Journal Description
Diagnostics
Diagnostics
is an international, peer-reviewed, open access journal on medical diagnosis published semimonthly online by MDPI. The British Neuro-Oncology Society (BNOS), the International Society for Infectious Diseases in Obstetrics and Gynaecology (ISIDOG) and the Swiss Union of Laboratory Medicine (SULM) are affiliated with Diagnostics and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, Embase, Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Medicine, General & Internal)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.7 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journal: LabMed.
Impact Factor:
3.6 (2022);
5-Year Impact Factor:
3.7 (2022)
Latest Articles
Local Diagnostic Reference Levels for Adult Computed Tomography Urography Exams
Diagnostics 2024, 14(6), 643; https://doi.org/10.3390/diagnostics14060643 (registering DOI) - 19 Mar 2024
Abstract
A Computed Tomography Urography (CTU) scan is a medical imaging test that examines the urinary tract, including the bladder, kidneys, and ureters. It helps diagnose various urinary tract diseases with precision. However, patients undergoing CTU imaging receive a relatively high dose of radiation,
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A Computed Tomography Urography (CTU) scan is a medical imaging test that examines the urinary tract, including the bladder, kidneys, and ureters. It helps diagnose various urinary tract diseases with precision. However, patients undergoing CTU imaging receive a relatively high dose of radiation, which can be a concern. In our research paper, we analyzed the Computed Tomography Dose Index (CTDIvol) and Dose-Length Product (DLP) for 203 adult patients who underwent CTU at one of the most important regional centers in Bosnia and Herzegovina that sees a large number of patients. Our study included the distribution of age and sex, the number of phases within one examination, and different clinical indications. We compared our findings with the results available in the scientific literature, particularly the recently published results from 20 European countries. Furthermore, we established the local diagnostic reference levels (LDRLs) that can help set the national diagnostic reference levels (NDRLs). We believe our research is a significant step towards optimizing the protocols used in different hospitals in our country.
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(This article belongs to the Special Issue Advanced Role of Computed Tomography in Clinical Diagnosis)
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The Role of SARS-CoV-2 Nucleocapsidic Antigen and Krebs von den Lungen 6 Serum Levels in Predicting COVID-19 Pneumonia Outcome
by
Stefano Sanduzzi Zamparelli, Vincenzo Fucci, Gaetano Rea, Francesco Perna, Marialuisa Bocchino and Alessandro Sanduzzi Zamparelli
Diagnostics 2024, 14(6), 642; https://doi.org/10.3390/diagnostics14060642 (registering DOI) - 18 Mar 2024
Abstract
Background: The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a significant threat worldwide, with severe cases leading to hospitalization and death. This study aims to evaluate the potential use of serum nucleocapsid antigen (NAg) and Krebs von den Lungen-6 glycoprotein (KL-6) as
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Background: The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a significant threat worldwide, with severe cases leading to hospitalization and death. This study aims to evaluate the potential use of serum nucleocapsid antigen (NAg) and Krebs von den Lungen-6 glycoprotein (KL-6) as biomarkers of severe COVID-19 and to investigate their correlation with clinical, radiological, and biochemical parameters. Methods: This retrospective study included 128 patients with confirmed SARS-CoV-2 infection admitted to a Neapolitan hospital in Italy between October 2020 and July 2021. Demographic, clinical, and laboratory data were collected, including serum levels of NAg and KL-6. The Chung et al. Computed Tomography Severity Score (TSS) was used to assess the severity of pneumonia, and outcomes were classified as home discharge, rehabilitation, and death. Statistical analyses were performed to compare Group I (home discharge and rehabilitation) and Group II (death, sub-intensive care, and ICU stay) based on demographic data, laboratory parameters, and TSS. Results: Group II patients showed worse outcomes with higher levels of NAg, KL-6, and inflammatory markers, including interleukin-6 (IL-6), interleukin-2 receptor (IL-2R), and adrenomedullin. TSS was also significantly higher in Group II, with a positive correlation between TSS and NAg and KL-6 levels. Group I patients had higher values of hemoglobin (Hb) and platelets (PLT), while Group II patients had higher values of C-reactive protein (CRP), procalcitonin (PCT), D-Dimer, and glycemia. No significant difference was observed in gender distribution. Conclusions: Serum NAg and KL-6 levels are potential biomarkers of severe COVID-19 pneumonia, with higher levels indicating greater inflammation and organ damage. NAg may help identify infected patients at an increased risk of severe COVID-19 and ensure their admission to the most appropriate level of care. KL-6 may help predict interstitial lung damage and the severity of clinical features. Further studies are needed to establish a decision-making cut-off for these biomarkers in COVID-19.
