Bone marrow metastasis in nonhematological malignancies: A study from tertiary care center.

Introduction: Metastatic cancer presents a treatment challenge to clinicians, particularly for patients with bone marrow infiltration. For tumor staging, therapy selection, and prognosis risk stratification, the status of the bone marrow should be known for the presence or absence of metastasis. The study aimed to evaluate the hematological findings and comprehensive analysis of bone marrow in cases of nonhematological malignancies with bone marrow metastasis. Materials and Methods: This retrospective study comprised a record retrieval of the departmental archives for the past 6 years. A total of 331 patients with nonhematological malignancies were found, of whom 31.42% (104/331) showed bone marrow metastasis. An integrated clinical approach with bone marrow examination findings and immunohistochemistry whenever necessary was used to achieve a definitive diagnosis of bone marrow metastasis. Results: Among the study population, 31.42% (104/331) of patients had nonhematological malignancies that metastasized to the bone marrow. Most of the patients with bone marrow metastasis had anemia, which was found in 77.88% (81/104) of the cases. Leukoerythroblastic reaction was noted in 31.73% (33/104) of the cases, and thrombocytopenia was found in 25% (26/104) of the cases. The most common malignancy with bone marrow metastasis in adults was prostatic adenocarcinoma (28.1%) (9/32) and in pediatric cases, neuroblastoma (53.9%) (52/98). Conclusions: It is essential to diagnose nonhematological malignancies that have metastasized to the bone marrow since this necessitates tumor staging, therapy selection, and prognosis risk stratification. To conclude, not a single hematological parameter is predictive of bone marrow metastasis; however, unexplained anemia, a leukoerythroblastic blood picture, and thrombocytopenia in peripheral blood should raise suspicion for bone marrow metastasis in cases of nonhematological malignancies.

Résumé Introduction: Le cancer métastatique présente un défi de traitement pour les cliniciens, en particulier pour les patients présentant une infiltration de moelle osseuse. Pour la stadification tumorale, la sélection du traitement et la stratification du risque de pronostic, l'état de la moelle osseuse doit être connu pour la présence ou l'absence de métastases. L'étude visait à évaluer les résultats hématologiques et l'analyse complète de la moelle osseuse dans les cas de tumeurs malignes non hématologiques avec métastases de la moelle osseuse. Matériel et méthodes: Cette étude rétrospective comprenait une récupération des archives ministérielles des 6 dernières années. Un total de patients atteints de tumeurs malignes non hématologiques ont été trouvés, dont 31,42% (104/331) présentaient des osmétastases médullaires. Une approche clinique intégrée avec les résultats de l'examen de la moelle osseuse et l'immunohistochimie chaque fois que nécessairea été utilisé pour établir un diagnostic définitif de métastases médullaires. Résultats: Dans la population étudiée, 31,42 % (104/331) des patients présentaient des tumeurs malignes non hématologiques qui se métastasaient à la moelle osseuse. La plupart des patients atteints de métastases de la moelle osseuse présentaient une anémie, qui a été trouvée dans 77,88% (81/104) des cas. Une réaction leucoérythroblastique a été observée dans 31,73 % (33/104) des cas, et une thrombocytopénie a été observée dans 25 % (26/104) des cas. La tumeur maligne la plus fréquente associée aux métastases de la moelle osseuse chez l'adulte était l'adénocarcinome de la prostate (28,1 %) (9/32) et, chez les enfants, le neuroblastome (53,9 %) (52/98). Conclusions: Il est essentiel de diagnostiquer les tumeurs malignes non hématologiques qui ontmétastasé à la moelle osseuse car cela nécessite une stadification tumorale, une sélection thérapeutique et une stratification du risque de pronostic. Pour conclure, pas un seul paramètre hématologique n'est prédictif des métastases de la moelle osseuse; Cependant, une anémie inexpliquée, une image sanguine leucoérythroblastique et une thrombocytopénie dans le sang périphérique devraient faire suspecter des métastases de la moelle osseuse en cas de tumeurs malignes non hématologiques. Mots-clés: Aspiration de moelle osseuse, biopsie de la moelle osseuse, métastases de la moelle osseuse, résultats hématologiques, immunohistochimie, tumeurs malignes non hématologiques, frottis sanguin périphérique.

