Diagnostics

COVID-19 is a disease caused by the SARS-CoV-2 virus. The COVID-19 virus spreads when a person comes into contact with an affected individual. This is mainly through drops of saliva or nasal discharge. Most of the affected people have mild symptoms while some people develop acute respiratory distress syndrome (ARDS), which damages organs like the lungs and heart. Chest X-rays (CXRs) have been widely used to identify abnormalities that help in detecting the COVID-19 virus. They have also been used as an initial screening procedure for individuals highly suspected of being infected. However, the availability of radiographic CXRs is still scarce. This can limit the performance of deep learning (DL) based approaches for COVID-19 detection. To overcome these limitations, in this work, we developed an Auxiliary Classifier Generative Adversarial Network (ACGAN), to generate CXRs. Each generated X-ray belongs to one of the two classes COVID-19 positive or normal. To ensure the goodness of the synthetic images, we performed some experimentation on the obtained images using the latest Convolutional Neural Networks (CNNs) to detect COVID-19 in the CXRs. We fine-tuned the models and achieved more than 98% accuracy. After that, we also performed feature selection using the Harmony Search (HS) algorithm, which reduces the number of features while retaining classification accuracy. We further release a GAN-generated dataset consisting of 500 COVID-19 radiographic images. Full article

Coronavirus disease 2019 (COVID-19) has shown the importance of postmortem investigation of deceased patients. For a correct interpretation of the pulmonary findings in this new era, it is, however, crucial to be familiar with pathologic pulmonary conditions observed in postmortem investigations in general. Adequate postmortem histopathological evaluation of the lungs may be affected by suboptimal gross work up, autolysis or poor fixation. Using a standardized preparation approach which consisted in instillation of 4% buffered formaldehyde through the large bronchi for proper fixation and preparing large frontal tissue sections of 1–2 cm thickness after at least 24 h fixation, we comprehensively analyzed postmortem pulmonary findings from consecutive adult autopsies of a two-year period before the occurrence of COVID-19 (2016–2017). In total, significant pathological findings were observed in 97/189 patients (51%), with 28 patients showing more than one pathologic condition. Acute pneumonia was diagnosed 33/128 times (26%), embolism 24 times (19%), primary pulmonary neoplasms 18 times (14%), organizing pneumonia and other fibrosing conditions 14 times (11%), pulmonary metastases 13 times (10%), diffuse alveolar damage 12 times (9%), severe emphysema 9 times (7%) and other pathologies, e.g., amyloidosis 5/128 times (4%). Pulmonary/cardiopulmonary disease was the cause of death in 60 patients (32%). Clinical and pathological diagnoses regarding lung findings correlated completely in 75 patients (40%). Autopsy led to confirmation of a clinically suspected pulmonary diagnosis in 57 patients (39%) and clarification of an unclear clinical lung finding in 16 patients (8%). Major discrepant findings regarding the lungs (N = 31.16%) comprised cases with clinical suspicions that could not be confirmed or new findings not diagnosed intra vitam. A significant proportion of acute pneumonias (N = 8; 24% of all cases with this diagnosis; p = 0.011) was not diagnosed clinically. We confirmed the frequent occurrence of pulmonary pathologies in autopsies, including inflammatory and neoplastic lesions as the most frequent pathological findings. Acute pneumonia was an important cause for discrepancy between clinical and postmortem diagnostics Full article

Detecting COVID-19 at an early stage is essential to reduce the mortality risk of the patients. In this study, a cascaded system is proposed to segment the lung, detect, localize, and quantify COVID-19 infections from computed tomography images. An extensive set of experiments were performed using Encoder–Decoder Convolutional Neural Networks (ED-CNNs), UNet, and Feature Pyramid Network (FPN), with different backbone (encoder) structures using the variants of DenseNet and ResNet. The conducted experiments for lung region segmentation showed a Dice Similarity Coefficient (DSC) of 97.19% and Intersection over Union (IoU) of 95.10% using U-Net model with the DenseNet 161 encoder. Furthermore, the proposed system achieved an elegant performance for COVID-19 infection segmentation with a DSC of 94.13% and IoU of 91.85% using the FPN with DenseNet201 encoder. The proposed system can reliably localize infections of various shapes and sizes, especially small infection regions, which are rarely considered in recent studies. Moreover, the proposed system achieved high COVID-19 detection performance with 99.64% sensitivity and 98.72% specificity. Finally, the system was able to discriminate between different severity levels of COVID-19 infection over a dataset of 1110 subjects with sensitivity values of 98.3%, 71.2%, 77.8%, and 100% for mild, moderate, severe, and critical, respectively. Full article