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(This article belongs to the Section Pathology and Molecular Diagnostics)
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Thoracic Biometry in Patients with Congenital Diaphragmatic Hernia, a Magnetic Resonance Imaging Study
by
Erick George Neștianu, Septimiu Popescu, Dragoș Ovidiu Alexandru, Laura Giurcăneanu and Radu Vlădăreanu
Diagnostics 2024, 14(6), 641; https://doi.org/10.3390/diagnostics14060641 - 18 Mar 2024
Abstract
This is a retrospective study investigating biometric measurements using magnetic resonance imaging (MRI) examinations in congenital diaphragmatic hernia (CDH). CDH is one of the more common causes of pulmonary hypoplasia, with grave consequences for the fetus. Inclusion criteria were patients diagnosed with CDH
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This is a retrospective study investigating biometric measurements using magnetic resonance imaging (MRI) examinations in congenital diaphragmatic hernia (CDH). CDH is one of the more common causes of pulmonary hypoplasia, with grave consequences for the fetus. Inclusion criteria were patients diagnosed with CDH as the only observed anomaly, who underwent MRI examination after the second-trimester morphology ultrasound. The patients came from three university hospitals in Bucharest, Romania. In total, 19 patients were included in the study after applying exclusion criteria. Comparing the observed values of the thoracic transverse diameter, the thoracic anterior–posterior diameter, the thoracic circumference, the thoracic area, and the thoracic volume with values from the literature, we observed a predictive alteration of these parameters, with most showing Gaussian distribution. We observed statistical significance for most of our correlations, except between the observed and expected thoracic anterior–posterior diameters and the observed and expected thoracic volume values. This is very helpful when complex studies that can calculate the pulmonary volume cannot be obtained, as in the case of movement artifacts, and allows the clinicians to better assess the severity of the disease. MRI follow-up in CDH cases is a necessity, as it offers the most accurate thoracic biometry.
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(This article belongs to the Special Issue Advanced MRI Imaging and Diagnostics in Lung Disease)
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Nodal Low-Grade B-Cell Lymphoma Co-Expressing CD5 and CD10 but Not CD23, IRTA1, or Cyclin D1: The Diagnostic Challenge of a Splenic Marginal Zone Lymphoma
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Khin-Than Win, Yen-Chuan Hsieh, Hung-Chang Wu and Shih-Sung Chuang
Diagnostics 2024, 14(6), 640; https://doi.org/10.3390/diagnostics14060640 - 18 Mar 2024
Abstract
The diagnosis of lymphoma is based on histopathological and immunophenotypical features. CD5 and CD10 are traditionally considered a T-cell antigen and a germinal center B-cell antigen, respectively. It is very unusual for a low-grade B-cell lymphoma (BCL) to co-express CD5 and CD10. Although
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The diagnosis of lymphoma is based on histopathological and immunophenotypical features. CD5 and CD10 are traditionally considered a T-cell antigen and a germinal center B-cell antigen, respectively. It is very unusual for a low-grade B-cell lymphoma (BCL) to co-express CD5 and CD10. Although the biologic basis or clinical significance of such co-expression is unclear, this rare event may pose a significant diagnostic challenge. Here, we report a case of a 63-year-old male presenting with bilateral cervical lymphadenopathy and lymphocytosis. Histologically, the nodal tumor was largely diffuse with neoplastic small atypical lymphocytes co-expressing CD5, CD10, and CD20, but not CD23 or cyclin D1. The leukemic cells in the peripheral blood exhibited hairy projections. Taking together the marked splenomegaly, involvement of lymph nodes, bone marrow, and peripheral blood, a final diagnosis of splenic marginal zone lymphoma (SMZL) was reached. The patient was alive with partial response for 10 months after immunochemotherapy. The dual expression of CD5 and CD10 is extremely unusual for low-grade BCL and may lead to an erroneous diagnosis. Integrating the findings into peripheral blood smear tests, flow cytometry, histopathology, imaging, and clinical features is mandatory to exclude other lymphoma types and to reach a correct diagnosis, particularly for a case with nodal presentation.
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(This article belongs to the Special Issue Recent Advances in Hematology and Oncology)
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Ultrasound Biomicroscopy as a Novel, Potential Modality to Evaluate Anterior Segment Ophthalmic Structures during Spaceflight: An Analysis of Current Technology
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Benjamin Soares, Joshua Ong, Daniela Osteicoechea, Cihan Mehmet Kadipasaoglu, Ethan Waisberg, Prithul Sarker, Nasif Zaman, Alireza Tavakkoli, Gianmarco Vizzeri and Andrew G. Lee
Diagnostics 2024, 14(6), 639; https://doi.org/10.3390/diagnostics14060639 - 18 Mar 2024
Abstract
Ocular health is currently a major concern for astronauts on current and future long-duration spaceflight missions. Spaceflight-associated neuro-ocular syndrome (SANS) is a collection of ophthalmic and neurologic findings that is one potential physiologic barrier to interplanetary spaceflight. Since its initial report in 2011,
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Ocular health is currently a major concern for astronauts on current and future long-duration spaceflight missions. Spaceflight-associated neuro-ocular syndrome (SANS) is a collection of ophthalmic and neurologic findings that is one potential physiologic barrier to interplanetary spaceflight. Since its initial report in 2011, our understanding of SANS has advanced considerably, with a primary focus on posterior ocular imaging including fundus photography and optical coherence tomography. However, there may be changes to the anterior segment that have not been identified. Additional concerns to ocular health in space include corneal damage and radiation-induced cataract formation. Given these concerns, precision anterior segment imaging of the eye would be a valuable addition to future long-duration spaceflights. The purpose of this paper is to review ultrasound biomicroscopy (UBM) and its potential as a noninvasive, efficient imaging modality for spaceflight. The analysis of UBM for spaceflight is not well defined in the literature, and such technology may help to provide further insights into the overall anatomical changes in the eye in microgravity.