Immune-mediated thrombocytopenia and IL-6-mediated thrombocytosis observed in idiopathic multicentric Castleman disease.

Idiopathic multicentric Castleman disease (iMCD) is a rare haematological disorder characterized by generalized lymphadenopathy with atypical histopathological features and systemic inflammation caused by a cytokine storm involving interleukin-6 (IL-6). Three clinical subtypes are recognized: thrombocytopenia, anasarca, fever, renal dysfunction, organomegaly (iMCD-TAFRO); idiopathic plasmacytic lymphadenopathy (iMCD-IPL), involving thrombocytosis and hypergammaglobulinaemia; and iMCD-not otherwise specified (iMCD-NOS), which includes patients who do not meet criteria for the other subtypes. Disease pathogenesis is poorly understood, with potential involvement of infectious, clonal and/or autoimmune mechanisms. To better characterize iMCD clinicopathology and gain mechanistic insights into iMCD, we analysed complete blood counts, other clinical laboratory values and blood smear morphology among 63 iMCD patients grouped by clinical subtype. Patients with iMCD-TAFRO had large platelets, clinical severity associated with lower platelet counts and transfusion-resistant thrombocytopenia, similar to what is observed with immune-mediated destruction of platelets in immune thrombocytopenic purpura. Conversely, elevated platelet counts in iMCD-IPL were associated with elevated IL-6 and declined following anti-IL-6 therapy. Our data suggest that autoimmune mechanisms contribute to the thrombocytopenia in at least a portion of iMCD-TAFRO patients whereas IL-6 drives thrombocytosis in iMCD-IPL, and these mechanisms likely contribute to disease pathogenesis.

Homozygous SPTA1-associated hereditary pyropoikilocytosis presenting as hydrops fetalis.

INTRODUCTION: Hereditary pyropoikilocytosis (HPP) is a heterogeneous inherited disorder of red blood cell (RBC) membrane and cytoskeletal proteins that leads to hemolytic anemia. HPP is characterized by marked poikilocytosis, microspherocytes, RBC fragmentation, and elliptocytes on peripheral blood smear. Mutations in SPTA1 can cause HPP due to a quantitative defect in α-spectrin and can lead to profound fetal anemia and nonimmune hydrops fetalis, which can be managed with intrauterine transfusion. CASE PRESENTATION: We present a case of a 26-year-old G4P2102 woman of Amish-Mennonite ancestry with a pregnancy complicated by fetal homozygosity for an SPTA1 gene variant (SPTA1c.6154delG) as well as severe fetal anemia and hydrops fetalis, which was managed with four intrauterine transfusions between 26 and 30 weeks gestation. Pre-transfusion peripheral smears from fetal blood samples showed RBC morphology consistent with HPP. The neonate had severe hyperbilirubinemia at birth, which has resolved, but remains transfusion-dependent at 6 months of life. DISCUSSION/CONCLUSION: To our knowledge, this is the first report that correlates homozygosity of the SPTA1c.6154delG gene variant with RBC dysmorphology and establishes the diagnosis of HPP.

Hematocytological Clues of Peripheral Blood in Different Clinical Presentations of COVID-19.

Background: To gain insight into the pathogenesis and clinical course of COVID-19 from a historical perspective, we reviewed paraclinical diagnostic tools of this disease and prioritized the patients with a more severe form of disease admitted to intensive care units (ICUs). The objective was to better predict the course and severity of the disease by collecting more paraclinical data, specifically by examining the relationship between hematological findings and cytological variation of blood neutrophils and monocytes. Methods: This retrospective study was conducted on 112 patients with confirmed COVID-19 admitted to Imam Hossein Hospital (Tehran, Iran) from August to September 2020. Peripheral blood smears of these patients were differentiated according to several cytological variations of neutrophils and monocytes, and the correlation to the severity of the disease was specified. Results: The mean percentages of degenerated monocytes, degenerated granulocytes, and spiky biky neutrophils were significantly different among critical and non-critical patients (P<0.05). Degenerated monocytes and granulocytes were higher in critical patients as opposed to spiky biky neutrophils, which were higher among non-critical ones. Comparing the peripheral blood smears of COVID-19 patients (regarding pulmonary involvement in chest computed tomography [CT] scans [subtle, mild, moderate, and severe groups]), the twisted form of neutrophils was significantly higher in the subtle group than in the mild and moderate groups (P=0.003). Conclusion: Different cytological morphologies of neutrophils and monocytes, including degenerated monocytes, degenerated granulocytes, and spiky biky and twisted neutrophils, could help to predict the course and severity of the disease.

