scholarly journals Unified framework for early stage status prediction of autism based on infant structural magnetic resonance imaging

2021 ◽  
Author(s):  
Kun Gao ◽  
Yue Sun ◽  
Sijie Niu ◽  
Li Wang
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Early Stage ◽  
Resonance Imaging ◽  
Structural Magnetic Resonance Imaging ◽  
Unified Framework

MRI FOR PRE-DEMENTIA TRIALS

2015 ◽  
pp. 1-3
Author(s):  
G.B. Frisoni ◽  
M. Boccardi
Keyword(s):  
Magnetic Resonance Imaging ◽  
Clinical Trials ◽  
Magnetic Resonance ◽  
Early Stage ◽  
Good Reproducibility ◽  
Resonance Imaging ◽  
Clinical Progression ◽  
Structural Magnetic Resonance Imaging ◽  
High Measurement ◽  
Magnetic Resonance Imaging Mri

Structural magnetic resonance imaging (MRI) provides valid markers of whole brain and regional areas of atrophy in Alzheimer’s disease (AD), which are sensitive to change and correlate with clinical progression. Recent efforts to develop standardized and harmonized protocols for MRI indicate high measurement stability and good reproducibility, supporting the use of these measures in clinical trials. Newer MRI measures of microstructural and connectivity changes are also showing promise as early stage biomarkers of neurodegeneration and potentially as measures of treatment effects. Further work is needed to validate these markers for use in clinical trials.

scholarly journals Combining Structural Magnetic Resonance Imaging and Visuospatial Tests to Classify Mild Cognitive Impairment

2018 ◽  
Vol 15 (3) ◽  
pp. 237-246 ◽  
Author(s):  
Fabrizio Fasano ◽  
Micaela Mitolo ◽  
Simona Gardini ◽  
Annalena Venneri ◽  
Paolo Caffarra ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Machine Learning ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Magnetic Resonance ◽  
Early Stage ◽  
Cognitive Test ◽  
Visuospatial Memory ◽  
Resonance Imaging ◽  
Structural Magnetic Resonance Imaging

Background: Recently, efforts have been made to combine complementary perspectives in the assessment of Alzheimer type dementia. Of particular interest is the definition of the fingerprints of an early stage of the disease known as Mild Cognitive Impairment or prodromal Alzheimer's Disease. Machine learning approaches have been shown to be extremely suitable for the implementation of such a combination. Methods: In the present pilot study we combined the machine learning approach with structural magnetic resonance imaging and cognitive test assessments to classify a small cohort of 11 healthy participants and 11 patients experiencing Mild Cognitive Impairment. Cognitive assessment included a battery of standardised tests and a battery of experimental visuospatial memory tests. Correct classification was achieved in 100% of the participants, suggesting that the combination of neuroimaging with more complex cognitive tests is suitable for early detection of Alzheimer Disease. Results: In particular, the results highlighted the importance of the experimental visuospatial memory test battery in the efficiency of classification, suggesting that the high-level brain computational framework underpinning the participant's performance in these ecological tests may represent a “natural filter” in the exploration of cognitive patterns of information able to identify early signs of the disease.

Early-stage cervical cancer: Tumor delineation by magnetic resonance imaging and ultrasound — A European multicenter trial

2013 ◽  
Vol 128 (3) ◽  
pp. 449-453 ◽  
Author(s):  
Elisabeth Epstein ◽  
Antonia Testa ◽  
Adrius Gaurilcikas ◽  
Alessia Di Legge ◽  
Liveke Ameye ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Cervical Cancer ◽  
Magnetic Resonance ◽  
Early Stage ◽  
Multicenter Trial ◽  
Resonance Imaging ◽  
Tumor Delineation ◽  
Early Stage Cervical Cancer ◽  
Cancer Tumor
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