ISSN / EISSN : 2075-4418 / 2075-4418
Published by: MDPI (10.3390)
Total articles ≅ 5,469
Latest articles in this journal
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071560
Background: Methotrexate (MTX) is one of the most common medications used for rheumatoid arthritis (RA) treatment. Single-nucleotide polymorphisms (SNPs) could potentially predict variability in therapeutic outcomes. Aim: This study aims to assess the impact of SNPs in genes encoding for the MTX pathway for predicting clinical and therapeutic responses to MTX in a cohort of Egyptian patients with RA. Subjects and Methods: Data from 107 Egyptian RA patients (aged 44.4 ± 11.4 years) treated with MTX monotherapy, for a duration of 3.7 ± 3.3 years, were collected. Genotypes of 10 SNPs from four different genes were analyzed using the allelic discrimination PCR technique. Results: The ATIC rs3821353 G/T (p = 0.034) and the C/T and C/C of SLC19A1 rs7279445 (p = 0.0018) were associated with a non-response to MTX, while DHFR rs10072026 C/T and C/C were associated with a good response (p < 0.001). Carriers of the ATIC rs382135 3 G (p = 0.001) and ATIC rs4673990 G (p < 0.001) alleles were more likely to develop RA, while the SLC19A1 rs11702425 T (p < 0.001) and GGH rs12681874 T (p = 0.003) allele carriers were more likely to be protected against RA. Carriers of the ATIC rs4673990 A/G genotype (p < 0.001) were at risk of developing RA, while carriers of the following genotypes were mostly protected against RA: ATIC rs3821353 T/T (p < 0.001), ATIC rs3821353 G/G (p = 0.004), SLC19A1 rs11702425 T/T (p = 0.001), SLC19A1 rs11702425 C/T (p = 0.003), GGH rs12681874 C/T (p = 0.004) and GGH rs12681874 T/T (0.002). Conclusion: The genotyping of genes involved in the MTX pathway may be helpful to predict which RA patients will/will not benefit from MTX, and thus, may help to apply a personalized medicine approach in RA.
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071562
We aimed to build a deep learning-based, objective, fast, and accurate collateral circulation assessment model. We included 92 patients who had suffered acute ischemic stroke (AIS) with large vessel occlusion in the anterior circulation in this study, following their admission to our hospital from June 2020 to August 2021. We analyzed their baseline whole-brain four-dimensional computed tomography angiography (4D-CTA)/CT perfusion. The images of the arterial, arteriovenous, venous, and late venous phases were extracted from 4D-CTA according to the perfusion time–density curve. The subtraction images of each phase were created by subtracting the non-contrast CT. Each patient was marked as having good or poor collateral circulation. Based on the ResNet34 classification network, we developed a single-image input and a multi-image input network for binary classification of collateral circulation. The training and test sets included 65 and 27 patients, respectively, and Monte Carlo cross-validation was employed for five iterations. The network performance was evaluated based on its precision, accuracy, recall, F1-score, and AUC. All the five performance indicators of the single-image input model were higher than those of the other model. The single-image input processing network, combining multiphase CTA images, can better classify AIS collateral circulation. This automated collateral assessment tool could help to streamline clinical workflows, and screen patients for reperfusion therapy.
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071558
The Heidenhain Variant of Creutzfeldt–Jakob disease (CJD) is an uncommon early clinical syndrome of the otherwise regular sporadic CJD, which belongs to the group of prion diseases caused by a transmissible agent, the misfolded form of the prion protein. The most characteristic symptoms of CJD are rapidly progressive cognitive impairment, typical motor manifestations and mental and behavioural changes. Conversely, in the Heidenhain Variant, different kinds of visual disturbances are observed at onset due to microvacuolar spongiform degeneration or, less frequently, confluent spongiform changes in the parieto-occipital area, detectable through brain MRI with hyperintensity in T2-FLAIR or DWI in the same areas. Since this an extremely rare condition with a heterogeneous clinical presentation, it may easily be misdiagnosed with other diseases at the earlier stages. Here, we describe the case of a patient initially diagnosed with posterior reversible encephalopathy syndrome (PRES), presenting with visual disturbances and headache at onset in a context of poorly controlled arterial hypertension. Subsequently, a rapid worsening of cognitive decline, associated with myoclonus and startle reaction led to further investigations, shifting the diagnosis toward a rapidly evolving neurodegenerative form. This hypothesis was also supported by EEG traces, MRI and CSF analysis. Finally, the clinical–instrumental evolution confirmed the diagnosis of Heidenhain Variant of CJD.
