Activity

We found the controlling role of winter mean temperature, for the first time, on the infection level of powdery mildew. The controlling role of winter temperature may have directly increase the infection level when winter temperature is high and indirectly increase the infection level through prolonging the duration of leaf development to maturation, although the duration itself had smaller influences. We detected a warming trend of the winter temperatures from 2003 to 2011, which indicates that the infection level of powdery mildew will be increased if the winter warming continues.

The recommendations cover indications for MRI examination including acquisition planes, patient preparation, imaging protocol including multi-parametric approaches such as diffusion-weighted imaging (DWI-MR),dynamic contrast-enhanced imaging (DCE-MR) and standardised reporting. The document also underscores the value of whole-body 18-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET/CT) and highlights potential futuremethods.

In 2019, the ESUR female pelvic imaging working group reviewed the revised 2018 FIGO staging system, the up-to-date clinical management guidelines, and the recent imaging literature. The RAND-UCLA Appropriateness Method (RAM) was followed to develop the current ESUR consensus guidelines following methodological steps literature research, questionnaire developments, panel selection, survey, data extraction and analysis.

The updated ESUR guidelinesarerecommendations based on ≥ 80% consensus among experts. If ≥ 80% agreement was not reached, the action was indicated as optional.

The present ESUR guidelinesfocuson the main role of MRIinthe initial staging, response monitoring and evaluation of disease recurrence. Whole-body FDG-PET plays an important role in the detection of lymph nodes(LNs) and distant metastases.

• T2WI and DWI-MR are now recommended for initial staging, monitoring of response and evaluation of recurrence. • DCE-MR is optional; its primary role remains in the research setting. • T2WI, DWI-MRI and whole-body FDG-PET/CT enable comprehensive assessment of treatment response and recurrence.

• T2WI and DWI-MR are now recommended for initial staging, monitoring of response and evaluation of recurrence. • DCE-MR is optional; its primary role remains in the research setting. • T2WI, DWI-MRI and whole-body FDG-PET/CT enable comprehensive assessment of treatment response and recurrence.

To evaluate a deep learning model for predicting gestational age from fetal brain MRI acquired after the first trimester in comparison to biparietal diameter (BPD).

Our Institutional Review Board approved this retrospective study, and a total of 184 T2-weighted MRI acquisitions from 184 fetuses (mean gestational age 29.4 weeks) who underwent MRI between January 2014 and June 2019 were included. The reference standard gestational age was based on the last menstruation and ultrasonography measurements in the first trimester. The deep learning model was trained with T2-weighted images from 126 training cases and 29 validation cases. The remaining 29 cases were used as test data, with fetal age estimated by both the model and BPD measurement. The relationship between the estimated gestational age and the reference standard was evaluated with Lin’s concordance correlation coefficient (ρc) and a Bland-Altman plot. The ρc was assessed with McBride’s definition.

The ρc of the model prediction was substantial (ρl age from fetal brain MRI acquired in the second and third trimester. • Prediction of gestational age by deep learning may have benefits for prenatal care in pregnancies that are underserved during the first trimester.

Quantum noise is a random process in X-ray-based imaging systems. We addressed and measured the uncertainty of radiomics features against this quantum noise in computed tomography (CT) images.

A clinical multi-detector CT scanner, two homogeneous phantom sets, and four heterogeneous samples were used. learn more A solid tumor tissue removed from a male BALB/c mouse was included. We the placed phantom sets on the CT scanning table and repeated 20 acquisitions with identical imaging settings. Regions of interest were delineated for feature extraction. Statistical quantities-average, standard deviation, and percentage uncertainty-were calculated from these 20 repeated scans. Percentage uncertainty was used to measure and quantify feature stability against quantum noise. Twelve radiomics features were measured. Random noise was added to study the robustness of machine learning classifiers against feature uncertainty.

We found the ranges of percentage uncertainties from homogeneous soft tissue phantoms, homogeneous bonatistical quantity of percentage uncertainty to measure the uncertainty of radiomics features against the inherent quantum noise in computed tomography (CT) images. • A clinical multi-detector CT scanner, two homogeneous phantom sets, and four heterogeneous samples were used in the stability measurement. A solid tumor tissue removed from a male BALB/c mouse was included in the heterogeneous sample.

2-Deoxy-2-[

F]fluoro-D-glucose ([

F]FDG) positron-emission tomography/computed tomography (PET/CT) is widely used to evaluate lung nodules, although respiratory motion artefacts may occur. We investigated the value of prone position PET/CT (pPET/CT) in lung nodule evaluation compared with standard supine position PET/CT (sPET/CT).

We retrospectively reviewed 28 consecutive patients (20 men; age, 65.6 ± 12.1 years) with a lung nodule (size, 16.8 ± 5.5 mm) located below the sub-carinal level who underwent [

F]FDG PET/CT in a standard supine position and additional prone position. The maximum standardised uptake value (SUV

), metabolic tumour volume (MTV), difference of diaphragm position between PET and CT (DDP), Dice’s similarity coefficient (DSC) and occurrence of mis-registration were analysed. The [

F]FDG uptake of 20 biopsy-confirmed (15 malignant) nodules was evaluated visually.

pPET/CT yielded a significantly higher SUV

, lower MTV and shorter DDP than with sPET/CT (p = 0.043, 0.007 and 0.021, respectively).