CovMediScanX: A medical imaging solution for COVID-19 diagnosis from chest X-ray images.

INTRODUCTION: Radiologists have extensively employed the interpretation of chest X-rays (CXR) to identify visual markers indicative of COVID-19 infection, offering an alternative approach for the screening of infected individuals. This research article presents CovMediScanX, a deep learning-based framework designed for a rapid and automated diagnosis of COVID-19 from CXR scan images. METHODS: The proposed approach encompasses gathering and preprocessing CXR image datasets, training deep learning-based custom-made Convolutional Neural Network (CNN), pre-trained and hybrid transfer learning models, identifying the highest-performing model based on key evaluation metrics, and embedding this model into a web interface called CovMediScanX, designed for radiologists to detect the COVID-19 status in new CXR images. RESULTS: The custom-made CNN model obtained a remarkable testing accuracy of 94.32% outperforming other models. CovMediScanX, employing the custom-made CNN underwent evaluation with an independent dataset also. The images in the independent dataset are sourced from a scanning machine that is entirely different from those used for the training dataset, highlighting a clear distinction of datasets in their origins. The evaluation outcome highlighted the framework's capability to accurately detect COVID-19 cases, showcasing encouraging results with a precision of 73% and a recall of 84% for positive cases. However, the model requires further enhancement, particularly in improving its detection of normal cases, as evidenced by lower precision and recall rates. CONCLUSION: The research proposes CovMediScanX framework that demonstrates promising potential in automatically identifying COVID-19 cases from CXR images. While the model's overall performance on independent data needs improvement, it is evident that addressing bias through the inclusion of diverse data sources during training could further enhance accuracy and reliability.

Post-COVID-19 polyautoimmunity - Fact or coincidence: A case report.

COVID-19 exhibits diverse and systemic clinical symptoms, much like systemic autoimmune diseases, and there are notable similarities in the immune responses seen in both conditions. There are rare reports of ulcerative colitis and autoimmune hepatitis triggered by COVID-19 infection. Reported herein is a case of a previously healthy patient who was diagnosed with chronic colitis resembling ulcerative colitis, autoimmune pancreatitis, and suspected immune-mediated hepatitis (AIH-like hepatitis) 2 months after a COVID-19 infection. A 33-year-old COVID-19-vaccinated male, presented with abdominal pain, nausea, and vomiting for 2 days. He also had bloody diarrhea that persisted for 2 months after recovering from a COVID-19 infection. A diagnosis of acute pancreatitis was confirmed by markedly elevated serum amylase and lipase and a CT scan of the abdomen. Colonoscopy and histopathology findings also confirmed a diagnosis of chronic colitis resembling ulcerative colitis (Mayo Endoscopy Subscore 3). Marked improvement in bloody diarrhea was observed within 72 h of treatment with IV prednisolone. MRI of the abdomen performed due to an unresolved clinical picture of pancreatitis revealed a bulky pancreas showing delayed diffuse homogenous enhancement, findings possibly consistent with autoimmune pancreatitis. Investigation for elevated liver transaminases showed high titers of antinuclear antibodies and anti-smooth muscle (anti-actin) antibodies while viral hepatitis markers were negative. The patient had already been started on steroid therapy before the lab results were available, with rapid normalization of liver enzymes following treatment. A liver biopsy was not performed. The patient is currently on mesalazine 4 gr/day, and azathioprine 100 mg/day - oral steroids had been tapered and discontinued. Seven months after the initial diagnosis, the patient remains symptom-free. A high level of suspicion for autoimmune disorders is required when assessing patients with a history of COVID-19 infection, although diagnostic pathways remain the same, with generally good response and remission rates to conventional treatment.

Regression Analysis between the Different Breast Dose Quantities Reported in Digital Mammography and Patient Age, Breast Thickness, and Acquisition Parameters.

