Diagnostics

11 pages, 2131 KiB

Open AccessArticle

Correlation between CT Value on Lung Subtraction CT and Radioactive Count on Perfusion Lung Single Photon Emission CT in Chronic Thromboembolic Pulmonary Hypertension

by Toshiya Kariyasu, Haruhiko Machida, Tsuneo Yamashiro, Keita Fukushima, Masamichi Koyanagi, Kenichi Yokoyama, Makiko Nishikawa and Toru Satoh

Diagnostics 2022, 12(11), 2895; https://doi.org/10.3390/diagnostics12112895 - 21 Nov 2022

Cited by 1 | Viewed by 1949

Abstract

Background: Lung subtraction CT (LSCT), the subtraction of noncontrast CT from CT pulmonary angiography (CTPA) without spatial misregistration, is easily applicable by utilizing a software-based deformable image registration technique without additional hardware and permits the evaluation of lung perfusion as iodine accumulation, similar [...] Read more.

Background: Lung subtraction CT (LSCT), the subtraction of noncontrast CT from CT pulmonary angiography (CTPA) without spatial misregistration, is easily applicable by utilizing a software-based deformable image registration technique without additional hardware and permits the evaluation of lung perfusion as iodine accumulation, similar to that observed in perfusion lung single photon emission CT (PL-SPECT). The aim of this study was to use LSCT to newly assess the quantitative correlation between the CT value on LSCT and radioactive count on PL-SPECT as a reference and validate the quantification of lung perfusion by measuring the CT value in chronic thromboembolic pulmonary hypertension (CTEPH). Methods: We prospectively enrolled 47 consecutive patients with CTEPH undergoing both LSCT and PL-SPECT; we used noncontrast CT, CTPA, and LSCT to measure CT values and PL-SPECT to measure radioactive counts in areas representing three different perfusion classes—no perfusion defect, subsegmental perfusion defect, and segmental perfusion defect; we compared CT values on noncontrast CT, CTPA, and LSCT and radioactive counts on PL-SPECT among the three classes, then assessed the correlation between them. Results: Both the CT values and radioactive counts differed significantly among the three classes (p < 0.01 for all) and showed weak correlation (ρ = 0.38) by noncontrast CT, moderate correlation (ρ = 0.61) by CTPA, and strong correlation (ρ = 0.76) by LSCT. Conclusions: The CT value measurement on LSCT is a novel quantitative approach to assess lung perfusion in CTEPH and only correlates strongly with radioactive count measurement on PL-SPECT. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

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16 pages, 4161 KiB

Open AccessArticle

Deep Learning-Based Glaucoma Screening Using Regional RNFL Thickness in Fundus Photography

by Hyunmo Yang, Yujin Ahn, Sanzhar Askaruly, Joon S. You, Sang Woo Kim and Woonggyu Jung

Diagnostics 2022, 12(11), 2894; https://doi.org/10.3390/diagnostics12112894 - 21 Nov 2022

Cited by 7 | Viewed by 2682

Abstract

Since glaucoma is a progressive and irreversible optic neuropathy, accurate screening and/or early diagnosis is critical in preventing permanent vision loss. Recently, optical coherence tomography (OCT) has become an accurate diagnostic tool to observe and extract the thickness of the retinal nerve fiber [...] Read more.

Since glaucoma is a progressive and irreversible optic neuropathy, accurate screening and/or early diagnosis is critical in preventing permanent vision loss. Recently, optical coherence tomography (OCT) has become an accurate diagnostic tool to observe and extract the thickness of the retinal nerve fiber layer (RNFL), which closely reflects the nerve damage caused by glaucoma. However, OCT is less accessible than fundus photography due to higher cost and expertise required for operation. Though widely used, fundus photography is effective for early glaucoma detection only when used by experts with extensive training. Here, we introduce a deep learning-based approach to predict the RNFL thickness around optic disc regions in fundus photography for glaucoma screening. The proposed deep learning model is based on a convolutional neural network (CNN) and utilizes images taken with fundus photography and with RNFL thickness measured with OCT for model training and validation. Using a dataset acquired from normal tension glaucoma (NTG) patients, the trained model can estimate RNFL thicknesses in 12 optic disc regions from fundus photos. Using intuitive thickness labels to identify localized damage of the optic nerve head and then estimating regional RNFL thicknesses from fundus images, we determine that screening for glaucoma could achieve 92% sensitivity and 86.9% specificity. Receiver operating characteristic (ROC) analysis results for specificity of 80% demonstrate that use of the localized mean over superior and inferior regions reaches 90.7% sensitivity, whereas 71.2% sensitivity is reached using the global RNFL thicknesses for specificity at 80%. This demonstrates that the new approach of using regional RNFL thicknesses in fundus images holds good promise as a potential screening technique for early stage of glaucoma. Full article

(This article belongs to the Special Issue Deep Learning Applications in Ophthalmology)

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12 pages, 554 KiB

Open AccessArticle

Clinical and Genetic Characterisation of Cystic Fibrosis Patients in Latvia: A Twenty-Five-Year Experience

by Madara Auzenbaha, Elina Aleksejeva, Gita Taurina, Liene Kornejeva, Inga Kempa, Vija Svabe and Linda Gailite

Diagnostics 2022, 12(11), 2893; https://doi.org/10.3390/diagnostics12112893 - 21 Nov 2022

Cited by 3 | Viewed by 2121

Abstract

Cystic fibrosis (CF) is the most common life-limiting genetic disorder in European descent populations. It is caused by pathogenic variants in the CFTR gene, and inheritance is autosomal recessive. This study provides an up-to-date, comprehensive estimation of the distribution of CFTR pathogenic variants [...] Read more.

Cystic fibrosis (CF) is the most common life-limiting genetic disorder in European descent populations. It is caused by pathogenic variants in the CFTR gene, and inheritance is autosomal recessive. This study provides an up-to-date, comprehensive estimation of the distribution of CFTR pathogenic variants in Latvia and their phenotypic characteristics. It also reports the first results of the CF newborn screening programme following its implementation in 2019. We analysed the clinical and molecular data of CF patients treated at the only tertiary hospital in Latvia providing specialised healthcare for the disorder. Between 1997 and 2022, 66 CF patients from 62 families were diagnosed based on symptoms or a molecular confirmation (six patients were diagnosed through the CF newborn screening programme). F508del was identified in 70.5% of all CF chromosomes. Known variants were identified in more than one family: dele2,3, R1006H, L1335P, W57R, R553X, 2143delT and 3849+10kb C>T (legacy names used). Furthermore, two novel variants were identified, namely, c.503C>A p.(Ser168Ter) and c.(743+1_744-1)_(1584+1_1585-1)del p.(?). The available follow-up results indicated that Latvian CF patients demonstrated similar tendencies to CF patients worldwide. The oldest age at diagnosis prior to the implementation of the CF newborn screening programme was 14 years. We provide here, for the first time, a comprehensive description of Latvian CF patients. An improvement in the healthcare of CF patients over time, including access to diagnosis, is evident. Two novel CF-causing variants are reported, and F508del is the most frequently occurring variant in the population, thus suggesting that F508del screening should be followed by the testing of the full CFTR gene. Full article

(This article belongs to the Section Pathology and Molecular Diagnostics)

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22 pages, 1655 KiB

Open AccessArticle

An Al-Biruni Earth Radius Optimization-Based Deep Convolutional Neural Network for Classifying Monkeypox Disease

by Doaa Sami Khafaga, Abdelhameed Ibrahim, El-Sayed M. El-Kenawy, Abdelaziz A. Abdelhamid, Faten Khalid Karim, Seyedali Mirjalili, Nima Khodadadi, Wei Hong Lim, Marwa M. Eid and Mohamed E. Ghoneim

Diagnostics 2022, 12(11), 2892; https://doi.org/10.3390/diagnostics12112892 - 21 Nov 2022

Cited by 33 | Viewed by 3581

Abstract

Human skin diseases have become increasingly prevalent in recent decades, with millions of individuals in developed countries experiencing monkeypox. Such conditions often carry less obvious but no less devastating risks, including increased vulnerability to monkeypox, cancer, and low self-esteem. Due to the low [...] Read more.

