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Objective The American College of Radiology (ACR) recently published the ovarian-adnexal reporting and data system (O-RADS) to provide guidelines to physicians who interpret ultrasound (US) examinations of adnexal masses (AM). This study aimed to compare the O-RADS with two other well-established US classification systems for diagnosis of AM. Methods This retrospective multicenter study between May 2016 and December 2019 assessed consecutive women with AM detected by the US. Five experienced consultant radiologists independently categorized each AM according to O-RADS, gynecologic imaging reporting and data system (GI-RADS), and international ovarian tumor analysis (IOTA) simple rules. Pathology and adequate follow-up were used as reference standards for calculating the validity of three US classification systems for diagnosis of AM. Kappa statistics were used to assess the inter-reviewer agreement (IRA). Results A total of 609 women (mean age, 48 ± 13.7 years; range, 18–72 years) with 647 AM were included. Of the 647 AM, 178 were malignant and 469 were benign. Malignancy rates were comparable to recommended rates by previous literature in O-RADS and IOTA, but higher in GI-RADS. O-RADS had significantly higher sensitivity for malignancy than GI-RAD and IOTA ( p = 0.003 and 0.0007, respectively), but non-significant slightly lower specificity ( p > 0.05). O-RADS, GI-RADS, and IOTA showed similar overall IRA ( κ = 0.77, 0.69, and 0.63, respectively) with a tendency toward higher IRA with O-RADS than with GI-RADS and IOTA. Conclusions O-RADS compares favorably with GI-RADS and IOTA. O-RADS had higher sensitivity than GI-RADS and IOTA simple rules with relatively similar specificity and reliability. Key Points • The malignancy rates were comparable to recommended rates by previous literature in O-RADS and IOTA, but higher in GI-RADS. • The O-RADS had significantly higher sensitivity for malignancy than GI-RADS and IOTA (96.8% vs 92.7% and 92.1%; p = 0.003 and 0.0007, respectively), but non-significant slightly lower specificity (92.8% vs 93.6% and 93.2%, respectively; p > 0.05). • The O-RADS, GI-RADS, and IOTA showed similar overall inter-reviewer agreement (IRA) (κ = 0.77, 0.69, and 0.63, respectively), with a tendency toward higher IRA with O-RADS than with GI-RADS and IOTA.

BackgroundThe Radiological Society of North America (RSNA) recently published a chest CT classification system and Dutch Association for Radiology has announced Coronavirus disease 2019 (COVID-19) reporting and data system (CO-RADS) to provide guidelines to radiologists who interpret chest CT images of patients with suspected COVID-19 pneumonia. This study aimed to compare CO-RADS and RSNA classification with respect to their sensitivity and reliability for diagnosis of COVID-19 pneumonia.ResultsA retrospective study assessed consecutive CT chest imaging of 359 COVID-19-positive patients. Three experienced radiologists who were aware of the final diagnosis of all patients, independently categorized each patient according to CO-RADS and RSNA classification. RT-PCR test performed within one week of chest CT scan was used as a reference standard for calculating sensitivity of each system. Kappa statistics and intraclass correlation coefficient were used to assess reliability of each system. The study group included 359 patients (180 men, 179 women; mean age, 45 ± 16.9 years). Considering combination of CO-RADS 3, 4 and 5 and combination of typical and indeterminate RSNA categories as positive predictors for COVID-19 diagnosis, the overall sensitivity was the same for both classification systems (72.7%). Applying both systems in moderate and severe/critically ill patients resulted in a significant increase in sensitivity (94.7% and 97.8%, respectively). The overall inter-reviewer agreement was excellent for CO-RADS (κ = 0.801), and good for RSNA classification (κ = 0.781).ConclusionCO-RADS and RSNA chest CT classification systems are comparable in diagnosis of COVID-19 pneumonia with similar sensitivity and reliability.