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(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Recent Advances in Optical Medical Imaging and Therapy Guidance)
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Periportal Edema as an Extrarenal Manifestation of Acute Pyelonephritis
by
Yu-Yun Chang and Kuei-Hong Kuo
Diagnostics 2024, 14(6), 638; https://doi.org/10.3390/diagnostics14060638 - 18 Mar 2024
Abstract
Acute pyelonephritis is a common infection of the upper urinary tract that affects approximately 250,000 adults in the United States. Individuals with acute pyelonephritis require hospitalization and intravenous antimicrobial therapy. Diagnoses of acute pyelonephritis are made on the basis of clinical and laboratory
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Acute pyelonephritis is a common infection of the upper urinary tract that affects approximately 250,000 adults in the United States. Individuals with acute pyelonephritis require hospitalization and intravenous antimicrobial therapy. Diagnoses of acute pyelonephritis are made on the basis of clinical and laboratory findings. Individuals with complex or severe acute pyelonephritis undergo contrast-enhanced computed tomography (CT) for the diagnosis and assessment of perirenal abnormalities. However, extrarenal manifestations, such as periportal edema and gallbladder wall thickening, may complicate the diagnostic process. We report the case of a 42-year-old woman who presented with fever, dysuria, and flank pain—the hallmarks of urosepsis. CT results confirmed acute pyelonephritis accompanied by periportal edema and elevated levels of hepatic enzymes and C-reactive protein. Despite antibiotic intervention, febrile episodes persisted for 4 days and abated over a fortnight. The patient’s blood and urine cultures yielded negative results, which may be attributed to her prior antimicrobial treatment. Recognition of extrarenal signs in acute pyelonephritis is crucial for obtaining accurate diagnoses and understanding their clinical implications.
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(This article belongs to the Special Issue Diagnosis and Management in Emergency Medicine)
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Calcinosis in Rheumatic Disease Is Still an Unmet Need: A Retrospective Single-Center Study
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Cristina Nita, Laura Groseanu, Daniela Opris, Denisa Predeteanu, Violeta Bojinca, Florian Berghea, Violeta Vlad, Mihai Abobului, Cosmin Constantinescu, Magdalena Negru, Ioana Saulescu, Sanziana Daia, Diana Mazilu, Andreea Borangiu, Claudia Cobilinschi, Denisse Mardale, Madalina Rosu and Andra Balanescu
Diagnostics 2024, 14(6), 637; https://doi.org/10.3390/diagnostics14060637 - 18 Mar 2024
Abstract
Patients with immune-mediated rheumatic disease-related calcinosis comprise a subgroup at risk of encountering a more severe clinical outcome. Early assessment is pivotal for preventing overall disease progression, as calcinosis is commonly overlooked until several years into the disease and is considered as a
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Patients with immune-mediated rheumatic disease-related calcinosis comprise a subgroup at risk of encountering a more severe clinical outcome. Early assessment is pivotal for preventing overall disease progression, as calcinosis is commonly overlooked until several years into the disease and is considered as a ‘non-lethal’ manifestation. This single-center retrospective study explored the prevalence, clinical associations, and impact on survival of subcutaneous calcinosis in 86 patients with immune-mediated rheumatic diseases (IMRD). Calcinosis predominantly appeared in individuals with longstanding disease, particularly systemic sclerosis (SSc), constituting 74% of cases. Smaller calcinosis lesions (≤1 cm) were associated with interstitial lung disease, musculoskeletal involvement, and digital ulcerations, while larger lesions (≥4 cm) were associated with malignancy, severe peripheral artery disease, and systemic arterial hypertension. The SSc calcinosis subgroup exhibited a higher mean adjusted European Scleroderma Study Group Activity Index score than those without. However, survival rates did not significantly differ between the two groups. Diltiazem was the most commonly used treatment, and while bisphosphonates reduced complications related to calcinosis, complete resolution was not achieved. The findings underscore current limitations in diagnosing, monitoring, and treating calcinosis, emphasizing the need for further research and improved therapeutic strategies to improve patient care and outcomes.
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(This article belongs to the Section Pathology and Molecular Diagnostics)
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An Improved Skin Lesion Classification Using a Hybrid Approach with Active Contour Snake Model and Lightweight Attention-Guided Capsule Networks
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Kavita Behara, Ernest Bhero and John Terhile Agee
Diagnostics 2024, 14(6), 636; https://doi.org/10.3390/diagnostics14060636 - 17 Mar 2024
Abstract
Skin cancer is a prevalent type of malignancy on a global scale, and the early and accurate diagnosis of this condition is of utmost importance for the survival of patients. The clinical assessment of cutaneous lesions is a crucial aspect of medical practice,
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Skin cancer is a prevalent type of malignancy on a global scale, and the early and accurate diagnosis of this condition is of utmost importance for the survival of patients. The clinical assessment of cutaneous lesions is a crucial aspect of medical practice, although it encounters several obstacles, such as prolonged waiting time and misinterpretation. The intricate nature of skin lesions, coupled with variations in appearance and texture, presents substantial barriers to accurate classification. As such, skilled clinicians often struggle to differentiate benign moles from early malignant tumors in skin images. Although deep learning-based approaches such as convolution neural networks have made significant improvements, their stability and generalization continue to experience difficulties, and their performance in accurately delineating lesion borders, capturing refined spatial connections among features, and using contextual information for classification is suboptimal. To address these limitations, we propose a novel approach for skin lesion classification that combines snake models of active contour (AC) segmentation, ResNet50 for feature extraction, and a capsule network with a fusion of lightweight attention mechanisms to attain the different feature channels and spatial regions within feature maps, enhance the feature discrimination, and improve accuracy. We employed the stochastic gradient descent (SGD) optimization algorithm to optimize the model’s parameters. The proposed model is implemented on publicly available datasets, namely, HAM10000 and ISIC 2020. The experimental results showed that the proposed model achieved an accuracy of 98% and AUC-ROC of 97.3%, showcasing substantial potential in terms of effective model generalization compared to existing state-of-the-art (SOTA) approaches. These results highlight the potential for our approach to reshape automated dermatological diagnosis and provide a helpful tool for medical practitioners.
