Clinical 7 T MRI: Are we there yet? A review about magnetic resonance imaging at ultra-high field

Brain structure and cognitive ability in healthy aging: a review on longitudinal correlated change

Little is still known about the neuroanatomical substrates related to changes in specific cognitive abilities in the course of healthy aging, and the existing evidence is predominantly based on cross-sectional studies. However, to understand the intricate dynamics between developmental changes in brain structure and changes in cognitive ability, longitudinal studies are needed. In the present article, we review the current longitudinal evidence on correlated changes between magnetic resonance imaging-derived measures of brain structure (e.g. gray matter/white matter volume, cortical thickness), and laboratory-based measures of fluid cognitive ability (e.g. intelligence, memory, processing speed) in healthy older adults. To theoretically embed the discussion, we refer to the revised Scaffolding Theory of Aging and Cognition. We found 31 eligible articles, with sample sizes ranging from n = 25 to n = 731 (median n = 104), and participant age ranging from 19 to 103. Several of these studies report positive correlated changes for specific regions and specific cognitive abilities (e.g. between structures of the medial temporal lobe and episodic memory). However, the number of studies presenting converging evidence is small, and the large methodological variability between studies precludes general conclusions. Methodological and theoretical limitations are discussed. Clearly, more empirical evidence is needed to advance the field. Therefore, we provide guidance for future researchers by presenting ideas to stimulate theory and methods for development.

Evaluating Magnetic Resonance Spectroscopy as a Tool for Monitoring Therapeutic Response of Whole Brain Radiotherapy in a Mouse Model for Breast-to-Brain Metastasis

Brain metastases are the most common intracranial tumor in adults and are associated with poor patient prognosis and median survival of only a few months. Treatment options for brain metastasis patients remain limited and largely depend on surgical resection, radio- and/or chemotherapy. The development and pre-clinical testing of novel therapeutic strategies require reliable experimental models and diagnostic tools that closely mimic technologies that are used in the clinic and reflect histopathological and biochemical changes that distinguish tumor progression from therapeutic response. In this study, we sought to test the applicability of magnetic resonance (MR) spectroscopy in combination with MR imaging to closely monitor therapeutic efficacy in a breast-to-brain metastasis model. Given the importance of radiotherapy as the standard of care for the majority of brain metastases patients, we chose to monitor the post-irradiation response by magnetic resonance spectroscopy (MRS) in combination with MR imaging (MRI) using a 7 Tesla small animal scanner. Radiation was applied as whole brain radiotherapy (WBRT) using the image-guided Small Animal Radiation Research Platform (SARRP). Here we describe alterations in different metabolites, including creatine and N-acetylaspartate, that are characteristic for brain metastases progression and lactate, which indicates hypoxia, while choline levels remained stable. Radiotherapy resulted in normalization of metabolite levels indicating tumor stasis or regression in response to treatment. Our data indicate that the use of MR spectroscopy in addition to MRI represents a valuable tool to closely monitor not only volumetrical but also metabolic changes during tumor progression and to evaluate therapeutic efficacy of intervention strategies. Adapting the analytical technology in brain metastasis models to those used in clinical settings will increase the translational significance of experimental evaluation and thus contribute to the advancement of pre-clinical assessment of novel therapeutic strategies to improve treatment options for brain metastases patients.

Image processing approaches to enhance perivascular space visibility and quantification using MRI

Imaging the perivascular spaces (PVS), also known as Virchow-Robin space, has significant clinical value, but there remains a need for neuroimaging techniques to improve mapping and quantification of the PVS. Current technique for PVS evaluation is a scoring system based on visual reading of visible PVS in regions of interest, and often limited to large caliber PVS. Enhancing the visibility of the PVS could support medical diagnosis and enable novel neuroscientific investigations. Increasing the MRI resolution is one approach to enhance the visibility of PVS but is limited by acquisition time and physical constraints. Alternatively, image processing approaches can be utilized to improve the contrast ratio between PVS and surrounding tissue. Here we combine T1- and T2-weighted images to enhance PVS contrast, intensifying the visibility of PVS. The Enhanced PVS Contrast (EPC) was achieved by combining T1- and T2-weighted images that were adaptively filtered to remove non-structured high-frequency spatial noise. EPC was evaluated on healthy young adults by presenting them to two expert readers and also through automated quantification. We found that EPC improves the conspicuity of the PVS and aid resolving a larger number of PVS. We also present a highly reliable automated PVS quantification approach, which was optimized using expert readings.