Automated feathered edge blood smear analysis: early diagnosis of carcinocythemia in a case of disseminated intravascular coagulation with multi-organ failure.

Carcinocythemia, known as the presence of circulating tumor cells in the peripheral blood, is difficult to detect when the carcinoma cells are minimally present. We describe a case of a 56-year-old patient presenting with disseminated intravascular coagulation (DIC) and multiple organ failure. Despite initial suspicion of sepsis, a peripheral blood smear showed the presence of atypical cells, mainly located at the feathered edge, leading to a presumptive diagnosis of carcinocythemia of unknown primary origin. The presence of a high-fluorescent cell population detected by our hematology analyzer (Sysmex XN-9100) and immunohistochemical staining with pancytokeratin AE1/AE3 confirmed the carcinoma cell origin. The patient died 4 days after referral to our hospital. Postmortem examination revealed a pleomorphic lobular breast carcinoma (triple-negative, androgen receptor-negative). Given the clinical acuity of patients with carcinocythemia, early diagnosis is essential to guide management. This case underscores the importance of optimizing current workflows relying on complex flagging algorithms and enhanced digital imaging to aid in the early detection of such rare condition. When patients present with DIC of unknown origin and high fluorescent signals are detected on the hematology analyzer, carcinocythemia should actively be ruled out by extensive microscopic peripheral blood examination.

Biophysical profiling of red blood cells from thin-film blood smears using deep learning.

Microscopic inspection of thin-film blood smears is widely used to identify red blood cell (RBC) pathologies, including malaria parasitism and hemoglobinopathies, such as sickle cell disease and thalassemia. Emerging research indicates that non-pathologic changes in RBCs can also be detected in images, such as deformability and morphological changes resulting from the storage lesion. In transfusion medicine, cell deformability is a potential biomarker for the quality of donated RBCs. However, a major impediment to the clinical translation of this biomarker is the difficulty associated with performing this measurement. To address this challenge, we developed an approach for biophysical profiling of RBCs based on cell images in thin-film blood smears. We hypothesize that subtle cellular changes are evident in blood smear images, but this information is inaccessible to human expert labellers. To test this hypothesis, we developed a deep learning strategy to analyze Giemsa-stained blood smears to assess the subtle morphologies indicative of RBC deformability and storage-based degradation. Specifically, we prepared thin-film blood smears from 27 RBC samples (9 donors evaluated at 3 storage time points) and imaged them using high-resolution microscopy. Using this dataset, we trained a convolutional neural network to evaluate image-based morphological features related to cell deformability. The prediction of donor deformability is strongly correlated to the microfluidic scores and can be used to categorize images into specific deformability groups with high accuracy. We also used this model to evaluate differences in RBC morphology resulting from cold storage. Together, our results demonstrate that deep learning models can detect subtle cellular morphology differences resulting from deformability and cold storage. This result suggests the potential to assess donor blood quality from thin-film blood smears, which can be acquired ubiquitously in clinical workflows.

MYH9-related disease with a normal platelet count.

MYH9-related disease (MYH9-RD) is characterized by congenital macrothrombocytopenia, progressive kidney failure, and sensorineural hearing loss. We describe a patient with MYH9-RD and a normal platelet count. A 13-year-old boy with a normal platelet count presented with proteinuria and hematuria and underwent a kidney biopsy. Light microscopy showed mild mesangial matrix expansion. Electron microscopy showed thinning of the glomerular basement membrane and splitting of the lamina densa. A tentative diagnosis of Alport syndrome was made. Unexpectedly, genetic analysis revealed a de novo MYH9 gene variant (p.Gln1068_Leu1074dup). A peripheral blood smear examination showed giant platelets and leukocyte inclusion bodies, confirming a diagnosis of MYH9-RD. In summary, we described a patient with MYH9-RD without thrombocytopenia who showed glomerular basement membrane abnormalities similar to Alport syndrome. Peripheral blood smear examinations may be helpful for an appropriate diagnosis of MYH9-RD, even in patients with proteinuria and a normal platelet count.

Application of image recognition technology in pathological diagnosis of blood smears.

