Notes

Reproducibility from the Ribosomal RNA Activity Ratio inside Sputum along with Connection to Indicators associated with Mycobacterium t . b Burden.
and an embolus being located in the central pulmonary artery (P<0.001) were independent risk factors for chronic persistence of thromboembolism following acute pulmonary embolism.

The protein S activity, location of the embolus, and S
/MPA
on CTPA at the onset of acute pulmonary embolism may suggest the progression of acute pulmonary embolism to CPTE.
The protein S activity, location of the embolus, and Sd/MPAd on CTPA at the onset of acute pulmonary embolism may suggest the progression of acute pulmonary embolism to CPTE.
The differential diagnosis of eyelid basal cell carcinoma (BCC) and sebaceous carcinoma (SC) is highly dependent on pathologist's experience. Herein, we proposed a fully automated differential diagnostic method, which used deep learning (DL) to accurately classify eyelid BCC and SC based on whole slide images (WSIs).

We used 116 haematoxylin and eosin (H&E)-stained sections from 116 eyelid BCC patients and 180 H&E-stained sections from 129 eyelid SC patients treated at the Shanghai Ninth People's Hospital from 2017 to 2019. The method comprises two stages patch prediction by the DenseNet-161 architecture-based DL model and WSI differentiation by an average-probability strategy-based integration module, and its differential performance was assessed by the carcinoma differentiation accuracy and F1 score. We compared the classification performance of the method with that of three pathologists, two junior and one senior. To validate the auxiliary value of the method, we compared the pathologists' BCC and SC classification with and without the assistance of our proposed method.

Our proposed method achieved an accuracy of 0.983, significantly higher than that of the three pathologists (0.644 and 0.729 for the two junior pathologists and 0.831 for the senior pathologist). With the method's assistance, the pathologists' accuracy increased significantly (P<0.05), by 28.8% and 15.2%, respectively, for the two junior pathologists and by 11.8% for the senior pathologist.

Our proposed method accurately classifies eyelid BCC and SC and effectively improves the diagnostic accuracy of pathologists. It may therefore facilitate the development of appropriate and timely therapeutic plans.
Our proposed method accurately classifies eyelid BCC and SC and effectively improves the diagnostic accuracy of pathologists. It may therefore facilitate the development of appropriate and timely therapeutic plans.
Ultra-low dose computed tomography (ULD-CT) was shown to be a good alternative to digital radiographs in various locations. This study aimed to assess the diagnostic sensitivity and specificity of ULD-CT versus digital radiographs in patients consulting for extremity traumas in emergency room.

Digital radiography and ULD-CT scan were performed in patients consulting at the emergency department (February-August 2018) for extremity traumas. Fracture detection was evaluated retrospectively by two blinded independent radiologists. Sensitivity and specificity were evaluated using best value comparator (BVC) and a Bayesian latent class model (LCM) approaches and clinical follow-up. Image quality, quality diagnostic and diagnostic confidence level were evaluated (Likert scale). The effective dose received was calculated.

Seventy-six consecutive patients (41 men, mean age 35.2±13.2 years), with 31 wrists/hands and 45 ankles/feet traumas were managed by emergency physicians. According to clinical data, radiography had 3 false positive and 10 false negative examinations, and ULD-CT, 2 of each. Radiography and ULD-CT specificities were similar; sensitivities were lower for radiography, with BVC and Bayesian. With Bayesian, ULD-CT and radiography sensitivities were 90% (95% CI 87-93%) and 76% (95% CI 71-81%, P<0.0001) and specificities 96% (95% CI 93-98%) and 93% (95% CI 87-97%, P=0.84). The inter-observer agreement was higher for ULD-CT for all subjective indexes. The effective dose for ULD-CT and radiography was 0.84±0.14 and 0.58±0.27 µSv (P=0.002) for hand/wrist, and 1.50±0.32 and 1.44±0.78 µSv (P=NS) for foot/ankle.

With an effective dose level close to radiography, ULD-CT showed better detection of extremities fractures in the emergency room and may allow treatment adaptation. Further studies need to be performed to assess impact of such examination in everyday practice.

ClinicalTrials.gov Identifier NCT04832490.
ClinicalTrials.gov Identifier NCT04832490.
Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to study brain functional alteration, but there have been no reports of research regarding the application of rs-fMRI in intracranial tuberculosis. The purpose of this prospective, cross-sectional study was to investigate spontaneous neural activity at different frequency bands in patients with intracranial tuberculosis using rs-fMRI with amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) methods.