Breast cancer is the leading cause of cancer death among women worldwide. Screening mammography is considered the primary imaging modality for the early detection of breast cancer. The radiation dose from mammography increases the patients' risk of radiation-induced cancer. The mean glandular dose (MGD), or the average glandular dose (AGD), provides an estimate of the absorbed dose of radiation by the glandular tissues of a breast. In this paper, MGD is estimated for the craniocaudal (CC) and mediolateral-oblique (MLO) views using entrance skin dose (ESD), X-ray spectrum information, patient age, breast glandularity, and breast thickness. Moreover, a regression analysis is performed to evaluate the impact of mammography acquisition parameters, age, and breast thickness on the estimated MGD and other machine-produced dose quantities, namely, ESD and organ dose (OD). Furthermore, a correlation study is conducted to evaluate the correlation between the ESD and OD, and the estimated MGD per image view. This retrospective study was applied to a dataset of 2035 mammograms corresponding to a cohort of 486 subjects with an age range of 28-86 years who underwent screening mammography examinations. Linear regression metrics were calculated to evaluate the strength of the correlations. The mean (and range) MGD for the CC view was 0.832 (0.110-3.491) mGy and for the MLO view was 0.995 (0.256-2.949) mGy. All the mammography dose quantities strongly correlated with tube exposure (mAs): ESD (R2 = 0.938 for the CC view and R2 = 0.945 for the MLO view), OD (R2 = 0.969 for the CC view and R2 = 0.983 for the MLO view), and MGD (R2 = 0.980 for the CC view and R2 = 0.972 for the MLO view). Breast thickness showed a better correlation with all the mammography dose quantities than patient age, which showed a poor correlation. Moreover, a strong correlation was found between the calculated MGD and both the ESD (R2 = 0.929 for the CC view and R2 = 0.914 for the MLO view) and OD (R2 = 0.971 for the CC view and R2 = 0.972 for the MLO view). Furthermore, it was found that the MLO scan views yield a slightly higher dose compared to CC scan views. It was also found that the glandular absorbed dose is more dependent on glandularity than size. Despite being more reflective of the dose absorbed by the glandular tissue than OD and ESD, MGD is considered labor-intensive and time-consuming to estimate.

Gender based lung cancer risks for symptomatic coronary artery disease patients undergone cardiac CT.

We estimate the lifetime attributable risk (LAR) of lung cancer incidence in symptomatic Coronary Artery Disease (CAD) patients receiving enhanced Coronary Computed Tomography Angiography (CCTA) and the unenhanced Computed Tomography Calcium Scoring (CTCS) examination. Retrospective analysis has been made of CCTA and CTCS data collected for 87 confirmed CAD adult patients. Patient effective dose (E) and organ doses (ODs) were calculated using CT-EXPO. Statistical correlation and the differences between E and ODs in enhanced CCTA and unenhanced CTCS were calculated using the Pearson coefficient and Wilcoxon unpaired t-test. Following BEIR VII report guidance, organ-specific LARs for the cohort were estimated using the organ-equivalent dose-to-risk conversion factor for numbers of cases per 100,000 patients exposed to low doses of 0.1 Gy. Significant statistical difference (p<0.0001) is found between E obtained for CTCS and that of CCTA. The scan length was found to be greater in CCTA (17.5 ± 2.9 cm) compared to that for CTCS (15 ± 2 cm). More elevated values of dose were noted for the esophagus (4.2 ± 2.15 mSv) and thymus (9.6 ± 2.54 mSv) for both CTCS and CCTA. CTCS organ doses were lower than that of CCTA. Per 100,000 patients, female cumulative doses are seen to give rise to greater lung cancer LARs compared to that for males, albeit with risk varying significantly, noticeably greater for females, younger patients and combined CCTA and CTCS scans. While scan parameters and tube-modulation methods clearly contribute to patient dose, mAs offers by far the greater contribution.

Assessing visceral and subcutaneous adiposity using segmented T2-MRI and multi-frequency segmental bioelectrical impedance: A sex-based comparative study.

