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Advanced MRI-based neuroimaging techniques, such as perfusion and spectroscopy, have been increasingly incorporated into routine follow-up protocols in patients treated for high-grade glioma (HGG), to help differentiate tumor progression from treatment effect. However, these techniques' influence on clinical management remains poorly understood. The purpose of this article was to evaluate the impact of MRI-based advanced neuroimaging on clinical decision-making in patients with HGG after treatment. This prospective study, performed at a comprehensive cancer center from March 1, 2017, to October 31, 2020, included adult patients treated by chemoradiation for WHO grade 4 diffuse glioma who underwent MRI-based advanced neuroimaging (comprising multiple perfusion imaging sequences and spectroscopy) to further evaluate findings on conventional MRI equivocal for tumor progression versus treatment effect. The ordering neurooncologists completed surveys before and after each advanced neuroimaging session. The percent of episodes of care with a change between the intended and actual management plan on the surveys conducted before and after advanced neuroimaging, respectively, was computed and compared with a published percent using the Wald test for independent samples proportions. The study included 63 patients (mean age, 54.6 ± 12.9 [SD] years; 36 women, 27 men) who underwent 70 advanced neuroimaging sessions. Ordering neurooncologists' intended and actual management plans on the surveys completed before and after advanced neuroimaging, respectively, differed in 44% (31/70; 95% CI: 33-56%) of episodes, which differed from the published frequency of 8.5% (5/59) ( < .001). These management plan changes included selection of a different plan for six of eight episodes with an intended plan to enroll patients in a clinical trial, 12 of 19 episodes with an intended plan to change chemotherapeutic agents, four of eight episodes with an intended plan of surgical intervention, and one of two episodes with an intended plan of reirradiation. The ordering neurooncologists found advanced neuroimaging to be helpful in 93% (65/70; 95% CI: 87-99%) of episodes. Neurooncologists' management plans changed in a substantial fraction of adult patients with HGG who underwent advanced neuroimaging to further evaluate conventional MRI findings equivocal for tumor progression versus treatment effect. The findings support incorporation of advanced neuroimaging into HGG posttreatment monitoring protocols.
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http://dx.doi.org/10.2214/AJR.24.31595 | DOI Listing |
Cereb Cortex
August 2025
Section of Brain Function Information, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan.
This study aimed to identify brain activity modulations associated with different types of visual tracking using advanced functional magnetic resonance imaging techniques developed by the Human Connectome Project (HCP) consortium. Magnetic resonance imaging data were collected from 27 healthy volunteers using a 3-T scanner. During a single run, participants either fixated on a stationary visual target (fixation block) or tracked a smoothly moving or jumping target (smooth or saccadic tracking blocks), alternating across blocks.
View Article and Find Full Text PDFThis manuscript explores the myriad ethical controversies associated with declaration of brain death/death by neurologic criteria (BD/DNC) during pregnancy raised by the case of Ms. Adriana Smith, a 30-year-old Georgia nurse, who came to international attention in May 2025. We will discuss: (1) the factors that may have impacted the decision not to perform neuroimaging when she first presented to medical attention; (2) the significance of identifying and deferring performance of futile interventions to decrease intracranial pressure relative to BD/DNC declaration; (3) the medical, ethical and legal complexities associated with BD/DNC declaration and continuation of maternal organ support in pregnancy; (4) the impact of continuing maternal organ support after BD/DNC declaration on the fetus, the family, Ms.
View Article and Find Full Text PDFHum Brain Mapp
September 2025
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA.
Investigating neuroimaging data to identify brain-based markers of mental illnesses has gained significant attention. Nevertheless, these endeavors encounter challenges arising from a reliance on symptoms and self-report assessments in making an initial diagnosis. The absence of biological data to delineate nosological categories hinders the provision of additional neurobiological insights into these disorders.
View Article and Find Full Text PDFInt J Gen Med
September 2025
Department of Neurology, Aerospace Center Hospital, Beijing, 100049, People's Republic of China.
Acute vestibular syndrome (AVS) is characterized by the sudden onset of dizziness or vertigo, accompanied by nausea, vomiting, gait instability, and nystagmus, lasting for more than 24 hours and often persisting for several days to weeks. Central AVS primarily involves central vestibular structures, such as the brainstem and cerebellum, and is most commonly caused by ischemic stroke in the posterior circulation. When acute posterior circulation infarction presents solely with isolated dizziness or vertigo, without other symptoms of central nervous system damage, it is often misdiagnosed as a peripheral vestibular disorder, this can lead to serious consequences.
View Article and Find Full Text PDFFront Sports Act Living
August 2025
Faculty of Physical Education, China West Normal University, Nanchong, China.
Understanding how athletes mentally simulate and anticipate actions provides key insights into experience-driven brain plasticity. While previous studies have investigated motor imagery and action anticipation separately, little is known about how their underlying neural mechanisms converge or diverge in expert performers. This study conducted a meta-analysis using activation likelihood estimation (ALE) and meta-analytic connectivity modeling (MACM) to compare brain activation patterns between athletes and non-athletes across both tasks.
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