Traditional manual blood smear diagnosis methods are time-consuming and prone to errors, often relying heavily on the experience of clinical laboratory analysts for accuracy. As breakthroughs in key technologies such as neural networks and deep learning continue to drive digital transformation in the medical field, image recognition technology is increasingly being leveraged to enhance existing medical processes. In recent years, advancements in computer technology have led to improved efficiency in the identification of blood cells in blood smears through the use of image recognition technology. This paper provides a comprehensive summary of the methods and steps involved in utilizing image recognition algorithms for diagnosing diseases in blood smears, with a focus on malaria and leukemia. Furthermore, it offers a forward-looking research direction for the development of a comprehensive blood cell pathological detection system.

Image cropping for malaria parasite detection on heterogeneous data.

Malaria is a deadly disease of significant concern for the international community. It is an infectious disease caused by a Plasmodium spp. parasite and transmitted by the bite of an infected female Anopheles mosquito. The parasite multiplies in the liver and then destroys the person's red blood cells until it reaches the severe stage, leading to death. The most used tools for diagnosing this disease are the microscope and the rapid diagnostic test (RDT), which have limitations preventing control of the disease. Computer vision technologies present alternatives by providing the means for early detection of this disease before it reaches the severe stage, facilitating treatment and saving patients. In this article, we suggest deep learning methods for earlier and more accurate detection of malaria parasites with high generalization capabilities using microscopic images of blood smears from many heterogeneous patients. These techniques are based on an image preprocessing method that mitigates some of the challenges associated with the variety of red cell characteristics due to patient diversity and other artifacts present in the data. For the study, we collected 65,970 microscopic images from 876 different patients to form a dataset of 33,007 images with a variety that enables us to create models with a high level of generalization. Three types of convolutional neural networks were used, namely Convolutional Neural Network (CNN), DenseNet, and LeNet-5, and the highest classification accuracy on the test data was 97.50% found with the DenseNet model.

Clinical and hematological findings in alpacas (Vicugna pacos) with and without Candidatus Mycoplasma haemolamae infection.

Anemia is a common problem in South American camelids (SACs). Infections with Candidatus Mycoplasma haemolamae (CMh), a cell-wall free, hemotropic bacterium, are often suspected to be an important cause of anemia, as the pathogen infects the erythrocytes and is found in the blood of up to 30% of SACs. The information on the clinical signs of animals infected with this pathogen vary widely. Most infections are clinically inapparent. Treatment is usually carried out with oxytetracycline. A detailed overview of the clinical and hematological findings in 13 alpacas infected with Candidatus M. haemolamae (CMh+), based on patients from our university clinic and comparing those findings with the results of 22 negative alpacas (CMh-) is provided. Assignment to both groups was based on the PCR result. No relevant clinical or hematological differences between CMh+ and CMh- were found, the clinical signs in CMh+ were usually due to comorbidities. The examination of a blood smear alone proved to be insufficient; a PCR test should be carried out to confirm or rule out an infection. A critical review of the need for antibiotic treatment on the basis of a positive test result alone is recommended.

Evaluating pathologist practices in peripheral blood smear review: A comprehensive practice survey.

OBJECTIVES: Widely accepted standardized criteria for peripheral blood (PB) smear review do not exist. The aim of this study was to collect data regarding PB smear review practices across multiple institutions, with a focus on pathologist review. METHODS: A 23-question survey was developed by members of the Society for Hematopathology (SH) Education Committee and distributed to SH members. The survey included questions on practice environment and PB smear review practices, including trainee involvement. RESULTS: Of 725 members contacted, 137 (19%) completed the entire survey. Over half of practices examined 5 to 20 smears a day. All respondents reported using complete blood count/differential leukocyte count data and clinical history as part of smear review. The reported proportion of laboratory-initiated vs clinician-requested reviews varied across respondents. Clinician-requested smear reviews were more likely to be billed and issued as a separate pathology report. Glass slide review (as opposed to digital microscopy) was used by most respondents. All respondents affirmed that PB smear review is an essential component of pathology training programs. Numerous free-text comments were submitted by respondents regarding their own experiences with PB smear review and suggested improvements. CONCLUSIONS: This survey elucidated the spectrum of practice patterns for pathologist review of blood smears and identified potential areas for process improvement.

