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Diagnostics, Volume 12, Issue 10 (October 2022) – 299 articles

Cover Story (view full-size image): The study of lateral cephalograms is absolutely common in daily practice among orthodontists and oromaxillofacial surgeons, and it is fundamental for correct diagnoses as well as for drafting correct treatment plans. However, a cephalometric study traced on 2D images has intrinsic limitations due to magnification, geometric distortion, and, above all, superimpositions of anatomical structures. Three-dimensional diagnostic imaging could overcome these limitations of 2D imaging even with a low dose of radiation absorption for the patient. The purpose of this study is to present a new 3D Enlow’s horizontal counterpart analysis that uses anatomical points traced on CBCT images in order to identify the different horizontal dimensions of Enlow’s 2D counterpart analysis. View this paper
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32 pages, 1170 KiB  
Review
Outcome Measures and Biomarkers for Disease Assessment in Takayasu Arteritis
by Durga Prasanna Misra, Neeraj Jain, Manish Ora, Kritika Singh, Vikas Agarwal and Aman Sharma
Diagnostics 2022, 12(10), 2565; https://doi.org/10.3390/diagnostics12102565 - 21 Oct 2022
Cited by 15 | Viewed by 3445
Abstract
Takayasu arteritis (TAK) is a less common large vessel vasculitis where histopathology of involved arteries is difficult to access except during open surgical procedures. Assessment of disease activity in TAK, therefore, relies on surrogate measures. Clinical disease activity measures such as the National [...] Read more.
Takayasu arteritis (TAK) is a less common large vessel vasculitis where histopathology of involved arteries is difficult to access except during open surgical procedures. Assessment of disease activity in TAK, therefore, relies on surrogate measures. Clinical disease activity measures such as the National Institutes of Health (NIH) score, the Disease Extent Index in TAK (DEI.TAK) and the Indian TAK Clinical Activity Score (ITAS2010) inconsistently associate with acute phase reactants (APRs). Computerized tomographic angiography (CTA), magnetic resonance angiography (MRA), or color Doppler Ultrasound (CDUS) enables anatomical characterization of stenosis, dilatation, and vessel wall characteristics. Vascular wall uptake of 18-fluorodeoxyglucose or other ligands using positron emission tomography computerized tomography (PET-CT) helps assess metabolic activity, which reflects disease activity well in a subset of TAK with normal APRs. Angiographic scoring systems to quantitate the extent of vascular involvement in TAK have been developed recently. Erythrocyte sedimentation rate and C-reactive protein have a moderate performance in distinguishing active TAK. Numerous novel biomarkers are under evaluation in TAK. Limited literature suggests a better assessment of active disease by combining APRs, PET-CT, and circulating biomarkers. Validated damage indices and patient-reported outcome measures specific to TAK are lacking. Few biomarkers have been evaluated to reflect vascular damage in TAK and constitute important research agenda. Full article
(This article belongs to the Special Issue Challenges in the Diagnosis and Management of Autoimmune Diseases)
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14 pages, 679 KiB  
Article
Pulmonary Hypertension Associated Genetic Variants in Sarcoidosis Associated Pulmonary Hypertension
by Karlijn Groen, Marloes P. Huitema, Joanne J. van der Vis, Marco C. Post, Jan C. Grutters, Robert P. Baughman and Coline H. M. van Moorsel
Diagnostics 2022, 12(10), 2564; https://doi.org/10.3390/diagnostics12102564 - 21 Oct 2022
Cited by 2 | Viewed by 1525
Abstract
Background: Pulmonary hypertension (PH) is a severe complication of sarcoidosis in a minority of patients. Several genetic defects are known to cause hereditary or sporadic PH, but whether variants in PH-associated genes are also involved in sarcoidosis-associated PH (SAPH) is unknown. Methods: 40 [...] Read more.
Background: Pulmonary hypertension (PH) is a severe complication of sarcoidosis in a minority of patients. Several genetic defects are known to cause hereditary or sporadic PH, but whether variants in PH-associated genes are also involved in sarcoidosis-associated PH (SAPH) is unknown. Methods: 40 patients with SAPH were individually matched to 40 sarcoidosis patients without PH (SA). Whole exome sequencing was performed to identify rare genetic variants in a diagnostic PH gene panel of 13 genes. Additionally, an exploratory analysis was performed to search for other genes of interest. From 572 genes biologically involved in PH pathways, genes were selected in which at least 15% of the SAPH patients and no more than 5% of patients without PH carried a rare variant. Results: In the diagnostic PH gene panel, 20 different rare variants, of which 18 cause an amino-acid substitution, were detected in 23 patients: 14 SAPH patients carried a variant, as compared to 5 SA patients without PH (p = 0.018). Most variants were of yet unknown significance. The exploratory approach yielded five genes of interest. First, the NOTCH3 gene that was previously linked to PH, and furthermore PDE6B, GUCY2F, COL5A1, and MMP21. Conclusions: The increased frequency of variants in PH genes in SAPH suggests a mechanism whereby the presence of such a genetic variant in a patient may increase risk for the development of PH in the context of pulmonary sarcoidosis. Replication and studies into the functionality of the variants are required for further understanding the pathogenesis of SAPH. Full article
(This article belongs to the Special Issue Molecular Diagnosis of Interstitial Lung Disease)
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10 pages, 627 KiB  
Systematic Review
Wearable Technology for Monitoring Respiratory Rate and SpO2 of COVID-19 Patients: A Systematic Review
by Shizuko Takahashi, Eisuke Nakazawa, Sakurako Ichinohe, Aru Akabayashi and Akira Akabayashi
Diagnostics 2022, 12(10), 2563; https://doi.org/10.3390/diagnostics12102563 - 21 Oct 2022
Cited by 6 | Viewed by 2672
Abstract
With the significant numbers of sudden home deaths reported worldwide due to coronavirus disease 2019 (COVID-19), wearable technology has emerged as a method for surveilling this infection. This review explored the indicators of COVID-19 surveillance, such as vitals, respiratory condition, temperature, oxygen saturation [...] Read more.
With the significant numbers of sudden home deaths reported worldwide due to coronavirus disease 2019 (COVID-19), wearable technology has emerged as a method for surveilling this infection. This review explored the indicators of COVID-19 surveillance, such as vitals, respiratory condition, temperature, oxygen saturation (SpO2), and activity levels using wearable devices. Studies published between 31 December 2019, and 8 July 2022, were obtained from PubMed, and grey literature, reference lists, and key journals were also searched. All types of articles with the keywords “COVID-19”, “Diagnosis”, and “Wearable Devices” were screened. Four reviewers independently screened the articles against the eligibility criteria and extracted the data using a data charting form. A total of 56 articles were on monitoring, of which 28 included SpO2 as a parameter. Although wearable devices are effective in the continuous monitoring of COVID-19 patients, further research on actual patients is necessary to determine the efficiency and effectiveness of wearable technology before policymakers can mandate its use. Full article
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11 pages, 1572 KiB  
Article
Construction and Validation of Mortality Risk Nomograph Model for Severe/Critical Patients with COVID-19
by Li Cheng, Wen-Hui Bai, Jing-Jing Yang, Peng Chou, Wan-Shan Ning, Qiang Cai and Chen-Liang Zhou
Diagnostics 2022, 12(10), 2562; https://doi.org/10.3390/diagnostics12102562 - 21 Oct 2022
Cited by 3 | Viewed by 1275
Abstract
Objective: A nomograph model of mortality risk for patients with coronavirus disease 2019 (COVID-19) was established and validated. Methods: We collected the clinical medical records of patients with severe/critical COVID-19 admitted to the eastern campus of Renmin Hospital of Wuhan University from January [...] Read more.