ObjectiveTo assess the diagnostic accuracy and illustrate positive findings of contrast-enhanced fluorine-18 fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) image in patients awaiting liver transplantation (LT) with rising alpha-fetoprotein (AFP) after bridge therapy of hepatocellular carcinoma (HCC).Materials and methodsThis prospective study included 100 patients who were waiting for LT and who previously underwent locoregional therapy (LRT) of HCC. These patients had rising AFP levels on a routine follow-up examination awaiting LT. All patients underwent a contrast-enhanced 18F-FDG PET/CT examination. We calculated for each patient the maximum standardised uptake value (SUVmax) of the tumour and the ratio of the tumoral SUVmax to the normal-liver SUVmax. The diagnostic accuracy and positive contrast-enhanced findings of 18F-FDG PET/CT were established by histopathology and clinical and imaging follow-up as the reference standards.ResultsContrast-enhanced 18F-FDG PET/CT detected tumour relapse in 78 patients (13 patients had intrahepatic lesions, 10 patients had extrahepatic metastases and 55 patients with combined lesions). The sensitivity, specificity and accuracy values of contrast-enhanced 18F-FDG PET/CT examination in the detection of HCC recurrence were 92.8%, 94.1% and 93%, respectively. A significant correlation was found between the AFP level and SUVmax ratio (r = 0.2283; p = 0.0224). The best threshold for 18F-FDG PET positivity was >1.21.ConclusionContrast-enhanced 18F-FDG PET/CT is a valuable tool for the detection of intrahepatic HCC recurrence or extrahepatic metastasis following rising AFP levels after LRT of HCC, and should be incorporated during routine workup awaiting LT.Key Points•18F-FDG PET/CT is a valuable tool for the detection of HCC recurrence•18F-FDG PET/CT should be incorporated during routine workup awaiting liver transplantation•Significant correlation was found between AFP level and SUVmax ratio•The best threshold for18F-FDG PET positivity was >1.21• The ideal cut-off value for AFP was >202

ObjectiveTo evaluate diagnostic performance and inter-reviewer agreement (IRA) of the Gynecologic Imaging Reporting and Data System (GI-RADS) for diagnosis of adnexal masses (AMs) by pelvic ultrasound (US).Patients and methodsA prospective multicenter study included 308 women (mean age, 41 ± 12.5 years; range, 15–73 years) with 325 AMs detected by US. All US examinations were analyzed, and AMs were categorized into five categories according to the GI-RADS classification. We used histopathology and US follow-up as the reference standards for calculating diagnostic performance of GI-RADS for detecting malignant AMs. The Fleiss kappa (κ) tests were applied to evaluate the IRA of GI-RADS scoring results for predicting malignant AMs.ResultsA total of 325 AMs were evaluated: 127 (39.1%) were malignant and 198 (60.9%) were benign. Of 95 AMs categorized as GI-RADS 2 (GR2), none was malignant; of 94 AMs categorized as GR3, three were malignant; of 13 AMs categorized as GR4, six were malignant; and of 123 AMs categorized as GR5, 118 were malignant. On a lesion-based analysis, the GI-RADS had a sensitivity, a specificity, and an accuracy of 92.9%, 97.5%, and 95.7%, respectively, when regarding only those AMs classified as GR5 for predicting malignancy. Considering combined GR4 and GR5 as a predictor for malignancy, the sensitivity, specificity, and accuracy of GI-RADS were 97.6%, 93.9%, and 95.4%, respectively. The IRA of the GI-RADS category was very good (κ = 0.896). The best cutoff value for predicting malignant AMs was >GR3.ConclusionsThe GI-RADS is very valuable for improving US structural reports.Key Points• There is still a lack of a standard in the assessment of AMs.• GI-RADS is very valuable for improving US structural reports of AMs.• GI-RADS criteria are easy and work at least as well as IOTA.