Efficient leukocytes detection and classification in microscopic blood images using convolutional neural network coupled with a dual attention network.

Leukocytes, also called White Blood Cells (WBCs) or leucocytes, are the cells that play a pivotal role in human health and are vital indicators of diseases such as malaria, leukemia, AIDS, and other viral infections. WBCs detection and classification in blood smears offers insights to pathologists, aiding diagnosis across medical conditions. Traditional techniques, including manual counting, detection, classification, and visual inspection of microscopic images by medical professionals, pose challenges due to their labor-intensive nature. However, traditional methods are time consuming and sometimes susceptible to errors. Here, we propose a high-performance convolutional neural network (CNN) coupled with a dual-attention network that efficiently detects and classifies WBCs in microscopic thick smear images. The main aim of this study was to enhance clinical hematology systems and expedite medical diagnostic processes. In the proposed technique, we utilized a deep convolutional generative adversarial network (DCGAN) to overcome the limitations imposed by limited training data and employed a dual attention mechanism to improve accuracy, efficiency, and generalization. The proposed technique achieved overall accuracy rates of 99.83%, 99.35%, and 99.60% for the peripheral blood cell (PBC), leukocyte images for segmentation and classification (LISC), and Raabin-WBC benchmark datasets, respectively. Our proposed approach outperforms state-of-the-art methods in terms of accuracy, highlighting the effectiveness of the strategies employed and their potential to enhance diagnostic capabilities and advance real-world healthcare practices and diagnostic systems.

Low diagnostic performance of thick blood smears of 50 µl in comparison with direct examination of 10 µl blood and the leukoconcentration technique of 5ml blood among loiasis-suspected patients with low microfilaremia in Gabon, Central Africa, using the STARD-BLCM guidelines.

BACKGROUND: The aim of this study was to determine performance indicators of thick blood smears of 50 µl (TBS-50), following the Standards for the Reporting of Diagnostic Accuracy Studies-Bayesian Latent Class Model (STARD-BLCM) guidelines. TBS-50 was compared with two common parasitological techniques-direct examination of 10 µl blood and a leukoconcentration of 5 ml-for the diagnosis of microfilaremic loiasis. METHODS: The study population was recruited among patients of the Department of Parasitology-Mycology-Tropical Medicine over a period of 1 year. Age, sex, symptoms, and eosinophilia variables were recorded from laboratory registers and medical files. Direct examination of 10 µl of blood, TBS-50, and the leukoconcentration technique with 5 ml of blood were performed for each patient. The classical formula and BLCM were used to determine the diagnostic accuracy of the three techniques as well as the prevalence of microfilaremic loiasis. Three models were built within the framework of BLCM-the BLCM model I and alternative models II and III-for sensitivity analysis. RESULTS: In total, 191 patients consented to be included. The direct blood examination and TBS-50 yielded comparable qualitative and quantitative results. Hence, they are reported together. The prevalence of Loa loa microfilaremia was 9.4% (95% CI 5.7-14.5; n = 18/191) with direct blood examination/TBS-50 and 12.6% [8.2-18.1] (n = 24/191) for leukoconcentration. Comparing TBS-50 with the leukoconcentration method using the classical formula, the sensitivity was 75.0% [53.3-90.2], specificity was 100.0% [97.8-100.0], the positive predictive value was 100.0% [81.5-100.0], and the negative predictive value was 96.5% [92.6-98.7]. The prevalence of microfilaremic loiasis was estimated at 9.7% [6.2-13.7] using BLCM model I. The outputs of BLCM model I showed sensitivity of 78.9% [65.3-90.3], specificity of 100.0% [99.3-100.0], a positive predictive value of 99.1% [87.2-100.0], and a negative predictive value of 93.0% [87.3-97.7] for direct blood examination/TBS-50. CONCLUSIONS: TBS-50 demonstrates low sensitivity relative to two other techniques. In one in five cases, the result will be falsely declared negative using these methods. However, this method can be deployed with limited funds.

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.

A comparison study between the Siemens ADVIA 120 and manual method for the differential white blood cell count in goats.