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071563
Diagnosis of pelvic gastrointestinal stromal tumors (GISTs) can be challenging because of their nonspecific presentation and similarity to gynecological neoplasms. In this series, we describe the clinicopathological features of 20 GIST cases: 18 patients presented with pelvic mass and/or abdominal pain concerning gynecological disease; 2 patients presented with a posterior rectovaginal mass or an anorectal mass. Total abdominal hysterectomy and/or salpingo-oophorectomy (unilateral or bilateral) were performed in 13 cases. Gross and histological examination revealed that the ovary/ovaries were involved in three cases, the uterus in two cases, the vagina in two cases and the broad ligament in one case. Immunohistochemically, all tumors (20/20, 100%) were diffusely immunoreactive for c-KIT. The tumor cells were also diffusely positive for DOG-1 (10/10, 100%) and displayed focal to diffuse positivity for CD34 (11/12, 92%). Desmin was focally and weakly expressed in 1 of the 14 tested tumors (1/14, 7%), whereas 2 of 8 tumors (2/8, 25%) showed focal SMA positivity. At the molecular level, 7 of 8 (87.5%) GISTs with molecular analysis contained c-KIT mutations with the second and third c-KIT mutations detected in some recurrent tumors. In addition to c-KIT mutation, a pathogenic RB1 mutation was detected in two cases. We extensively discussed these cases focusing on their differential diagnosis described by the submitting pathologists during consultation. Our study emphasizes the importance of precision diagnosis of GISTs. Alertness to this entity in unusual locations, in combination with clinical history, morphological features as well as immunophenotype, is crucial in leading to a definitive classification.
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071559
Thrombocytopenic purpura (TTP) is a rare, potentially fatal pathology characterized by microangiopathic thrombotic syndrome and caused by an acute protease deficiency of von Willebrand factor, ADAMTS13. Moreover, ADAMTS13 deficiency promotes microthrombosis led by the persistence of ultra-large VWF multimers in the blood circulation. According to the few studies involving pregnant participants, the heterogeneity of manifestations has made this pathology difficult to diagnose, with an unexpected occurrence and increased risk of maternal and fetal morbidity and mortality. We reported on the case of a 28-year-old pregnant woman with an obstetric score of G2P0 who presented to the obstetrics and gynecology department of our clinic with the complaint of minimal vaginal bleeding. The evolution of our case was severe and life-threatening, a “race against the clock”, with our goal being to emphasize the importance and difficulty of diagnosing TTP in the absence of specific symptomatology. We faced a lack of technological support for a correct and complete diagnosis, and the first manifestation of this disease was the intrauterine death of the fetus. After completing all the necessary procedures, the placental tissue was sent for further histopathological evaluation. We highlighted the importance of monitoring ADAMTS13 for relapses monthly, with prophylaxis being essential for maternal and fetal mortality and morbidity.
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071561
Background: Rapid diagnosis of COVID-19 is essential in order to restrict the spread of the pandemic, and different approaches for SARS-CoV-2 testing have been proposed as cost-effective and less time-consuming alternatives. For virus detection, the real-time reverse transcriptase–polymerase chain reaction (RT-PCR) technique is still the “gold standard” for accuracy and reliability, but its performance is affected by the efficiency of nucleic acid extraction methods. Objective: In order to improve the SARS-CoV-2 diagnostic workflow, we compared a “standard” commercially available kit, based on viral RNA extraction from human swab samples by magnetic beads, with its technological evolution. The two methods differ mainly in their time consumption (9 vs. 35 min). Methods: We adopted the MAGABIO PLUS VIRUS DNA/RNA PURIFICATION KIT II (BIOER), defined as “standard”, with the automatic extractor BIOER (GenePure Pro fully automatic nucleic acid purification system) to isolate RNA from nasopharyngeal swabs for the detection of SARS-CoV-2 by RT-PCR. We tested this kit with a new faster version of the first one, defined as “rapid” (MAGABIO PLUS VIRUS RNA PURIFICATION KIT II). Results and Conclusion: The two evaluated procedures provided similar analytical results, but the faster method proved to be a more suitable tool for the detection of SARS-CoV-2 from nasopharyngeal swabs, due to a more rapid availability of results, which may contribute to improving both clinical decision making and patient safety.