PurposeWe investigated the added value of diffusion-weighted imaging (DWI)/apparent diffusion coefficient (ADC) in the categorization of small hepatic observation (≤ 20 mm) detected in patients with chronic liver disease in reference to LI-RADS (liver imaging reporting and data system) classification system.MethodsWe prospectively evaluated 165 patients with chronic liver disease with small hepatic observations (≤ 20 mm) which were previously categorized as LI-RADS grade 3–5 on dynamic contrast-enhanced CT (DCE-CT). All patients were submitted to a functional MRI including DCE and DWI. Using LI-RADS v2017, two radiologists independently evaluated the observations and assigned a LI-RADS category to each observation using DCE-MRI alone and combined DCE-MRI and DWI/ADC. In the combined technique, the radiologists assigned a LI-RADS category based on a modified LI-RADS criteria in which restricted diffusion on DWI was considered a major feature of HCC. We evaluated the inter-reader agreement with Kappa statistics and compared the diagnostic performance of the LI-RADS with two imaging techniques by Fisher’s exact test using histopathology as the reference standard.ResultsCombined technique in LI-RADS yielded better sensitivities (reader 1, 97% [65/67]; reader 2, 95.5% [64/67]) for HCC diagnosis than DCE-MRI alone (reader 1, 80.6% [54/67], p = 0.005; reader 2, 83.6% [56/67], p = 0.04). The specificities were insignificantly lower in combined technique (reader 1, 88.4% [107/121]; reader 2, 77.7% [94/121]) than in DCE-MRI alone (reader 1, 90.9% [110/121], p = 0.67; reader 2, 79.3% [96/121], p = 0.88). The inter-reader agreement of the LI-RADS scores between combined technique and DCE-MRI was good (κ = 0.765).ConclusionThe use of DWI/ADC as an additional major criterion, improved the sensitivity of LI-RADS in the diagnosis of HCC while keeping high specificity.

ObjectiveTo compare diagnostic performance and agreement between CT, MRI and combined CT/MRI in reference to LI-RADS classification system to categorize hepatic observations detected in hepatic patients during screening ultrasound.Methods240 patients with 296 liver observations detected during ultrasound surveillance underwent hepatic CT and MRI examinations, histopathology, and clinical and radiological follow-up. Using LI-RADS v2014, six radiologists evaluated the observations independently and assigned a LI-RADS category to each observation using CT, MRI and combined CT/MRI.ResultsCombined CT and MRI in LI-RADS yielded better accuracy (91.29 %), sensitivity (90.71 %) and specificity (92.31 %) for hepatocellular carcinoma (HCC) diagnosis than using MRI or CT alone; accuracy, sensitivity and specificity decreased to 85.37 %, 86.34 %, and 83.65 %, respectively, for MRI and 67.6 %, 54.10 % and 91.35 %, respectively, for CT. The intraclass agreement of the LI-RADS scores between CT, MRI and combined CT/MRI was excellent (κ=0.9624 (95 % CI: 0.9318–0.9806)).ConclusionCT and MRI are complementary to each other. Combined CT/MRI enabled a more precise determination of LI-RADS category of hepatic observations; however, due to the expense and minor increase in accuracy, the combined methodology should only be utilized in cases of suspected HCC.Key Points• Hepatic observation may be categorized differently depending on the imaging modality used.• We compared LI-RADS categorization between CT, MRI and combined CT/MRI.• MRI produces higher accuracy and sensitivity, while CT produces higher specificity.• Combining CT and MRI improves LIRADS categorization reports.• Considering additional cost, combined methodology could be restricted to challenging cases.

The blue carbon ecosystems possess the potential to mitigate climate change impacts, support adaptation, assist in reaching the national and global net-zero goals, and secure social, economic, and environmental outcomes through sequestering and storing carbon in sediments. The marine environment along the Red Sea coast of Egypt is distinguished by a high biodiversity with key marine ecosystems such as seagrasses meadows, coral reefs, and mangroves that can play a role in blue carbon ecosystems. To understand the capacity of the seagrasses to store carbon, this study aims at quantifying the vertical distribution of the organic carbon density (OCD) and the carbon sequestration potential (CSR) and evaluate the economic feasibility of seagrasses vegetation as a tool for mitigating climate change. Two sediment cores were sampled from vegetated areas (inhabited with seagrasses species: Thalassia hemprichii) and one core from a non-vegetated area (for comparison) from three nearshore locations within Wadi El Gemal Protected Area, Red Sea Egypt. The OCD in the vegetated areas increased with depth and showed higher capacities of carbon storage compared to the non-vegetated area. The overall calculated CSR for seagrasses in Wadi El-Gemal is 341.65 g C m−2 yr−1. These findings support the key role of seagrasses to mitigate climate change through CO2 sequestration and return an equivalent of 6,000 to 11,000 USD per year for every 100 hectares in monetary value. This highlights the importance of the conservation and restoration of seagrasses along the Red Sea coast and the potential of blue carbon finance that can be leveraged to meet national-level climate mitigation strategies and policies in Egypt.