Human skin diseases have become increasingly prevalent in recent decades, with millions of individuals in developed countries experiencing monkeypox. Such conditions often carry less obvious but no less devastating risks, including increased vulnerability to monkeypox, cancer, and low self-esteem. Due to the low visual resolution of monkeypox disease images, medical specialists with high-level tools are typically required for a proper diagnosis. The manual diagnosis of monkeypox disease is subjective, time-consuming, and labor-intensive. Therefore, it is necessary to create a computer-aided approach for the automated diagnosis of monkeypox disease. Most research articles on monkeypox disease relied on convolutional neural networks (CNNs) and using classical loss functions, allowing them to pick up discriminative elements in monkeypox images. To enhance this, a novel framework using Al-Biruni Earth radius (BER) optimization-based stochastic fractal search (BERSFS) is proposed to fine-tune the deep CNN layers for classifying monkeypox disease from images. As a first step in the proposed approach, we use deep CNN-based models to learn the embedding of input images in Euclidean space. In the second step, we use an optimized classification model based on the triplet loss function to calculate the distance between pairs of images in Euclidean space and learn features that may be used to distinguish between different cases, including monkeypox cases. The proposed approach uses images of human skin diseases obtained from an African hospital. The experimental results of the study demonstrate the proposed framework’s efficacy, as it outperforms numerous examples of prior research on skin disease problems. On the other hand, statistical experiments with Wilcoxon and analysis of variance (ANOVA) tests are conducted to evaluate the proposed approach in terms of effectiveness and stability. The recorded results confirm the superiority of the proposed method when compared with other optimization algorithms and machine learning models. Full article

(This article belongs to the Special Issue Machine Learning in Signal and Image Analysis for Biomedical Application)

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14 pages, 4678 KiB

Open AccessArticle

Identification and Application of a Novel Immune-Related lncRNA Signature on the Prognosis and Immunotherapy for Lung Adenocarcinoma

by Zhimin Zeng, Yuxia Liang, Jia Shi, Lisha Xiao, Lu Tang, Yubiao Guo, Fengjia Chen and Gengpeng Lin

Diagnostics 2022, 12(11), 2891; https://doi.org/10.3390/diagnostics12112891 - 21 Nov 2022

Cited by 5 | Viewed by 1903

Abstract

Background: Long non-coding RNA (lncRNA) participates in the immune regulation of lung cancer. However, limited studies showed the potential roles of immune-related lncRNAs (IRLs) in predicting survival and immunotherapy response of lung adenocarcinoma (LUAD). Methods: Based on The Cancer Genome Atlas (TCGA) and [...] Read more.

Background: Long non-coding RNA (lncRNA) participates in the immune regulation of lung cancer. However, limited studies showed the potential roles of immune-related lncRNAs (IRLs) in predicting survival and immunotherapy response of lung adenocarcinoma (LUAD). Methods: Based on The Cancer Genome Atlas (TCGA) and ImmLnc databases, IRLs were identified through weighted gene coexpression network analysis (WGCNA), Cox regression, and Lasso regression analyses. The predictive ability was validated by Kaplan–Meier (KM) and receiver operating characteristic (ROC) curves in the internal dataset, external dataset, and clinical study. The immunophenoscore (IPS)-PD1/PD-L1 blocker and IPS-CTLA4 blocker data of LUAD were obtained in TCIA to predict the response to immune checkpoint inhibitors (ICIs). The expression levels of immune checkpoint molecules and markers for hyperprogressive disease were analyzed. Results: A six-IRL signature was identified, and patients were stratified into high- and low-risk groups. The low-risk had improved survival outcome (p = 0.006 in the training dataset, p = 0.010 in the testing dataset, p < 0.001 in the entire dataset), a stronger response to ICI (p < 0.001 in response to anti-PD-1/PD-L1, p < 0.001 in response to anti-CTLA4), and higher expression levels of immune checkpoint molecules (p < 0.001 in PD-1, p < 0.001 in PD-L1, p < 0.001 in CTLA4) but expressed more biomarkers of hyperprogression in immunotherapy (p = 0.002 in MDM2, p < 0.001 in MDM4). Conclusion: The six-IRL signature exhibits a promising prediction value of clinical prognosis and ICI efficacy in LUAD. Patients with low risk might gain benefits from ICI, although some have a risk of hyperprogressive disease. Full article

(This article belongs to the Special Issue Clinical Prognostic and Predictive Biomarkers)

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12 pages, 1576 KiB

Open AccessArticle

Ultrasound Versus Computed Tomography for Diaphragmatic Thickness and Skeletal Muscle Index during Mechanical Ventilation

by Stefano Gatti, Chiara Abbruzzese, Davide Ippolito, Sophie Lombardi, Andrea De Vito, Davide Gandola, Veronica Meroni, Vittoria Ludovica Sala, Sandro Sironi, Antonio Pesenti, Giuseppe Foti, Emanuele Rezoagli and Giacomo Bellani

Diagnostics 2022, 12(11), 2890; https://doi.org/10.3390/diagnostics12112890 - 21 Nov 2022

Cited by 4 | Viewed by 2318

Abstract

Background: Diaphragmatic alterations occurring during mechanical ventilation (MV) can be monitored using ultrasound (US). The performance of computed tomography (CT) to evaluate diaphragmatic thickness is limited. Further, the association between muscle mass and outcome is increasingly recognized. However, no data are available on [...] Read more.

Background: Diaphragmatic alterations occurring during mechanical ventilation (MV) can be monitored using ultrasound (US). The performance of computed tomography (CT) to evaluate diaphragmatic thickness is limited. Further, the association between muscle mass and outcome is increasingly recognized. However, no data are available on its correlation with diaphragmatic thickness. We aimed to determine correlation and agreement of diaphragmatic thickness between CT and US; and its association with muscle mass and MV parameters. Methods: Prospective observational study. US measurements of the diaphragmatic thickness were collected in patients undergoing MV within 12 h before or after performing a CT scan of the thorax and/or upper abdomen. Data on skeletal muscle index (SMI), baseline, and ventilatory data were recorded and correlated with US and CT measures of diaphragmatic thickness. Agreement was explored between US and CT data. Results: Twenty-nine patients were enrolled and the diaphragm measured by CT resulted overall thicker than US-based measurement of the right hemidiaphragm. The US thickness showed the strongest correlation with the left posterior pillar at CT (r = 0.49, p = 0.008). The duration of the controlled MV was negatively correlated with US thickness (r = −0.45, p = 0.017), the thickness of the right anterior pillar (r = −0.41, p = 0.029), and splenic dome by CT (r = −0.43, p = 0.023). SMI was positively correlated with US diaphragmatic thickness (r = 0.50, p = 0.007) and inversely correlated with the duration of MV before enrollment (r = −0.426, p = 0.027). Conclusions: CT scan of the left posterior pillar can estimate diaphragmatic thickness and is moderately correlated with US measurements. Both techniques show that diaphragm thickness decreases with MV duration. The diaphragmatic thickness by US showed a good correlation with SMI. Full article

(This article belongs to the Special Issue Critical Care Imaging)

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10 pages, 3205 KiB

Open AccessArticle

Comparison of Conventional Imaging and 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in the Diagnostic Accuracy of Staging in Patients with Intrahepatic Cholangiocarcinoma

by Eiko Nishioka, Masakatsu Tsurusaki, Ryohei Kozuki, Sung-Woon Im, Atsushi Kono, Kazuhiro Kitajima, Takamichi Murakami and Kazunari Ishii

Diagnostics 2022, 12(11), 2889; https://doi.org/10.3390/diagnostics12112889 - 21 Nov 2022

Cited by 7 | Viewed by 1743

Abstract

We aimed to examine the accuracy of tumor staging of intrahepatic cholangiocarcinoma (ICC) by using 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET-CT). From January 2001 to December 2021, 202 patients underwent PET-CT, CT, and MRI for the initial staging of ICC in two [...] Read more.