Heart failure (HF) is a leading cause of cardiovascular morbidity and mortality. However, its symptoms and signs are not specific or can be absent. In this context, transthoracic echocardiography plays a key role in diagnosing the various forms of HF, guiding therapeutic decision making and monitoring response to therapy. Over the last few decades, new ultrasound modalities have been introduced in the field of echocardiography, aiming at better understanding the morpho-functional abnormalities occurring in cardiovascular diseases. However, they are still struggling to enter daily and routine use. In our review article, we turn the spotlight on some of the newest ultrasound technologies; in particular, analysis of myocardial deformation by speckle tracking echocardiography, and intracardiac flow dynamics by color Doppler flow mapping, highlighting their promising applications to HF diagnosis and management. We also focus on the importance of these imaging modalities in the selection of responses to cardiac resynchronization therapy. Full article

Sentinel lymph node (SLN) biopsy has gained attention as a method of minimizing the extent of neck dissection with a similar survival rate as elective neck dissection in oral cancer. Indocyanine green (ICG) imaging is widely used in the field of surgical oncology. Real-time ICG-guided SLN imaging has been widely used in minimally invasive surgeries for various types of cancers. Here, we provide an overview of conventional SLN biopsy and ICG-guided SLN mapping techniques for oral cancer. Although ICG has many strengths, it still has limitations regarding its potential use as an ideal compound for SLN mapping. The development of novel fluorophores and imaging technology is needed for accurate identification of SLNs, which will allow precision surgery that would reduce morbidities and increase patient survival. Full article

Background: Heart rate variability (HRV) indices have been shown to be associated with prognosis in various types of cancer. This study aims to assess the ability of these indices to predict survival in hepatocellular carcinoma (HCC) patients after diagnosis. Methods: We retrospectively collected data from 231 patients diagnosed with HCC between January 2014 and March 2018. The baseline clinical-pathological variables and HRV indices (extracted from Holter electrocardiogram recordings) were analyzed. Results: Univariate and multivariate analyses were performed to identify the predictive value of the above factors for overall survival (OS). The univariate analysis revealed that an age > 60 years, hepatitis C, portal vein involvement (thrombosis), a tumor size > 5 cm, alpha-fetoprotein (AFP) > 400 ng/mL, serum albumin, and C-reactive protein (CRP) were risk factors for poor OS. Multivariable Cox regression analyses identified that a tumor size > 5 cm and AFP > 400 ng/mL predict poorer outcomes in HCC patients. It should be mentioned that, in both the univariate analysis and in the multivariate analysis, between HRV indices, SDNN (standard deviation of all normal-to-normal (NN) intervals) < 110 ms was an independent risk factor for OS with an HR of 3.646 (95% CI 2.143 to 6.205). Conclusion: This study demonstrates that HRV indices identify HCC patients at high risk of death and suggests that such monitoring might guide the need for early therapy in these types of patients, as well as the fact that HRV can be a potential noninvasive biomarker for HCC prognosis. Full article

Obstructive sleep apnea (OSA) is the most common form of sleep-disordered breathing, exhibiting an increasing prevalence and several cardiovascular complications. Continuous positive airway pressure (CPAP) is the gold-standard treatment for moderate-severe OSA, but it is associated with poor patient adherence. We performed a prospective study that included 57 patients with newly diagnosed moderate-severe OSA, prior to CPAP initiation. The objective of our study was to assess the impact of short-term CPAP on ventricular function in patients with moderate-severe OSA and cardiometabolic comorbidities. The patients underwent a clinical exam, ambulatory blood pressure monitoring and comprehensive echocardiographic assessment at baseline and after 8 weeks of CPAP. Hypertension, obesity and diabetes were highly prevalent among patients with moderate-severe OSA. Baseline echocardiographic parameters did not significantly differ between patients with moderate and severe OSA. Short-term CPAP improved left ventricular global longitudinal strain (LV-GLS), isovolumetric relaxation time, transmitral E wave amplitude, transmitral E/A ratio, right ventricular (RV) diameter, RV wall thickness, RV systolic excursion velocity (RV S‘) and tricuspid annular plane systolic excursion (TAPSE). Short-term CPAP improves biventricular function, especially the LV-GLS, which is a more sensitive marker of CPAP-induced changes in LV systolic function, compared to LVEF. All these benefits are dependent on CPAP adherence. Full article