DSCNet: Deep Skip Connections-Based Dense Network for ALL Diagnosis Using Peripheral Blood Smear Images.

Acute lymphoblastic leukemia (ALL) is a life-threatening hematological malignancy that requires early and accurate diagnosis for effective treatment. However, the manual diagnosis of ALL is time-consuming and can delay critical treatment decisions. To address this challenge, researchers have turned to advanced technologies such as deep learning (DL) models. These models leverage the power of artificial intelligence to analyze complex patterns and features in medical images and data, enabling faster and more accurate diagnosis of ALL. However, the existing DL-based ALL diagnosis suffers from various challenges, such as computational complexity, sensitivity to hyperparameters, and difficulties with noisy or low-quality input images. To address these issues, in this paper, we propose a novel Deep Skip Connections-Based Dense Network (DSCNet) tailored for ALL diagnosis using peripheral blood smear images. The DSCNet architecture integrates skip connections, custom image filtering, Kullback-Leibler (KL) divergence loss, and dropout regularization to enhance its performance and generalization abilities. DSCNet leverages skip connections to address the vanishing gradient problem and capture long-range dependencies, while custom image filtering enhances relevant features in the input data. KL divergence loss serves as the optimization objective, enabling accurate predictions. Dropout regularization is employed to prevent overfitting during training, promoting robust feature representations. The experiments conducted on an augmented dataset for ALL highlight the effectiveness of DSCNet. The proposed DSCNet outperforms competing methods, showcasing significant enhancements in accuracy, sensitivity, specificity, F-score, and area under the curve (AUC), achieving increases of 1.25%, 1.32%, 1.12%, 1.24%, and 1.23%, respectively. The proposed approach demonstrates the potential of DSCNet as an effective tool for early and accurate ALL diagnosis, with potential applications in clinical settings to improve patient outcomes and advance leukemia detection research.

A Rare Concurrence of Myelodysplastic Neoplasia and Tetrasomy 8 in a 3-Year-Old Bahraini Male.

Myelodysplastic neoplasia (MDS) is a group of stem cell disorders involving ineffective hematopoiesis. It can be associated with an increased risk of progression toward acute myeloid leukemia (AML). In Bahrain, MDS is the fifth most common primary hematologic malignancy. MDS has an annual incidence of up to 4 million cases. Some of the presenting signs and symptoms of MDS are often nonspecific, such as fatigue, pallor, malaise, fevers, bleeding, bruising, weight loss, and anorexia. Approximately 40% of patients with MDS progress to AML. This paper outlines a case of a 3-year-old Bahraini male (known to have sickle cell trait) who presented to the emergency department of Salmaniya Medical Complex with a five-day history of fever, congested throat, left ear pain, and abdominal pain. He had one episode of vomiting gastric content the previous day. He had previously gone to a private clinic with similar symptoms. Physical examination revealed a short neck and short stature, which was found to be below the 5th percentile. He had generalized pallor and hepatosplenomegaly. A blood smear showed leukopenia and normochromic normocytic anemia. There were excessive blasts found which consisted of 17% of nucleated cells and few granulopoietic cells. Erythropoiesis was active with a few showing mild megaloblastic changes. There were rare megakaryocytes noted. Moreover, the bone marrow aspirate showed two populations on dim CD45. The first population consisted of 3.15% on dim CD45 comprising of hematogones which brightly expressed CD19, HLA-DR, CD79a, and dim CD10. The second population consisted of 14.85% on dim CD45 which expressed CD34, CD13, CD117, HLA-DR, and dim CD7. Based on the peripheral blood smear and bone marrow immunophenotyping findings, a diagnosis of myelodysplastic syndrome with excessive blasts was made, which soon transformed into a diagnosis of AML. Furthermore, increased levels of dysplastic changes and percentage of blasts in the peripheral blood smear and bone marrow lead to a higher possibility of transformation into AML. As per the WHO classification, a diagnosis of MDS needs evaluation of the morphology of blood and bone marrow.

Howell-Jolly Body-Like Inclusions in Coronavirus Disease 2019 (COVID-19): Possible Novel Findings.