We aimed to examine the accuracy of tumor staging of intrahepatic cholangiocarcinoma (ICC) by using 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET-CT). From January 2001 to December 2021, 202 patients underwent PET-CT, CT, and MRI for the initial staging of ICC in two institutions. Among them, 102 patients had undergone surgical treatment. Ninety patients who had a histopathological diagnosis of ICC were retrospectively reviewed. The sensitivity and specificity of 18F-FDG PET-CT, CT, and magnetic resonance imaging (MRI) in detecting tumors, satellite focus, vascular invasion, and lymph node metastases were analyzed. Ninety patients with histologically diagnosed ICC were included. PET-CT demonstrated no statistically significant advantage over CT and MR in the diagnosis of multiple tumors and macrovascular invasion, and bile duct invasion. The overall sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of PET-CT in lymph node metastases were 84%, 86%, 91%, 84%, and 86%, respectively. PET-CT revealed a significantly higher accuracy compared to CT or MRI (86%, 67%, and 76%, p < 0.01, respectively) in the diagnosis of regional lymph node metastases. The accuracy of tumor staging by PET-CT was higher than that by CT/MRI (PET-CT vs. CT vs. MRI: 68/90 vs. 47/90 vs. 51/90, p < 0.05). 18F-FDG PET-CT had sensitivity and specificity values for diagnosing satellite focus and vascular and bile duct invasion similar to those of CT or MRI; however, PET-CT showed higher accuracy in diagnosing regional lymph node metastases. 18F-FDG PET-CT exhibited higher tumor staging accuracy than that of CT/MRI. Thus, 18FDG PET-CT may support tumor staging in ICC. Full article

(This article belongs to the Special Issue The Role of Imaging in Liver Surgery)

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23 pages, 6415 KiB

Open AccessArticle

DeepTumor: Framework for Brain MR Image Classification, Segmentation and Tumor Detection

by Ghazanfar Latif

Diagnostics 2022, 12(11), 2888; https://doi.org/10.3390/diagnostics12112888 - 21 Nov 2022

Cited by 18 | Viewed by 3021

Abstract

The proper segmentation of the brain tumor from the image is important for both patients and medical personnel due to the sensitivity of the human brain. Operation intervention would require doctors to be extremely cautious and precise to target the brain’s required portion. [...] Read more.

The proper segmentation of the brain tumor from the image is important for both patients and medical personnel due to the sensitivity of the human brain. Operation intervention would require doctors to be extremely cautious and precise to target the brain’s required portion. Furthermore, the segmentation process is also important for multi-class tumor classification. This work primarily concentrated on making a contribution in three main areas of brain MR Image processing for classification and segmentation which are: Brain MR image classification, tumor region segmentation and tumor classification. A framework named DeepTumor is presented for the multistage-multiclass Glioma Tumor classification into four classes; Edema, Necrosis, Enhancing and Non-enhancing. For the brain MR image binary classification (Tumorous and Non-tumorous), two deep Convolutional Neural Network) CNN models were proposed for brain MR image classification; 9-layer model with a total of 217,954 trainable parameters and an improved 10-layer model with a total of 80,243 trainable parameters. In the second stage, an enhanced Fuzzy C-means (FCM) based technique is proposed for the tumor segmentation in brain MR images. In the final stage, an enhanced CNN model 3 with 11 hidden layers and a total of 241,624 trainable parameters was proposed for the classification of the segmented tumor region into four Glioma Tumor classes. The experiments are performed using the BraTS MRI dataset. The experimental results of the proposed CNN models for binary classification and multiclass tumor classification are compared with the existing CNN models such as LeNet, AlexNet and GoogleNet as well as with the latest literature. Full article

(This article belongs to the Special Issue AI as a Tool to Improve Hybrid Imaging in Cancer—2nd Edition)

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4 pages, 1026 KiB

Open AccessInteresting Images

Microduplication 3p26.3p24.3 and 4q34.3q35.2 Microdeletion Identified in a Patient with Developmental Delay Associated with Brain Malformation

by Georgeta Cardos, Nicolae Gica, Corina Gica, Anca Maria Panaitescu, Mariana Predescu, Gheorghe Peltecu and Florina Mihaela Nedelea

Diagnostics 2022, 12(11), 2887; https://doi.org/10.3390/diagnostics12112887 - 21 Nov 2022

Viewed by 1855

Abstract

Microdeletions and microduplications are involved in many of prenatal and postnatal cases of multiple congenital malformations (MCM), developmental delay/intellectual disability (DD/ID), and autism spectrum disorders (ASD). Molecular karyotyping analysis (MCA), performed by DNA microarray technology, is a valuable method used to elucidate the [...] Read more.

Microdeletions and microduplications are involved in many of prenatal and postnatal cases of multiple congenital malformations (MCM), developmental delay/intellectual disability (DD/ID), and autism spectrum disorders (ASD). Molecular karyotyping analysis (MCA), performed by DNA microarray technology, is a valuable method used to elucidate the ethology of these clinical expressions, essentially contributing to the diagnosis of rare genetic diseases produced by DNA copy number variations (CNVs). MCA is frequently used as the first-tier cytogenetic diagnostic test for patients with MCM, DD/ID, or ASD due to its much higher resolution (≥10×) for detecting microdeletions and microduplications than classic cytogenetic analysis by G-banded karyotyping. Therefore, MCA can detect about 10% pathogenic genomic imbalances more than G-banded karyotyping alone. In addition, MCA using the Single Nucleotide Polymorphism-array (SNP-array) method also allows highlighting the regions of loss of heterozygosity and uniparental disomy, which are the basis of some genetic syndromes. We presented a case of a five-year-old patient, with global development delay, bilateral fronto-parietal lysencephaly, and pachygyria, for which MCA through SNP-Array led to the detection of the genetic changes, such as 3p26.3p24.3 microduplication and 4q34.3q35.2 microdeletion, which were the basis of the patient’s phenotype and to the precise establishment of the diagnosis. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

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14 pages, 10355 KiB

Open AccessArticle

Classification of Blood Pressure Levels Based on Photoplethysmogram and Electrocardiogram Signals with a Concatenated Convolutional Neural Network

by Yunendah Nur Fuadah and Ki Moo Lim

Diagnostics 2022, 12(11), 2886; https://doi.org/10.3390/diagnostics12112886 - 21 Nov 2022

Cited by 5 | Viewed by 2654

Abstract

Hypertension is a severe public health issue worldwide that significantly increases the risk of cardiac vascular disease, stroke, brain hemorrhage, and renal dysfunction. Early screening of blood pressure (BP) levels is essential to prevent the dangerous complication associated with hypertension as the leading [...] Read more.

Hypertension is a severe public health issue worldwide that significantly increases the risk of cardiac vascular disease, stroke, brain hemorrhage, and renal dysfunction. Early screening of blood pressure (BP) levels is essential to prevent the dangerous complication associated with hypertension as the leading cause of death. Recent studies have focused on employing photoplethysmograms (PPG) with machine learning to classify BP levels. However, several studies claimed that electrocardiograms (ECG) also strongly correlate with blood pressure. Therefore, we proposed a concatenated convolutional neural network which integrated the features extracted from PPG and ECG signals. This study used the MIMIC III dataset, which provided PPG, ECG, and arterial blood pressure (ABP) signals. A total of 14,298 signal segments were obtained from 221 patients, which were divided into 9150 signals of train data, 2288 signals of validation data, and 2860 signals of test data. In the training process, five-fold cross-validation was applied to select the best model with the highest classification performance. The proposed concatenated CNN architecture using PPG and ECG obtained the highest test accuracy of 94.56–95.15% with a 95% confidence interval in classifying BP levels into hypotension, normotension, prehypertension, hypertension stage 1, and hypertension stage 2. The result shows that the proposed method is a promising solution to categorize BP levels effectively, assisting medical personnel in making a clinical diagnosis. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

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9 pages, 543 KiB

Open AccessArticle

From Death Triad to Death Tetrad—The Addition of a Hypotension Component to the Death Triad Improves Mortality Risk Stratification in Trauma Patients: A Retrospective Cohort Study

by Wei-Juo Tzeng, Hsiang-Yu Tseng, Teng-Yuan Hou, Sheng-En Chou, Wei-Ti Su, Shiun-Yuan Hsu and Ching-Hua Hsieh

Diagnostics 2022, 12(11), 2885; https://doi.org/10.3390/diagnostics12112885 - 21 Nov 2022

Cited by 2 | Viewed by 5254

Abstract

The death triad, including coagulopathy, hypothermia, and acidosis, is shown to be a strong predictor of mortality in trauma patients. We aimed to investigate whether the inclusion of hypotension, defined as systolic blood pressure (SBP) < 60 mmHg, as a fourth factor in [...] Read more.