A false negative can happen in many kinds of medical tests, regardless of whether they are screening or diagnostic in nature. However, it inevitably poses serious concerns especially in a prenatal setting because its sequelae can mark the birth of an affected child beyond expectation. False negatives are not a new thing because of emerging new tests in the field of reproductive, especially prenatal, genetics but has occurred throughout the evolution of prenatal screening and diagnosis programs. In this paper we aim to discuss the basic differences between screening and diagnosis, the trade-offs and the choices, and also shed light on the crucial points clinicians need to know and be aware of so that a quality service can be provided in a coherent and sensible way to patients so that vital issues related to a false negative result can be appropriately comprehended by all parties. Full article

Machine learning (ML) algorithms are widely used to develop predictive frameworks. Accurate prediction of Alzheimer’s disease (AD) age of onset (ADAOO) is crucial to investigate potential treatments, follow-up, and therapeutic interventions. Although genetic and non-genetic factors affecting ADAOO were elucidated by other research groups and ours, the comprehensive and sequential application of ML to provide an exact estimation of the actual ADAOO, instead of a high-confidence-interval ADAOO that may fall, remains to be explored. Here, we assessed the performance of ML algorithms for predicting ADAOO using two AD cohorts with early-onset familial AD and with late-onset sporadic AD, combining genetic and demographic variables. Performance of ML algorithms was assessed using the root mean squared error (RMSE), the R-squared (R²), and the mean absolute error (MAE) with a 10-fold cross-validation procedure. For predicting ADAOO in familial AD, boosting-based ML algorithms performed the best. In the sporadic cohort, boosting-based ML algorithms performed best in the training data set, while regularization methods best performed for unseen data. ML algorithms represent a feasible alternative to accurately predict ADAOO with little human intervention. Future studies may include predicting the speed of cognitive decline in our cohorts using ML. Full article

Sudden death (SD) is defined as the unexpected natural death occurred within an hour after the onset of symptoms or from the last moment the subject has been seen in a healthy condition. Brugada syndrome (BrS) is one of the most remarkable cardiac causes of SD among young people. We report the case of a 20-year-old man who suddenly died after reportedly having smoked cannabis. Autopsy, toxicology, and genetic testing were performed. Autopsy found a long and thick myocardial bridging (MB) at 2 cm from the beginning of the left anterior descending coronary artery. Furthermore, at the histopathological examination, fibrosis and disarray in myocardial area above the MB, fatty tissue in the right ventricle and fibrosis of the sino-atrial node area were found. Toxicology testing was inconclusive, while genetic testing found a rare missense variant of the TTN gene, classified as likely benign, and a variant of unknown significance in the SLMAP gene (a gene that can be associated with BrS). Hence, despite several atypical features were found, no inference on the cause of the death could be made under current evidence. Full article

Background and aims: Cerebrospinal fluid (CSF) protein content presents a sexual dimorphism in humans. We investigated sex-related differences in CSF IgG levels and in the quantification of intrathecal IgG synthesis (IIS). Methods: CSF, serum albumin and IgG were measured in 1519 neurological patients and both linear and hyperbolic formulas were used for the quantification of IIS. CSF-restricted oligoclonal IgG bands (OCBs) were used as “gold standard”. Results: The linear IgG Index showed a weak agreement with OCBs in males and females (k = 0.559, k = 0.587, respectively), while the hyperbolic Reiber’s formulas had a moderate agreement with OCBs in females (k = 0.635) and a weak agreement in males (k = 0.565). Higher CSF albumin and IgG levels were found in men than in women in the whole population and in subjects without IIS after adjusting for age and for serum concentrations of albumin and IgG, respectively (Quade statistics, p < 0.000001). CSF and serum albumin and IgG levels positively correlated to age in both sexes. CSF total protein content did not correlate with CSF leukocyte numbers but was higher in patients with marked pleocytosis. Conclusions: In neurological patients, men have higher levels of CSF serum-derived proteins, such as albumin and IgG. Full article

