Background Magnetic resonance imaging (MRI) and amino acid positron-emission
tomography (PET) of the brain contain a vast amount of structural and functional information …

Personalized medicine has revolutionized approaches to treatment in the field of lung
cancer by enabling therapies to be specific to each patient. However, physicians encounter …

Brain metastasis (BM) is one of the main complications of many cancers, and the most
frequent malignancy of the central nervous system. Imaging studies of BMs are routinely …

Neurosurgeons receive extensive technical training, which equips them with the knowledge
and skills to specialise in various fields and manage the massive amounts of information …

Background Radiation necrosis (RN) secondary to stereotactic radiosurgery is a significant
cause of morbidity. The optimal management of corticosteroid-refractory brain RN remains …

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

Imaging diagnosis is crucial for early detection and monitoring of brain tumors. Radiomics
enable the extraction of a large mass of quantitative features from complex clinical imaging …

Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumours of the
head and neck, and improving the efficiency of its diagnosis and treatment strategies is an …

Gliomas are the most common primary brain tumors. They are classified into 4 grades
(Grade I–II-III–IV) according to the guidelines of the World Health Organization (WHO). The …

We developed artificial intelligence models to predict the brain metastasis (BM) treatment
response after stereotactic radiosurgery (SRS) using longitudinal magnetic resonance …