Prognostic and clinical significance of contrast enhancement in WHO grade 2 oligodendrogliomas.

Purpose: To investigate the prognostic significance of contrast enhancement (CE) in grade 2 oligodendroglioma (ODG) and explore its clinical implications.

Methods: Patients diagnosed with isocitrate dehydrogenase (IDH)-mutant, 1p/19q co-deleted ODG between 2009 and 2016 were retrospectively enrolled from a single institution. The presence of CE was identified on preoperative MRIs, and clinical, radiologic, and histopathological data that was extracted.

Subventricular zone-associated classification in isocitrate dehydrogenase-wildtype glioblastomas: improved prognostic value through integration of FLAIR with contrast-enhanced imaging.

Objective: Controversy surrounds the prognostic value of contrast-enhanced T1-weighted (T1CE) imaging-based subventricular zone (SVZ) classification in isocitrate dehydrogenase (IDH)-wildtype glioblastomas (GBMs). In this study, the authors aimed to assess the potential of incorporating FLAIR imaging into T1CE imaging-based classification for improving prognostic accuracy.

Methods: A retrospective analysis was conducted on 281 patients with IDH-wildtype GBM.

Laser interstitial thermal therapy for recurrent glioblastomas: a systematic review and meta-analysis.

We aim to investigate the efficacy and safety of laser interstitial thermal therapy (LITT) in treating recurrent glioblastomas (rGBMs). A comprehensive search was conducted in four databases to identify studies published between January 2001 and June 2022 that reported prognosis information of rGBM patients treated with LITT as the primary therapy. The primary outcomes of interest were progression-free survival (PFS) and overall survival (OS) at 6 and 12 months after LITT intervention.

Prediction of IDH mutation status of glioma based on terahertz spectral data.

Gliomas are the most common type of primary tumor in the central nervous system in adults. Isocitrate dehydrogenase (IDH) mutation status is an important molecular biomarker for adult diffuse gliomas. In this study, we were aiming to predict IDH mutation status based on terahertz time-domain spectroscopy technology.

Hybrid Prediction Method for ECG Signals Based on VMD, PSR, and RBF Neural Network.

To explore a method to predict ECG signals in body area networks (BANs), we propose a hybrid prediction method for ECG signals in this paper. The proposed method combines variational mode decomposition (VMD), phase space reconstruction (PSR), and a radial basis function (RBF) neural network to predict an ECG signal. To reduce the nonstationarity and randomness of the ECG signal, we use VMD to decompose the ECG signal into several intrinsic mode functions (IMFs) with finite bandwidth, which is helpful to improve the prediction accuracy.