Background: During COVID-19 pandemic, it is difficult to distinguish febrile patient infected by SARS-CoV-2 or bacterial causes. Howell-Jolly bodies are a well-known entity found in red blood cells. They are nuclear fragments, composed of deoxyribonucleic acid, commonly observed in the peripheral blood smears of hyposplenic or asplenic patients. Recently, similar inclusions often referred to as Howell-Jolly body-like inclusions (HJBLIs) have been reported in the neutrophils of patients with acquired immune deficiency syndrome (AIDS) and COVID-19 patient. Aim: To explore whether HJBLIs in peripheral blood smear could differentiate between patients with confirmed SARS-CoV-2 and bacterial pneumonia. Methods: We performed cross-sectional study using secondary data from COVID-19 database and re-evaluated peripheral blood smears to identify HJBLIs. We included confirmed COVID-19 adults age >18 years who were hospitalized in Dr. Hasan Sadikin General Hospital, Bandung, Indonesia from March 1st 2020-May 31st 2020. We also examined peripheral blood smears in patients with confirmed bacterial pneumonia as a control group. Clinical characteristics including disease severity, CURB-65 score, comorbidity, and the present of HJBLIs in peripheral blood smears were evaluated. Results: Overall, 33 patients were included: 22 were confirmed COVID-19 and 11 were confirmed bacterial pneumonia. The median (interquartile range) age in COVID-19 and patients with bacterial pneumonia were 53 years (40-64) vs 57 years (53-71), respectively. Compared with patients with bacterial pneumonia, HJBLIs were significantly higher in COVID-19 patients [21/22 (80.8%) vs 5/11 (45.5%), p 0.001]. Conclusion: Howell-Jolly body-like inclusions could be a potential feature to help differentiate between COVID-19 and bacterial pneumonia.

PROSER: A Web-Based Peripheral Blood Smear Interpretation Support Tool Utilizing Electronic Health Record Data.

OBJECTIVES: Peripheral blood smear (PBS) interpretation represents a cornerstone of pathology practice and resident training but has remained largely static for decades. Here, we describe a novel PBS interpretation support tool. METHODS: In a mixed-methods quality improvement study, a web-based clinical decision support (CDS) tool to assist pathologists in PBS interpretation, PROSER, was deployed in an academic hospital over a 2-month period in 2022. PROSER interfaced with the hospital system's electronic health record and data warehouse to obtain and display relevant demographic, laboratory, and medication information for patients with pending PBS consults. PROSER used these data along with morphologic findings entered by the pathologist to draft a PBS interpretation using rule-based logic. We evaluated users' perceptions of PROSER with a Likert-type survey. RESULTS: PROSER displayed 46 laboratory values with corresponding reference ranges and abnormal flags, allowed for entry of 14 microscopy findings, and computed 2 calculations based on laboratory values; it composed automated PBS reports using a library of 92 prewritten phrases. Overall, PROSER was well received by residents. CONCLUSIONS: In this quality improvement study, we successfully deployed a web-based CDS tool for PBS interpretation. Future work is needed to quantitatively evaluate this intervention's effects on clinical outcomes and resident training.

Neutrophil-mediated erythrophagocytosis following Russell's viper (Daboia russelii) bite.

Snakebite envenomation is regarded as a high-priority neglected tropical disease by the World Health Organisation, as it results in significant loss of lives and permanent disabilities. Russell's viper is one of the important venomous snakes that causes morbidities, mortalities and disabilities in India. The clinical presentation of Russell's viper envenomation is characterised by local envenoming effects including tissue damage, venom-induced coagulopathy, neurotoxicity, and kidney injury. However, venom composition and its mechanisms of toxicity are highly variable even within snakes of the same species including Russell's viper. This variation in venom composition results in a broad range of clinical complications. Here, we present a previously undocumented case of neutrophil-mediated erythrophagocytosis in a healthy 28-year-old female following Russell's viper bite. Systemic envenomation effects and bleeding abnormalities in this patient were corrected by the administration of polyvalent antivenom. Two days later, the patient developed progressive swelling and ecchymosis in the bitten limb. Observed abnormal limits within blood testing were followed up by a peripheral blood smear where it was found that 30% of neutrophils had phagocytosed erythrocytes as they were found within the cytoplasm. The patient underwent a fasciotomy for compartmental syndrome and received packed red cells and a course of corticosteroids. Following this treatment, the patient made a full recovery. This case report outlines a previously undocumented pathological event induced by Russell's viper envenomation, guiding diagnosis and treatment. Clinicians' knowledge of the mechanisms of toxicity of Russell's viper envenomation and its clinical manifestations are essential for improving the treatment of snakebites to achieve positive outcomes.