The death triad, including coagulopathy, hypothermia, and acidosis, is shown to be a strong predictor of mortality in trauma patients. We aimed to investigate whether the inclusion of hypotension, defined as systolic blood pressure (SBP) < 60 mmHg, as a fourth factor in the death triad would comprise a death tetrad to help stratify mortality risk in trauma patients. A total of 3361 adult trauma patients between 1 January 2009 and 31 December 2019 were allocated into groups to investigate whether hypotension matters in determining the mortality outcome of trauma patients who possess 1–3 death triad components compared to those without any component. Hypotension was added to the death tetrad, and the adjusted mortality outcome was compared among groups with 0–4 death tetrad components. Herein, we showed that SBP < 60 mmHg could be used to identify patients at risk of mortality among patients with one or two death triad components. Patients with one, two, and three death tetrad components had respective adjusted mortality rates of 3.69-, 10.10-, and 40.18-fold, determined by sex, age, and comorbidities. The mortality rate of trauma patients with all the four death tetrad components was 100%. The study suggested that hypotension, defined as an SBP < 60 mmHg, may act as a proper death tetrad component to stratify the mortality risk of trauma patients. Full article

(This article belongs to the Section Pathology and Molecular Diagnostics)

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11 pages, 1556 KiB

Open AccessReview

Patient Self-Performed Point-of-Care Ultrasound: Using Communication Technologies to Empower Patient Self-Care

by Andrew W. Kirkpatrick, Jessica L. McKee, Kyle Couperus and Christopher J. Colombo

Diagnostics 2022, 12(11), 2884; https://doi.org/10.3390/diagnostics12112884 - 21 Nov 2022

Cited by 5 | Viewed by 2313

Abstract

Point-of-Care ultrasound (POCUS) is an invaluable tool permitting the understanding of critical physiologic and anatomic details wherever and whenever a patient has a medical need. Thus the application of POCUS has dramatically expanded beyond hospitals to become a portable user-friendly technology in a [...] Read more.

Point-of-Care ultrasound (POCUS) is an invaluable tool permitting the understanding of critical physiologic and anatomic details wherever and whenever a patient has a medical need. Thus the application of POCUS has dramatically expanded beyond hospitals to become a portable user-friendly technology in a variety of prehospital settings. Traditional thinking holds that a trained user is required to obtain images, greatly handicapping the scale of potential improvements in individual health assessments. However, as the interpretation of ultrasound images can be accomplished remotely by experts, the paradigm wherein experts guide novices to obtain meaningful images that facilitate remote care is being embraced worldwide. The ultimate extension of this concept is for experts to guide patients to image themselves, enabling secondary disease prevention, home-focused care, and self-empowerment of the individual to manage their own health. This paradigm of remotely telementored self-performed ultrasound (RTMSPUS) was first described for supporting health care on the International Space Station. The TeleMentored Ultrasound Supported Medical Interventions (TMUSMI) Research Group has been investigating the utility of this paradigm for terrestrial use. The technique has particular attractiveness in enabling surveillance of lung health during pandemic scenarios. However, the paradigm has tremendous potential to empower and support nearly any medical question poised in a conscious individual with internet connectivity able to follow the directions of a remote expert. Further studies and development are recommended in all areas of acute and chronic health care. Full article

(This article belongs to the Special Issue Lung Ultrasound: A Leading Diagnostic Tool)

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9 pages, 1131 KiB

Open AccessArticle

Comparative Analysis of In-House RT-qPCR Detection of SARS-CoV-2 for Resource-Constrained Settings

by Yesit Bello-Lemus, Marco Anaya-Romero, Janni Gómez-Montoya, Moisés Árquez, Henry J. González-Torres, Elkin Navarro-Quiroz, Leonardo Pacheco-Londoño, Lisandro Pacheco-Lugo and Antonio J. Acosta-Hoyos

Diagnostics 2022, 12(11), 2883; https://doi.org/10.3390/diagnostics12112883 - 21 Nov 2022

Cited by 4 | Viewed by 3119

Abstract

We developed and standardized an efficient and cost-effective in-house RT-PCR method to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated sensitivity, specificity, and other statistical parameters by different RT-qPCR methods including triplex, duplex, and simplex assays adapted from the initial World [...] Read more.

We developed and standardized an efficient and cost-effective in-house RT-PCR method to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated sensitivity, specificity, and other statistical parameters by different RT-qPCR methods including triplex, duplex, and simplex assays adapted from the initial World Health Organization- (WHO) recommended protocol. This protocol included the identification of the E envelope gene (E gene; specific to the Sarvecovirus genus), RdRp gene of the RNA-dependent RNA polymerase (specific for SARS-CoV-2), and RNase P gene as endogenous control. The detection limit of the E and the RdRp genes were 3.8 copies and 33.8 copies per 1 µL of RNA, respectively, in both triplex and duplex reactions. The sensitivity for the RdRp gene in the triplex and duplex RT-qPCR tests were 98.3% and 83.1%, respectively. We showed a decrease in sensitivity for the RdRp gene by 60% when the E gene acquired Ct values > 31 in the diagnostic tests. This is associated with the specific detection limit of each gene and possible interferences in the protocol. Hence, developing efficient and cost-effective methodologies that can be adapted to various health emergency scenarios is important, especially in developing countries or settings where resources are limited. Full article

(This article belongs to the Topic Fighting against COVID-19: Latest Advances, Challenges and Methodologies)

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16 pages, 4654 KiB

Open AccessArticle

The Analysis of Relevant Gene Networks Based on Driver Genes in Breast Cancer

by Luxuan Qu, Zhiqiong Wang, Hao Zhang, Zhongyang Wang, Caigang Liu, Wei Qian and Junchang Xin

Diagnostics 2022, 12(11), 2882; https://doi.org/10.3390/diagnostics12112882 - 21 Nov 2022

Cited by 2 | Viewed by 1793

Abstract

Background: The occurrence and development of breast cancer has a strong correlation with a person’s genetics. Therefore, it is important to analyze the genetic factors of breast cancer for future development of potential targeted therapies from the genetic level. Methods: In this study, [...] Read more.

Background: The occurrence and development of breast cancer has a strong correlation with a person’s genetics. Therefore, it is important to analyze the genetic factors of breast cancer for future development of potential targeted therapies from the genetic level. Methods: In this study, we complete an analysis of the relevant protein–protein interaction network relating to breast cancer. This includes three steps, which are breast cancer-relevant genes selection using mutual information method, protein–protein interaction network reconstruction based on the STRING database, and vital genes calculating by nodes centrality analysis. Results: The 230 breast cancer-relevant genes were chosen in gene selection to reconstruct the protein–protein interaction network and some vital genes were calculated by node centrality analyses. Node centrality analyses conducted with the top 10 and top 20 values of each metric found 19 and 39 statistically vital genes, respectively. In order to prove the biological significance of these vital genes, we carried out the survival analysis and DNA methylation analysis, inquired about the prognosis in other cancer tissues and the RNA expression level in breast cancer. The results all proved the validity of the selected genes. Conclusions: These genes could provide a valuable reference in clinical treatment among breast cancer patients. Full article

(This article belongs to the Special Issue Breast Cancer Biomarkers)

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17 pages, 1209 KiB

Open AccessArticle

A Study of the Metabolic Pathways Affected by Gestational Diabetes Mellitus: Comparison with Type 2 Diabetes

by Loukia Spanou, Aikaterini Dimou, Christina E. Kostara, Eleni Bairaktari, Eleni Anastasiou and Vasilis Tsimihodimos

Diagnostics 2022, 12(11), 2881; https://doi.org/10.3390/diagnostics12112881 - 21 Nov 2022

Cited by 4 | Viewed by 2717

Abstract

Background: Gestational diabetes mellitus (GDM) remains incompletely understood and increases the risk of developing Diabetes mellitus type 2 (DM2). Metabolomics provides insights etiology and pathogenesis of disease and discovery biomarkers for accurate detection. Nuclear magnetic resonance (NMR) spectroscopy is a key platform defining [...] Read more.