The rs-fMRI data of 31 patients with intracranial tuberculosis and 30 gender-, age-, and education-matched healthy controls (HCs) were included. The ALFF and fALFF values in the conventional frequency band (0.01-0.08 Hz) and 2 sub-frequency bands (slow-4 0.027-0.073 Hz; slow-5 0.01-0.027 Hz) were calculated and compared between the groups. The resultant T-maps were corrected using the Gaussian random field (GRF) theory (voxel P<0.01, cluster P<0.05). Correlations between the ALFF and fALFF values and neurocol tuberculosis showed abnormal intrinsic brain activity at different frequency bands, and ALFF abnormalities in different brain regions could be better detected in the slow-4 band. This preliminary study might provide new insights into understanding the pathophysiological mechanism in intracranial tuberculosis.
Patients with intracranial tuberculosis showed abnormal intrinsic brain activity at different frequency bands, and ALFF abnormalities in different brain regions could be better detected in the slow-4 band. This preliminary study might provide new insights into understanding the pathophysiological mechanism in intracranial tuberculosis.
Conventionally, identifying isocitrate dehydrogenase (
) mutation in gliomas is based on histopathological analysis of tissue specimens acquired via stereotactic biopsy or definitive resection. Accurate pre-treatment prediction of
mutation status using magnetic resonance imaging (MRI) can guide clinical decision-making. We aim to evaluate the diagnostic performance of deep learning (DL) to determine
mutation status in gliomas.

A systematic search of Cochrane Library, Web of Science, Medline, and Scopus was conducted to identify relevant publications until August 1, 2021. Articles were included if all the following criteria were met (I) patients with histopathologically confirmed World Health Organization (WHO) grade II, III, or IV gliomas; (II) histopathological examination with the
mutation; (III) DL was used to predict the
mutation status; (IV) sufficient data for reconstruction of confusion matrices in terms of the diagnostic performance of the DL algorithms; and (V) original research artidiagnostic performance in predicting
mutation in gliomas. Radiomic features associated with
mutation, and its underlying pathophysiology extracted from advanced MRI may improve prediction probability. However, more studies are required to optimize and increase its reliability. Limitations include obtaining some data via email and lack of training and test sets statistics.
This is the first meta-analysis that summarizes the diagnostic performance of DL in predicting IDH mutation status in gliomas via the Bayes theorem. DL algorithms demonstrate excellent diagnostic performance in predicting IDH mutation in gliomas. Radiomic features associated with IDH mutation, and its underlying pathophysiology extracted from advanced MRI may improve prediction probability. However, more studies are required to optimize and increase its reliability. Limitations include obtaining some data via email and lack of training and test sets statistics.
Clinical-standard morphologic magnetic resonance imaging (MRI) is limited in the refined diagnosis of posterior cruciate ligament (PCL) injuries. Quantitative MRI sequences such as ultrashort echo-time (UTE)-T2* mapping or conventional T2* mapping have been theorized to quantify ligament (ultra-) structure and integrity beyond morphology. This study evaluates their diagnostic potential in identifying and differentiating partial and complete PCL injuries in a standardized graded injury model.

Ten human cadaveric knee joint specimens were imaged on a clinical 3.0 T MRI scanner using morphologic, conventional T2* mapping, and UTE-T2* mapping sequences before and after standardized arthroscopic partial and complete PCL transection. Following manual segmentation, quantitative T2* and underlying texture features (i.e., energy, homogeneity, and variance) were analyzed for each specimen and PCL condition, both for the entire PCL and its subregions. For statistical analysis, Friedman's test followed by Dunn's multmmation.
In contrast to the conventional T2* mapping, UTE-T2* mapping is more receptive in the detection of structural damage of the PCL and allows quantitative assessment of ligament (ultra-)structure and integrity that may help to improve diagnostic differentiation of distinct injury states. Once further substantiated beyond the in-situ setting, UTE-T2* mapping may refine diagnostic evaluation of PCL injuries and -possibly- monitor ligament healing, ageing, degeneration, and inflammation.Cystic lesions of the humeral head are commonly encountered on routine shoulder magnetic resonance imaging (MRI). Differential diagnoses include degenerative lesions, calcific tendinitis with osseous involvement, perianchor cysts, abscesses and less often, tumours. Degenerative lesions, including subcortical and subchondral cysts, are the most commonly encountered. These may be associated with rotator cuff disease and degenerative joint diseases or considered part of ageing depending on the location of the cystic lesions. For instance, cysts of the bare area of the humeral head are considered benign age-related entities, whereas cysts of the greater or lesser tuberosity may herald rotator cuff disease. Infectious lesions, particularly osteomyelitis and intraosseous (Brodie's) abscesses, are intramedullary in location and should be suspected in the context of clinical features such as fever and radiological features such as the penumbra sign. click here Perianchor cysts are postoperative lesions associated with the use of suture anchors in surgeries such as rotator cuff tear repairs. They generally self-resolve over 18 to 24 months. On MRI, the distribution, morphology, and signal characteristics can help point towards a specific diagnosis. The patient's demographic, clinical presentation, and past surgical history can be discriminatory. Knowledge of different cystic lesions in the humeral head and underlying aetiology can be useful in helping the radiologist develop a more thorough search pattern for associated conditions. Determining the underlying cause of cysts can have important implications on management, such as when differentiating perianchor cysts from infection. This pictorial review outlines the differential diagnoses of humeral head cysts on MRI and provides a diagnostic approach for the radiologist.
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