UNASSIGNED: Just as failure to diagnose an acute ischemic stroke (AIS) in a timely manner affects the patient\'s outcome; an inaccurate and misplaced impression of the AIS diagnosis is not without its drawbacks. Here, we introduce a two-stage clinical tool to aid in the screening of AIS cases in need of imaging in the emergency department (ED).
UNASSIGNED: This was a multicenter cross-sectional study, in which suspected AIS patients who underwent a brain magnetic resonance imaging (MRI) were included. The 18 variables from nine existing AIS screening tools were extracted and a two-stage screening tool was developed based on expert opinion (stage-one or rule in stage) and multivariate logistic regression analysis (stage-two or rule out stage). Then, the screening performance characteristics of the two-stage mode was evaluated.
UNASSIGNED: Data from 803 patients with suspected AIS were analyzed. Among them, 57.4 % were male, and their overall mean age was 66.9 ± 13.9 years. There were 561 (69.9%) cases with a final confirmed diagnosis of AIS. The total sensitivity and specificity of the two-stage screening model were 99.11% (95% CI: 98.33 to 99.89) and 35.95% (95% CI: 29.90 to 42.0), respectively. Also, the positive and negative predictive values of two-stage screening model were 78.20% (95% CI: 75.17 to 81.24) and 94.57% (95% CI: 89.93 to 81.24), respectively. The area under the receiver operating characteristic (ROC) curve of the two-stage screening model for AIS was 67.53% (95% CI: 64.48 to 70.58). Overall, using the two-stage screening model presented in this study, more than 11% of suspected AIS patients were not referred for MRI, and the error of this model is about 5%.
UNASSIGNED: Here, we proposed a 2-step model for approaching suspected AIS patients in ED for an attempt to safely exclude patients with the least probability of having an AIS as a diagnosis. However, further surveys are required to assess its accuracy and it may even need some modifications.

BACKGROUND: This study aimed to identify the characteristic radiological signs for the diagnosis of Langerhans cell histiocytosis (LCH) of the bone.
METHODS: We retrospectively studied 82 cases of LCH with bone lesions confirmed by pathology. Clinical and radiological features of the patients were analyzed.
RESULTS: A total of 64 and 18 patients had single and multiple bone lesions, respectively. With regard to LCH with single bone lesions, 37.5% (24/64) of lesions were located in the skull and presented as bone destruction with or without soft tissue mass. The correct diagnosis rate of these lesions was 60.0% (9/15) in children and adolescents, but was only 22.2% (2/9) in adults. A total of 26.5% (17/64) of the solitary lesions were found in the spine. Of these, 88.2% (15/17) were located in the vertebral body and appeared to have different degrees of collapse, and 66.7% (10/15) of these lesions were correctly diagnosed. Of the unifocal lesions, 21.8% (14/64) were located in other flat and irregular bones and manifested as osteolysis. Only 21.4% (3/14) of these cases were correctly diagnosed. In total, 14.1% (9/64) of the isolated bone LCH lesions were located in the long bones. Of these, 77.8% (7/9) were located in the diaphysis and presented as central bone destruction with or without fusiform periosteal reaction and extensive peripheral edema, of which 42.9% (3/7) were correctly diagnosed before surgery or biopsy. With regard to LCH with multiple bony destructive lesions, 71.4% (10/14) of cases in children and adolescents were correctly diagnosed; however, all four cases among adults were misdiagnosed.
CONCLUSIONS: In all age groups, isolated diaphyseal destruction of the long bone with fusiform periosteal reaction and extensive peripheral edema, vertebra plana of the spine, and bevelled edge of skull defects accompanied by soft tissue masses strongly suggest LCH diagnosis. Moreover, the multiple bone osteolytic destruction in children and adolescents strongly suggests LCH diagnosis. Familiarity with these typical radiological signs of LCH is necessary to decrease misdiagnoses.