Background: Gestational diabetes mellitus (GDM) remains incompletely understood and increases the risk of developing Diabetes mellitus type 2 (DM2). Metabolomics provides insights etiology and pathogenesis of disease and discovery biomarkers for accurate detection. Nuclear magnetic resonance (NMR) spectroscopy is a key platform defining metabolic signatures in intact serum/plasma. In the present study, we used NMR-based analysis of macromolecules free-serum to accurately characterize the altered metabolic pathways of GDM and assessing their similarities to DM2. Our findings could contribute to the understanding of the pathophysiology of GDM and help in the identification of metabolomic markers of the disease. Methods: Sixty-two women with GDM matched with seventy-seven women without GDM (control group). ¹H NMR serum spectra were acquired on an 11.7 T Bruker Avance DRX NMR spectrometer. Results: We identified 55 metabolites in both groups, 25 of which were significantly altered in the GDM group. GDM group showed elevated levels of ketone bodies, 2-hydroxybutyrate and of some metabolic intermediates of branched-chain amino acids (BCAAs) and significantly lower levels of metabolites of one-carbon metabolism, energy production, purine metabolism, certain amino acids, 3-methyl-2-oxovalerate, ornithine, 2-aminobutyrate, taurine and trimethylamine N-oxide. Conclusion: Metabolic pathways affected in GDM were beta-oxidation, ketone bodies metabolism, one-carbon metabolism, arginine and ornithine metabolism likewise in DM2, whereas BCAAs catabolism and aromatic amino acids metabolism were affected, but otherwise than in DM2. Full article

(This article belongs to the Special Issue Recent Advances in the Diagnosis of Metabolic Disorders)

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12 pages, 1119 KiB

Open AccessReview

The Role of Cytokinome in the HNSCC Tumor Microenvironment: A Narrative Review and Our Experience

by Nerina Denaro, Cinzia Solinas, Ornella Garrone, Carolina Cauchi, Fiorella Ruatta, Demi Wekking, Andrea Abbona, Matteo Paccagnella, Marco Carlo Merlano and Cristiana Lo Nigro

Diagnostics 2022, 12(11), 2880; https://doi.org/10.3390/diagnostics12112880 - 21 Nov 2022

Cited by 4 | Viewed by 2267

Abstract

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer. In locally advanced (LA) HNSCC, a multidisciplinary approach consisting of surgery followed by chemoradiation (CRT) or definitive CRT is the mainstay of treatment. In recurrent metastatic (R/M), HNSCC immune checkpoint [...] Read more.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer. In locally advanced (LA) HNSCC, a multidisciplinary approach consisting of surgery followed by chemoradiation (CRT) or definitive CRT is the mainstay of treatment. In recurrent metastatic (R/M), HNSCC immune checkpoint inhibitors (ICIs) with or without chemotherapy represent the new first-line option. However, cancer will recur in about two out of five patients with LA HNSCC. If progression occurs within six months from platin-radiotherapy treatment, anti-programmed cell death-1 (PD-1) may be prescribed. Otherwise, immunotherapy with or without chemotherapy might be considered if PD-L1 is expressed. Despite several improvements in the outcome of patients with R/M HNSCC, overall survival (OS) remains dismal, equaling a median of 14 months. In-depth knowledge of the tumor microenvironment (TME) would be required to change the course of this complex disease. In recent years, many predictive and prognostic biomarkers have been studied in the HNSCC TME, but none of them alone can select the best candidates for response to ICIs or targeted therapy (e.g., Cetuximab). The presence of cytokines indicates an immune response that might occur, among other things, after tumor antigen recognition, viral and bacterial infection, and physic damage. An immune response against HNSCC results in the production of some cytokines that induce a pro-inflammatory response and attract cells, such as neutrophils, macrophages, and T cell effectors, to enhance the innate and adaptive anti-tumor response. We revised the role of a group of cytokines as biomarkers for treatment response in HNSCC. Full article

(This article belongs to the Special Issue Head and Neck Cancers: Diagnosis and Management)

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26 pages, 4345 KiB

Open AccessArticle

Application of Machine Learning in Epileptic Seizure Detection

by Ly V. Tran, Hieu M. Tran, Tuan M. Le, Tri T. M. Huynh, Hung T. Tran and Son V. T. Dao

Diagnostics 2022, 12(11), 2879; https://doi.org/10.3390/diagnostics12112879 - 21 Nov 2022

Cited by 21 | Viewed by 3977

Abstract

Epileptic seizure is a neurological condition caused by short and unexpectedly occurring electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide have had an epileptic seizure. Experiencing an epileptic seizure can have serious consequences for the patient. Automatic [...] Read more.

Epileptic seizure is a neurological condition caused by short and unexpectedly occurring electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide have had an epileptic seizure. Experiencing an epileptic seizure can have serious consequences for the patient. Automatic seizure detection on electroencephalogram (EEG) recordings is essential due to the irregular and unpredictable nature of seizures. By thoroughly analyzing EEG records, neurophysiologists can discover important information and patterns, and proper and timely treatments can be provided for the patients. This research presents a novel machine learning-based approach for detecting epileptic seizures in EEG signals. A public EEG dataset from the University of Bonn was used to validate the approach. Meaningful statistical features were extracted from the original data using discrete wavelet transform analysis, then the relevant features were selected using feature selection based on the binary particle swarm optimizer. This facilitated the reduction of 75% data dimensionality and 47% computational time, which eventually sped up the classification process. After having been selected, relevant features were used to train different machine learning models, then hyperparameter optimization was utilized to further enhance the models’ performance. The results achieved up to 98.4% accuracy and showed that the proposed method was very effective and practical in detecting seizure presence in EEG signals. In clinical applications, this method could help relieve the suffering of epilepsy patients and alleviate the workload of neurologists. Full article

(This article belongs to the Special Issue Advances in the Diagnosis of Nervous System Diseases)

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8 pages, 2066 KiB

Open AccessCase Report

Hyaline Vascular Type of Unicentric Castleman Disease in a Kidney with End-Stage Renal Disease: A Case Report of a Rare Entity at an Unusual Location and a Special Clinical Setting

by Chuan-Han Chen and Hsin-Ni Li

Diagnostics 2022, 12(11), 2878; https://doi.org/10.3390/diagnostics12112878 - 21 Nov 2022

Cited by 2 | Viewed by 1923

Abstract

Castleman disease (CD) is an unusual heterogeneous lymphoproliferative disorder that has been classified based on either clinical presentation and disease course or histologic features. Clinically, CD is divided into a unicentric CD (UCD) type and multicentric CD (MCD) type according to the extent [...] Read more.

Castleman disease (CD) is an unusual heterogeneous lymphoproliferative disorder that has been classified based on either clinical presentation and disease course or histologic features. Clinically, CD is divided into a unicentric CD (UCD) type and multicentric CD (MCD) type according to the extent of lymph node region involvement and the absence or presence of systemic symptoms. Histologically, it can be categorized into hyaline vascular (HV) type, plasma cell (PC) type and mixed type. The majority of HV-type CD involves a solitary lymph node, and excision surgery is often curative. On the contrary, MCD is a progressive and often fatal disease with lymphadenopathy in multiple nodes, and systemic therapy is needed. Herein we report a unique case of HV-type CD presenting as a single renal mass in a patient with end-stage renal disease (ESRD). Despite the rarity, CD should be included in the differential diagnosis of solitary renal mass lesions. An accurate diagnosis is important to avoid unnecessarily risky or extensive operations. Full article

(This article belongs to the Special Issue Kidney Disease: Biomarkers, Diagnosis, and Prognosis: 2nd Edition)

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14 pages, 1097 KiB

Open AccessArticle

Analysis of Factors Determining Patient Survival after Receiving Free-Flap Reconstruction at a Single Center—A Retrospective Cohort Study

by Nicholas Moellhoff, Sara Taha, Nikolaus Wachtel, Maximilian Hirschmann, Marc Hellweg, Riccardo E. Giunta and Denis Ehrl

Diagnostics 2022, 12(11), 2877; https://doi.org/10.3390/diagnostics12112877 - 21 Nov 2022

Cited by 2 | Viewed by 2098

Abstract

Background: Microsurgical tissue transfer revolutionized reconstructive surgery after extensive trauma, oncological resections, and severe infections. Complex soft tissue reconstructions are increasingly performed in multimorbid and elderly patients. Therefore, it is crucial to investigate whether these patients benefit from these complex procedures. Objective: To [...] Read more.