Objective: A nomograph model of mortality risk for patients with coronavirus disease 2019 (COVID-19) was established and validated. Methods: We collected the clinical medical records of patients with severe/critical COVID-19 admitted to the eastern campus of Renmin Hospital of Wuhan University from January 2020 to May 2020 and to the north campus of Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, from April 2022 to June 2022. We assigned 254 patients to the former group, which served as the training set, and 113 patients were assigned to the latter group, which served as the validation set. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the variables and build the mortality risk prediction model. Results: The nomogram model was constructed with four risk factors for patient mortality following severe/critical COVID-19 (≥3 basic diseases, APACHE II score, urea nitrogen (Urea), and lactic acid (Lac)) and two protective factors (percentage of lymphocyte (L%) and neutrophil-to-platelets ratio (NPR)). The area under the curve (AUC) of the training set was 0.880 (95% confidence interval (95%CI), 0.837~0.923) and the AUC of the validation set was 0.814 (95%CI, 0.705~0.923). The decision curve analysis (DCA) showed that the nomogram model had high clinical value. Conclusion: The nomogram model for predicting the death risk of patients with severe/critical COVID-19 showed good prediction performance, and may be helpful in making appropriate clinical decisions for high-risk patients. Full article
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35 pages, 2904 KiB  
Systematic Review
Genetic Factors for Coronary Heart Disease and Their Mechanisms: A Meta-Analysis and Comprehensive Review of Common Variants from Genome-Wide Association Studies
by Khairul Anwar Zarkasi, Noraidatulakma Abdullah, Nor Azian Abdul Murad, Norfazilah Ahmad and Rahman Jamal
Diagnostics 2022, 12(10), 2561; https://doi.org/10.3390/diagnostics12102561 - 21 Oct 2022
Cited by 2 | Viewed by 2796
Abstract
Genome-wide association studies (GWAS) have discovered 163 loci related to coronary heart disease (CHD). Most GWAS have emphasized pathways related to single-nucleotide polymorphisms (SNPs) that reached genome-wide significance in their reports, while identification of CHD pathways based on the combination of all published [...] Read more.
Genome-wide association studies (GWAS) have discovered 163 loci related to coronary heart disease (CHD). Most GWAS have emphasized pathways related to single-nucleotide polymorphisms (SNPs) that reached genome-wide significance in their reports, while identification of CHD pathways based on the combination of all published GWAS involving various ethnicities has yet to be performed. We conducted a systematic search for articles with comprehensive GWAS data in the GWAS Catalog and PubMed, followed by a meta-analysis of the top recurring SNPs from ≥2 different articles using random or fixed-effect models according to Cochran Q and I2 statistics, and pathway enrichment analysis. Meta-analyses showed significance for 265 of 309 recurring SNPs. Enrichment analysis returned 107 significant pathways, including lipoprotein and lipid metabolisms (rs7412, rs6511720, rs11591147, rs1412444, rs11172113, rs11057830, rs4299376), atherogenesis (rs7500448, rs6504218, rs3918226, rs7623687), shared cardiovascular pathways (rs72689147, rs1800449, rs7568458), diabetes-related pathways (rs200787930, rs12146487, rs6129767), hepatitis C virus infection/hepatocellular carcinoma (rs73045269/rs8108632, rs56062135, rs188378669, rs4845625, rs11838776), and miR-29b-3p pathways (rs116843064, rs11617955, rs146092501, rs11838776, rs73045269/rs8108632). In this meta-analysis, the identification of various genetic factors and their associated pathways associated with CHD denotes the complexity of the disease. This provides an opportunity for the future development of novel CHD genetic risk scores relevant to personalized and precision medicine. Full article
(This article belongs to the Special Issue Risk Factors and Biomarkers for Cardiovascular Disease)
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11 pages, 1462 KiB  
Article
The Value of Deep Learning Image Reconstruction in Improving the Quality of Low-Dose Chest CT Images
by Jiu-Ming Jiang, Lei Miao, Xin Liang, Zhuo-Heng Liu, Li Zhang and Meng Li
Diagnostics 2022, 12(10), 2560; https://doi.org/10.3390/diagnostics12102560 - 21 Oct 2022
Cited by 3 | Viewed by 1726
Abstract
This study aimed to evaluate the value of the deep learning image reconstruction (DLIR) algorithm (GE Healthcare’s TrueFidelity™) in improving the image quality of low-dose computed tomography (LDCT) of the chest. First, we retrospectively extracted raw data of chest LDCT from 50 patients [...] Read more.
This study aimed to evaluate the value of the deep learning image reconstruction (DLIR) algorithm (GE Healthcare’s TrueFidelity™) in improving the image quality of low-dose computed tomography (LDCT) of the chest. First, we retrospectively extracted raw data of chest LDCT from 50 patients and reconstructed them by using model-based adaptive statistical iterative reconstruction-Veo at 50% (ASIR-V 50%) and DLIR at medium and high strengths (DLIR-M and DLIR-H). Three sets of images were obtained. Next, two radiographers measured the mean CT value/image signal and standard deviation (SD) in Hounsfield units at the region of interest (ROI) and calculated the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Two radiologists subjectively evaluated the image quality using a 5-point Likert scale. The differences between the groups of data were analyzed through a repeated measures ANOVA or the Friedman test. Last, our result show that the three reconstructions did not differ significantly in signal (p > 0.05) but had significant differences in noise, SNR, and CNR (p < 0.001). The subjective scores significantly differed among the three reconstruction modalities in soft tissue (p < 0.001) but not in lung tissue (p > 0.05). DLIR-H had the best noise reduction ability and improved SNR and CNR without distorting the image texture, followed by DLIR-M and ASIR-V 50%. In summary, DLIR can provide a higher image quality at the same dose, enhancing the physicians’ diagnostic confidence and improving the diagnostic efficacy of LDCT for lung cancer screening. Full article
(This article belongs to the Special Issue Advances in Lung Imaging)
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10 pages, 1713 KiB  
Case Report
A Diagnostic of Acquired Hemophilia Following PD1/PDL1 Inhibitors in Advanced Melanoma: The Experience of Two Patients and a Literature Review
by Antonio Gidaro, Giuseppe Palmieri, Mattia Donadoni, Lucia A. Mameli, Leyla La Cava, Giuseppe Sanna, Dante Castro, Alessandro P. Delitala, Roberto Manetti and Roberto Castelli
Diagnostics 2022, 12(10), 2559; https://doi.org/10.3390/diagnostics12102559 - 21 Oct 2022
Cited by 6 | Viewed by 1929
Abstract
Acquired hemophilia A (AHA) is a rare bleeding disorder caused by the development of specific autoantibodies against factor VIII (FVIII). Immunotherapy is a recent therapeutic option that targets the patient’s self-tolerance against tumor cells. Because therapeutic effects of the immune checkpoint inhibitors (ICIs) [...] Read more.
Acquired hemophilia A (AHA) is a rare bleeding disorder caused by the development of specific autoantibodies against factor VIII (FVIII). Immunotherapy is a recent therapeutic option that targets the patient’s self-tolerance against tumor cells. Because therapeutic effects of the immune checkpoint inhibitors (ICIs) are mediated by enhancing the immune response to restore antitumor immunity, autoimmune-related adverse effects can be seen in up to 80% of patients during treatment and after treatment. A rare hematologic ICIs-related adverse event is AHA. Hereafter we report two cases of AHA developed during anti-PD-1 immunotherapy for advanced melanoma: one secondary to treatment with nivolumab and one secondary to pembrolizumab. Both patients were treated with activated FVII (Novoseven®, Novo Nordisk, Bagsværd, Denmark) as hemostatic treatment combined with the eradication of antibodies anti-FVIII obtained with rituximab. In the last few years these drugs have significantly improved the therapeutic armamentarium for the management of AHA. Indeed, while FVIIa has proven to be an effective and safe tool for the treatment of acute bleeding related to FVIII autoantibodies, rituximab is a promising alternative for the autoantibodies’ elimination and the restoration of normal hemostasis. Our finding supports the use of this combination even in AHA secondary to ICIs treatment. Full article
(This article belongs to the Collection Vascular Diseases Diagnostics)
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11 pages, 2102 KiB  
Article
Multiregional Radiomic Signatures Based on Functional Parametric Maps from DCE-MRI for Preoperative Identification of Estrogen Receptor and Progesterone Receptor Status in Breast Cancer
by Shiling Zhong, Fan Wang, Zhiying Wang, Minghui Zhou, Chunli Li and Jiandong Yin
Diagnostics 2022, 12(10), 2558; https://doi.org/10.3390/diagnostics12102558 - 21 Oct 2022
Cited by 6 | Viewed by 1652
Abstract
Radiomics based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been used for breast estrogen receptor (ER) and progesterone receptor (PR) status evaluation. However, the radiomic features of peritumoral regions were not thoroughly analyzed. This study aimed to establish and validate the multiregional [...] Read more.