Artificial intelligence of digital morphology analyzers improves the efficiency of manual leukocyte differentiation of peripheral blood.

BACKGROUND AND OBJECTIVE: Morphological identification of peripheral leukocytes is a complex and time-consuming task, having especially high requirements for personnel expertise. This study is to investigate the role of artificial intelligence (AI) in assisting the manual leukocyte differentiation of peripheral blood. METHODS: A total of 102 blood samples that triggered the review rules of hematology analyzers were enrolled. The peripheral blood smears were prepared and analyzed by Mindray MC-100i digital morphology analyzers. Two hundreds leukocytes were located and their cell images were collected. Two senior technologists labeled all cells to form standard answers. Afterward, the digital morphology analyzer unitized AI to pre-classify all cells. Ten junior and intermediate technologists were selected to review the cells with the AI pre-classification, yielding the AI-assisted classifications. Then the cell images were shuffled and re-classified without AI. The accuracy, sensitivity and specificity of the leukocyte differentiation with or without AI assistance were analyzed and compared. The time required for classification by each person was recorded. RESULTS: For junior technologists, the accuracy of normal and abnormal leukocyte differentiation increased by 4.79% and 15.16% with the assistance of AI. And for intermediate technologists, the accuracy increased by 7.40% and 14.54% for normal and abnormal leukocyte differentiation, respectively. The sensitivity and specificity also significantly increased with the help of AI. In addition, the average time for each individual to classify each blood smear was shortened by 215 s with AI. CONCLUSION: AI can assist laboratory technologists in the morphological differentiation of leukocytes. In particular, it can improve the sensitivity of abnormal leukocyte differentiation and lower the risk of missing detection of abnormal WBCs.

Machine Learning-Based Detection of Dengue from Blood Smear Images Utilizing Platelet and Lymphocyte Characteristics.

Dengue fever, also known as break-bone fever, can be life-threatening. Caused by DENV, an RNA virus from the Flaviviridae family, dengue is currently a globally important public health problem. The clinical methods available for dengue diagnosis require skilled supervision. They are manual, time-consuming, labor-intensive, and not affordable to common people. This paper describes a method that can support clinicians during dengue diagnosis. It is proposed to automate the peripheral blood smear (PBS) examination using Artificial Intelligence (AI) to aid dengue diagnosis. Nowadays, AI, especially Machine Learning (ML), is increasingly being explored for successful analyses in the biomedical field. Digital pathology coupled with AI holds great potential in developing healthcare services. The automation system developed incorporates a blob detection method to detect platelets and thrombocytopenia from the PBS images. The results achieved are clinically acceptable. Moreover, an ML-based technique is proposed to detect dengue from the images of PBS based on the lymphocyte nucleus. Ten features are extracted, including six morphological and four Gray Level Spatial Dependance Matrix (GLSDM) features, out of the lymphocyte nucleus of normal and dengue cases. Features are then subjected to various popular supervised classifiers built using a ten-fold cross-validation policy for automated dengue detection. Among all the classifiers, the best performance was achieved by Support Vector Machine (SVM) and Decision Tree (DT), each with an accuracy of 93.62%. Furthermore, 1000 deep features extracted using pre-trained MobileNetV2 and 177 textural features extracted using Local binary pattern (LBP) from the lymphocyte nucleus are subjected to feature selection. The ReliefF selected 100 most significant features are then fed to the classifiers. The best performance was attained using an SVM classifier with 95.74% accuracy. With the obtained results, it is evident that this proposed approach can efficiently contribute as an adjuvant tool for diagnosing dengue from the digital microscopic images of PBS.

Classification of peripheral blood neutrophils using deep learning.