Background: Microsurgical tissue transfer revolutionized reconstructive surgery after extensive trauma, oncological resections, and severe infections. Complex soft tissue reconstructions are increasingly performed in multimorbid and elderly patients. Therefore, it is crucial to investigate whether these patients benefit from these complex procedures. Objective: To evaluate the outcome for multimorbid patients who underwent microsurgical soft tissue reconstruction and to identify potential risk factors that may increase mortality. Methods: This single-center study retrospectively analyzed prospectively collected data of patients receiving free gracilis (GM) or latissimus dorsi muscle (LDM) flap reconstruction between September 2017 and December 2021. Cases were divided into two groups (dead vs. alive), depending on patient survival. Patient demographics, comorbidities and medication, perioperative details, free flap outcome, as well as microcirculation were determined. Results: A total of 151 flaps (LDM, n = 67; GM, n = 84) performed in 147 patients with a mean age of 61.15 ± 17.5 (range 19–94) years were included. A total of 33 patients (22.45%) passed away during the study period. Deceased patients were significantly older (Alive: 58.28 ± 17.91 vs. Dead: 71.39 ± 11.13; p = 0.001), were hospitalized significantly longer (Alive: 29.66 ± 26.97 vs. Dead: 36.88 ± 15.04 days; p = 0.046) and suffered from cardiovascular (Alive: 36.40% vs. Dead: 66.70%; p = 0.002) and metabolic diseases (Alive: 33.90% vs. Dead: 54.50%; p = 0.031) more frequently, which corresponded to a significantly higher ASA Score (p = 0.004). Revision rates (Alive: 11.00% vs. Dead: 18.20%; p = 0.371) and flap loss (Alive: 3.39% vs. Dead: 12.12%; p = 0.069) were higher in patients that died by the end of the study period. Conclusions: Free flap transfer is safe and effective, even in multimorbid patients. However, patient age, comorbidities, preoperative ASA status, and medication significantly impact postoperative patient survival in the short- and mid-term and must, therefore, be taken into account in preoperative decision-making and informed consent. Full article

(This article belongs to the Collection Vascular Diseases Diagnostics)

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10 pages, 3005 KiB

Open AccessCase Report

A Novel Deletion Mutation of the F8 Gene for Hemophilia A

by Jingwei Wang, Jian Gu, Hongbing Chen, Qian Wu, Liang Xiong, Bin Qiao, Yan Zhang, Hongjun Xiao and Yongqing Tong

Diagnostics 2022, 12(11), 2876; https://doi.org/10.3390/diagnostics12112876 - 21 Nov 2022

Cited by 3 | Viewed by 3304

Abstract

Background: Hemophilia A (HA) is an X-linked recessive blood coagulation disorder caused by a variety of abnormalities in F8 gene, resulting in the absence of impaired molecule production of factor VIII (FVIII) in the plasma. The genetic testing of the F8 gene encoding [...] Read more.

Background: Hemophilia A (HA) is an X-linked recessive blood coagulation disorder caused by a variety of abnormalities in F8 gene, resulting in the absence of impaired molecule production of factor VIII (FVIII) in the plasma. The genetic testing of the F8 gene encoding FVIII is used for confirmation of HA diagnosis, which significantly reduced serious complications of this disease and, ultimately, increased life expectancy. Methods: Sanger sequencing was performed in F8 gene exons of the suspected patients with blood coagulation-related indicators. Results: A novel F8 indel variant c.6343delC, p.Leu2115SerfsTer28 in exon 22 of the F8 gene was identified in the suspected families. The infant with this novel variant appeared the symptom of minor bleeding and oral cavity bleeding, and decreased activity of FVIII, which is consistent with that of F8 deleterious variants. The 3’D protein structural analysis of the novel variant shows a change in FVIII protein stability, which may be responsible for the pathogenesis of HA. Conclusions: A novel deleterious variant was identified in our case, which expands the F8 variants spectrum. Our result is helpful for HA diagnosis and benefits carrier detection and prenatal diagnosis. Our study also reveals that mutation screening of the F8 gene should be necessary for HA suspected patients. Full article

(This article belongs to the Section Pathology and Molecular Diagnostics)

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15 pages, 4967 KiB

Open AccessArticle

Detection and Morphological Analysis of Micro-Ruptured Cortical Arteries in Subdural Hematoma: Three-Dimensional Visualization Using the Tissue-Clearing Clear, Unobstructed, Brain/Body Imaging Cocktails and Computational Analysis Method

by Kazuhisa Funayama, Kazuki Tainaka, Akihide Koyama, Rieka Katsuragi-Go, Natsumi Nishikawa-Harada, Ryoko Higuchi, Takashi Aoyama, Hiraku Watanabe, Naoya Takahashi and Hisakazu Takatsuka

Diagnostics 2022, 12(11), 2875; https://doi.org/10.3390/diagnostics12112875 - 20 Nov 2022

Cited by 2 | Viewed by 1909

Abstract

One of the causes of bleeding in subdural hematoma is cortical artery rupture, which is difficult to detect at autopsy. Therefore, reports of autopsy cases with this condition are limited and hence, the pathogenesis of subdural hematoma remains unclear. Herein, for the detection [...] Read more.

One of the causes of bleeding in subdural hematoma is cortical artery rupture, which is difficult to detect at autopsy. Therefore, reports of autopsy cases with this condition are limited and hence, the pathogenesis of subdural hematoma remains unclear. Herein, for the detection and morphological analysis of cortical artery ruptures as the bleeding sources of subdural hematoma, we used the tissue-clearing CUBIC (clear, unobstructed, brain/body imaging cocktails and computational analysis) method with light-sheet fluorescence microscopy and reconstructed the two-dimensional and three-dimensional images. Using the CUBIC method, we could clearly visualize and detect cortical artery ruptures that were missed by conventional methods. Indeed, the CUBIC method enables three-dimensional morphological analysis of cortical arteries including the ruptured area, and the creation of cross-sectional two-dimensional images in any direction, which are similar to histopathological images. This highlights the effectiveness of the CUBIC method for subdural hematoma analysis. Full article

(This article belongs to the Section Pathology and Molecular Diagnostics)

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19 pages, 5977 KiB

Open AccessReview

Hypersensitivity Pneumonitis: A Pictorial Review Based on the New ATS/JRS/ALAT Clinical Practice Guideline for Radiologists and Pulmonologists

by Mona Dabiri, Maham Jehangir, Pegah Khoshpouri and Hamid Chalian

Diagnostics 2022, 12(11), 2874; https://doi.org/10.3390/diagnostics12112874 - 20 Nov 2022

Cited by 5 | Viewed by 10759

Abstract

Hypersensitivity pneumonitis (HP) is a complicated and heterogeneous interstitial lung disease (ILD) caused by an excessive immune response to an inhaled antigen in susceptible individuals. Accurate diagnosis of HP is difficult and necessitates a detailed exposure history, as well as a multidisciplinary discussion [...] Read more.

Hypersensitivity pneumonitis (HP) is a complicated and heterogeneous interstitial lung disease (ILD) caused by an excessive immune response to an inhaled antigen in susceptible individuals. Accurate diagnosis of HP is difficult and necessitates a detailed exposure history, as well as a multidisciplinary discussion of clinical, histopathologic, and radiologic data. We provide a pictorial review based on the latest American Thoracic Society (ATS)/Japanese Respiratory Society (JRS)/Asociación Latinoamericana del Tórax (ALAT) guidelines for diagnosing HP through demonstrating new radiologic terms, features, and a new classification of HP which will benefit radiologists and pulmonologists. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

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9 pages, 1793 KiB

Open AccessArticle

Extremely Precise Blood–Plasma Separation from Whole Blood on a Centrifugal Microfluidic Disk (Lab-on-a-Disk) Using Separator Gel

by Ali Hatami and Maryam Saadatmand

Diagnostics 2022, 12(11), 2873; https://doi.org/10.3390/diagnostics12112873 - 20 Nov 2022

Cited by 11 | Viewed by 4011

Abstract

Due to the expansion of point-of-care devices, proposing a convenient and efficient method for blood–plasma separation would help with the use of point-of-care devices. Commercial microfluidic chips are only able to separate a limited amount of plasma, and the majority of these chips [...] Read more.