Radiomics based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been used for breast estrogen receptor (ER) and progesterone receptor (PR) status evaluation. However, the radiomic features of peritumoral regions were not thoroughly analyzed. This study aimed to establish and validate the multiregional radiomic signatures (RSs) for the preoperative identification of the ER and PR status in breast cancer. A total of 443 patients with breast cancer were divided into training (n = 356) and validation (n = 87) sets. Radiomic features were extracted from intra- and peritumoral regions on six functional parametric maps from DCE-MRI. A two-sample t-test, least absolute shrinkage and selection operator regression, and stepwise were used for feature selections. Three RSs for predicting the ER and PR status were constructed using a logistic regression model based on selected intratumoral, peritumoral, and combined intra- and peritumoral radiomic features. The area under the receiver operator characteristic curve (AUC) was used to assess the discriminative performance of three RSs. The AUCs of intra- and peritumoral RSs for identifying the ER status were 0.828/0.791 and 0.755/0.733 in the training and validation sets, respectively. For predicting the PR status, intra- and peritumoral RSs resulted in AUCs of 0.816/0.749 and 0.806/0.708 in the training and validation sets, respectively. Multiregional RSs achieved the best AUCs among three RSs for evaluating the ER (0.851 and 0.833) and PR (0.848 and 0.763) status. In conclusion, multiregional RSs based on functional parametric maps from DCE-MRI showed promising results for preoperatively evaluating the ER and PR status in breast cancer patients. Further studies using a larger cohort from multiple centers are necessary to confirm the reliability of the established models before clinical application. Full article
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6 pages, 233 KiB  
Communication
Groin Puncture to Recanalization Time May Be a Strong Predictor of mTICI 2c/3 over mTICI 2b in Patients with Large Vessel Occlusions Successfully Recanalized with Mechanical Thrombectomy
by Richard Wang, Alperen Aslan, Neda Khalili, Tushar Garg, Apoorva Kotha, Omar Hamam, Meisam Hoseinyazdi and Vivek Yedavalli
Diagnostics 2022, 12(10), 2557; https://doi.org/10.3390/diagnostics12102557 - 21 Oct 2022
Cited by 1 | Viewed by 1434
Abstract
Mechanical thrombectomy (MT) is an important therapeutic option in the management of acute ischemic stroke (AIS) caused by large vessel occlusions (LVO). While achieving a modified thrombolysis in cerebral infarction (mTICI), grades of 2b, 2c, and 3 are all considered successful recanalization; recent [...] Read more.
Mechanical thrombectomy (MT) is an important therapeutic option in the management of acute ischemic stroke (AIS) caused by large vessel occlusions (LVO). While achieving a modified thrombolysis in cerebral infarction (mTICI), grades of 2b, 2c, and 3 are all considered successful recanalization; recent literature suggests that mTICI grades of 2c/3 are associated with superior outcomes than 2b. The aim of this preliminary study is to determine whether any baseline or procedural parameters can predict whether successfully recanalized patients achieve an mTICI grade of 2c/3 over 2b. Consecutive patients from 9/2019 to 10/2021 who were successfully recanalized following MT for confirmed LVO were included in the study. Baseline and procedural data were collected through manual chart review and analyzed to ascertain whether any variables of interest could predict mTICI 2c/3. A total of 47 patients were included in the preliminary study cohort, with 35 (74.5%) achieving an mTICI score of 2c/3 and 12 (25.5%) achieving an mTICI score of 2b. We found that a lower groin puncture to recanalization time was a strong, independent predictor of TICI 2c/3 (p = 0.015). These findings emphasize the importance of minimizing procedure time in achieving superior reperfusion but must be corroborated in larger scale studies. Full article
(This article belongs to the Special Issue Advances in the Diagnosis of Nervous System Diseases)
14 pages, 577 KiB  
Article
Platelet-to-White Blood Cell Ratio: A Feasible Biomarker for Pyogenic Liver Abscess
by Dong-Gyun Ko, Ji-Won Park, Jung-Hee Kim, Jang-Han Jung, Hyoung-Su Kim, Ki-Tae Suk, Myoung-Kuk Jang, Sang-Hoon Park, Myung-Seok Lee, Dong-Joon Kim and Sung-Eun Kim
Diagnostics 2022, 12(10), 2556; https://doi.org/10.3390/diagnostics12102556 - 21 Oct 2022
Cited by 5 | Viewed by 1731
Abstract
The platelet-to-white blood cell ratio (PWR) has been reported to predict the severity of patients with various diseases. However, no previous studies have assessed the use of the PWR as a prognostic marker for pyogenic liver abscesses (PLA). This observational retrospective study was [...] Read more.
The platelet-to-white blood cell ratio (PWR) has been reported to predict the severity of patients with various diseases. However, no previous studies have assessed the use of the PWR as a prognostic marker for pyogenic liver abscesses (PLA). This observational retrospective study was performed between January 2008 and December 2017, including 833 patients with PLA from multiple centers. The enrolled patients, on average, had a PWR of 17.05, and 416 patients had a PWR lower than 17.05. A total of 260 patients (31.2%) with PLA showed complications of metastatic infection, pleural effusion and abscess rupture. A low PWR level was identified as a strong risk factor for metastatic infection and pleural effusion. The low PWR group also had a longer hospital stay. In the multivariate analysis, old age, anemia, albumin and CRP levels and unidentified pathogens were significant factors for low PWR levels. A low PWR, old age, male sex, abscess size, albumin, ALP and unidentified causative pathogens showed significant associations with a hospital stay longer than 28 days. As a result, PLA patients presenting with a low PWR were shown to have more complications and a poor prognosis. Considering its cost-effectiveness, PWR could be a novel biomarker used to predict a prognosis of PLA. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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5 pages, 190 KiB  
Viewpoint
Need to Introduce the Finding of Obesity or Normal Body Weight in the Current Diagnostic Criteria and in the Classification of PCOS
by Enrico Carmina
Diagnostics 2022, 12(10), 2555; https://doi.org/10.3390/diagnostics12102555 - 21 Oct 2022
Cited by 2 | Viewed by 1422
Abstract
The diagnosis of PCOS is based on the Rotterdam guidelines: chronic anovulation, hyperandrogenism (biologic or clinical) and polycystic ovaries on ultrasound. Two of these three criteria are sufficient for making diagnosis of PCOS. However, one characteristic that is often associated to PCOS (obesity [...] Read more.
The diagnosis of PCOS is based on the Rotterdam guidelines: chronic anovulation, hyperandrogenism (biologic or clinical) and polycystic ovaries on ultrasound. Two of these three criteria are sufficient for making diagnosis of PCOS. However, one characteristic that is often associated to PCOS (obesity with severe insulin resistance and metabolic alteration regarding glucose metabolism and lipid pattern) has remained out of the current classification of PCOS. Because of this, patients with different metabolic and cardiovascular risk may be included in the same phenotype, and it makes more difficult to establish clear strategies of follow-up and treatment of the patients with increased risks, and also may hide genetic or environmental differences between PCOS patients. Our recent study has shown that metabolic alterations are linked to the weight and not to the Rotterdam phenotypes. Because of this, we suggest a new classification of PCOS phenotypes that divides each Rotterdam phenotype in obese (ob) or lean (l) sub-phenotype. An improved classification of PCOS may be essential for permitting new progress in our understanding of pathogenesis and treatment of PCOS (or of the different disorders that are part of PCOS). Full article
9 pages, 1623 KiB  
Article
Calprotectin Levels and Neutrophil Count Are Prognostic Markers of Mortality in COVID-19 Patients
by Giovanna Cardiero, Daniela Palma, Martina Vano, Claudia Anastasio, Biagio Pinchera, Martina Ferrandino, Carlo Gianfico, Luca Gentile, Marcella Savoia, Ivan Gentile, Maria Donata Di Taranto and Giuliana Fortunato
Diagnostics 2022, 12(10), 2554; https://doi.org/10.3390/diagnostics12102554 - 20 Oct 2022
Cited by 5 | Viewed by 1566
Abstract
Inflammation plays a crucial role in worsening coronavirus disease (COVID-19). Calprotectin is a pro-inflammatory molecule produced by monocytes and neutrophilic granulocytes. The aim of the study was to evaluate both the prognostic role of circulating calprotectin levels and neutrophil count toward fatal outcome [...] Read more.