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071555
The novel mRNA vaccinations against COVID-19 are gaining worldwide attention for their efficacy, as well as the diagnosis of some post-vaccination-reported adverse reactions. In this state-of-the-art review article, we present the current evidence regarding mainly the diagnosis of spontaneous allergic reactions, the skin occurrences, the vascular, blood, endocrine and heart events, the respiratory reports, the gastrointestinal, hepatic and kidney events, the reproductive and pregnancy issues and the muscle events, as well as the ear, eye, neurologic and psychiatric events following mRNA vaccination against COVID-19. We further present some evidence regarding the mRNA strategies and we discuss our expert opinion on the knowns and the unknowns towards the topic.
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071552
Lung cancer is a deadly disease with a high mortality rate. Endobronchial ultrasonography (EBUS) is one of the methods for detecting pulmonary lesions. Computer-aided diagnosis of pulmonary lesions from images can help radiologists to classify lesions; however, most of the existing methods need a large volume of data to give good results. Thus, this paper proposes a novel pulmonary lesion classification framework for EBUS images that works well with small datasets. The proposed framework integrates the statistical results from three classification models using the weighted ensemble classification. The three classification models include the radiomics feature and patient data-based model, the single-image-based model, and the multi-patch-based model. The radiomics features are combined with the patient data to be used as input data for the random forest, whereas the EBUS images are used as input data to the other two CNN models. The performance of the proposed framework was evaluated on a set of 200 EBUS images consisting of 124 malignant lesions and 76 benign lesions. The experimental results show that the accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve are 95.00%, 100%, 86.67%, 92.59%, 100%, and 93.33%, respectively. This framework can significantly improve the pulmonary lesion classification.
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071556
Myelodysplastic syndromes (MDSs) are clonal hematopoietic diseases of the elderly, characterized by chronic cytopenia, ineffective and dysplastic hematopoiesis, recurrent genetic abnormalities and increased risk of progression to acute myeloid leukemia. Diagnosis on a complete blood count (CBC) can be challenging due to numerous other non-neoplastic causes of cytopenias. New generations of hematology analyzers provide cell population data (CPD) that can be exploited to reliably detect MDSs from a routine CBC. In this review, we first describe the different technologies used to obtain CPD. We then give an overview of the currently available data regarding the performance of CPD for each lineage in the diagnostic workup of MDSs. Adequate exploitation of CPD can yield very strong diagnostic performances allowing for faster diagnosis and reduction of time-consuming slide reviews in the hematology laboratory.
Diagnostics, Volume 12; https://doi.org/10.3390/diagnostics12071553
Computed tomography (CT) imaging of the orbit with measurement of extraocular muscle size can be useful for diagnosing and monitoring conditions that affect extraocular muscles. However, the manual measurement of extraocular muscle size can be time-consuming and tedious. The purpose of this study is to evaluate the effectiveness of deep learning algorithms in segmenting extraocular muscles and measuring muscle sizes from CT images. Consecutive CT scans of orbits from 210 patients between 1 January 2010 and 31 December 2019 were used. Extraocular muscles were manually annotated in the studies, which were then used to train the deep learning algorithms. The proposed U-net algorithm can segment extraocular muscles on coronal slices of 32 test samples with an average dice score of 0.92. The thickness and area measurements from predicted segmentations had a mean absolute error (MAE) of 0.35 mm and 3.87 mm2, respectively, with a corresponding mean absolute percentage error (MAPE) of 7 and 9%, respectively. On qualitative analysis of 32 test samples, 30 predicted segmentations from the U-net algorithm were accepted while 2 were rejected. Based on the results from quantitative and qualitative evaluation, this study demonstrates that CNN-based deep learning algorithms are effective at segmenting extraocular muscles and measuring muscles sizes.