Background: Advanced magnetic resonance (MR) techniques provide physiological and metabolic information that complements the anatomical information available from conventional MR imaging. The purpose of this study was to evaluate the clinical usefulness of proton MR spectroscopy (1H-MRS) in preoperative quantitative assessment of intracranial gliomas.
Patients And Methods: Eight patients with histologically verified gliomas, comprising 2 cases with glioblastoma multiforme (GBM, grade 4), 5 cases with anaplastic oligodendroglioma (AO, grade 3; high-grade glioma), and 1 case with fibrillary astrocytoma (FA, grade 2; low-grade glioma) were evaluated using the 1H-MRS protocol following conventional MR imaging, diffusion-weighted imaging (DWI), and perfusion-weighted imaging (PWI) preoperatively.
Results: High-grade gliomas tended to demonstrate signal hyperintensity by DWI and higher relative cerebral blood volume (rCBV) by PWI. Increased ratios of choline (Cho) to N-acetylaspartate (NAA) (Cho/NAA) and Cho to creatine (Cr) (Cho/Cr) correlated highly with tumor malignancy. The presence of lactate and lipid was predominately detected in patients with high-grade glioma.
Conclusion: The combination of multiple MR parameters, based on DWI, PWI and 1H-MRS, appears valuable for preoperatively predicting the degree of malignancy in glioma.
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J Med Internet Res
January 2025
Knight Foundation of Computing & Information Sciences, Florida International University, Miami, FL, United States.
Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech.
View Article and Find Full Text PDFAnal Chem
January 2025
Department of Cancer Biology and Molecular Medicine, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.
Extracellular vesicles (EVs), membrane-encapsulated nanoparticles shed from all cells, are tightly involved in critical cellular functions. Moreover, EVs have recently emerged as exciting therapeutic modalities, delivery vectors, and biomarker sources. However, EVs are difficult to characterize, because they are typically small and heterogeneous in size, origin, and molecular content.
View Article and Find Full Text PDFJAMA Neurol
January 2025
Department of Radiology, Mayo Clinic, Rochester, Minnesota.
Importance: Although 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established cross-sectional biomarker of brain metabolism in dementia with Lewy bodies (DLB), the longitudinal change in FDG-PET has not been characterized.
Objective: To investigate longitudinal FDG-PET in prodromal DLB and DLB, including a subsample with autopsy data, and report estimated sample sizes for a hypothetical clinical trial in DLB.
Design, Setting, And Participants: Longitudinal case-control study with mean (SD) follow-up of 3.
Anesth Analg
February 2025
SC Terapia Intensiva Neurochirurgica, Ospedale San Carlo Borromeo, ASST Santi Paolo e Carlo, Milano, Italy.
Background: Computed tomography (CT)-derived low muscle mass is associated with adverse outcomes in critically ill patients. Muscle ultrasound is a promising strategy for quantitating muscle mass. We evaluated the association between baseline ultrasound rectus femoris cross-sectional area (RF-CSA) and intensive care unit (ICU) mortality.
View Article and Find Full Text PDFPhys Eng Sci Med
January 2025
School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, WA, Australia.
Artificial Intelligence (AI) based auto-segmentation has demonstrated numerous benefits to clinical radiotherapy workflows. However, the rapidly changing regulatory, research, and market environment presents challenges around selecting and evaluating the most suitable solution. To support the clinical adoption of AI auto-segmentation systems, Selection Criteria recommendations were developed to enable a holistic evaluation of vendors, considering not only raw performance but associated risks uniquely related to the clinical deployment of AI.
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