Deep learning has been used to classify the while blood cells in peripheral blood smears. However, the classification of developing neutrophils is rarely studied. Moreover, it is still unknown whether deep learning can work well on the data coming from different sources. In this study, we therefore investigate the classification performance of deep learning for immature and mature neutrophils. In particular, we used three open-access datasets obtained from different imaging systems: CellaVision DM 96, CellaVision DM 100, and iCELL ME-150. A total of 26,050 images identified by one laboratory technologist were randomly split into training, validation, and testing datasets. A total of 10 convolutional neural networks were trained to classify six blood cell types: myeloblast, promyelocyte, myelocyte, metamyelocyte, banded neutrophil, and segmented neutrophil. The experimental results showed that compared to any single model, the average ensemble model could achieve a better classification performance and provide a testing accuracy of 90.1%. The sensitivity and specificity of the average ensemble model for the six blood cell types were above 83.5% and 96.9%, respectively. Our results suggest that deep learning is a promising tool for the classification of developing neutrophils, but further improvement is required.

Fulminant Streptococcus suis infection detected on peripheral blood smear: A case report.

Streptococcus suis, a gram-positive coccus, is recognized as an emerging zoonotic pathogen that causes serious infections in humans, such as bacterial meningitis and sepsis, with poor outcomes. The pathogen is known to be transmitted through the consumption of raw pork or occupational exposure to pigs. A previously healthy 38-year-old woman with occupational exposure to raw pork was presented to our emergency department with a clinical diagnosis of rapidly progressive septic shock. Peripheral blood smears detected chains of cocci inside granulocytes, which led to the early recognition of gram-positive cocci in short chains before the blood culture test results. Blood cultures later tested positive for S. suis serotype 2. The patient's condition deteriorated despite aggressive resuscitative measures including antibiotics, vasopressors, multiple blood transfusions, mechanical ventilation, and renal replacement therapy. Initiation of veno-arterial extracorporeal membrane oxygenation was ineffective, and the patient died 16 h after admission. The identification of bacteria in the peripheral blood smear indicated an overwhelming infection and led to the rapid recognition of bacteremia. Our report aims to raise awareness about fatal zoonotic pathogens and to promote the unique role of peripheral blood smears that could provide preliminary diagnostic information before blood culture results.

Morphological abnormalities of leukocytes in SARS-CoV-2 infection.

Introduction: The causative agent of COVID-19 (Coronavirus Disease 2019) is an enveloped RNA (ribonucleic acid) virus of the SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) family. The effects of SARS-CoV-2 on the differentiation and maturation of blood cells have been the subject of several studies, we report our experience of an investigation of the morphologic abnormalities of leukocytes observed during COVID-19. Patients and methods: This is a prospective study of 5 months, from February 2021 to June 2021. Forty COVID-19 patients and 20 healthy controls were included in this study. We performed complete blood count and peripheral blood smear of all patients and control samples. Leukocytes abnormalities were quantified as a percentage of 100 leukocytes of the same lineage. Results: The morphological abnormalities of the leukocytes found in percentage of patients have been mainly neutrophils bilobed 72,5%, hypogranulation 45%, acquired pseudo Pelger-Huet 35%, vacuolated neutrophils 42,5%, Apoptotic neutrophils 35,5 %, neutrophils with toxic granulations 30%, myelemia 45%, atypical lymphocytes 52,5%, lymphoplasmocytes 60% and vacuolated monocytes 27, 5%. Conclusion: Our study revealed several morphological abnormalities of the different cells of the leukocyte lineage. The presence of toxic granulations in the cytoplasm of the myelocytes was specific to this study.

Post-cardiac Arrest Leukocytosis Mimicking Acute Monocytic Leukemia.

Leukocytosis is defined by an increased WBC count in the peripheral blood. This can be caused by many pathologies from benign conditions such as stress, infection, and inflammation or malignant origins such as leukemia. Although leukocytosis is regularly encountered clinically and has many etiologies making a definitive diagnosis, at times, may be difficult. A case of severe leukocytosis requires careful consideration of symptoms and confirmation with serial complete blood count (CBC) testing before pursuing further invasive testing such as bone marrow biopsy. Here, we report the case of a 78-year-old male patient who, after a cardiac arrest, presented with reactive hyperleukocytosis mimicking acute monocytic leukemia.

A telepathology based screening tool for COVID-19 by leveraging morphological changes related to leukocytes in peripheral blood smears.