Inflammation plays a crucial role in worsening coronavirus disease (COVID-19). Calprotectin is a pro-inflammatory molecule produced by monocytes and neutrophilic granulocytes. The aim of the study was to evaluate both the prognostic role of circulating calprotectin levels and neutrophil count toward fatal outcome in COVID-19 patients. We retrospectively collected and analyzed data on 195 COVID-19 adult patients, 156 hospitalized in the infectious disease unit and 39 in the intensive care unit (ICU). Calprotectin levels and neutrophil counts measured at the first hospitalization day were higher in the patients with a fatal outcome than in surviving ones. The association of high calprotectin levels and neutrophil count to patient death remain significant by logistic regression, independent of patient age. ROC curves analysis for calprotectin levels and neutrophil count revealed a good discriminatory power toward survival (area under the curve of 0.759 and 0.843, respectively) and identified the best cut-off (1.66 mg/L and 16.39 × 103/µL, respectively). Kaplan–Meier analysis confirmed the prognostic role of high calprotectin levels and neutrophil count in death prediction. In conclusion, this study highlights that calprotectin levels together with neutrophil count should be considered as biomarkers of mortality in COVID-19 patients. Full article
(This article belongs to the Special Issue Molecular Diagnostics of Emerging Pathogens for Infectious Diseases)
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6 pages, 2053 KiB  
Interesting Images
Ultrasound-Guided Radiofrequency Ablation for Primary Hyperparathyroidism Induced by Multiple Endocrine Neoplasia 1—A Case Report
by Zhenping Han, Tingting Li, Siyi Wang, Li Gao, Ying Hu, Yu Zhao and Jieping Yan
Diagnostics 2022, 12(10), 2553; https://doi.org/10.3390/diagnostics12102553 - 20 Oct 2022
Cited by 1 | Viewed by 1259
Abstract
Multiple endocrine neoplasia type 1 (MEN1) is a syndrome characterized by the occurrence of two or more endocrine gland tumors. Here, we show a case of a 52-year-old man diagnosed with MEN1 through gastrinoma, parathyroid adenoma and gene detection. The MEN1 patient’s case [...] Read more.
Multiple endocrine neoplasia type 1 (MEN1) is a syndrome characterized by the occurrence of two or more endocrine gland tumors. Here, we show a case of a 52-year-old man diagnosed with MEN1 through gastrinoma, parathyroid adenoma and gene detection. The MEN1 patient’s case was complicated with relapsed primary hyperparathyroidism (PHPT), and they received ultrasound-guided radiofrequency ablation (RFA). The patient had a remarkable recovery after RFA treatment for the relapsed PHPT. It might be an alternative treatment for MEN1 patients with poor conditions such as high surgical risk, unwillingness to choose parathyroid surgery or those unable to tolerate surgery. Individualized therapy significantly benefits the prognosis of MEN1 patients. Full article
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14 pages, 1109 KiB  
Article
Reference Intervals for Coagulation Parameters in Developmental Hemostasis from Infancy to Adolescence
by Giovina Di Felice, Matteo Vidali, Gelsomina Parisi, Simona Pezzi, Alessandra Di Pede, Giulia Deidda, Matteo D’Agostini, Michaela Carletti, Stefano Ceccarelli and Ottavia Porzio
Diagnostics 2022, 12(10), 2552; https://doi.org/10.3390/diagnostics12102552 - 20 Oct 2022
Cited by 3 | Viewed by 1859
Abstract
Background: The objective of this study was to establish the age and sex-dependent reference intervals for coagulation assays evaluated in healthy children, ranging from 0 days to 16 years old. Methods: PT, aPTT, Fibrinogen (functional), Antithrombin activity, Protein C anticoagulant activity, [...] Read more.
Background: The objective of this study was to establish the age and sex-dependent reference intervals for coagulation assays evaluated in healthy children, ranging from 0 days to 16 years old. Methods: PT, aPTT, Fibrinogen (functional), Antithrombin activity, Protein C anticoagulant activity, Protein S free antigen, Thrombin time, D-Dimer, Von Willebrand Factor antigen, Lupus anticoagulant (screening), extrinsic and intrinsic pathway factors, and activated Protein C resistance were evaluated using STA-R Max2. Results: A total of 1280 subjects (671 males and 609 females) were divided into five groups, according to their age: 0–15 days (n = 280, 174 M and 106 F), 15–30 days (n = 208, 101 M and 107 F), 1–6 months (n = 369, 178 M and 191 F), 6–12 months (n = 214, 110 M and 104 F), and 1–16 years (n = 209, 108 M and 101 F). The 95% reference intervals and the 90% CI were established using the Harrell–Davis bootstrap method and the bootstrap percentile method, respectively. Conclusions: The present study supports the concept that adult and pediatric subjects should be evaluated using different reference intervals, at least for some coagulation tests, to avoid misdiagnosis, which can potentially lead to serious consequences for patients and their families, and ultimately the healthcare system. Full article
(This article belongs to the Special Issue New Assays in the Diagnosis of Coagulation Protein Disorders)
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13 pages, 3666 KiB  
Article
Use of a Small Car-Mounted Magnetic Resonance Imaging System for On-Field Screening for Osteochondritis Dissecans of the Humeral Capitellum
by Kazuhiro Ikeda, Yoshikazu Okamoto, Takeshi Ogawa, Yasuhiko Terada, Michiru Kajiwara, Tomoki Miyasaka, Ryuhei Michinobu, Yuki Hara, Yuichi Yoshii, Takahito Nakajima and Masashi Yamazaki
Diagnostics 2022, 12(10), 2551; https://doi.org/10.3390/diagnostics12102551 - 20 Oct 2022
Cited by 2 | Viewed by 1632
Abstract
Mobile magnetic resonance imaging (MRI) using a car is a recent advancement in imaging technology. Specifically, a car-mounted mobile MRI system is expected to be used for medical check-ups; however, this is still in the research stage. This study demonstrated the practicality of [...] Read more.
Mobile magnetic resonance imaging (MRI) using a car is a recent advancement in imaging technology. Specifically, a car-mounted mobile MRI system is expected to be used for medical check-ups; however, this is still in the research stage. This study demonstrated the practicality of a small car-mounted mobile MRI in on-field screening for osteochondritis dissecans (OCD) of the humeral capitellum. In the primary check-up, we screened the throwing elbows of 151 young baseball players using mobile MRI and ultrasonography. We definitively diagnosed OCD at the secondary check-up using X-ray photography and computed tomography or MRI. We investigated the sensitivity and specificity of mobile MRI and ultrasonography for OCD. Six patients were diagnosed with OCD. The sensitivity was 83.3% for mobile MRI and 66.7% for ultrasonography, with specificity of 99.3% vs. 100%, respectively. One patient was detected using ultrasonography but was missed by mobile MRI due to poor imaging quality at the first medical check-up. Following this false-negative case, we replaced a damaged radio frequency coil to improve the image quality, and the mobile MRI could detect all subsequent OCD cases. Two patients were diagnosed by mobile MRI only; ultrasonography missed cases lacking subchondral bone irregularity, such as a healing case, and an early-stage case. Mobile MRI could screen for OCD from the very early stages through the healing process and is therefore a practical tool for on-field screening. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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8 pages, 1507 KiB  
Communication
Isolation and Quantification of Plasma Cell-Free DNA Using Different Manual and Automated Methods
by Eleni Polatoglou, Zsuzsanna Mayer, Vida Ungerer, Abel J. Bronkhorst and Stefan Holdenrieder
Diagnostics 2022, 12(10), 2550; https://doi.org/10.3390/diagnostics12102550 - 20 Oct 2022
Cited by 10 | Viewed by 3269
Abstract
Plasma cell-free DNA (cfDNA) originates from various tissues and cell types and can enable minimally invasive diagnosis, treatment and monitoring of cancer and other diseases. Proper extraction of cfDNA is critical to obtain optimal yields and purity. The goal of this study was [...] Read more.