Multifidus muscle (MF) is one of the back muscles of the spine that is involved in the pathogenesis of low back pain. Its role as a stabilizer of the spine continues to present diagnostic and therapeutic challenges. The degree of MF degeneration is dependent on multiple clinical and radiological factors. We proposed a new equation to predict MF degeneration based upon clinical and radiological changes in magnetic resonance imaging. Clinical factors associated with MF degeneration include visual analogue scale (VAS) for pain, body mass index, duration of complaint, age of the patients and the presence of sciatica. Other radiological factors include the number of disc pathologies, neural canal stenosis and facet joint arthropathies, by building a module of a univariate and multivariate linear regression analysis for the parameters affecting MF degeneration score as a dependent variable. Regarding the univariate and multivariate linear regression for factors affecting MF degeneration, the most common factors associated with increased multifidus score were the duration in years and VAS score in the multivariate analysis model with B value equal to 0.184 according to duration in years and equal to 0.287 with VAS score according to 95% confidence interval. The equation for multifidus score is a helpful method to predict the degree of MF degeneration in relation to clinical variable.

Background: Stomach cancer usually does not become symptomatic until there is extensive disease. Early symptoms are nonspecific. Weight loss, nausea, vomiting, anorexia and fatigue frequently present at the time of diagnosis and manifest late in the disease process. The location or type of tumor may affect the symptoms at presentation. Dysphagia is associated with proximal masses whereas distal tumors manifest with gastric outlet obstruction. Patients with scirrhous-type (linitis plastica) lesions will complain of early satiety due to loss of stomach distensibility. Typical symptoms in patients with linitis plastica tumors include nausea and vomiting (61%), weight loss (58%),dysphagia (46%) and abdominal pain (38%) Endoscopy and Upper gastrointestinal imaging series (UGIS) have traditionally been considered the primary modalities for the detection of gastric carcinoma due to their ability to provide excellent mucosal detail. The depth of mural invasion and the presence of extragastric lesions can be determined with endoscopic ultrasonography (EUS) and computed tomography (CT) . The development of multidetector computed tomography (MDCT) has provided improved visualization and evaluation of the stomach. With advancements in computer and scanner technology, as well as development of 3 dimensional (3D) software programs, MDCT now allows improved detection and staging of stomach cancer. In addition, evaluation of intramural, extraluminal, and metastatic disease is not possible with endoscopy or UGIS, but is readily performed with thecross-sectional capabilities of MDCT. The recent development of multi-detector row CT (MDCT) has allowed imaging with a thinner section collimation, translating into increased quality on transverse computed tomography scans and multiplanar reconstruction, contributing to the improved accuracy of TNM (Tumour, Nodal, Metastases) staging. Nowadays MDCT has been widely used in preoperative staging of gastric cancer. Preoperative staging of gastric carcinoma appears to be the main clinical indication for multidetector CT. In addition, multidetector CT allows detection of other gastric malignancies (lymphoma, carcinoid tumors, metastases, gastrointestinal stromal tumors) and benign gastric tumors (neural tumors, polyps). Gastric inflammation (gastritis, ulcers, Ménétrier disease) and miscellaneous gastric conditions (emphysema, gastric outlet obstruction, varices) can also be visualized with multidetector CT. Multidetector CT is a valuable tool for the evaluation of gastric wall disease and serves as an adjunct to endoscopy