Background: The use of ¹⁸F-2-Fluor-2-desoxy-D-glucose Positron Emission Tomography/Computed Tomography FDG-PET/CT in clinical routine for staging, treatment response monitoring and post treatment surveillance in metastatic melanoma patients has noticeably increased due to significant improvement of the overall survival rate in melanoma patients. However, determining the dignity of the findings with increased metabolic activity on FDG-PET/CT can be sometimes challenging and may need further investigation. Purpose: We aimed to investigate the malignancy rate of indeterminate findings on FDG-PET/CT in metastatic cutaneous melanoma patients. Methods: This single-center retrospective study included cutaneous melanoma patients who underwent FDG-PET/CT in clinical routine between 2015 and 2017 with findings reported as indeterminate and therefore requiring further evaluation. The dignity of the included findings was determined by subsequent imaging and, if required, additional histopathology. The impact of the outcome on the clinical management was also reported. Results: A total of 842 FDG-PET/CT reports of 244 metastatic cutaneous melanoma patients were reviewed. Sixty indeterminate findings were included. Almost half of all indeterminate findings were lymph nodes, lung nodules and cerebral lesions. In total, 43.3% of all included findings proved to be malignant. 81% of all malignant lesions were metastases of cutaneous melanoma, while 19% of all malignant lesions could be attributed to other primary malignancies, such as lung, breast, thyroid and colorectal cancers. Malignant findings influenced clinical management in 60% of the cases. Conclusion: Indeterminate findings on FDG-PET/CT in metastatic cutaneous melanoma patients should be further investigated. Almost one out of every two indeterminate findings on FDG-PET/CT is malignant. The majority of the findings are melanoma manifestations, however, in a significant percentage, other primary tumors are found. Upon verification, patient management is changed in most cases. Full article

Background: The impact of MRI-lesion targeted (TB) and systematic biopsy (SB) Gleason score (GS) as a predictor for final pathological GS still remains unclear. Methods: All patients with TB + SB, and subsequent radical prostatectomy (RP) between 01/2014-12/2020 were analyzed. Rank correlation coefficient predicted concordance with pathological GS for patients’ TB and SB GS, as well as for the combined effect of SB + TB. Results: Of 159 eligible patients, 77% were biopsy naïve. For SB taken in addition to TB, a Spearman’s correlation of +0.33 was observed regarding final GS. Rates of concordance, upgrading, and downgrading were 37.1, 37.1 and 25.8%, respectively. For TB, a +0.52 correlation was computed regarding final GS. Rates of concordance, upgrading and downgrading for TB biopsy GS were 45.9, 33.3, and 20.8%, respectively. For the combination of SB + TB, a correlation of +0.59 was observed. Rates of concordance, upgrading and downgrading were 49.7, 15.1 and 35.2%, respectively. The combined effect of SB + TB resulted in a lower upgrading rate, relative to TB and SB (both p < 0.001), but a higher downgrading rate, relative to TB (p < 0.01). Conclusions: GS obtained from TB provided higher concordance and lower upgrading and downgrading rates, relative to SB GS with regard to final pathology. The combined effect of SB + TB led to the highest concordance rate and the lowest upgrading rate. Full article

Despite important advancements in acute myocardial infarction (AMI) management, it continues to represent a leading cause of mortality worldwide. Fast and reliable AMI diagnosis can significantly reduce mortality in this high-risk population. Diagnosis of AMI has relied on biomarker evaluation for more than 50 years. The upturn of high-sensitivity cardiac troponin testing provided extremely sensitive means to detect cardiac myocyte necrosis, but this increased sensitivity came at the cost of a decrease in diagnostic specificity. In addition, although cardiac troponins increase relatively early after the onset of AMI, they still leave a time gap between the onset of myocardial ischemia and our ability to detect it, thus precluding very early management of AMI. Newer biomarkers detected in processes such as inflammation, neurohormonal activation, or myocardial stress occur much earlier than myocyte necrosis and the diagnostic rise of cardiac troponins, allowing us to expand biomarker research in these areas. Increased understanding of the complex AMI pathophysiology has spurred the search of new biomarkers that could overcome these shortcomings, whereas multi-omic and multi-biomarker approaches promise to be game changers in AMI biomarker assessment. In this review, we discuss the evolution, current application, and emerging blood biomarkers for the diagnosis of AMI; we address their advantages and promises to improve patient care, as well as their challenges, limitations, and technical and diagnostic pitfalls. Questions that remain to be answered and hotspots for future research are also emphasized. Full article