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(This article belongs to the Special Issue Advances in Diagnosis of Skin and Superficial Tissues Disorders—“Old and Emerging” Diagnostic Tools)
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Exploring PGE2 and LXA4 Levels in Migraine Patients: The Potential of LXA4-Based Therapies
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Idris Kocaturk, Sedat Gulten, Bunyamin Ece and Fatma Mutlu Kukul Guven
Diagnostics 2024, 14(6), 635; https://doi.org/10.3390/diagnostics14060635 - 17 Mar 2024
Abstract
Neurogenic inflammation plays a significant role in the pathogenesis of migraines. This study aimed to investigate the serum levels of prostaglandin E2 (PGE2), lipoxin A4 (LXA4), and other inflammatory biomarkers (C-reactive protein, fibrinogen) in migraine patients. In total, 53 migraine patients and 53
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Neurogenic inflammation plays a significant role in the pathogenesis of migraines. This study aimed to investigate the serum levels of prostaglandin E2 (PGE2), lipoxin A4 (LXA4), and other inflammatory biomarkers (C-reactive protein, fibrinogen) in migraine patients. In total, 53 migraine patients and 53 healthy controls were evaluated. Blood serum samples were collected during both attack and interictal periods and compared with the control group. In both the attack and interictal periods, PGE2 and LXA4 values were significantly lower in migraine patients compared to the control group (p < 0.001). Additionally, PGE2 values during the attack period were significantly higher than those during the interictal period (p = 0.016). Patients experiencing migraine attacks lasting ≥ 12 h had significantly lower serum PGE2 and LXA4 levels compared to those with attacks lasting < 12 h (p = 0.028 and p = 0.009, respectively). In ROC analysis, cut-off values of 332.7 pg/mL for PGE2 and 27.2 ng/mL for LXA4 were determined with 70–80% sensitivity and specificity. In conclusion, PGE2 and LXA4 levels are significantly lower in migraine patients during both interictal and attack periods. Additionally, the levels of LXA4 and PGE2 decrease more with the prolongation of migraine attack duration. Our findings provide a basis for future treatment planning.
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(This article belongs to the Special Issue Clinical Prognostic and Predictive Biomarkers—2nd Edition)
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Pan-Immune-Inflammation Value Could Be a New Marker to Predict Amyloidosis and Disease Severity in Familial Mediterranean Fever
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Tuğba Ocak, Ahmet Görünen, Belkıs Nihan Coşkun, Burcu Yağız, Sebnem Ozemri Sağ, Gökhan Ocakoğlu, Ediz Dalkılıç and Yavuz Pehlivan
Diagnostics 2024, 14(6), 634; https://doi.org/10.3390/diagnostics14060634 - 16 Mar 2024
Abstract
Familial Mediterranean fever (FMF) is characterized by recurrent episodes of fever and serositis. Blood-based biomarkers determined in FMF patients during attack-free periods could be used to predict the risk of amyloidosis and the severity of the disease. The recently defined pan-immune-inflammation value (PIV)
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Familial Mediterranean fever (FMF) is characterized by recurrent episodes of fever and serositis. Blood-based biomarkers determined in FMF patients during attack-free periods could be used to predict the risk of amyloidosis and the severity of the disease. The recently defined pan-immune-inflammation value (PIV) comprises four distinct subsets of blood cells and serves as an easily accessible and cost-effective marker. The objective of this study was to assess the role of PIV in predicting amyloidosis and moderate-to-severe disease. Clinical characteristics and laboratory values during the attack-free period were retrospectively analyzed in 321 patients over 18 years of age diagnosed with familial Mediterranean fever (FMF). In our tertiary adult rheumatology outpatient clinic, disease severity and laboratory markers were evaluated during the first attack-free interval. At baseline, patients with amyloidosis were excluded. Patients were categorized based on the presence of amyloidosis and the severity of the disease. When focusing on amyloidosis in receiver operating characteristic (ROC) analysis, optimal cut-off values for pan-immune-inflammation value (PIV), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio were determined as ≥518.1, ≥2.3, and ≥127.2, respectively. In multivariate analysis, PIV, C-reactive protein (CRP), and the presence of the M694V homozygous mutation emerged as independent risk factors for both amyloidosis and moderate-to-severe disease. Additionally, NLR was identified as an independent risk factor for amyloidosis, while red blood cell distribution width was associated with moderate-to-severe disease. In patients with FMF, especially in the presence of the M694V homozygous mutation, CRP and PIV may be useful in predicting both amyloidosis and moderate-to-severe disease.
