Objective
To develop a nomogram based on MRI radiomics and clinical features for preoperatively predicting H3K27M mutation in pediatric high-grade gliomas (pHGGs) with a midline location of the ...brain.
Methods
The institutional database was reviewed to identify patients with pHGGs with a midline location of the brain who underwent tumor biopsy with preoperative MRI scans between June 2016 and June 2021. A total of 107 patients with pHGGs, including 79 patients with H3K27M mutation, were consecutively included and randomly divided into training and test sets. Radiomics features were extracted from fluid-attenuated inversion recovery (FLAIR), diffusion-weighted (DW) and post-contrast T1-weighted images, and apparent diffusion coefficient (ADC) maps. The minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) logistic regression were performed for radiomics signature construction. Clinical and radiological features were analyzed to select clinical predictors. A nomogram was then developed by incorporating the radiomics signature and selected clinical predictors.
Results
Nine radiomics features were selected to construct the radiomics signature, which showed a favorable discriminatory ability in training and test sets with an area under the curve (AUC) of 0.95 and 0.92, respectively. Ring enhancement was identified as an independent clinical predictor (
p
< 0.01). The nomogram, constructed with radiomics signature and ring enhancement, showed good calibration and discrimination in training and testing sets (AUC: 0.95 and 0.90 respectively).
Conclusions
The nomogram which combined radiomics signature and ring enhancement had a satisfactory ability to predict H3K27M mutation in pHGGs with a midline of the brain.
Key Points
•
Conventional MRI features were not powerful enough to predict H3K27M mutation status in pediatric high-grade gliomas (pHGGs) with a midline location of the brain.
•
An MRI-based radiomics signature showed satisfactory ability to predict H3K27M mutation status of pHGGs located in the midline of the brain.
•
Associating the radiomics signature with clinical factors improved predictive performance.
Objectives
To construct a CT-based radiomics signature and assess its performance in predicting
MYCN
amplification (MNA) in pediatric patients with neuroblastoma.
Methods
Seventy-eight pediatric ...patients with neuroblastoma were recruited (55 in training cohort and 23 in test cohort). Radiomics features were extracted automatically from the region of interest (ROI) manually delineated on the three-phase computed tomography (CT) images. Selected radiomics features were retained to construct radiomics signature and a radiomics score (rad-score) was calculated by using the radiomics signature–based formula. A clinical model was established with clinical factors, including clinicopathological data, and CT image features. A combined nomogram was developed with the incorporation of a radiomics signature and clinical factors. The predictive performance was assessed by receiver operating characteristics curve (ROC) analysis and decision curve analysis (DCA)
.
Results
The radiomics signature was constructed using 7 selected radiomics features. The clinical radiomics nomogram, which was based on the radiomics signature and two clinical factors, showed superior predictive performance compared with the clinical model alone (area under the curve (AUC) in the training cohort: 0.95 vs. 0.82, the test cohort: 0.91 vs. 0.70). The clinical utility of clinical radiomics nomogram was confirmed by DCA.
Conclusions
This proposed CT-based radiomics signature was able to predict MNA. Combining the radiomics signature with clinical factors outperformed using clinical model alone for MNA prediction.
Key Points
• A CT-based radiomics signature has the ability to predict MYCN amplification (MNA) in neuroblastoma.
• Both pre- and post-contrast CT images are valuable in predicting MNA.
• Associating the radiomics signature with clinical factors improved the predictive performance of MNA, compared with clinical model alone.
In this work, amino-functionalized mesoporous silica nanospheres (NH2-mSiO2) anchored with carbon dots (CDs) have been designed to construct an outstanding fluorescent sensor for heavy metal ...detection. Uniform mSiO2 was chosen to provide an optically transparent scaffold for immobilizing CDs. With the help of amino group modification on the surface of silica, benzene-1,4-diboronic acid (BA) was used as raw material to load CDs in the pores of mSiO2 by one-step solvothermal method. The proposed nanohybrid can solve the problem of aggregation-induced fluorescence quenching, leading to bright blue emission at 450 nm. Meanwhile, the fluorescence of NH2-mSiO2@CDs showed high sensitivity to Cr(VI) in acetic acid buffer solution (pH = 4) with detection limit as low as 5 nM by inner filter effect (IFE) and electrostatic interaction (EI). The proposed method can also be extended to other CDs-based detection systems for chemical/biological sensors.
Display omitted
•Mesoporous silica nanosphere and fluorescent carbon dots nanohybrid was developed.•The nanohybrid exhibited bright blue emission at 450 nm under UV excitation.•The blue fluorescence was effectively quenched by Cr(VI).•Detection of Cr(VI) in lake water by the proposed method was achieved.
This study presents an innovative approach for estimating the azimuth cutoff wavelength (<inline-formula><tex-math notation="LaTeX">\lambda _{c}</tex-math></inline-formula>) using a multipolarization ...combination technique to enhance the retrieval of significant wave height (SWH) and wind speed (WS) from Gaofen-3 (GF-3) SAR wave mode data. The study identifies distinct advantages of copolarization for low to moderate sea states and cross-polarization for high sea states in the <inline-formula><tex-math notation="LaTeX">\lambda _{c}</tex-math></inline-formula> estimation. Consequently, a suite of dual and quad-polarization combination methods is proposed, with the VV+VH combination demonstrating superior cost-efficiency, reducing the root mean square error (RMSE) of <inline-formula><tex-math notation="LaTeX">\lambda _{c}</tex-math></inline-formula> estimation by around 20% compared with VV polarization. Correlation analysis between <inline-formula><tex-math notation="LaTeX">\lambda _{c}</tex-math></inline-formula> at various polarizations, particularly VV+VH, and factors such as SWH, WS, wind direction, wave direction, and incidence angle, indicates a strong positive relationship with SWH and WS, and a moderate relationship with incidence angle. This insight informs the development of three <inline-formula><tex-math notation="LaTeX">\lambda _{c}</tex-math></inline-formula>-based SWH and WS retrieval models: single linear regression, multiple linear regression (MLR), and Gaussian process regression (GPR). The MLR and GPR models integrate normalized radar cross section (NRCS) and incidence angle to improve retrieval accuracy. The GPR model achieves more accurate estimation of SWH and WS compared with existing <inline-formula><tex-math notation="LaTeX">\lambda _{c}</tex-math></inline-formula>-based algorithms, with an RMSE of 0.485 m for SWH retrieval and 1.390 m/s for WS retrieval. Despite the performance gap with state-of-the-art algorithms, the GPR model offers exceptional cost-effectiveness and surpasses NRCS-based models for WS retrieval without requiring wind direction input.
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