MRI-Based Radiomics to Differentiate between Benign and Malignant Parotid Tumors With External Validation.

BACKGROUND: The differentiation between benign and malignant parotid lesions is crucial to defining the treatment plan, which highly depends on the tumor histology. We aimed to evaluate the role of MRI-based radiomics using both T2-weighted (T2-w) images and Apparent Diffusion Coefficient (ADC) maps in the differentiation of parotid lesions, in order to develop predictive models with an external validation cohort. MATERIALS AND METHODS: A sample of 69 untreated parotid lesions was evaluated retrospectively, including 37 benign (of which 13 were Warthin's tumors) and 32 malignant tumors. The patient population was divided into three groups: benign lesions (24 cases), Warthin's lesions (13 cases), and malignant lesions (32 cases), which were compared in pairs. First- and second-order features were derived for each lesion. Margins and contrast enhancement patterns (CE) were qualitatively assessed. The model with the final feature set was achieved using the support vector machine binary classification algorithm. RESULTS: Models for discriminating between Warthin's and malignant tumors, benign and Warthin's tumors and benign and malignant tumors had an accuracy of 86.7%, 91.9% and 80.4%, respectively. After the feature selection process, four parameters for each model were used, including histogram-based features from ADC and T2-w images, shape-based features and types of margins and/or CE. Comparable accuracies were obtained after validation with the external cohort. CONCLUSIONS: Radiomic analysis of ADC, T2-w images, and qualitative scores evaluating margins and CE allowed us to obtain good to excellent diagnostic accuracies in differentiating parotid lesions, which were confirmed with an external validation cohort.

Alterations of frontal-temporal gray matter volume associate with clinical measures of older adults with COVID-19.

COVID-19, the infectious disease caused by the most recently discovered severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has become a global pandemic. It dramatically affects people's health and daily life. Neurological complications are increasingly documented for patients with COVID-19. However, the effect of COVID-19 on the brain is less studied, and existing quantitative neuroimaging analyses of COVID-19 were mainly based on the univariate voxel-based morphometry analysis (VBM) that requires corrections for a large number of tests for statistical significance, multivariate approaches that can reduce the number of tests to be corrected have not been applied to study COVID-19 effect on the brain yet. In this study, we leveraged source-based morphometry (SBM) analysis, a multivariate extension of VBM, to identify changes derived from computed tomography scans in covarying gray matter volume patterns underlying COVID-19 in 120 neurological patients (including 58 cases with COVID-19 and 62 patients without COVID-19 matched for age, gender and diseases). SBM identified that lower gray matter volume (GMV) in superior/medial/middle frontal gyri was significantly associated with a higher level of disability (modified Rankin Scale) at both discharge and six months follow-up phases even when controlling for cerebrovascular diseases. GMV in superior/medial/middle frontal gyri was also significantly reduced in patients receiving oxygen therapy compared to patients not receiving oxygen therapy. Patients with fever presented significant GMV reduction in inferior/middle temporal gyri and fusiform gyrus compared to patients without fever. Patients with agitation showed GMV reduction in superior/medial/middle frontal gyri compared to patients without agitation. Patients with COVID-19 showed no significant GMV differences from patients without COVID-19 in any brain region. Results suggest that COVID-19 may affect the frontal-temporal network in a secondary manner through fever or lack of oxygen.

Management of a Case of Peritonitis Due to Neisseria gonorrhoeae Infection Following Pelvic Inflammatory Disease (PID).

Pelvic inflammatory disease (PID), a serious infection in sexually active women, is one of the reasons for which females seek care in emergency departments and therefore represents an important public health problem. PID is the result of an endocervical infection with different microorganisms, which then ascend to the endometrium and fallopian tubes. Symptoms of PID may be mild and aspecific, making its diagnosis difficult. However, this clinical condition requires effective antibiotic treatment to reduce incidence of complications and late sequelae. We describe here a case of peritonitis as a complication of pelvic inflammatory disease (PID) due to Neisseria gonorrhoeae infection in a 49-year-old woman who presented at the Emergency Department with acute abdominal pain.