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(This article belongs to the Special Issue A Useful Diagnostic Method: Blood Test)
Open AccessArticle
A Web-Based Dynamic Nomogram to Predict the Risk of Methicillin-Resistant Staphylococcal Infection in Patients with Pneumonia
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Van Duong-Thi-Thanh, Binh Truong-Quang, Phu Tran-Nguyen-Trong, Mai Le-Phuong, Phu Truong-Thien, Dung Lam-Quoc, Thong Dang-Vu, Minh-Loi Nguyen and Vu Le-Thuong
Diagnostics 2024, 14(6), 633; https://doi.org/10.3390/diagnostics14060633 - 16 Mar 2024
Abstract
The aim of this study was to create a dynamic web-based tool to predict the risks of methicillin-resistant Staphylococcus spp. (MRS) infection in patients with pneumonia. We conducted an observational study of patients with pneumonia at Cho Ray Hospital from March 2021 to
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The aim of this study was to create a dynamic web-based tool to predict the risks of methicillin-resistant Staphylococcus spp. (MRS) infection in patients with pneumonia. We conducted an observational study of patients with pneumonia at Cho Ray Hospital from March 2021 to March 2023. The Bayesian model averaging method and stepwise selection were applied to identify different sets of independent predictors. The final model was internally validated using the bootstrap method. We used receiver operator characteristic (ROC) curve, calibration, and decision curve analyses to assess the nomogram model’s predictive performance. Based on the American Thoracic Society, British Thoracic Society recommendations, and our data, we developed a model with significant risk factors, including tracheostomies or endotracheal tubes, skin infections, pleural effusions, and pneumatoceles, and used 0.3 as the optimal cut-off point. ROC curve analysis indicated an area under the curve of 0.7 (0.63–0.77) in the dataset and 0.71 (0.64–0.78) in 1000 bootstrap samples, with sensitivities of 92.39% and 91.11%, respectively. Calibration analysis demonstrated good agreement between the observed and predicted probability curves. When the threshold is above 0.3, we recommend empiric antibiotic therapy for MRS. The web-based dynamic interface also makes our model easier to use.
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(This article belongs to the Special Issue Artificial Intelligence Applications in the Diagnosis and Prevention of Hospital-Acquired Infections)
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Automatic Active Lesion Tracking in Multiple Sclerosis Using Unsupervised Machine Learning
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Jason Uwaeze, Ponnada A. Narayana, Arash Kamali, Vladimir Braverman, Michael A. Jacobs and Alireza Akhbardeh
Diagnostics 2024, 14(6), 632; https://doi.org/10.3390/diagnostics14060632 (registering DOI) - 16 Mar 2024
Abstract
Background: Identifying active lesions in magnetic resonance imaging (MRI) is crucial for the diagnosis and treatment planning of multiple sclerosis (MS). Active lesions on MRI are identified following the administration of Gadolinium-based contrast agents (GBCAs). However, recent studies have reported that repeated administration
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Background: Identifying active lesions in magnetic resonance imaging (MRI) is crucial for the diagnosis and treatment planning of multiple sclerosis (MS). Active lesions on MRI are identified following the administration of Gadolinium-based contrast agents (GBCAs). However, recent studies have reported that repeated administration of GBCA results in the accumulation of Gd in tissues. In addition, GBCA administration increases health care costs. Thus, reducing or eliminating GBCA administration for active lesion detection is important for improved patient safety and reduced healthcare costs. Current state-of-the-art methods for identifying active lesions in brain MRI without GBCA administration utilize data-intensive deep learning methods. Objective: To implement nonlinear dimensionality reduction (NLDR) methods, locally linear embedding (LLE) and isometric feature mapping (Isomap), which are less data-intensive, for automatically identifying active lesions on brain MRI in MS patients, without the administration of contrast agents. Materials and Methods: Fluid-attenuated inversion recovery (FLAIR), T2-weighted, proton density-weighted, and pre- and post-contrast T1-weighted images were included in the multiparametric MRI dataset used in this study. Subtracted pre- and post-contrast T1-weighted images were labeled by experts as active lesions (ground truth). Unsupervised methods, LLE and Isomap, were used to reconstruct multiparametric brain MR images into a single embedded image. Active lesions were identified on the embedded images and compared with ground truth lesions. The performance of NLDR methods was evaluated by calculating the Dice similarity (DS) index between the observed and identified active lesions in embedded images. Results: LLE and Isomap, were applied to 40 MS patients, achieving median DS scores of 0.74 ± 0.1 and 0.78 ± 0.09, respectively, outperforming current state-of-the-art methods. Conclusions: NLDR methods, Isomap and LLE, are viable options for the identification of active MS lesions on non-contrast images, and potentially could be used as a clinical decision tool.