BACKGROUND AND AIM: This study aims to quantify abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) using T2-weighted magnetic resonance imaging (MRI), and assess the extent of its concordance with VAT surface-area measured by a state-of-the-art segmental multi-frequency bioelectrical impedance analysis (BIA) device. A comparison between manual and semi-automated segmentation was conducted. Further, abdominal VAT and SAT sex-based comparison in healthy Arab adults was piloted. METHODS: A cross-sectional design was followed to recruit subjects. Abdominal VAT and SAT were determined on T2-weighted MRI manually and semi-automatically. Body composition was assessed using a BIA machine. Statistical differences between the abdominal VAT areas defined by BIA, manual, and semi-automated MRI were compared. Correlation between all methods was assessed, and statistical differences between sex abdominal VAT/SAT defined areas were compared. RESULTS: A total of 165 abdominal T2-weighted MR images taken for 55 overweight/obese adult subjects were analyzed Differences between manual and semi-automated MRI-obtained abdominal VAT and SAT were found statistically significant (P<0.001) for all subjects. Mean abdominal VAT using the BIA technique was found to correlate significantly with manually and semi-automated T2-weighted MRI defined VAT (r=0.7436; P<0.001 and r=0.8275; P<0.001, respectively). Abdominal VAT was significantly (P<0.001) different between male and female subjects accumulating at different abdominal levels. CONCLUSION: Semi-automatic segmentation showed a stronger significant correlation with BIA compared to manual segmentation, implying a more reliable quantification of abdominal VAT/SAT. Segmental BIA technique may serve as a feasible and convenient assessment tool for the visceral adiposity in obese subjects.

Challenges estimating patient organs doses undergoing enhanced chest CT examination: exploratory study.

Purpose: Estimate organs doses (ODs) of patients subjected to unenhanced (S1) and enhanced (S2) chest CT studies relying on image parameters such as Hounsfield Units (HUs).Materials and Methods: CT scans and images of a total of 16 patients who underwent two series of chest CT studies were obtained and retrospectively examined. OD increments of liver and pancreas for both series (S1 & S2) were estimated using two different independent methods, namely simulation approach using CT-EXPO and Amato's phantom-based fitting model (APFM). HUs were quantified for each organ by manually drawing fixed area-sized regions of interest (ROIs). The mean HUs were collected to obtain the ODs increments following APFM. Regression analysis was applied to find and assess the relationship between the HUs and the OD increments estimated using APFM and that using CT-EXPO. Spearman Coefficient and Wilcoxon Matched Pairedt-testwere conducted to show statistical correlation and difference between ODs increments using the two methods.Results:A strong significant difference was depicted between S1 and S2 scan series of liver and pancreas using CT-EXPO simulation. Mean HU values for S1 were lower than S2, resulting in statistically significant (p < 0.0001) HU changes. CT-EXPO simulation yielded significantly higher difference in ODs compared to the APFM for liver (p = 0.0455) and pancreas (p = 0.0031). Regression analysis revealed a strong relationship between HU of S1 and S2 and ODs increments using APFM in both organs (R2 = 0.99), dissimilar to CT-EXPO (R2 = 0.39 in liver andR2 = 0.05 in pancreas).Conclusions: Although CT-EXPO allows for estimating ODs accounting for major acquisition scan parameters, it is not a reliable tool to evaluate the impact of contrast enhancement on ODs. On the other hand, the APFM accounts for contrast enhancement accumulation yet only provides relative OD increments, an information of limited clinical use.

Effect of Ramadan diurnal fasting on visceral adiposity and serum adipokines in overweight and obese individuals.

AIM: Excessive visceral adiposity is a major risk factor for developing insulin resistance and systemic low-grade inflammation. Ramadan diurnal fasting (RDF) is a religious ritual practiced by more than one billion Muslim throughout the world. It has been considered as one of the most common types of complementary and integrative health practices. The aim of this study is to examine the impact of RDF on visceral adiposity, circulating adipokines and glucoregulatory markers in patients with overweight or obesity. METHODS: Overweight and obese subjects (n = 61; 23 men and 38 women) were included in the study. Body weight, visceral fat tissue area (measured by 3D-MRI), glucoregulatory factors, serum adipokines concentrations, dietary intake, and physical activity were assessed one week before and at the end of the lunar month of Ramadan. RESULTS: From baseline, body weight and visceral fat tissue area serum total cholesterol, triglycerides, HDL-cholesterol, and systolic blood pressure significantly decreased (P < 0.05 for each) at the end of Ramadan. The serum levels of adiponectin, IL-6, TNF-α, and IGF-1 significantly decreased (P < 0.05 for each), but serum visfatin, leptin, apelin, IL-10, and IL-10/IL-6 ratio significantly increased (P < 0.05 for each) at the end of Ramadan. Changes in visceral adiposity significantly correlated with changes in plasma glucose (r = 0.4, P < 0.5) and resistin (r = 0.44, P < 0.001) at the end of Ramadan. CONCLUSION: RDF lowers visceral adiposity, body weight and variably affects adipokines without adversely affecting markers of glucose homeostasis in individuals with overweight or obesity.