Plasma cell-free DNA (cfDNA) originates from various tissues and cell types and can enable minimally invasive diagnosis, treatment and monitoring of cancer and other diseases. Proper extraction of cfDNA is critical to obtain optimal yields and purity. The goal of this study was to compare the performance of six commercial cfDNA kits to extract pure, high-quality cfDNA from human plasma samples and evaluate the quantity and size profiles of cfDNA extracts—among them, two spin-column based, three magnetic bead-based and two automatic magnetic bead-based methods. Significant differences were observed in the yield of DNA among the different extraction kits (up to 4.3 times), as measured by the Qubit Fluorometer and Bioanalyzer. All kits isolated mostly small fragments corresponding to mono-nucleosomal sizes. The highest yield and reproducibility were obtained by the manual QIAamp Circulating Nucleic Acid Kit and automated MagNA Pure Total NA Isolation Kit. The results highlight the importance of standardizing preanalytical conditions depending on the requirements of the downstream applications. Full article
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34 pages, 4532 KiB  
Review
Demystifying Supervised Learning in Healthcare 4.0: A New Reality of Transforming Diagnostic Medicine
by Sudipta Roy, Tanushree Meena and Se-Jung Lim
Diagnostics 2022, 12(10), 2549; https://doi.org/10.3390/diagnostics12102549 - 20 Oct 2022
Cited by 69 | Viewed by 5299
Abstract
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare industry still uses labor-intensive, time-consuming, and error-prone traditional, manual, and manpower-based methods. This review addresses [...] Read more.
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare industry still uses labor-intensive, time-consuming, and error-prone traditional, manual, and manpower-based methods. This review addresses the current paradigm, the potential for new scientific discoveries, the technological state of preparation, the potential for supervised machine learning (SML) prospects in various healthcare sectors, and ethical issues. The effectiveness and potential for innovation of disease diagnosis, personalized medicine, clinical trials, non-invasive image analysis, drug discovery, patient care services, remote patient monitoring, hospital data, and nanotechnology in various learning-based automation in healthcare along with the requirement for explainable artificial intelligence (AI) in healthcare are evaluated. In order to understand the potential architecture of non-invasive treatment, a thorough study of medical imaging analysis from a technical point of view is presented. This study also represents new thinking and developments that will push the boundaries and increase the opportunity for healthcare through AI and SML in the near future. Nowadays, SML-based applications require a lot of data quality awareness as healthcare is data-heavy, and knowledge management is paramount. Nowadays, SML in biomedical and healthcare developments needs skills, quality data consciousness for data-intensive study, and a knowledge-centric health management system. As a result, the merits, demerits, and precautions need to take ethics and the other effects of AI and SML into consideration. The overall insight in this paper will help researchers in academia and industry to understand and address the future research that needs to be discussed on SML in the healthcare and biomedical sectors. Full article
(This article belongs to the Special Issue Deep Learning Models for Medical Imaging Processing)
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11 pages, 852 KiB  
Article
Low Arousal Threshold Estimation Predicts Failure of Mandibular Advancement Devices in Obstructive Sleep Apnea Syndrome
by Caterina Antonaglia, Gabriele Vidoni, Luca Contardo, Fabiola Giudici, Francesco Salton, Barbara Ruaro, Marco Confalonieri and Martina Caneva
Diagnostics 2022, 12(10), 2548; https://doi.org/10.3390/diagnostics12102548 - 20 Oct 2022
Cited by 5 | Viewed by 1693
Abstract
Introduction: The treatment of choice for obstructive sleep apnea syndrome (OSAS) is continuous positive airway pressure (CPAP). However, CPAP is usually poorly tolerated and mandibular advancement devices (MADs) are an alternative innovative therapeutic approach. Uncertainty still remains as to the most suitable candidates [...] Read more.
Introduction: The treatment of choice for obstructive sleep apnea syndrome (OSAS) is continuous positive airway pressure (CPAP). However, CPAP is usually poorly tolerated and mandibular advancement devices (MADs) are an alternative innovative therapeutic approach. Uncertainty still remains as to the most suitable candidates for MAD. Herein, it is hypothesized that the presence of low arousal threshold (low ArTH) could be predictive of MAD treatment failure. Methods: A total of 32 consecutive patients, with OSAS of any severity, who preferred an alternate therapy to CPAP, were treated with a tailored MAD aimed at obtaining 50% of their maximal mandibular advancement. Treatment response after 6 months of therapy was defined as AHI < 5 events per hour or a reduction of AHI ≥ 50% from baseline. Low ArTH was predicted based on the following polysomnography features, as previously shown by Edwards et al.: an AHI of 82.5% and a hypopnea fraction of total respiratory events of >58.3%. Results: There were 25 (78.1%) responders (p-value < 0.01) at 6 months. Thirteen patients (40.6%) in the non-severe group reached AHI lower than 5 events per hour. MAD treatment significantly reduced the median AHI in all patients from a median value of 22.5 to 6.5 (74.7% of reduction, p-value < 0.001). The mandibular advancement device reduced AHI, whatever the disease severity. A significant higher reduction of Delta AHI, after 6 months of treatment, was found for patients without low ArTH. Conclusions: Low ArTH at baseline was associated with a poorer response to MAD treatment and a lower AHI reduction at 6 months. A non-invasive assessment of Low ArTH can be performed through the Edwards’ score, which could help to identify an endotype with a lower predicted response to oral appliances in a clinical setting. Full article
(This article belongs to the Topic Diagnostic Imaging in Oral and Maxillofacial Diseases)
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10 pages, 633 KiB  
Article
Prognostic Impact of EBUS TBNA for Lung Adenocarcinoma Patients with Postoperative Recurrences
by Ying-Yi Chen, Ying-Shian Chen and Tsai-Wang Huang
Diagnostics 2022, 12(10), 2547; https://doi.org/10.3390/diagnostics12102547 - 20 Oct 2022
Cited by 1 | Viewed by 1142
Abstract
Background: The aim of this study was to verify the importance and the timing of endobronchial ultrasound with transbronchial biopsy (EBUS TBNA) among lung adenocarcinoma patients after radical resection. Methods: We retrospectively reviewed consecutive patients with non-small cell lung cancer (NSCLC) who had [...] Read more.
Background: The aim of this study was to verify the importance and the timing of endobronchial ultrasound with transbronchial biopsy (EBUS TBNA) among lung adenocarcinoma patients after radical resection. Methods: We retrospectively reviewed consecutive patients with non-small cell lung cancer (NSCLC) who had ever received radical resection from January 2002 to December 2021. The patients were divided into two groups, with and without EBUS TBNA, for diagnosis or staging. Results: Of 2018 patients with NSCLC, after surgical resection of lung tumors, there were 232 with recurrences. Under multivariate Cox regression analysis, patients with recurrences who received EBUS TBNA had a statistically higher mean maximum standardized uptake value (SUVmax) (hazard ratio (HR) = 1.115, confidence interval (CI) = 1.004–1.238, p = 0.042) and better survival (HR = 5.966, CI = 1.473–24.167, p = 0.012). Although KM survival analysis showed no statistically significant difference between groups with and without EBUS TBNA (p = 0.072) of lung adenocarcinoma patients with recurrences, patients with mutated epidermal growth factor receptor (EGFR) showed significantly better survival than wild-type EGFR (p = 0.007). Conclusions: The clinical practice of EBUS TBNA is not only for diagnosis, but also for nodal staging. We found that lung adenocarcinoma patients with recurrences who received EBUS TBNA had better overall survival. Therefore, EBUS TBNA is a reliable and feasible tool that could be used in lung adenocarcinoma patients with recurrences for early diagnosis and for adequate tissue specimens for further molecular analysis. Full article
(This article belongs to the Special Issue Ultrasound-Guided Diagnosis of Lung Cancer)
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10 pages, 2075 KiB  
Article
Influence of Medial Osteotomy Height and Hinge Position in Open Wedge High Tibial Osteotomy: A Simulation Study
by Grégoire Thürig, Alexander Korthaus, Jannik Frings, Markus Thomas Berninger, Karl-Heinz Frosch and Matthias Krause
Diagnostics 2022, 12(10), 2546; https://doi.org/10.3390/diagnostics12102546 - 20 Oct 2022
Cited by 1 | Viewed by 1578
Abstract
(1) Background: In treating medial unicompartmental gonarthrosis, medial open wedge high tibial osteotomy (mOWHTO) reduces pain and is intended to delay a possible indication for joint replacement by relieving the affected compartment. This study aimed to investigate the influence of the osteotomy height [...] Read more.