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(This article belongs to the Topic AI in Medical Imaging and Image Processing)
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Open AccessReview
The Role and Value of Professional Rapid Testing of Acute Respiratory Infections (ARIs) in Europe: A Special Focus on the Czech Republic, Poland, and Romania
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Pavel Drevinek, Robert Flisiak, Roxana Nemes, Katya A. Nogales Crespo and Krzysztof Tomasiewicz
Diagnostics 2024, 14(6), 631; https://doi.org/10.3390/diagnostics14060631 - 16 Mar 2024
Abstract
This review aims to explore the role of professional diagnostic rapid testing of acute respiratory infections (ARIs), especially COVID-19 and influenza, ensuring proper disease management and treatment in Europe, and particularly in Czech Republic, Poland, and Romania. The paper was constructed based on
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This review aims to explore the role of professional diagnostic rapid testing of acute respiratory infections (ARIs), especially COVID-19 and influenza, ensuring proper disease management and treatment in Europe, and particularly in Czech Republic, Poland, and Romania. The paper was constructed based on a review of scientific evidence and national and international policies and recommendations, as well as a process of validation by four experts. The development of new testing technologies, treatment options, and increased awareness of the negative multidimensional impact of ARI profiles transformed differential diagnosis into a tangible and desirable reality. This review covers the following topics: (1) the multidimensional impact of ARIs, (2) ARI rapid diagnostic testing platforms and their value, (3) the policy landscape, (4) challenges and barriers to implementation, and (5) a set of recommendations illustrating a path forward. The findings indicate that rapid diagnostic testing, including at the point of care (POC), can have a positive impact on case management, antimicrobial and antibiotic stewardship, epidemiological surveillance, and decision making. Integrating this strategy will require the commitment of governments and the international and academic communities, especially as we identified room for improvement in the access and expansion of POC rapid testing in the focus countries and the inclusion of rapid testing in relevant policies.
Full article
(This article belongs to the Special Issue Microbiology Laboratory: Sample Collection and Diagnosis Advances)
Open AccessArticle
Optimization of Traction Magnetic Resonance Imaging to Improve Visibility of the Elbow Cartilage
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Sho Kohyama, Kazuhiro Ikeda, Yoshikazu Okamoto, Naoyuki Ochiai and Yuichi Yoshii
Diagnostics 2024, 14(6), 630; https://doi.org/10.3390/diagnostics14060630 - 16 Mar 2024
Abstract
We previously reported that elbow magnetic resonance imaging (MRI) with 7 kg traction increases the joint space width of the radiocapitellar joint and improves articular cartilage visibility without arthrography. However, the optimal traction weight remains unclear. We assessed the effects of different traction
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We previously reported that elbow magnetic resonance imaging (MRI) with 7 kg traction increases the joint space width of the radiocapitellar joint and improves articular cartilage visibility without arthrography. However, the optimal traction weight remains unclear. We assessed the effects of different traction weights on elbow MRI in 30 healthy volunteers. Elbow MRI was performed without traction and with 3, 5, and 7 kg axial tractions. The joint space width, humeral articular cartilage outline visibility, and intraprocedural pain/discomfort were evaluated. The joint and cartilage parameters were measured at the radiocapitellar joint and the lateral and medial thirds of the ulnohumeral joint. At the radiocapitellar joint, the joint space width increased significantly with traction. The cartilage outline visibility significantly increased with traction, with no significant differences among the traction weights. No significant result was observed at the lateral and medial thirds of the ulnohumeral joint. Pain and discomfort significantly increased as we used heavier traction weights. Elbow MRI with 3 kg traction showed sufficient effects similar to those observed with 7 kg traction with minimal pain and discomfort. There was no difference in the effect of traction between male and female participants. This procedure may enable enhanced visualization of intra-articular elbow injuries.
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(This article belongs to the Special Issue Diagnosis and Management of Musculoskeletal Disorders)
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Innovative Strategies for Early Autism Diagnosis: Active Learning and Domain Adaptation Optimization
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Mohammad Shafiul Alam, Elfatih A. A. Elsheikh, F. M. Suliman, Muhammad Mahbubur Rashid and Ahmed Rimaz Faizabadi
Diagnostics 2024, 14(6), 629; https://doi.org/10.3390/diagnostics14060629 - 16 Mar 2024
Abstract
The early diagnosis of autism spectrum disorder (ASD) encounters challenges stemming from domain variations in facial image datasets. This study investigates the potential of active learning, particularly uncertainty-based sampling, for domain adaptation in early ASD diagnosis. Our focus is on improving model performance
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The early diagnosis of autism spectrum disorder (ASD) encounters challenges stemming from domain variations in facial image datasets. This study investigates the potential of active learning, particularly uncertainty-based sampling, for domain adaptation in early ASD diagnosis. Our focus is on improving model performance across diverse data sources. Utilizing the Kaggle ASD and YTUIA datasets, we meticulously analyze domain variations and assess transfer learning and active learning methodologies. Two state-of-the-art convolutional neural networks, Xception and ResNet50V2, pretrained on distinct datasets, demonstrate noteworthy accuracies of 95% on Kaggle ASD and 96% on YTUIA, respectively. However, combining datasets results in a modest decline in average accuracy, underscoring the necessity for effective domain adaptation techniques. We employ uncertainty-based active learning to address this, which significantly mitigates the accuracy drop. Xception and ResNet50V2 achieve 80% and 79% accuracy when pretrained on Kaggle ASD and applying active learning on YTUIA, respectively. Our findings highlight the efficacy of uncertainty-based active learning for domain adaptation, showcasing its potential to enhance accuracy and reduce annotation needs in early ASD diagnosis. This study contributes to the growing body of literature on ASD diagnosis methodologies. Future research should delve deeper into refining active learning strategies, ultimately paving the way for more robust and efficient ASD detection tools across diverse datasets.