UNASSIGNED: Differentiating actual epileptic seizures (ESs) from psychogenic non-epileptic seizures (PNES) is of great interest. This study compares the serum proteomics of patients diagnosed with ESs and PNES.
UNASSIGNED: Eight patients with seizure (4 with PNES and 4 with TLE (temporal lope epilepsy)) were enrolled in this comparative study. Venous blood samples were drawn during the first hour following the seizure. Standard protein purification technique was employed and proteins were subsequently separated via 2-D electrophoresis. After comparison of the serum proteomes from the two groups, protein expression was analyzed. The differentially expressed bands were determined using both matrix-assisted laser ionization time-of-flight (MALDI/TOF) and electrospray ionization quadruple mass spectrometry (MS).
UNASSIGNED: This study identified 361 proteins, the expression of 110 proteins increased, and 87 proteins decreased in the PNES group compared with TLE group. Four separate proteins were finally identified with MALDI/TOF MS analysis. Compared with PNES group, alpha 1-acid glycoprotein, ceruloplasmin, and S100-β were down-regulated and malate dehydrogenase 2 was up-regulated in the serum of TLE patients.
UNASSIGNED: Our results indicated that changes in serum levels of S100-β, ceruloplasmin, alpha 1-acid glycoprotein 1, and malate dehydrogenase 2 after seizure could be introduced as potential markers to differentiate ES from PNES; however, more advanced studies are required to reach a better understanding of the underlying mechanisms.

BACKGROUND: The clinical manifestations of early mycosis fungoides (eMF) are non-specific and similar to inflammatory skin diseases. High-frequency ultrasonography (HF-US) can show small structure of skin lesions and is helpful to provide information objectively.
METHODS: A case-control study was designed in 62 patients with multiple erythemas and scales, including 18 eMF and 44 age-matched patients with eczema (EC) or psoriasis vulgaris (PsV). The most significant lesions were collected by 50 MHz HF-US. The assessment of ultrasound included epidermal morphology and thickness, infiltration depth, subepidermal low echogenic band (SLEB) boundary and thickness, internal echo, and number of linear acoustic shadows (LAS) behind the epidermis. The ultrasonic characteristics of eMF, EC, and PsV lesions were analyzed.
RESULTS: Epidermal thickness (P < .001, sensitivity 88.9%, specificity 75.0%) and SLEB thickness (P = 0.006, sensitivity 55.6%, specificity 90.9%) were useful for differential diagnosis of eMF and PsV/EC. When eMF was diagnosed by epidermal thickness < 0.2375 mm, the AUC was 0.845, which had the highest diagnostic efficacy among all ultrasound signs. In addition, compared with eMF and EC, the LAS number of PsV lesions was the highest and statistically significant.
CONCLUSIONS: The results showed that HF-US could provide some extra information in identification of eMF, EC, and PsV and has potential clinical value.

BACKGROUND: There is an increasing interest in the use of different biomarkers to help distinguish psychogenic non-epileptic seizure (PNES) from epileptic seizures (ES). This study aimed to evaluate the patterns of differentially expressed serum proteins in ES and PNES cases.
METHODS: In this cross-sectional study, 4 patients with mesial temporal lobe epilepsy and 4 patients with PNES were selected from patients with history of recurrent seizures. Venous blood samples were obtained within 1 hour after seizure and serum proteomes as well as the extent of protein expression were analyzed.
RESULTS: 361 proteins were identified; of these, expression of 197 proteins had altered. 110 (55.9%) proteins were down-regulated and 87 (44.1%) were up-regulated in the PNES samples compared to ES samples. The mean pI for deregulated proteins with 1.5 to 3 fold changes were 6.69 ± 1.68 in proteins with increasing expression in ES group and 5.88 ± 1.39 in proteins with increasing expression in PNES group (p = 0.008). The median and interquartile range (IQR) of molecular weight changes in proteins with 1.5 to 3 fold changes were 64 (22.0-86.0) in proteins whose expression had increased in ES group and 39.5 (26.0-61.5) in proteins whose expression had increased in PNES cases (p = 0.05).
CONCLUSIONS: Several spots with differential expression were observed by comparing patients with ES against the PNES groups, which could be potential biomarkers of the disease. Damage to the blood-brain barrier is the most important difference between the two groups, thus identifying total protein changes offers a key to the future of differentiating ES and PNES patients.

