Executive function and cortical thickness in biomarker aMCI.

Introduction: Memory deficits are the primary symptom in amnestic Mild Cognitive Impairment (aMCI); however, executive function (EF) deficits are common. The current study examined EF in aMCI based upon amyloid status (A+/A-) and regional atrophy in signature areas of Alzheimer's disease (AD).

Method: Participants included 110 individuals with aMCI (A+ = 66; A- = 44) and 33 cognitively healthy participants (HP).

Precision targeting in the globus pallidus interna: insights from the multicenter, prospective, blinded VA/NINDS CSP 468 study.

Objective: Deep brain stimulation (DBS) targeting the globus pallidus interna (GPi) has been shown to significantly improve motor symptoms for the treatment of medication-refractory Parkinson's disease. Yet, heterogeneity in clinical outcomes persists, possibly due to suboptimal target identification within the GPi. By leveraging robust sampling of the GPi and 6-month postsurgical outcomes, this study aims to determine optimal symptom-specific GPi DBS targets.

Towards Machine Learning Prediction of Deep Brain Stimulation (DBS) Intra-operative Efficacy Maps.

Deep brain stimulation (DBS) has the potential to improve the quality of life of people with a variety of neurological diseases. A key challenge in DBS is in the placement of a stimulation electrode in the anatomical location that maximizes efficacy and minimizes side effects. Pre-operative localization of the optimal stimulation zone can reduce surgical times and morbidity.

Predictive modeling of brain tumor laser ablation dynamics.

Introduction: Laser interstitial thermal therapy (LITT) is a novel MR thermometry-guided thermoablative tool revolutionizing the clinical management of brain tumors. A limitation of LITT is our inability to estimate a priori how tissues will respond to thermal energy, which hinders treatment planning and delivery. The aim of this study was to determine whether brain tumor LITT ablation dynamics may be predicted by features of the preoperative MRI and the relevance of these data, if any, to the recurrence of metastases after LITT.

Multi-modal imaging with specialized sequences improves accuracy of the automated subcortical grey matter segmentation.

The basal ganglia and limbic system, particularly the thalamus, putamen, internal and external globus pallidus, substantia nigra, and sub-thalamic nucleus, comprise a clinically relevant signal network for Parkinson's disease. In order to manually trace these structures, a combination of high-resolution and specialized sequences at 7 T are used, but it is not feasible to routinely scan clinical patients in those scanners. Targeted imaging sequences at 3 T have been presented to enhance contrast in a select group of these structures.

Multi-Modal and Targeted Imaging Improves Automated Mid-Brain Segmentation.

The basal ganglia and limbic system, particularly the thalamus, putamen, internal and external globus pallidus, substantia nigra, and sub-thalamic nucleus, comprise a clinically relevant signal network for Parkinson's disease. In order to manually trace these structures, a combination of high-resolution and specialized sequences at 7T are used, but it is not feasible to scan clinical patients in those scanners. Targeted imaging sequences at 3T such as F-GATIR, and other optimized inversion recovery sequences, have been presented which enhance contrast in a select group of these structures.

On the Fallacy of Quantitative Segmentation for T1-Weighted MRI.

T1-weighted magnetic resonance imaging (MRI) generates contrasts with primary sensitivity to local T1 properties (with lesser T2 and PD contributions). The observed signal intensity is determined by these local properties and the sequence parameters of the acquisition. In common practice, a range of acceptable parameters is used to ensure "similar" contrast across scanners used for any particular study (e.