BACKGROUND: Although widely used, the ADVIA 120 hematology analyzer has not been previously validated for determining the differential leukocyte count in goats. OBJECTIVES: The aim of this study was to compare the differential leukocyte counts provided by the ADVIA 120 (A-diff) and the manual method (M-Diff) in goats. METHODS: EDTA blood samples that were analyzed within 4 h of collection were used in the study. The following exclusion criteria were applied: inappropriately filled tubes or tubes containing clots, erroneous ADVIA peroxidase cytograms, and blood smears of poor quality. The A-Diff was compared with the M-Diff performed by two independent observers on 200 leukocytes. RESULTS: Forty samples were included after previously excluding eight samples. The correlation between the A-Diff and M-Diff was very strong for eosinophils (r = .870, p < .001) and strong for lymphocytes (r = .796, p < .001) and neutrophils (r = .730, p < .001), while no significant correlation was observed for monocytes (r = .026, p = .872). The Passing-Bablok regression analyses revealed statistically significant constant errors for neutrophils (5.83%; 95% confidence interval [CI]: 0.41%, 12.18%) and eosinophils (1.89%; 95% CI: 1.17%, 2.71%). Bland-Altman analyses showed a statistically significant negative bias for lymphocytes (-5.0%) and a statistically significant positive bias for eosinophils (2.2%). The very low basophil percentages precluded a meaningful method comparison. CONCLUSIONS: The ADVIA 120 overall demonstrated good performance for the differential WBC count in goats under the conditions of this study. Therefore, it can be considered suitable for routine hematologic screening in goats. Nonetheless, it should be emphasized that any abnormal result should be confirmed with a blood smear evaluation.

Automatic patient-level recognition of four Plasmodium species on thin blood smear by a real-time detection transformer (RT-DETR) object detection algorithm: a proof-of-concept and evaluation.

Malaria remains a global health problem, with 247 million cases and 619,000 deaths in 2021. Diagnosis of Plasmodium species is important for administering the appropriate treatment. The gold-standard diagnosis for accurate species identification remains the thin blood smear. Nevertheless, this method is time-consuming and requires highly skilled and trained microscopists. To overcome these issues, new diagnostic tools based on deep learning are emerging. This study aimed to evaluate the performances of a real-time detection transformer (RT-DETR) object detection algorithm to discriminate Plasmodium species on thin blood smear images. The algorithm was trained and validated on a data set consisting in 24,720 images from 475 thin blood smears corresponding to 2,002,597 labels. Performances were calculated with a test data set of 4,508 images from 170 smears corresponding to 358,825 labels coming from six French university hospitals. At the patient level, the RT-DETR algorithm exhibited an overall accuracy of 79.4% (135/170) with a recall of 74% (40/54) and 81.9% (95/116) for negative and positive smears, respectively. Among Plasmodium-positive smears, the global accuracy was 82.7% (91/110) with a recall of 90% (38/42), 81.8% (18/22), and 76.1% (35/46) for P. falciparum, P. malariae, and P. ovale/vivax, respectively. The RT-DETR model achieved a World Health Organization (WHO) competence level 2 for species identification. Besides, the RT-DETR algorithm may be run in real-time on low-cost devices such as a smartphone and could be suitable for deployment in low-resource setting areas lacking microscopy experts.IMPORTANCEMalaria remains a global health problem, with 247 million cases and 619,000 deaths in 2021. Diagnosis of Plasmodium species is important for administering the appropriate treatment. The gold-standard diagnosis for accurate species identification remains the thin blood smear. Nevertheless, this method is time-consuming and requires highly skilled and trained microscopists. To overcome these issues, new diagnostic tools based on deep learning are emerging. This study aimed to evaluate the performances of a real-time detection transformer (RT-DETR) object detection algorithm to discriminate Plasmodium species on thin blood smear images. Performances were calculated with a test data set of 4,508 images from 170 smears coming from six French university hospitals. The RT-DETR model achieved a World Health Organization (WHO) competence level 2 for species identification. Besides, the RT-DETR algorithm may be run in real-time on low-cost devices and could be suitable for deployment in low-resource setting areas.

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.