As we approach the aftermath of a global pandemic caused by Severe Acute Respiratory Syndrome-Corona Virus (SARS-CoV-2), the importance of quickly developing rapid screening tests has become very clear from the point of view of containment and also saving lives. Here, we present an explorative study to develop a telepathology-based screening tool using peripheral blood smears (PBS) to identify Coronavirus Disease (COVID-19)-positive cases from a group of 138 patients with flu-like symptoms, consisting of 82 positive and 56 negative samples. Stained blood smear slides were imaged using an automated slide scanner (AI 100) and the images uploaded to the cloud were analyzed by a pathologist to generate semi-quantitative leukocyte morphology-related data. These telepathology data were compared with the data generated from manual microscopy of the same set of smear slides and also the same pathologist. Besides good correlation between the data from telepathology and manual microscopy, we were able to achieve a sensitivity and specificity of 0.83 and 0.71, respectively, for identifying positive and negative COVID-19 cases using a six-parameter combination associated with leukocyte morphology. The morphological features included plasmacytoid cells, neutrophil dysplastic promyelocyte, neutrophil blast-like cells, apoptotic cells, smudged neutrophil, and neutrophil-to-immature granulocyte ratio. Although Polymerase Chain Reaction (PCR) and antibody tests have a superior performance, the PBS-based telepathology tool presented here has the potential to be an interim screening tool in resource-limited settings in underdeveloped and developing countries.

Case series on Silvery Hair Syndromes: Single Center Experience.

Background: Silvery Hair Syndromes (SHS), an autosomal recessive inherited disorder, includes Chediak-Higashi syndrome (CHS), Griscelli syndrome (GS), Hermansky-Pudlak syndrome (HPS), and Elejalde syndrome. Associated immunological and neurological defects and predilection for hemophagocytic lymphohistiocytosis (HLH) makes them a distinctive entity in pediatric practice. Thorough clinical examination, bedside investigations such as peripheral blood smear (PBS) and hair microscopy, and bone marrow (BM) examination are inexpensive and reliable diagnostic tools. Methods: We report 12 cases with SHS (CHS, n = 06; GS, n = 04; HPS, n = 02). Results: 8 out of 12 SHS children (CHS-05, GS-03) presented with HLH. Out of 5 cases of CHS with HLH, 2 died, 3rd is stable post-chemotherapy; 4th completed chemotherapy, underwent matched related hematopoietic stem cell transplant (HSCT), and is stable 8 months off treatment. The 5th child completed chemotherapy and is in process of transplant. One CHS child without HLH is thriving without any treatment. Of the 4 GS cases, 3 presented with HLH and received chemotherapy (HLH 2004 protocol). One lost follow-up after initial remission; another had recurrence 7 months off treatment and discontinued further treatment. The third child had recurrence 1.5 years after initial chemotherapy; HLH 2004 protocol was restarted followed by HSCT from matched sibling donor; is currently well, 2.5 years post-transplant. One child with GS had neurological features with no evidence of HLH and did not take treatment. Of 2 children with HPS, one presented with severe sepsis and the other with neurological problems. They were managed symptomatically. Conclusion: In SHS with HLH, chemotherapy followed by allogeneic hematopoietic stem cell transplantation is a promising curative option.

Automatic analysis system for abnormal red blood cells in peripheral blood smears.

The type and ratio of abnormal red blood cells (RBCs) in blood can be identified through peripheral blood smear test. Accurate classification is important because the accompanying diseases indicated by abnormal RBCs vary. In clinical practice, this task is time-consuming because the RBCs are manually classified. In addition, because the classification depends on the subjective criteria of pathologists, objective classification is difficult to achieve. In this paper, an automatic classification method that is solely based on images of RBCs captured under a microscope and processed using machine learning (ML) is proposed. The size and hemoglobin abnormalities of RBCs were classified by optimizing the criteria used in clinical practice. For morphologically abnormal RBCs classification, used seven geometric features information (major axis, minor axis, ratio of major and minor axis, perimeter, circularity, number of convex hulls, difference between area and convex area) and five types of multiple classifiers (Support Vector Machine, Decision Tree, K-Nearest Neighbor, Random Forest, and Adaboost models). Among was categorized using SVM, highly accurate results (99.9%) were obtained. The classification is performed simultaneously, and results are provided to the user through a graphical user interface (GUI).