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(This article belongs to the Special Issue Artificial Intelligence and Pattern Recognition Methods for the Automatic Detection and Evaluation of Neurological Disorders)
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Open AccessCase Report
A Rare Case of Dirofilariasis in the Genian Region
by
Andrei Nicolau, Florin Petrică Sava, Florentina Severin, Mihai Liviu Ciofu, Dan Ferariu, Daniela Dodu and Victor Vlad Costan
Diagnostics 2024, 14(6), 628; https://doi.org/10.3390/diagnostics14060628 - 15 Mar 2024
Abstract
Dirofilariasis is an infectious disease caused by species of the Dirofilaria genus. It is manifested by the appearance of a subcutaneous swelling, especially in the eye region. We present the case of a 29-year-old patient who presented with facial asymmetry in the right
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Dirofilariasis is an infectious disease caused by species of the Dirofilaria genus. It is manifested by the appearance of a subcutaneous swelling, especially in the eye region. We present the case of a 29-year-old patient who presented with facial asymmetry in the right genian region. Following clinical and paraclinical evaluations, the diagnosis of a parasitic cyst was established in the context of dirofilariasis with Dirofilaria repens (D. repens). Treatment consisted of surgical excision of the formation associated with prophylactic antibiotic medication. Macroscopic analysis of the excision piece revealed a structure that contained a cystic cavity and a filamentous form with a length of approximately 10 mm and a diameter of 1 mm. This is the first case of dirofilariasis located in the genian region reported in Romania. The overview of this pathology is important to raise awareness among physicians about its presence and clinical variations. Understanding such cases helps healthcare professionals enhance diagnostic skills, refine treatment strategies, and provide valuable insights into the prevalence and clinical presentation, fostering early detection and timely intervention. Detailed case reports contribute to the understanding of the disease’s epidemiology, including risk factors and transmission patterns, which is essential for effective public health strategies.
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(This article belongs to the Special Issue Advances in the Diagnosis of Infectious Diseases and Microorganisms)
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Open AccessArticle
Optimizing Arterial Vessel Contrast in Portal Venous Phase with Virtual Monoenergetic Images from Photon-Counting Detector CT Scans of the Abdomen—First Clinical Experiences
by
Daniel Dillinger, Daniel Overhoff, Isabelle Ayx, Hanns L. Kaatsch, Achim Hagen, Stefan O. Schönberg and Stephan Waldeck
Diagnostics 2024, 14(6), 627; https://doi.org/10.3390/diagnostics14060627 - 15 Mar 2024
Abstract
Background: Photon-counting detector (PCD) computed tomography (CT) allows for the reconstruction of virtual monoenergetic images (VMI) at different thresholds. Objective: The aim of our study was to evaluate the optimal arterial contrast in portal venous (pv) scans regarding objective parameters and subjective image
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Background: Photon-counting detector (PCD) computed tomography (CT) allows for the reconstruction of virtual monoenergetic images (VMI) at different thresholds. Objective: The aim of our study was to evaluate the optimal arterial contrast in portal venous (pv) scans regarding objective parameters and subjective image quality for different virtual keV levels. Methods: We identified 40 patients that underwent a CT scan with an arterial and pv phase on a PCD-CT (NAEOTOM alpha, Siemens Healthineers, Forchheim, Germany). The attenuation of abdominal arteries on pv phases was measured for different virtual keV levels in a monoenergetic+ application profile and for polychromatic (pc) arterial images. Two independent readers assessed subjective image quality, including vascular contrast in pv scans at different energy levels. Additionally, signal- and contrast-to-noise ratios (SNR and CNR) were measured. Results: Our results showed increasing arterial attenuation levels with decreasing energy levels in virtual monoenergetic imaging on pv scans with the highest attenuation at 40 keV, significantly higher than in the pc arterial phase (439 ± 97 HU vs. 360 ± 97, p < 0.001). Noise, SNR, and CNR were worse at this energy level (p < 0.001). Pv VMI showed less noise at energy levels above 70 keV (all p < 0.001). Subjective image quality was rated best at 70 keV, vascular contrast was best at 40 keV. Conclusions: Our research suggests that virtual monoenergetic images at 40 keV in Mono+ mode derived from a PCD-CT can be a feasible alternative to a true arterial phase for assessment of vessels with worse CNR and SNR.
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(This article belongs to the Special Issue New Insights in Cardiovascular Imaging: 2023)
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Photon-Counting Detector CT Virtual Monoenergetic Images in Cervical Trauma Imaging—Optimization of Dental Metal Artifacts and Image Quality
by
Daniel Dillinger, Daniel Overhoff, Matthias F. Froelich, Hanns L. Kaatsch, Christian Booz, Achim Hagen, Thomas J. Vogl, Stefan O. Schönberg and Stephan Waldeck
Diagnostics 2024, 14(6), 626; https://doi.org/10.3390/diagnostics14060626 - 15 Mar 2024
Abstract
Objectives: The aim of this study was to analyze the extent of dental metal artifacts in virtual monoenergetic (VME) images, as they often compromise image quality by obscuring soft tissue affecting vascular attenuation reducing sensitivity in the detection of dissections. Methods: Neck photon-counting
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Objectives: The aim of this study was to analyze the extent of dental metal artifacts in virtual monoenergetic (VME) images, as they often compromise image quality by obscuring soft tissue affecting vascular attenuation reducing sensitivity in the detection of dissections. Methods: Neck photon-counting CT datasets of 50 patients undergoing contrast-enhanced trauma CT were analyzed. Hyperattenuation and hypoattenuation artifacts, muscle with and without artifacts and vessels with and without artifacts were measured at energy levels from 40 keV to 190 keV. The corrected artifact burden, corrected image noise and artifact index were calculated. We also assessed subjective image quality on a Likert-scale. Results: Our study showed a lower artifact burden and less noise in artifact-affected areas above the energy levels of 70 keV for hyperattenuation artifacts (conventional polychromatic CT images 1123 ± 625 HU vs. 70 keV VME 1089 ± 733 HU, p = 0.125) and above of 80 keV for hypoattenuation artifacts (conventional CT images −1166 ± 779 HU vs. 80 keV VME −1170 ± 851 HU, p = 0.927). Vascular structures were less hampered by metal artifacts than muscles (e.g., corrected artifact burden at 40 keV muscle 158 ± 125 HU vs. vessels −63 ± 158 HU p < 0.001), which was also reflected in the subjective image assessment, which showed better ratings at higher keV values and overall better ratings for vascular structures than for the overall artifact burden. Conclusions: Our research suggests 70 keV might be the best compromise for reducing metal artifacts affecting vascular structures and preventing vascular contrast if solely using VME reconstructions. VME imaging shows only significant effects on the general artifact burden. Vascular structures generally experience fewer metal artifacts than soft tissue due to their greater distance from the teeth, which are a common source of such artifacts.