Preoperative differentiation between malignant and benign soft-tissue masses is important for treatment decisions.
To construct/validate a radiomics-based machine method for differentiation between malignant and benign soft-tissue masses.
Retrospective.
In all, 206 cases.
The T1 sequence was acquired with the following range of parameters: relaxation time / echo time (TR/TE), 352-550/2.75-19 msec. The T2 sequence was acquired with the following parameters: TR/TE, 700-6370/40-120 msec. The data were divided into a 3.0T training cohort, a 1.5T MR validation cohort, and a 3.0T external validationcohort.
Twelve machine-learning methods were trained to establish classification models to predict the likelihood of malignancy of each lesion. The data of 206 cases were separated into a training set (n = 69) and two validation sets (n = 64, 73, respectively).
1) Demographic characteristics: a one-way analysis of variance (ANOVA) test was performed for continuous variables as appropriate. The χ2 test or Fisher\'s exact test was performed for comparing categorical variables as appropriate. 2) The performance of four feature selection methods (least absolute shrinkage and selection operator [LASSO], Boruta, Recursive feature elimination [RFE, and minimum redundancy maximum relevance [mRMR]) and three classifiers (support vector machine [SVM], generalized linear models [GLM], and random forest [RF]) were compared for selecting the likelihood of malignancy of each lesion. The performance of the radiomics model was assessed using area under the receiver-operating characteristic curve (AUC) and accuracy (ACC) values.
The LASSO feature method + RF classifier achieved the highest AUC of 0.86 and 0.82 in the two validation cohorts. The nomogram achieved AUCs of 0.96 and 0.88, respectively, in the two validation sets, which was higher than that of the radiomic algorithm in the two validation sets and clinical model of the validation 1 set (0.92, 0.88 respectively). The accuracy, sensitivity, and specificity of the radiomics nomogram were 90.5%, 100%, and 80.6%, respectively, for validation set 1; and 80.8%, 75.8%, and 85.0% for validation set 2.
A machine-learning nomogram based on radiomics was accurate for distinguishing between malignant and benign soft-tissue masses.
3 TECHNICAL EFFICACY: Stage 2 J. Magn. Reson. Imaging 2020;52:873-882.

To assess the transcultural equivalency of the Spanish version of the Fibromyalgia Rapid Screening Tool (FiRST) and its discriminatory ability in different Latin American samples.
Validation study.
Departments of Rheumatology in general hospitals and private centers; fibromyalgia unit in a university hospital.
350 chronic pain patients from Spain, Argentina, Mexico, Peru, and Ecuador.
The cultural relevance of the Spanish version of the FiRST was evaluated. The ability of the FiRST as a screening tool for fibromyalgia was assessed by logistic regression analysis. To determine the degree to which potential confounders, such as differences in demographics, pain, affective distress, catastrophizing, and disability, might affect the discriminatory ability, the tool was reassessed by hierarchical multivariate logistic regression.
Slightly different versions of the FiRST were recommended for use in each Latin American subsample. The FiRST showed acceptable criterion validity and was able to discriminate between fibromyalgia and non-fibromyalgia patients even after controlling for the effect of potential confounders. However, low specificities were observed in samples from Spain and Mexico.
The Spanish version of the FiRST may be used as a screening tool for fibromyalgia in several Latin American subsamples, even in those patients with high scores on potential confounders. In Spain and Mexico, the low specificity of the FiRST suggests, however, that it would be best used to support a suspected diagnosis of fibromyalgia, rather than to exclude the diagnosis.