(1) Background: In treating medial unicompartmental gonarthrosis, medial open wedge high tibial osteotomy (mOWHTO) reduces pain and is intended to delay a possible indication for joint replacement by relieving the affected compartment. This study aimed to investigate the influence of the osteotomy height with different hinge points in HTO in genu varum on the leg axis. (2) Methods: Fifty-five patients with varus lower leg alignment obtained full-weight bearing long-leg radiographs were analyzed. Different simulations were performed: Osteotomy height was selected at 3 and 4 cm distal to the tibial articular surface, and the hinge points were selected at 0.5 cm, 1 cm, and 1.5 cm medial to the fibular head, respectively. The target of each correction was 55% of the tibial plateau measured from the medial. Then, the width of the opening wedge was measured. Intraobserver and interobserver reliability were calculated. (3) Results: Statistically significant differences in wedge width were seen at an osteotomy height of 3 cm below the tibial plateau when the distance of the hinge from the fibular head was 0.5 cm to 1.5 cm (3 cm and 0.5 cm: 8.9 +/− 3.88 vs. 3 cm and 1.5 cm: 11.6 +/− 4.39 p = 0.012). Statistically significant differences were also found concerning the wedge width between the distances 0.5 to 1.5 cm from the fibular head at the osteotomy height of 4 cm below the tibial plateau. (4 cm and 0.5 cm: 9.0 +/− 3.76 vs. 4 cm and 1.5 cm: 11.4 +/− 4.27 p = 0.026). (4) Conclusion: A change of the lateral hinge position of 1 cm results in a change in wedge width of approximately 2 mm. If hinge positions are chosen differently in preoperative planning and intraoperatively, the result can lead to over- or under-correction. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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10 pages, 534 KiB  
Article
A Nomogram for Predicting Prostate Cancer with Lymph Node Involvement in Robot-Assisted Radical Prostatectomy Era: A Retrospective Multicenter Cohort Study in Japan (The MSUG94 Group)
by Makoto Kawase, Shin Ebara, Tomoyuki Tatenuma, Takeshi Sasaki, Yoshinori Ikehata, Akinori Nakayama, Masahiro Toide, Tatsuaki Yoneda, Kazushige Sakaguchi, Takuma Ishihara, Jun Teishima, Kazuhide Makiyama, Takahiro Inoue, Hiroshi Kitamura, Kazutaka Saito, Fumitaka Koga, Shinji Urakami and Takuya Koie
Diagnostics 2022, 12(10), 2545; https://doi.org/10.3390/diagnostics12102545 - 20 Oct 2022
Cited by 3 | Viewed by 3114
Abstract
Background: To create a nomogram for predicting prostate cancer (PCa) with lymph node involvement (LNI) in the robot-assisted radical prostatectomy (RARP) era. Methods: A retrospective multicenter cohort study was conducted on 3195 patients with PCa who underwent RARP at nine institutions in Japan [...] Read more.
Background: To create a nomogram for predicting prostate cancer (PCa) with lymph node involvement (LNI) in the robot-assisted radical prostatectomy (RARP) era. Methods: A retrospective multicenter cohort study was conducted on 3195 patients with PCa who underwent RARP at nine institutions in Japan between September 2012 and August 2021. A multivariable logistic regression model was used to identify factors strongly associated with LNI. The Bootstrap-area under the curve (AUC) was calculated to assess the internal validity of the prediction model. Results: A total of 1855 patients were enrolled in this study. Overall, 93 patients (5.0%) had LNI. On multivariable analyses, initial prostate-specific antigen, number of cancer-positive and-negative biopsy cores, biopsy Gleason grade, and clinical T stage were independent predictors of PCa with LNI. The nomogram predicting PCa with LNI has been demonstrated (AUC 84%). Using a nomogram cut-off of 6%, 492 of 1855 patients (26.5%) would avoid unnecessary pelvic lymph node dissection, and PCa with LNI would be missed in two patients (0.1%). The sensitivity, specificity, and negative predictive values associated with a cutoff of 6% were 74%, 80%, and 99.6%, respectively. Conclusions: We developed a clinically applicable nomogram for predicting the probability of patients with PCa with LNI. Full article
(This article belongs to the Special Issue Advances in the Diagnosis and Management of Prostate Cancer)
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14 pages, 972 KiB  
Article
TMP19: A Novel Ternary Motif Pattern-Based ADHD Detection Model Using EEG Signals
by Prabal Datta Barua, Sengul Dogan, Mehmet Baygin, Turker Tuncer, Elizabeth Emma Palmer, Edward J. Ciaccio and U. Rajendra Acharya
Diagnostics 2022, 12(10), 2544; https://doi.org/10.3390/diagnostics12102544 - 20 Oct 2022
Cited by 7 | Viewed by 2125
Abstract
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental condition worldwide. In this research, we used an ADHD electroencephalography (EEG) dataset containing more than 4000 EEG signals. Moreover, these EEGs are noisy signals. A new hand-modeled EEG classification model has been proposed to [...] Read more.
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental condition worldwide. In this research, we used an ADHD electroencephalography (EEG) dataset containing more than 4000 EEG signals. Moreover, these EEGs are noisy signals. A new hand-modeled EEG classification model has been proposed to separate healthy versus ADHD individuals using the EEG signals. In this model, a new ternary motif pattern (TMP) has been incorporated. We have mimicked deep learning networks to create this hand-modeled classification method. The Tunable Q Wavelet Transform (TQWT) has been utilized to generate wavelet subbands. We applied the proposed TMP and statistics to construct informative features from both raw EEG signals and wavelet bands by generating TQWT. Herein, features have been generated by 18 subbands and the original EEG signal. Thus, this model is named TMP19. The most informative features have been chosen by deploying neighborhood component analysis (NCA), and the selected features have been classified using the k-nearest neighbor (kNN) classifier. The used ADHD EEG dataset has 14 channels. Thus, these three phases—(i) feature extraction with TQWT, TMP, and statistics; (ii) feature selection by deploying NCA; and (iii) classification with kNN—have been applied to each channel. Iterative hard majority voting (IHMV) has been applied to obtain a higher and more general classification response. Our model attained 95.57% and 77.93% classification accuracies by deploying 10-fold and leave one subject out (LOSO) cross-validations, respectively. Full article
(This article belongs to the Special Issue Artificial Intelligence in Medical Signal Processing and Analysis)
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19 pages, 3231 KiB  
Review
Multimodality Imaging of Benign Primary Cardiac Tumor
by Yixia Lin, Wenqian Wu, Lang Gao, Mengmeng Ji, Mingxing Xie and Yuman Li
Diagnostics 2022, 12(10), 2543; https://doi.org/10.3390/diagnostics12102543 - 20 Oct 2022
Cited by 10 | Viewed by 2754
Abstract
Primary cardiac tumors (PCTs) are rare, with benign PCTs being relatively common in approximately 75% of all PCTs. Benign PCTs are usually asymptomatic, and they are found incidentally by imaging. Even if patients present with symptoms, they are usually nonspecific. Before the application [...] Read more.
Primary cardiac tumors (PCTs) are rare, with benign PCTs being relatively common in approximately 75% of all PCTs. Benign PCTs are usually asymptomatic, and they are found incidentally by imaging. Even if patients present with symptoms, they are usually nonspecific. Before the application of imaging modalities to the heart, our understanding of these tumors is limited to case reports and autopsy studies. The advent and improvement of various imaging technologies have enabled the non-invasive evaluation of benign PCTs. Although echocardiography is the most commonly used imaging examination, it is not the best method to describe the histological characteristics of tumors. At present, cardiac magnetic resonance (CMR) and cardiac computed tomography (CCT) are often used to assess benign PCTs providing detailed information on anatomical and tissue features. In fact, each imaging modality has its own advantages and disadvantages, multimodality imaging uses two or more imaging types to provide valuable complementary information. With the widespread use of multimodality imaging, these techniques play an indispensable role in the management of patients with benign PCTs by providing useful diagnostic and prognostic information to guide treatment. This article reviews the multimodality imaging characterizations of common benign PCTs. Full article
(This article belongs to the Special Issue Noninvasive Diagnosis of Cardiac Tumors)
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11 pages, 14216 KiB  
Article
Dual-Energy CT for Accurate Discrimination of Intraperitoneal Hematoma and Intestinal Structures
by Moritz T. Winkelmann, Florian Hagen, Kerstin Artzner, Malte N. Bongers and Christoph Artzner
Diagnostics 2022, 12(10), 2542; https://doi.org/10.3390/diagnostics12102542 - 20 Oct 2022
Cited by 4 | Viewed by 1349
Abstract
The purpose of this study was to evaluate the potential of dual-energy CT (DECT) with virtual unenhanced imaging (VNC) and iodine maps (IM) to differentiate between intraperitoneal hematomas (IH) and bowel structures (BS) compared to linearly blended DECT (DE-LB) images (equivalent to single-energy [...] Read more.
