Factors associated with the local control of brain metastases: a systematic search and machine learning application.

Background: Enhancing Local Control (LC) of brain metastases is pivotal for improving overall survival, which makes the prediction of local treatment failure a crucial aspect of treatment planning. Understanding the factors that influence LC of brain metastases is imperative for optimizing treatment strategies and subsequently extending overall survival. Machine learning algorithms may help to identify factors that predict outcomes.

Predicting Cognitive Functioning for Patients with a High-Grade Glioma: Evaluating Different Representations of Tumor Location in a Common Space.

Cognitive functioning is increasingly considered when making treatment decisions for patients with a brain tumor in view of a personalized onco-functional balance. Ideally, one can predict cognitive functioning of individual patients to make treatment decisions considering this balance. To make accurate predictions, an informative representation of tumor location is pivotal, yet comparisons of representations are lacking.

Cognitive complaints in patients with untreated obstructive sleep apnea versus patients with neurological and respiratory diseases: prevalence, severity and risk factors.

Purpose: Little is known about cognitive complaints (self-reported problems in cognitive functioning) in patients with Obstructive Sleep Apnea (OSA). We compared the prevalence and severity of cognitive complaints in patients with untreated OSA to patients with neurological and respiratory diseases. We also studied risk factors for cognitive complaints across these diseases, including OSA.

Preoperative executive functioning impairments in patients with a meningioma: does a frontal location matter?

Patients with meningiomas frequently exhibit impairments in executive functioning. There are few studies specifically examining the role of frontal meningioma localization in executive functioning impairments. This study examines whether frontally located meningiomas are specifically associated with executive functioning impairments in a large sample of meningioma patients before treatment, using an axis-wise and lobe-based approach to meningioma localization.

Can structure predict function at individual level in the human connectome?

Several studies predicting Functional Connectivity (FC) from Structural Connectivity (SC) at individual level have been published in recent years, each promising increased performance and utility. We investigated three of these studies, analyzing whether the results truly represent a meaningful individual-level mapping from SC to FC. Using data from the Human Connectome Project shared accross the three studies, we constructed a predictor by averaging FC of training data and analyzed its performance in the same way.