This review describes the definition, incidence, clinical implications, and magnetic
resonance imaging (MRI) findings of pseudoprogression of brain tumors, in particular, but …

Texture analysis is a technique used for the quantification of image texture. It has been
successfully used in many fields, and in the past years it has been applied in magnetic …

We aimed to investigate the feasibility of machine learning (ML) algorithm to distinguish
pseudoprogression (PsPD) from progression (PD) in patients with glioblastoma (GBM). We …

Various MRI sequences have shown their potential to discriminate parotid gland tumors,
including but not limited to T2‐weighted, postcontrast T1‐weighted, and diffusion‐weighted …

The purpose of this study was to examine the dependence of image texture features on MR
acquisition parameters and reconstruction using a digital MR imaging phantom. MR signal …

Differentiating pseudoprogression from true tumor progression has become a significant
challenge in follow-up of diffuse infiltrating gliomas, particularly high grade, which leads to a …

Objectives. Radiomic features extracted from diverse MRI modalities have been investigated
regarding their predictive and/or prognostic value in a variety of cancers. With the aid of a 3D …

AIM To investigate machine learning based models combining clinical, radiomic, and
molecular information to distinguish between early true progression (tPD) and …

After chemoradiotherapy for glioblastoma, pseudoprogression can occur and must be
distinguished from true progression to correctly manage glioblastoma treatment and follow …

Background Melanoma brain metastases historically portend a dismal prognosis, but recent
advances in immune checkpoint inhibitors (ICIs) have been associated with durable …