Evaluation of Malaria Microscopy Diagnostic Performance at 40 Public Health Facilities in Abidjan, Côte d'Ivoire in 2020.

PURPOSE: Microscopic diagnosis of Giemsa-stained thick and thin blood films remained the gold standard laboratory method for the diagnosis of malaria. In this context, we felt it was important to conduct this evaluation with 40 public medical biology laboratories (MBLs) in the Abidjan 1 health region that perform blood parasitology tests to improve their implementation process. METHODS: This descriptive and analytical study took place in July 2020 and involved participating laboratories (PLs) from the public sector in Abidjan. A set of 3 blood smear slides of variable parasite densities (PDs) with assigned values (AVs) of parasite densities and assigned Plasmodium species was used. The criterion for establishing the parasite density compliance interval was assigned values of ± 25%, and the performance rates were compared to the 80% recommended by the WHO for the African region. RESULTS: Nearly a quarter (11/40) of the participating laboratories had a compliance rate greater than 80%, including 10 with a performance of 100% for the ability to identify parasites. Regarding identifying plasmodial species, a concordance rate of 100% was obtained for slide 1 for Plasmodium falciparum, while this rate was 20% for slide 2 for Plasmodium ovale. For parasite densities < 200/µl, 87.5% of the participating laboratories (PLs) had a performance rate lower than 80%, while 95% of these PLs had a performance rate higher than 80% for parasitaemia > 2000/µl. CONCLUSIONS: There is a need to strengthen adapted to low parasitaemia, to improve the biological confirmation of malaria in Côte d'Ivoire.

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.

CLINICAL AND EPIDEMIOLOGICAL FEATURES OF MENINGOCOCCAL INFECTION AND ITS EARLY DIAGNOSIS IN RESIDENTS OF THE TRANSCARPATHIAN REGION.

OBJECTIVE: The aim: To identify clinical and epidemiological features of meningococcal infection on the initial day of a patient's medical consultation, as well as the efficacy of laboratory examinations. PATIENTS AND METHODS: Materials and methods: A retrospective analysis of 76 patients' histories diagnosed with meningococcal disease was carried out. CONCLUSION: Conclusions: Patients in the Transcarpathian region mainly develop an atypical form of meningococcal disease. Only half of all patients diagnosed with meningococcemia had a classical hemorrhagic rash. Generalized forms of meningococcal disease may proceed with normal or subfebrile temperature and without severe leukocytosis. We doubt the use of bacteriological methods of laboratory diagnosis due to their low effectiveness. The most sensitive method of laboratory diagnosis is a microscopic examination of blood smear, and cerebrospinal fluid.

Application of Deep Learning in Clinical Settings for Detecting and Classifying Malaria Parasites in Thin Blood Smears.

Background: Scarcity of annotated image data sets of thin blood smears makes expert-level differentiation among Plasmodium species challenging. Here, we aimed to establish a deep learning algorithm for identifying and classifying malaria parasites in thin blood smears and evaluate its performance and clinical prospect. Methods: You Only Look Once v7 was used as the backbone network for training the artificial intelligence algorithm model. The training, validation, and test sets for each malaria parasite category were randomly selected. A comprehensive analysis was performed on 12 708 thin blood smear images of various infective stages of 12 546 malaria parasites, including P falciparum, P vivax, P malariae, P ovale, P knowlesi, and P cynomolgi. Peripheral blood samples were obtained from 380 patients diagnosed with malaria. Additionally, blood samples from monkeys diagnosed with malaria were used to analyze P cynomolgi. The accuracy for detecting Plasmodium-infected blood cells was assessed through various evaluation metrics. Results: The total time to identify 1116 malaria parasites was 13 seconds, with an average analysis time of 0.01 seconds for each parasite in the test set. The average precision was 0.902, with a recall and precision of infected erythrocytes of 96.0% and 94.9%, respectively. Sensitivity and specificity exceeded 96.8% and 99.3%, with an area under the receiver operating characteristic curve >0.999. The highest sensitivity (97.8%) and specificity (99.8%) were observed for trophozoites and merozoites. Conclusions: The algorithm can help facilitate the clinical and morphologic examination of malaria parasites.