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(This article belongs to the Special Issue Diagnosis and Management in Emergency Medicine)
Open AccessArticle
Machine Learning-Based Algorithms for Enhanced Prediction of Local Recurrence and Metastasis in Low Rectal Adenocarcinoma Using Imaging, Surgical, and Pathological Data
by
Cristian-Constantin Volovat, Dragos-Viorel Scripcariu, Diana Boboc, Simona-Ruxandra Volovat, Ingrid-Andrada Vasilache, Corina Ursulescu-Lupascu, Liliana Gheorghe, Luiza-Maria Baean, Constantin Volovat and Viorel Scripcariu
Diagnostics 2024, 14(6), 625; https://doi.org/10.3390/diagnostics14060625 - 15 Mar 2024
Abstract
(1) Background: Numerous variables could influence the risk of rectal cancer recurrence or metastasis, and machine learning (ML)-based algorithms can help us refine the risk stratification process of these patients and choose the best therapeutic approach. The aim of this study was to
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(1) Background: Numerous variables could influence the risk of rectal cancer recurrence or metastasis, and machine learning (ML)-based algorithms can help us refine the risk stratification process of these patients and choose the best therapeutic approach. The aim of this study was to assess the predictive performance of 4 ML-based models for the prediction of local recurrence or distant metastasis in patients with locally advanced low rectal adenocarcinomas who underwent neoadjuvant chemoradiotherapy and surgical treatment; (2) Methods: Patients who were admitted at the first Oncologic Surgical Clinic from the Regional Institute of Oncology, Iasi, Romania were retrospectively included in this study between November 2019 and July 2023. Decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF) were used to analyze imagistic, surgical, and pathological data retrieved from the medical files, and their predictive performance was assessed; (3) Results: The best predictive performance was achieved by RF when used to predict disease recurrence (accuracy: 90.85%) or distant metastasis (accuracy: 89.63%). RF was closely followed by SVM (accuracy for recurrence 87.8%; accuracy for metastasis: 87.2%) in terms of predictive performance. NB and DT achieved moderate predictive power for the evaluated outcomes; (4) Conclusions: Complex algorithms such as RF and SVM could be useful for improving the prediction of adverse oncological outcomes in patients with low rectal adenocarcinoma.
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(This article belongs to the Special Issue Abdominal Diseases: Diagnosis, Treatment and Management)
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DengueFog: A Fog Computing-Enabled Weighted Random Forest-Based Smart Health Monitoring System for Automatic Dengue Prediction
by
Ashima Kukkar, Yugal Kumar, Jasminder Kaur Sandhu, Manjit Kaur, Tarandeep Singh Walia and Mohammed Amoon
Diagnostics 2024, 14(6), 624; https://doi.org/10.3390/diagnostics14060624 - 15 Mar 2024
Abstract
Dengue is a distinctive and fatal infectious disease that spreads through female mosquitoes called Aedes aegypti. It is a notable concern for developing countries due to its low diagnosis rate. Dengue has the most astounding mortality level as compared to other diseases due
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Dengue is a distinctive and fatal infectious disease that spreads through female mosquitoes called Aedes aegypti. It is a notable concern for developing countries due to its low diagnosis rate. Dengue has the most astounding mortality level as compared to other diseases due to tremendous platelet depletion. Hence, it can be categorized as a life-threatening fever as compared to the same class of fevers. Additionally, it has been shown that dengue fever shares many of the same symptoms as other flu-based fevers. On the other hand, the research community is closely monitoring the popular research fields related to IoT, fog, and cloud computing for the diagnosis and prediction of diseases. IoT, fog, and cloud-based technologies are used for constructing a number of health care systems. Accordingly, in this study, a DengueFog monitoring system was created based on fog computing for prediction and detection of dengue sickness. Additionally, the proposed DengueFog system includes a weighted random forest (WRF) classifier to monitor and predict the dengue infection. The proposed system’s efficacy was evaluated using data on dengue infection. This dataset was gathered between 2016 and 2018 from several hospitals in the Delhi-NCR region. The accuracy, F-value, recall, precision, error rate, and specificity metrics were used to assess the simulation results of the suggested monitoring system. It was demonstrated that the proposed DengueFog monitoring system with WRF outperforms the traditional classifiers.
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(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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