The purpose of this study was to evaluate the potential of dual-energy CT (DECT) with virtual unenhanced imaging (VNC) and iodine maps (IM) to differentiate between intraperitoneal hematomas (IH) and bowel structures (BS) compared to linearly blended DECT (DE-LB) images (equivalent to single-energy CT). This retrospective study included the DECT of 30 patients (mean age: 64.5 ± 15.1 years, 19 men) with intraperitoneal hematomas and 30 negative controls. VNC, IM, and DE-LB were calculated. Imaging follow-up and surgical reports were used as references. Three readers assessed diagnostic performance and confidence in distinguishing IH and BS for DE-LB, VNC, and IM. Diagnostic confidence was assessed on a five-point Likert scale. The mean values of VNC, IM, and DE-LB were compared with nonparametric tests. Diagnostic accuracy was assessed by calculating receiver operating characteristics (ROC). The results are reported as medians with interquartile ranges. Subjective image analysis showed higher diagnostic performance (sensitivity: 96.7–100% vs. 88.2–96.7%; specificity: 100% vs. 96.7–100%; p < 0.0001; ICC: 0.96–0.99) and confidence (Likert: 5; IRQ [5–5] vs. 4, IRQ [3–4; 4–5]; p < 0.0001; ICC: 0.80–0.96) for DECT compared to DE-LB. On objective image analysis, IM values for DECT showed significant differences between IH (3.9 HU; IQR [1.6, 8.0]) and BS (39.5 HU; IQR [29.2, 43.3]; p ≤ 0.0001). VNC analysis revealed a significantly higher attenuation of hematomas (50.5 HU; IQR [44.4, 59.4]) than BS (26.6 HU; IQR [22.8, 32.4]; p ≤ 0.0001). DE-LB revealed no significant differences between hematomas (60.5 HU, IQR [52.7, 63.9]) and BS (63.9 HU, IQR [58.0, 68.8]; p > 0.05). ROC analysis revealed the highest AUC values and sensitivity for IM (AUC = 100%; threshold by Youden-Index ≤ 19 HU) and VNC (0.93; ≥34.1 HU) compared to DE-LB (0.64; ≤63.8; p < 0.001). DECT is suitable for accurate discrimination between IH and BS by calculating iodine maps and VNC images. Full article
(This article belongs to the Special Issue Advances in CT Images)
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19 pages, 4190 KiB  
Article
Classification Framework for Medical Diagnosis of Brain Tumor with an Effective Hybrid Transfer Learning Model
by Nagwan Abdel Samee, Noha F. Mahmoud, Ghada Atteia, Hanaa A. Abdallah, Maali Alabdulhafith, Mehdhar S. A. M. Al-Gaashani, Shahab Ahmad and Mohammed Saleh Ali Muthanna
Diagnostics 2022, 12(10), 2541; https://doi.org/10.3390/diagnostics12102541 - 20 Oct 2022
Cited by 19 | Viewed by 3386
Abstract
Brain tumors (BTs) are deadly diseases that can strike people of every age, all over the world. Every year, thousands of people die of brain tumors. Brain-related diagnoses require caution, and even the smallest error in diagnosis can have negative repercussions. Medical errors [...] Read more.
Brain tumors (BTs) are deadly diseases that can strike people of every age, all over the world. Every year, thousands of people die of brain tumors. Brain-related diagnoses require caution, and even the smallest error in diagnosis can have negative repercussions. Medical errors in brain tumor diagnosis are common and frequently result in higher patient mortality rates. Magnetic resonance imaging (MRI) is widely used for tumor evaluation and detection. However, MRI generates large amounts of data, making manual segmentation difficult and laborious work, limiting the use of accurate measurements in clinical practice. As a result, automated and dependable segmentation methods are required. Automatic segmentation and early detection of brain tumors are difficult tasks in computer vision due to their high spatial and structural variability. Therefore, early diagnosis or detection and treatment are critical. Various traditional Machine learning (ML) techniques have been used to detect various types of brain tumors. The main issue with these models is that the features were manually extracted. To address the aforementioned insightful issues, this paper presents a hybrid deep transfer learning (GN-AlexNet) model of BT tri-classification (pituitary, meningioma, and glioma). The proposed model combines GoogleNet architecture with the AlexNet model by removing the five layers of GoogleNet and adding ten layers of the AlexNet model, which extracts features and classifies them automatically. On the same CE-MRI dataset, the proposed model was compared to transfer learning techniques (VGG-16, AlexNet, SqeezNet, ResNet, and MobileNet-V2) and ML/DL. The proposed model outperformed the current methods in terms of accuracy and sensitivity (accuracy of 99.51% and sensitivity of 98.90%). Full article
(This article belongs to the Special Issue Artificial Intelligence in Clinical Medical Imaging Analysis)
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14 pages, 1014 KiB  
Article
Factors Influencing the Prognosis of Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome
by Alaa Ghali, Carole Lacout, Jacques-Olivier Fortrat, Karine Depres, Maria Ghali and Christian Lavigne
Diagnostics 2022, 12(10), 2540; https://doi.org/10.3390/diagnostics12102540 - 19 Oct 2022
Cited by 7 | Viewed by 4635
Abstract
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a long-term debilitating multisystem condition with poor prognosis. Studies that examined predictors of ME/CFS outcomes yielded contradictory results. We aimed to explore epidemiological and clinical prognostic factors of ME/CFS using operationalized criteria for recovery/improvement. Adult ME/CFS patients [...] Read more.
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a long-term debilitating multisystem condition with poor prognosis. Studies that examined predictors of ME/CFS outcomes yielded contradictory results. We aimed to explore epidemiological and clinical prognostic factors of ME/CFS using operationalized criteria for recovery/improvement. Adult ME/CFS patients who attended the Internal Medicine Department of Angers University Hospital, Angers, France between October 2011 and December 2019, and were followed up until December 2020, were included retrospectively. Their medical records were reviewed for data collection. Patients were classified into two groups according to the presence or absence of recovery/improvement (R/I) and compared for epidemiological characteristics, fatigue features, post-exertional malaise severity, clinical manifestations, and comorbidities. The subgroups of recovered and significantly improved patients were then compared. 168 patients were included. Recovery and improvement rates were 8.3% and 4.8%, respectively. Older age at disease onset was associated with R/I (OR 1.06 [95% CI 1.007–1.110] (p = 0.028)), while diagnostic delay was inversely associated with R/I (OR 0.98 [95% CI 0.964–0.996] (p = 0.036)). The study findings confirmed the poor prognosis of ME/CFS and the deleterious effect of diagnostic delay on disease progression. Interestingly, being older at disease onset was associated with better outcomes, which offers hope to patients for recovery/improvement even at an advanced age. Full article
(This article belongs to the Special Issue Chronic Fatigue-Spectrum Disorders in the Era of COVID-19)
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25 pages, 3579 KiB  
Article
Probabilistic Approach to COVID-19 Data Analysis and Forecasting Future Outbreaks Using a Multi-Layer Perceptron Neural Network
by Riaz Ullah Khan, Sultan Almakdi, Mohammed Alshehri, Rajesh Kumar, Ikram Ali, Sardar Muhammad Hussain, Amin Ul Haq, Inayat Khan, Aman Ullah and Muhammad Irfan Uddin
Diagnostics 2022, 12(10), 2539; https://doi.org/10.3390/diagnostics12102539 - 19 Oct 2022
Cited by 9 | Viewed by 1734
Abstract
The present outbreak of COVID-19 is a worldwide calamity for healthcare infrastructures. On a daily basis, a fresh batch of perplexing datasets on the numbers of positive and negative cases, individuals admitted to hospitals, mortality, hospital beds occupied, ventilation shortages, and so on [...] Read more.
