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"Allergic fungal sinusitis (AFS)" is typically diagnosed using radiologic images like computed tomography (CT) scans and magnetic resonance imaging (MRI), with the "Hounsfield unit (HU)" in CT scans and T2-weighted images (T2WI) in MRI serving as reliable objective parameters. However, diagnosing AFS might be difficult because of possible signal changes and densities caused by variations in the secretion concentration in the sinus. Few studies have compared the diagnostic performance of MRI and CT scans. This study aimed to investigate the value of MRI signal intensity in evaluating AFS compared with CT HUs. This retrospective study included 111 patients with pathologically confirmed AFS who underwent CT imaging followed by MRI evaluation at King Saud Medical City, Riyadh, Saudi Arabia, from January 2012 to December 2022. Radiographic densities of sinus opacities on CT scan, including the mean HU values, and MRI findings, including signal voids on T1-weighted images and T2WI, were gathered and analyzed. To determine the efficacy of these radiographic characteristics in predicting the disease and the best cutoff value, we employed receiver operator characteristic curves. The mean age was 31.9 ± 15.6 years, and most patients were 74 females (66.7%). The main symptom was nasal obstruction in 73 patients (65.8%). In comparison, between HU and signal void on T2WI, there was moderate predictive performance [area under the curve: 0.856, P = .001]. An ideal HU cutoff value of 69.50 HU was obtained with a sensitivity of 100% and a specificity of 44.7%. However, the receiver operator characteristic for T1-weighted images could not be plotted, as no signal was avoided to predict AFS and it was not statistically significant (area under the curve: 0.566; P = .287). The study found a CT HU of 69.5 can predict MRI T2WI signal values with a void signal, aiding in diagnostic workup and evaluation for AFS., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

The first diagnostic tool for thyroid disease management is ultrasound. Despite its importance, ultrasound is an extremely subjective procedure that requires a high level of performance skill. Few studies have assessed thyroid ultrasound performance and its effectiveness, particularly the variability between observers in the assessment of ultrasound images. This study evaluated the variability in ultrasound assessments and diagnoses of thyroid nodules between 2 radiologists. In this retrospective study, 75 thyroid nodules in 39 patients were reviewed by 2 experienced radiologists. The nodule composition, margin, shape, calcification, and vasculitis were determined using echogenicity. The study evaluation included these 5 assessments and the final diagnosis. Interobserver variation was determined using Cohen kappa statistics. The interobserver agreements in the interpretation of echogenicity, shape, and margin were fair (κ = 0.21-0.40), whereas there were substantial agreements for vascularity and calcification (κ = 0.62-0.78). The agreements between the observers for individual ultrasound features in this study were the highest for vascularity and the presence/absence of calcification. The interobserver reproducibility for thyroid nodule ultrasound reporting was adequate, but the diagnostic evaluation ability of the observers was inconsistent. The variability in the interpretation of sonographic features could influence the level of suspicion of thyroid malignancy. This study emphasizes the need for consistency in the training of sonographic interpretation of thyroid nodules, particularly for echogenicity, shape, and margin., Competing Interests: The authors have no conflicts of interest to declare., (Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.)