Morquio syndrome is a rare disease caused by a disorder in the storage of mucopolysaccharides that affects multiple organs, including musculoskeletal, respiratory, cardiovascular, and digestive systems. Respiratory failure is one of the leading causes of mortality in Morquio patients; thus, respiratory function testing is vital to the management of the disease. An automated respiratory assessment methodology using the pneuRIP device and a machine-learning algorithm was developed. pneuRIP is a noninvasive approach that uses differences between thoracic and abdominal movements (thoracic-abdominal asynchrony) during respiration to assess respiratory status. The technique was evaluated on 17 patients with Morquio (9 females and 8 males) between the ages of 2 and 57 years. The results of the automated technique agreed with the clinical assessment in 16 out of the 17 patients. It was found that the inverse cumulative percentage representation of the time delay between the thorax and abdomen was the most critical variable for accurate evaluation. It was demonstrated that the technique could be successfully used on patients with Morquio who have difficulty breathing with 100% compliance. This technique is highly accurate, portable, noninvasive, and easy to administer, making it suitable for a variety of settings, such as outpatient clinics, at home, and emergency rooms. Full article

Giant cell arteritis (GCA) is the most common form of large vessel vasculitis. GCA is a medical and ophthalmological emergency, and rapid diagnosis and treatment with high-dose corticosteroids is critical in order to reduce the risk of stroke and sudden irreversible loss of vision. GCA can be difficult to diagnose due to insidious and unspecific symptoms—especially if typical superficial extracranial arteries are not affected. In these cases, verification of clinical diagnosis using temporal artery biopsy is not possible. This example illustrates the diagnostic value of hybrid imaging with 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission tomography/computed tomography (2-[¹⁸F]FDG PET/CT), and the limitations of the temporal artery biopsy in bilateral vertebral GCA, causing transient ischemic attack in the visual cortex. In addition it indicates that inflammation in the artery wall can be visualized on 2-[¹⁸F]FDG PET/CT despite long term and ongoing high dose glucocorticoid treatment. Full article

The purpose of our work was to assess the independent and incremental value of AI-derived quantitative determination of lung lesions extent on initial CT scan for the prediction of clinical deterioration or death in patients hospitalized with COVID-19 pneumonia. 323 consecutive patients (mean age 65 ± 15 years, 192 men), with laboratory-confirmed COVID-19 and an abnormal chest CT scan, were admitted to the hospital between March and December 2020. The extent of consolidation and all lung opacities were quantified on an initial CT scan using a 3D automatic AI-based software. The outcome was known for all these patients. 85 (26.3%) patients died or experienced clinical deterioration, defined as intensive care unit admission. In multivariate regression based on clinical, biological and CT parameters, the extent of all opacities, and extent of consolidation were independent predictors of adverse outcomes, as were diabetes, heart disease, C-reactive protein, and neutrophils/lymphocytes ratio. The association of CT-derived measures with clinical and biological parameters significantly improved the risk prediction (p = 0.049). Automated quantification of lung disease at CT in COVID-19 pneumonia is useful to predict clinical deterioration or in-hospital death. Its combination with clinical and biological data improves risk prediction. Full article

Background and Aims: The Spanish prison population includes two groups: people in prison and those who are serving non-custodial sentences. The latter has not yet been studied. This study aims to describe this population and the results of a test-and-treat strategy for hepatitis C including a holistic health assessment. Method: This prospective study included all subjects serving non-custodial sentences at the Center for Social Integration. It was assisted by the medical team, a navigator, and a systematic screening of HCV (Hepatitis C Virus) performed by point-of-care tests. All cases with active infection are evaluated using telemedicine by a specialist to prescribe antiviral treatment. The navigator facilitates continuity for medical and social assistance. Results: The screening rate reached 92.8% (548/590). HCV seroprevalence and viraemia prevalence were 8% (44) and 2.9% (16), respectively. Regarding comorbidities: problems related to drug dependence were detected in 264 (48.2%), suspected serious mental disorder in 44 (8.3%), and previous stay in prison in 122 cases (22.2%). The navigator monitored 59 (15.2%) patients regarding HCV treatment or comorbidities. All patients (10/10) completing 12 weeks follow-up achieved sustained virological response. Conclusions: The population serving non-custodial sentences is a challenging group with a high prevalence of HCV infection. Micro-elimination programs using point of care diagnostic tests, telemedicine, and a navigator are necessary in this underserved vulnerable population. Full article