Due to the expansion of point-of-care devices, proposing a convenient and efficient method for blood–plasma separation would help with the use of point-of-care devices. Commercial microfluidic chips are only able to separate a limited amount of plasma, and the majority of these chips need an active valve system, which leads to increase manufacturing cost and complexity. In this research study, we designed a centrifugal microfluidic disk with a passive valve for ultra-accurate and efficient blood–plasma separation on a large scale (2–3 mL). The disk contained a separator gel, which, after applying the centrifugal force, separated the plasma and red blood cells. The passive valve worked based on the inertial force and was able to transfer more than 90% of the separated plasma to the next chamber. The results demonstrated that the separated plasma was 99.992% pure. This study compared the efficiency of the disk containing separating gel with the common lab-on-a-disk design for plasma separation. A comparison of the results showed that although the common lab-on-a-disk design could separate almost pure plasma as the disk contained separator gel, it could only transfer 60% of plasma to the next chamber. Full article

(This article belongs to the Special Issue Low-Cost Diagnostic Devices)

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15 pages, 3815 KiB

Open AccessArticle

Bone-Metabolism-Related Serum microRNAs to Diagnose Osteoporosis in Middle-Aged and Elderly Women

by Sheng-Li Zhao, Zhen-Xing Wen, Xiao-Yi Mo, Xiao-Yan Zhang, Hao-Nan Li, Wing-Hoi Cheung, Dan Fu, Shi-Hong Zhang, Yong Wan and Bai-Ling Chen

Diagnostics 2022, 12(11), 2872; https://doi.org/10.3390/diagnostics12112872 - 19 Nov 2022

Cited by 9 | Viewed by 1977

Abstract

Objective: Postmenopausal osteoporosis (PMOP), a chronic systemic metabolic disease prevalent in middle-aged and elderly women, heavily relies on bone mineral density (BMD) measurement as the diagnostic indicator. In this study, we investigated serum microRNAs (miRNAs) as a possible screening tool for PMOP. [...] Read more.

Objective: Postmenopausal osteoporosis (PMOP), a chronic systemic metabolic disease prevalent in middle-aged and elderly women, heavily relies on bone mineral density (BMD) measurement as the diagnostic indicator. In this study, we investigated serum microRNAs (miRNAs) as a possible screening tool for PMOP. Methods: This investigation recruited 83 eligible participants from 795 community-dwelling postmenopausal women between June 2020 and August 2021. The miRNA expression profiles in the serum of PMOP patients were evaluated via miRNA microarray (six PMOP patients and four postmenopausal women without osteoporosis (n-PMOP) as controls). Subsequently, results were verified in independent sample sets (47 PMOP patients and 26 n-PMOP controls) using quantitative real-time PCR. In addition, the target genes and main functions of the differentially expressed miRNAs were explored by bioinformatics analysis. Results: Four highly expressed miRNAs in the serum of patients (hsa-miR-144-5p, hsa-miR-506-3p, hsa-miR-8068, and hsa-miR-6851-3p) showed acceptable disease-independent discrimination performance (area under the curve range: 0.747–0.902) in the training set and verification set, outperforming traditional bone turnover markers. Among four key miRNAs, hsa-miR-144-5p is the only one that can simultaneously predict changes in BMD in lumbar spine 1–4, total hip, and femoral neck (β = −0.265, p = 0.022; β = −0.301, p = 0.005; and β = −0.324, p = 0.003, respectively). Bioinformatics analysis suggested that the differentially expressed miRNAs were targeted mainly to YY1, VIM, and YWHAE genes, which are extensively involved in bone metabolism processes. Conclusions: Bone-metabolism-related serum miRNAs, such as hsa-miR-144-5p, hsa-miR-506-3p, hsa-miR-8068, and hsa-miR-6851-3p, can be used as novel biomarkers for PMOP diagnosis independent of radiological findings and traditional bone turnover markers. Further study of these miRNAs and their target genes may provide new insights into the epigenetic regulatory mechanisms of the onset and progression of the disease. Full article

(This article belongs to the Special Issue Epigenetic Biomarkers and Diagnostics)

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7 pages, 1327 KiB

Open AccessArticle

Safety of Bedside Portable Low-Field Brain MRI in ECMO Patients Supported on Intra-Aortic Balloon Pump

by Christopher Wilcox, Matthew Acton, Hannah Rando, Steven Keller, Haris I. Sair, Ifeanyi Chinedozi, John Pitts, Bo Soo Kim, Glenn Whitman and Sung Min Cho

Diagnostics 2022, 12(11), 2871; https://doi.org/10.3390/diagnostics12112871 - 19 Nov 2022

Cited by 8 | Viewed by 4566

Abstract

(1) Background: Fifty percent of patients supported on veno-arterial extracorporeal membrane oxygenation (VA-ECMO) are concurrently supported with an intra-aortic balloon pump (IABP). Acute brain injury (ABI) is a devastating complication related to ECMO and IABP use. The standard of care for ABI diagnosis [...] Read more.

(1) Background: Fifty percent of patients supported on veno-arterial extracorporeal membrane oxygenation (VA-ECMO) are concurrently supported with an intra-aortic balloon pump (IABP). Acute brain injury (ABI) is a devastating complication related to ECMO and IABP use. The standard of care for ABI diagnosis requires transport to a head CT (HCT) scanner. Recent data suggest that point-of-care (POC) magnetic resonance imaging (MRI) is safe and may be effective in diagnosing ABI in ECMO patients; however, no data exist in patients supported on ECMO with an IABP. We report pre-clinical safety data and a case series to evaluate the safety and feasibility of POC brain MRI in ECMO patients supported with IABP. (2) Methods: Prior to patient use, ex vivo testing with an IABP catheter within the Swoop^® Portable MRI (0.064 T) System™ was conducted. After IRB approval, clinical testing was performed for the safety and feasibility of early ABI detection. (3) Results: No deflection force was measured with a 7.5 French Maquet Linear IABP within the 0.064 T field. Three adult ECMO patients (average age: 40 years; 67% female) supported with IABP completed four POC brain MRI exams (median exam time: 30 min). Multiple signal abnormalities were detected on the POC brain MRI, corresponding to HCT results. (4) Conclusions: Our preliminary results suggest that adult VA-ECMO patients with IABP support can be safely imaged with low-field POC brain MRI in the intensive care unit, allowing for the early and bedside imaging of patients. Full article

(This article belongs to the Special Issue Critical Care Imaging)

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19 pages, 3579 KiB

Open AccessArticle

Optimized Intelligent Classifier for Early Breast Cancer Detection Using Ultra-Wide Band Transceiver

by Ahmad Ashraf Abdul Halim, Allan Melvin Andrew, Wan Azani Mustafa, Mohd Najib Mohd Yasin, Muzammil Jusoh, Vijayasarveswari Veeraperumal, Mohd Amiruddin Abd Rahman, Norshuhani Zamin, Mervin Retnadhas Mary and Sabira Khatun

Diagnostics 2022, 12(11), 2870; https://doi.org/10.3390/diagnostics12112870 - 19 Nov 2022

Cited by 5 | Viewed by 1975

Abstract

Breast cancer is the most common cancer diagnosed in women and the leading cause of cancer-related deaths among women worldwide. The death rate is high because of the lack of early signs. Due to the absence of a cure, immediate treatment is necessary [...] Read more.

Breast cancer is the most common cancer diagnosed in women and the leading cause of cancer-related deaths among women worldwide. The death rate is high because of the lack of early signs. Due to the absence of a cure, immediate treatment is necessary to remove the cancerous cells and prolong life. For early breast cancer detection, it is crucial to propose a robust intelligent classifier with statistical feature analysis that considers parameter existence, size, and location. This paper proposes a novel Multi-Stage Feature Selection with Binary Particle Swarm Optimization (MSFS–BPSO) using Ultra-Wideband (UWB). A collection of 39,000 data samples from non-tumor and with tumor sizes ranging from 2 to 7 mm was created using realistic tissue-like dielectric materials. Subsequently, the tumor models were inserted into the heterogeneous breast phantom. The breast phantom with tumors was imaged and represented in both time and frequency domains using the UWB signal. Consequently, the dataset was fed into the MSFS–BPSO framework and started with feature normalization before it was reduced using feature dimension reduction. Then, the feature selection (based on time/frequency domain) using seven different classifiers selected the frequency domain compared to the time domain and continued to perform feature extraction. Feature selection using Analysis of Variance (ANOVA) is able to distinguish between class-correlated data. Finally, the optimum feature subset was selected using a Probabilistic Neural Network (PNN) classifier with the Binary Particle Swarm Optimization (BPSO) method. The research findings found that the MSFS–BPSO method has increased classification accuracy up to 96.3% and given good dependability even when employing an enormous data sample. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

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13 pages, 257 KiB

Open AccessArticle

Investigation of SARS-CoV-2 Variants and Their Effect on SARS-CoV-2 Monoclonal Antibodies, Convalescent and Vaccine Plasma by a Novel Web Tool

by Ayse Arikan and Murat Sayan

Diagnostics 2022, 12(11), 2869; https://doi.org/10.3390/diagnostics12112869 - 19 Nov 2022

Cited by 1 | Viewed by 1789

Abstract

(1) Background: SARS-CoV-2 variants possess specific mutations throughout their genome; however, the effect of these mutations on pathogenesis is little known. The study aimed to identify SARS-CoV-2 variants and their susceptibility rate against monoclonal antibodies, convalescent, and vaccine plasma. (2) Methods: Strains isolated [...] Read more.

