uses a unitone conversion to obtain a single-channel image that has the highest contrast. From the resulting image, which has a bimodal distribution due to the H&E stain, a cell-likelihood image is generated. Finally, a two-step CB detection procedure is applied. In the first step, we identify evident nonCB cells based on size and shape. In the second step, the CB detection is further refined by learning and utilizing the texture distribution of nonCB cells. We evaluated the proposed approach on 100 region-of-interest images extracted from ten distinct tissue samples and obtained a promising 80.7% detection accuracy.

Detection of follicles from IHC-stained slides of follicular lymphoma using iterative watershed.

Follicular lymphoma (FL) is one of the most common types of nonHodgkin lymphoma in the U.S. Diagnosis of FL is based on tissue biopsy that shows characteristic morphologic and immunohistochemical (IHC) findings. Our group's work focuses on the development of computer-aided image-analysis techniques to improve the FL grading. Since centroblast enumeration needs to be performed in malignant follicles, the development of an automated system to accurately identify follicles on digital images of lymphoid tissue is an important step. In this letter, we describe an automated system to identify follicles in IHC-stained tissue sections. A unique feature of the system described here is the use of texture and color information to mimic the process that a human expert might use to identify follicle regions. Comparison of system-generated results with expert-generated ground truth has shown promising results with a mean similarity score of 87.11%.

Computer-aided classification of centroblast cells in follicular lymphoma.

OBJECTIVE: To distinguish centroblast cells from non-centroblast cells using a novel automated method in follicular lymphoma cases and measure its performance on cases obtained by a consensus of six pathologists. STUDY DESIGN: Geometric and color texture features were used in the training and testing of the supervised quadratic discriminant analysis classifier. The technique was trained and tested on a data set composed of 218 centroblast images and 218 non-centroblast images. Computer performance was tested by measuring sensitivity and specificity among cells classified as centroblast and non-centroblast by consensus of six board-certified hematopathologists. RESULTS: Automated classification distinguished centroblast from non-centroblast cells with a classification accuracy of 82.56% and sensitivity and specificity of 86.67% and 86.96%, respectively, when the approach was tested. CONCLUSION: The novelty of our approach is the identification of the centroblast cells with prior information and the introduction of the principal component analysis in the spectral domain to extract texture color features.