The present outbreak of COVID-19 is a worldwide calamity for healthcare infrastructures. On a daily basis, a fresh batch of perplexing datasets on the numbers of positive and negative cases, individuals admitted to hospitals, mortality, hospital beds occupied, ventilation shortages, and so on is published. Infections have risen sharply in recent weeks, corresponding with the discovery of a new variant from South Africa (B.1.1.529 also known as Omicron). The early detection of dangerous situations and forecasting techniques is important to prevent the spread of disease and restart economic activities quickly and safely. In this paper, we used weekly mobility data to analyze the current situation in countries worldwide. A methodology for the statistical analysis of the current situation as well as for forecasting future outbreaks is presented in this paper in terms of deaths caused by COVID-19. Our method is evaluated with a multi-layer perceptron neural network (MLPNN), which is a deep learning model, to develop a predictive framework. Furthermore, the Case Fatality Ratio (CFR), Cronbach’s alpha, and other metrics were computed to analyze the performance of the forecasting. The MLPNN is shown to have the best outcomes in forecasting the statistics for infected patients and deaths in selected regions. This research also provides an in-depth analysis of the emerging COVID-19 variants, challenges, and issues that must be addressed in order to prevent future outbreaks. Full article
(This article belongs to the Special Issue Deep Disease Detection and Diagnosis Models)
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13 pages, 2537 KiB  
Article
Automatic Cardiopulmonary Endurance Assessment: A Machine Learning Approach Based on GA-XGBOOST
by Jia Deng, Yan Fu, Qi Liu, Le Chang, Haibo Li and Shenglin Liu
Diagnostics 2022, 12(10), 2538; https://doi.org/10.3390/diagnostics12102538 - 19 Oct 2022
Cited by 3 | Viewed by 1517
Abstract
Objective: Among various assessment paradigms, the cardiopulmonary exercise test (CPET) provides rich evidence as part of the cardiopulmonary endurance (CPE) assessment. However, methods and strategies for interpreting CPET results are not in agreement. The purpose of this study is to validate the possibility [...] Read more.
Objective: Among various assessment paradigms, the cardiopulmonary exercise test (CPET) provides rich evidence as part of the cardiopulmonary endurance (CPE) assessment. However, methods and strategies for interpreting CPET results are not in agreement. The purpose of this study is to validate the possibility of using machine learning to evaluate CPET data for automatically classifying the CPE level of workers in high-latitude areas. Methods: A total of 120 eligible workers were selected for this cardiopulmonary exercise experiment, and the physiological data and completion of the experiment were recorded in the simulated high-latitude workplace, within which 84 sets of data were used for XGBOOST model training and36 were used for the model validation. The model performance was compared with Support Vector Machine and Random Forest. Furthermore, hyperparameter optimization was applied to the XGBOOST model by using a genetic algorithm. Results: The model was verified by the method of tenfold cross validation; the correct rate was 0.861, with a Micro-F1 Score of 0.864. Compared with RF and SVM, all data achieved a better performance. Conclusion: With a relatively small number of training samples, the GA-XGBOOST model fits well with the training set data, which can effectively evaluate the CPE level of subjects, and is expected to provide automatic CPE evaluation for selecting, training, and protecting the working population in plateau areas. Full article
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12 pages, 3137 KiB  
Article
Automated Detection of Cervical Carotid Artery Calcifications in Cone Beam Computed Tomographic Images Using Deep Convolutional Neural Networks
by Maryam Ajami, Pavani Tripathi, Haibin Ling and Mina Mahdian
Diagnostics 2022, 12(10), 2537; https://doi.org/10.3390/diagnostics12102537 - 19 Oct 2022
Cited by 5 | Viewed by 2200
Abstract
The aim of this study was to determine if a convolutional neural network (CNN) can be trained to automatically detect and localize cervical carotid artery calcifications (CACs) in CBCT. A total of 56 CBCT studies (15,257 axial slices) were utilized to train, validate, [...] Read more.
The aim of this study was to determine if a convolutional neural network (CNN) can be trained to automatically detect and localize cervical carotid artery calcifications (CACs) in CBCT. A total of 56 CBCT studies (15,257 axial slices) were utilized to train, validate, and test the deep learning model. The study comprised of two steps: Step 1: Localizing axial slices that are below the C2–C3 disc space. For this step the openly available Inception V3 architecture was trained on the ImageNet dataset of real-world images, and retrained on 40 CBCT studies. Step 2: Detecting CACs in slices from step 1. For this step, two methods were implemented; Method A: Segmentation neural network trained using small patches at random coordinates of the original axial slices; Method B: Segmentation neural network trained using two larger patches at fixed coordinates of the original axial slices with an improved loss function to account for class imbalance. Our approach resulted in 94.2% sensitivity and 96.5% specificity. The mean intersection over union metric for Method A was 76.26% and Method B improved this metric to 82.51%. The proposed CNN model shows the feasibility of deep learning in the detection and localization of CAC in CBCT images. Full article
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25 pages, 1808 KiB  
Article
Pneumonia and Pulmonary Thromboembolism Classification Using Electronic Health Records
by Sinhue Siordia-Millán, Sulema Torres-Ramos, Ricardo A. Salido-Ruiz, Daniel Hernández-Gordillo, Tracy Pérez-Gutiérrez and Israel Román-Godínez
Diagnostics 2022, 12(10), 2536; https://doi.org/10.3390/diagnostics12102536 - 19 Oct 2022
Viewed by 1936
Abstract
Pneumonia and pulmonary thromboembolism (PTE) are both respiratory diseases; their diagnosis is difficult due to their similarity in symptoms, medical subjectivity, and the large amount of information from different sources necessary for a correct diagnosis. Analysis of such clinical data using computational tools [...] Read more.
Pneumonia and pulmonary thromboembolism (PTE) are both respiratory diseases; their diagnosis is difficult due to their similarity in symptoms, medical subjectivity, and the large amount of information from different sources necessary for a correct diagnosis. Analysis of such clinical data using computational tools could help medical staff reduce time, increase diagnostic certainty, and improve patient care during hospitalization. In addition, no studies have been found that analyze all clinical information on the Mexican population in the Spanish language. Therefore, this work performs automatic diagnosis of pneumonia and pulmonary thromboembolism using machine-learning tools along with clinical laboratory information (structured data) and clinical text (unstructured data) obtained from electronic health records. A cohort of 173 clinical records was obtained from the Mexican Social Security Institute. The data were preprocessed, transformed, and adjusted to be analyzed using several machine-learning algorithms. For structured data, naïve Bayes, support vector machine, decision trees, AdaBoost, random forest, and multilayer perceptron were used; for unstructured data, a BiLSTM was used. K-fold cross-validation and leave-one-out were used for evaluation of structured data, and hold-out was used for unstructured data; additionally, 1-vs.-1 and 1-vs.-rest approaches were used. Structured data results show that the highest AUC-ROC was achieved by the naïve Bayes algorithm classifying PTE vs. pneumonia (87.0%), PTE vs. control (75.1%), and pneumonia vs. control (85.2%) with the 1-vs.-1 approach; for the 1-vs.-rest approach, the best performance was reported in pneumonia vs. rest (86.3%) and PTE vs. rest (79.7%) using naïve Bayes, and control vs. diseases (79.8%) using decision trees. Regarding unstructured data, the results do not present a good AUC-ROC; however, the best F1-score were scored for control vs. disease (72.7%) in the 1-vs.-rest approach and control vs. pneumonia (63.6%) in the 1-to-1 approach. Additionally, several decision trees were obtained to identify important attributes for automatic diagnosis for structured data, particularly for PTE vs. pneumonia. Based on the experiments, the structured datasets present the highest values. Results suggest using naïve Bayes and structured data to automatically diagnose PTE vs. pneumonia. Moreover, using decision trees allows the observation of some decision criteria that the medical staff could consider for diagnosis. Full article
(This article belongs to the Special Issue Intelligent Data Analysis for Medical Diagnosis)
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