(1) Background: SARS-CoV-2 variants possess specific mutations throughout their genome; however, the effect of these mutations on pathogenesis is little known. The study aimed to identify SARS-CoV-2 variants and their susceptibility rate against monoclonal antibodies, convalescent, and vaccine plasma. (2) Methods: Strains isolated from COVID-19 cases in Turkey in April and September 2021 were involved. Illuma Nextera XT was processed for NGS, followed by virtual phenotyping (Coronavirus Antiviral and Resistance Database (CoV-RDB) by Stanford University). (3) Results: Among 211 strains, 79% were SARS-CoV-2 variants. B.1.1.7 (Alpha) was the most dominant, followed by B.1.617.2 (Delta), B.1.351 (Beta), and B.1.525 (Eta). Alpha and Delta were less susceptible to Etesevimab—Sotrovimab and Bamlanivimab—Etesevimab, respectively. Reduced efficacy was observed for convalescent plasma in Beta and Delta; AstraZeneca, Comirnaty plus AstraZeneca in Alpha; Comirnaty, Moderna, Novovax in Beta; Comirnaty in Delta. (4) Conclusion: CoV-RDB analysis is an efficient, rapid, and helpful web tool for SARS-CoV-2 variant detection and susceptibility analysis. Full article

(This article belongs to the Special Issue Monitoring and Detection for SARS-CoV-2 and Its Variants)

13 pages, 2741 KiB

Open AccessReview

Behçet’s Disease: A Radiological Review of Vascular and Parenchymal Pulmonary Involvement

by Caterina Giannessi, Olga Smorchkova, Diletta Cozzi, Giulia Zantonelli, Elena Bertelli, Chiara Moroni, Edoardo Cavigli and Vittorio Miele

Diagnostics 2022, 12(11), 2868; https://doi.org/10.3390/diagnostics12112868 - 19 Nov 2022

Cited by 13 | Viewed by 2897

Abstract

Behcet’s disease (BD) is a chronic systemic inflammatory disorder characterized by underlying chronic vasculitis of both large- and small-caliber vessels. Thoracic involvement in BD can occur with various types of manifestations, which can be detected with contrast-enhanced MSCT scanning. In addition, MR can [...] Read more.

Behcet’s disease (BD) is a chronic systemic inflammatory disorder characterized by underlying chronic vasculitis of both large- and small-caliber vessels. Thoracic involvement in BD can occur with various types of manifestations, which can be detected with contrast-enhanced MSCT scanning. In addition, MR can be useful in diagnosis. Characteristic features are aneurysms of the pulmonary arteries that can cause severe hemoptysis and SVC thrombosis that manifests as SVC syndrome. Other manifestations are aortic and bronchial artery aneurysms, alveolar hemorrhage, pulmonary infarction, and rarely pleural effusion. Achieving the right diagnosis of these manifestations is important for setting the correct therapy and improving the patient’s outcome. Full article

(This article belongs to the Special Issue Imaging of Pulmonary Vascular Disease)

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9 pages, 655 KiB

Open AccessArticle

Predictive Factors of Adequate Bowel Cleansing for Colonoscopy in the Elderly: A Retrospective Analysis of a Prospective Cohort

by Marcello Maida, Antonio Facciorusso, Emanuele Sinagra, Gaetano Morreale, Sandro Sferrazza, Giuseppe Scalisi, Socrate Pallio and Salvatore Camilleri

Diagnostics 2022, 12(11), 2867; https://doi.org/10.3390/diagnostics12112867 - 19 Nov 2022

Cited by 6 | Viewed by 1485

Abstract

Factors affecting the quality of bowel preparation for colonoscopy in the elderly are not fully known, and current guidelines provide no specific recommendations. This study aimed to assess the difference in bowel cleansing in young and elderly patients and evaluate predictors of bowel [...] Read more.

Factors affecting the quality of bowel preparation for colonoscopy in the elderly are not fully known, and current guidelines provide no specific recommendations. This study aimed to assess the difference in bowel cleansing in young and elderly patients and evaluate predictors of bowel cleansing in the elderly. We retrospectively reviewed a prospective cohort of 1289 patients performing colonoscopy after a 1-, 2-, or 4-L PEG-based preparation. All 1289 were included in the analysis. Overall, 44.6% of patients were aged ≥65 years. Cleansing success (CS) was achieved in 77.3% and 70.3% of patients aged <65 years and ≥65 years, respectively. At multivariable analysis, split regimen (OR = 2.43, 95% CI = 1.34–4.38; p = 0.003), adequate cleansing at previous colonoscopy (OR = 2.29, 95% CI = 1.14–4.73; p = 0.02), tolerability score (OR = 1.29, 95% CI = 1.16–1.44; p < 0.001), a low-fiber diet for at least 3 days (OR = 2.45, 95% CI = 1.42–4.24; p = 0.001), and colonoscopy within 5 h after the end of preparation (OR = 2.67, 95% CI = 1.28–5.56; p = 0.008) were independently associated with CS in the elderly. Combining a low-fiber diet for at least 3 days, split preparation, and colonoscopy within 5 h allowed a CS rate above 90% and should always be encouraged. A 1-L PEG-ASC preparation was also associated with greater high-quality cleansing of the right colon and may be preferred. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

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8 pages, 438 KiB

Open AccessCase Report

Molecular Characterization of Hepatitis B Virus Infection in a Patient with Cutaneous Lupus Erythematosus

by Umbertina Villano, Elida Mataj, Maria Dorrucci, Francesca Farchi, Carmelo Pirone, Catia Valdarchi, Michele Equestre, Elisabetta Madonna, Roberto Bruni, Giulio Pisani, Antonio Martina, Matteo Simeoni, Giancarlo Iaiani, Massimo Ciccozzi, Anna Rita Ciccaglione, Fabrizio Conti, Fulvia Ceccarelli and Alessandra Lo Presti

Diagnostics 2022, 12(11), 2866; https://doi.org/10.3390/diagnostics12112866 - 19 Nov 2022

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Abstract

Hepatitis B virus (HBV) infection is a serious global health problem. Patients with autoimmune diseases, such as Lupus Erythematosus, are exposed to a higher risk of acquiring infections. In this study, a molecular characterization, genomic investigation of the Hepatitis B virus, polymerase (P) [...] Read more.

Hepatitis B virus (HBV) infection is a serious global health problem. Patients with autoimmune diseases, such as Lupus Erythematosus, are exposed to a higher risk of acquiring infections. In this study, a molecular characterization, genomic investigation of the Hepatitis B virus, polymerase (P) and surface (S) genes, from a patient affected by Cutaneous Lupus Erythematosus (CLE), was presented. Viral DNA was extracted from 200 μL of serum, and the HBV-DNA was amplified by real-time polymerase chain reaction (PCR) with the Platinum Taq DNA Polymerase. The PCR products were purified and sequencing reactions were performed. A phylogenetic analysis was performed through maximum likelihood and Bayesian approaches. The HBV CLE isolate was classified as sub-genotype D3 and related to other Italian HBV D3 genomes, and some from foreign countries. No drug resistant mutations were identified. One mutation (a.a. 168 M) was located in the last part of the major hydrophilic region (MHR) of the surface antigen (HBsAg). Moreover, three sites (351G, 526Y, 578C) in the polymerase were exclusively present in the CLE patient. The mutations identified exclusively in the HBsAg of our CLE patient may have been selected because of the Lupus autoantibodies, which are characteristic in the Lupus autoimmune disease, using a possible molecular mimicry mechanism. Full article

(This article belongs to the Section Diagnostic Microbiology and Infectious Disease)

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Diagnostics, Volume 12, Issue 11 (November 2022) – 330 articles

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